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• What Is a Case Study? | Definition, Examples & Methods

What Is a Case Study? | Definition, Examples & Methods

Published on May 8, 2019 by Shona McCombes . Revised on November 20, 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating and understanding different aspects of a research problem .

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When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyze the case, other interesting articles.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

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Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.

Unlike quantitative or experimental research , a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.

However, you can also choose a more common or representative case to exemplify a particular category, experience or phenomenon.

Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews , observations , and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data.

Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.

The aim is to gain as thorough an understanding as possible of the case and its context.

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In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis , with separate sections or chapters for the methods , results and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyze its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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The theory contribution of case study research designs

• Original Research
• Open access
• Published: 16 February 2017
• Volume 10 , pages 281–305, ( 2017 )

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• Hans-Gerd Ridder 1  

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The objective of this paper is to highlight similarities and differences across various case study designs and to analyze their respective contributions to theory. Although different designs reveal some common underlying characteristics, a comparison of such case study research designs demonstrates that case study research incorporates different scientific goals and collection and analysis of data. This paper relates this comparison to a more general debate of how different research designs contribute to a theory continuum. The fine-grained analysis demonstrates that case study designs fit differently to the pathway of the theory continuum. The resulting contribution is a portfolio of case study research designs. This portfolio demonstrates the heterogeneous contributions of case study designs. Based on this portfolio, theoretical contributions of case study designs can be better evaluated in terms of understanding, theory-building, theory development, and theory testing.

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Case Study Research

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1 Introduction

Case study research scientifically investigates into a real-life phenomenon in-depth and within its environmental context. Such a case can be an individual, a group, an organization, an event, a problem, or an anomaly (Burawoy 2009 ; Stake 2005 ; Yin 2014 ). Unlike in experiments, the contextual conditions are not delineated and/or controlled, but part of the investigation. Typical for case study research is non-random sampling; there is no sample that represents a larger population. Contrary to quantitative logic, the case is chosen, because the case is of interest (Stake 2005 ), or it is chosen for theoretical reasons (Eisenhardt and Graebner 2007 ). For within-case and across-case analyses, the emphasis in data collection is on interviews, archives, and (participant) observation (Flick 2009 : 257; Mason 2002 : 84). Case study researchers usually triangulate data as part of their data collection strategy, resulting in a detailed case description (Burns 2000 ; Dooley 2002 ; Eisenhardt 1989 ; Ridder 2016 ; Stake 2005 : 454). Potential advantages of a single case study are seen in the detailed description and analysis to gain a better understanding of “how” and “why” things happen. In single case study research, the opportunity to open a black box arises by looking at deeper causes of the phenomenon (Fiss 2009 ). The case data can lead to the identification of patterns and relationships, creating, extending, or testing a theory (Gomm et al. 2000 ). Potential advantages of multiple case study research are seen in cross-case analysis. A systematic comparison in cross-case analysis reveals similarities and differences and how they affect findings. Each case is analyzed as a single case on its own to compare the mechanisms identified, leading to theoretical conclusions (Vaughan 1992 : 178). As a result, case study research has different objectives in terms of contributing to theory. On the one hand, case study research has its strength in creating theory by expanding constructs and relationships within distinct settings (e.g., in single case studies). On the other hand, case study research is a means of advancing theories by comparing similarities and differences among cases (e.g., in multiple case studies).

Unfortunately, such diverging objectives are often neglected in case study research. Burns ( 2000 : 459) emphasizes: “The case study has unfortunately been used as a ‘catch –all’ category for anything that does not fit into experimental, survey, or historical methods.”

Therefore, this paper compares case study research designs. Such comparisons have been conducted previously regarding their philosophical assumptions and orientations, key elements of case study research, their range of application, and the lacks of methodological procedures in publications. (Baxter and Jack 2008 ; Dooley 2002 ; Dyer and Wilkins 1991 ; Piekkari et al. 2009 ; Welch et al. 2011 ). This paper aims to compare case study research designs regarding their contributions to theory.

Case study research designs will be analyzed regarding their various strengths on a theory continuum. Edmondson and McManus ( 2007 ) initiated a debate on whether the stage of theory fits to research questions, style of data collection, and analyses. Similarly, Colquitt and Zapata-Phelan ( 2007 ) created a taxonomy capturing facets of empirical article’s theoretical contributions by distinguishing between theory-building and theory testing. Corley and Gioia ( 2011 ) extended this debate by focusing on the practicality of theory and the importance of prescience. While these papers consider the whole range of methodological approaches on a higher level, they treat case studies as relatively homogeneous. This paper aims to delve into a deeper level of analysis by solely focusing on case study research designs and their respective fit on this theory continuum. This approach offers a more fine-grained understanding that sheds light on the diversity of case study research designs in terms of their differential theory contributions. Such a deep level of analysis on case study research designs enables more rigor in theory contribution. To analyze alternative case study research designs regarding their contributions to theory, I engage into the following steps:

First, differences between case study research designs are depicted. I outline and compare the case study research designs with regard to the key elements, esp. differences in research questions, frameworks, sampling, data collection, and data analysis. These differences result in a portfolio of various case study research designs.

Second, I outline and substantiate a theory continuum that varies between theory-building, theory development, and testing theory. Based on this continuum, I analyze and discuss each of the case study research designs with regard to their location on the theory continuum. This analysis is based on a detailed differentiation of the phenomenon (inside or outside the theory), the status of the theory, research strategy, and methods.

As a result, the contribution to the literature is a portfolio of case study research designs explicating their unique contributions to theory. The contribution of this paper lies in a fine-grained analysis of the interplay of methods and theory (van Maanen et al. 2007 ) and the methodological fit (Edmondson and McManus 2007 ) of case study designs and the continuum of theory. It demonstrates that different designs have various strengths and that there is a fit between case study designs and different points on a theory continuum. If there is no clarity as to whether a case study design aims at creating, elaborating, extending, or testing theory, the contribution to theory is difficult to identify for authors, reviewers, and readers. Consequently, this paper aims to clarify at which point of the continuum of theory case study research designs can provide distinct contributions that can be identified beyond their traditionally claimed exploratory character.

2 Differences across case study design: a portfolio approach

Only few papers have compared case study research designs so far. In all of these comparisons, the number of designs differs as well as the issues under consideration. In an early debate between Dyer and Wilkins ( 1991 ) and Eisenhardt ( 1991 ), Dyer and Wilkins compared the case study research design by Eisenhardt ( 1989 ) with “classical” case studies. The core of the debate concerns a difference between in-depth single case studies (classical case study) to a focus on the comparison of multiple cases. Dyer and Wilkins ( 1991 : 614) claim that the essence of a case study lies in the careful study of a single case to identify new relationships and, as a result, question the Eisenhardt approach which puts a lot of emphasis on comparison of multiple cases. Eisenhardt, on the contrary, claims that multiple cases allow replication between cases and is, therefore, seen as a means of corroboration of propositions (Eisenhardt 1991 ). Classical case studies prefer deep descriptions of a single case, considering the context to reveal insights into the single case and by that elaborate new theories. The comparison of multiple cases, therefore, tends—in the opinion of Dyer and Wilkens—to surface descriptions. This weakens the possibility of context-related, rich descriptions. While, in classic case study, good stories are the aim, the development of good constructs and their relationships is aimed in Eisenhardt’s approach. Eisenhardt ( 1991 : 627) makes a strong plea on more methodological rigor in case study research, while Dyer and Wilkins ( 1991 : 613) criticize that the new approach “… includes many of the attributes of hypothesis-testing research (e.g., sampling and controls).”

Dooley ( 2002 : 346) briefly takes the case study research designs by Yin (1994) and Eisenhardt ( 1989 ) as exemplars of how the processes of case study research can be applied. The approach by Eisenhardt is seen as an exemplar that advances conceptualization and operationalization in the phases of theory-building, while the approach by Yin is seen as exemplar that advances minimally conceptualized and operationalized existing theory.

Baxter and Jack ( 2008 ) describe the designs by Yin (2003) and Stake ( 1995 ) to demonstrate key elements of qualitative case study. The authors outline and carefully compare the approaches by Yin and Stake in conducting the research process, neglecting philosophical differences and theoretical goals.

Piekkari et al. ( 2009 ) outline the methodological richness of case study research using the approaches of Yin et al. (1998), and Stake. They specifically exhibit the role of philosophical assumptions, establishing differences in conventionally accepted practices of case study research in published papers. The authors analyze 135 published case studies in four international business journals. The analysis reveals that, in contrast to the richness of case study approaches, the majority of published case studies draw on positivistic foundations and are narrowly declared as explorative with a lack of clarity of the theoretical purpose of the case study. Case studies are often designed as multiple case studies with cross-sectional designs based on interviews. In addition to the narrow use of case study research, the authors find out that “… most commonly cited methodological literature is not consistently followed” (Piekkari et al. 2009 : 567).

Welch et al. ( 2011 ) develop a typology of theorizing modes in case study methods. Based on the two dimensions “contextualization” and “causal explanation”, they differentiate in their typology between inductive theory-building (Eisenhardt), interpretive sensemaking (Stake), natural experiment (Yin), and contextualised explanation (Ragin/Bhaskar). The typology is used to analyze 199 case studies from three highly ranked journals over a 10-year period for whether the theorizing modes are exercised in the practice of publishing case studies. As a result, the authors identify a strong emphasis on the exploratory function of case studies, neglecting the richness of case study methods to challenge, refine, verify, and test theories (Welch et al. 2011 : 755). In addition, case study methods are not consistently related to theory contribution: “By scrutinising the linguistic elements of texts, we found that case researchers were not always clear and consistent in the way that they wrote up their theorising purpose and process” (Welch et al. 2011 : 756).

As a result, the comparisons reveal a range of case study designs which are rarely discussed. In contrast, published case studies are mainly introduced as exploratory design. Explanatory, interpretivist, and critical/reflexive designs are widely neglected, narrowing the possible applications of case study research. In addition, comparisons containing an analysis of published case studies reveal a low degree in accuracy when applying case study methods.

What is missing is a comparison of case study research designs with regard to differences in the contribution to theory. Case study designs have different purposes in theory contribution. Confusing these potential contributions by inconsistently utilizing the appropriate methods weakens the contribution of case studies to scientific progress and, by that, damages the reputation of case studies.

To conduct such a comparison, I consider the four case study research approaches of Yin, Eisenhardt, Burawoy, and Stake for the following reasons.

These approaches are the main representatives of case study research design outlined in the comparisons elaborated above (Baxter and Jack 2008 ; Dooley 2002 ; Dyer and Wilkins 1991 ; Piekkari et al. 2009 ; Welch et al. 2011 ). I follow especially the argument by Piekkari et al. ( 2009 ) that these approaches contain a broad spectrum of methodological foundations of exploratory, explanatory, interpretivist, and critical/reflexive designs. The chosen approaches have an explicit and detailed methodology which can be reconstructed and compared with regard to their theory contribution. Although there are variations in the application of the designs, to the best of my knowledge, the designs represent the spectrum of case study methodologies. A comparison of these methodologies revealed main distinguishable differences. To highlight these main differences, I summarized these differences into labels of “no theory first”; “gaps and holes”; “social construction of reality”; and “anomalies”.

I did not consider descriptions of case study research in text books which focus more or less on general descriptions of the common characteristics of case studies, but do not emphasize differences in methodologies and theory contribution. In addition, I did not consider so-called “home grown” designs (Eisenhardt 1989 : 534) which lack a systematic and explicit demonstration of the methodology and where “… the hermeneutic process of inference—how all these interviews, archival records, and notes were assembled into a coherent whole, what was counted and what was discounted—remains usually hidden from the reader” (Fiss 2009 : 425).

Finally, although often cited in the methodological section of case studies, books are not considered which concentrate on data analysis in qualitative research per se (Miles et al. 2014 ; Corbin and Strauss 2015 ). Therefore, to analyze the contribution of case study research to the scientific development, it needs to compare explicit methodology. This comparison will be outlined in the following sections with regard to main methodological steps: the role of the case, the collection of data, and the analysis of data.

2.1 Case study research design 1: no theory first

A popular template for building theory from case studies is a paper by Eisenhardt ( 1989 ). It follows a dramaturgy with a precise order of single steps for constructing a case study and is one of the most cited papers in methods sections (Ravenswood 2011 ). This is impressive for two reasons. On the one hand, Eisenhardt herself has provided a broader spectrum of case study research designs in her own empirical papers, for example, by combining theory-building and theory elaboration (Bingham and Eisenhardt 2011 ). On the other hand, she “updated” her design in a paper with Graebner (Eisenhardt and Graebner 2007 ), particularly by extending the range of inductive theory-building. These developments do not seem to be seriously considered by most authors, as differences and elaborations of this spectrum are rarely found in publications. Therefore, in the following, I focus on the standards provided by Eisenhardt ( 1989 ) and Eisenhardt and Graebner ( 2007 ) as exemplary guidelines.

Eisenhardt follows the ideal of ‘no theory first’ to capture the richness of observations without being limited by a theory. The research question may stem from a research gap meaning that the research question is of relevance. Tentative a priori constructs or variables guide the investigation, but no relationships between such constructs or variables are assumed so far: “Thus, investigators should formulate a research problem and possibly specify some potentially important variables, with some reference to extant literature. However, they should avoid thinking about specific relationships between variables and theories as much as possible, especially at the outset of the process” (Eisenhardt 1989 : 536).

Cases are chosen for theoretical reasons: for the likelihood that the cases offer insights into the phenomenon of interest. Theoretical sampling is deemed appropriate for illuminating and extending constructs and identifying relationships for the phenomenon under investigation (Eisenhardt and Graebner 2007 ). Cases are sampled if they provide an unusual phenomenon, replicate findings from other cases, use contrary replication, and eliminate alternative explanations.

With respect to data collection, qualitative data are the primary choice. Data collection is based on triangulation, where interviews, documents, and observations are often combined. A combination of qualitative data and quantitative data is possible as well (Eisenhardt 1989 : 538). Data analysis is conducted via the search for within-case patterns and cross-case patterns. Systematic procedures are conducted to compare the emerging constructs and relationships with the data, eventually leading to new theory.

A good exemplar for this design is the investigation of technology collaborations (Davis and Eisenhardt 2011 ). The purpose of this paper is to understand processes by which technology collaborations support innovations. Eight technology collaborations among ten firms were sampled for theoretical reasons. Qualitative and quantitative data were used from semi-structured interviews, public and private data, materials provided by informants, corporate intranets, and business publications. The data was measured, coded, and triangulated. Writing case histories was a basis for within-case and cross-case analysis. Iteration between cases and emerging theory and considering the relevant literature provided the basis for the development of a theoretical framework.

Another example is the investigation of what is learned in organizational processes (Bingham and Eisenhardt 2011 ). This paper demonstrates that the case study design is not only used for theory-building, but can also be combined with theory elaboration. Based on the lenses of the organizational knowledge literature, organizational routines literature, and heuristics literature, six technology-based ventures were chosen for theoretical reasons. Several data sources were used, especially quantitative and qualitative data from semi-structured interviews, archival data, observations, e-mails, phone calls, and follow-up interviews. Within-case analysis revealed what each firm has learned from process experience. Cross-case analysis revealed emerging patterns from which tentative constructs and propositions were formed. In replication logic constructs and propositions were refined across the cases. When mirroring the findings with the literature, both the emergences of the constructs were compared and unexpected types were considered. The iteration of theory and data as well as the consideration of related research sharpened the theoretical arguments, eventually leading to a theoretical framework. “Thus, we combined theory elaboration (Lee 1999 ) and theory generation (Eisenhardt 1989 )” (Bingham and Eisenhardt 2011 : 1448).

2.2 Case study research design 2: gaps and holes

Contrary to “No Theory First”, case study research design can also aim at specifying gaps or holes in existing theory with the ultimate goal of advancing theoretical explanations (Ridder 2016 ). A well-known template for this case study research design is the book by Yin ( 2014 ). It is a method-orientated handbook of how to design single and multiple case studies with regard to this purpose. Such a case study research design includes: “A ‘how’ and ‘why’ question” (Yin 2014 : 14). Research questions can be identified and shaped using literature to narrow the interest in a specific topic, looking for key studies and identifying questions in these studies. According to Yin’s design, existing theory is the starting point of case study research. In addition, propositions or frameworks provide direction, reflect the theoretical perspective, and guide the search for relevant evidence.

There are different rationales for choosing a single case design (Yin 2014 : 51). Purposeful sampling is conducted if an extreme case or an unusual case is chosen and if rarely observable phenomena can be investigated with regard to unknown matters and their relationships. Common cases allow conclusions for a broader class of cases. Revelatory cases provide the opportunity to investigate into a previously inaccessible inquiry, and the longitudinal study enables one to investigate a single case at several points in time. A rationale for multiple case designs has its strength in replication logic (Yin 2014 : 56). In the case of literal replication, cases are selected to predict similar results. In the case of theoretical replication, cases are selected to predict contrasting results but for theoretical reasons. Yin provides several tactics to increase the reliability (protocol; data base) of the study.

Yin ( 2014 : 103) emphasizes that interviews are one of the most important sources of data collection but considers other sources of qualitative data as well. Data triangulation is designed to narrow problems of construct validity, as multiple sources of data provide multiple measures of the same phenomenon. Yin ( 2014 : 133) offers a number of data analysis strategies (e.g., case description; examining rival explanations) and analytic techniques which are apt to compare the proposed relationships with empirical patterns. Pattern-matching logic compares empirically based patterns with predicted patterns, enabling further data analysis techniques (explanation building, time series analysis, logic models, and cross-case synthesis). In analytical generalization, the theory is compared with the empirical results, leading to the modification or extension of the theory.

An appropriate model for this case study design can be identified in a paper by Ellonen et al. ( 2009 ). The paper is based on the emerging dynamic capability theory. The four cases were chosen for theoretical reasons to deliver an empirical contribution to the dynamic capability theory by investigating the relationship of dynamic capabilities and innovation outcomes. The authors followed a literal replication strategy and identified patterns between dynamic capabilities of the firms and their innovation outcomes.

Shane ( 2000 ) is an author who developed specific propositions from a framework and examined the propositions in eight entrepreneurial cases. Using several sources of interviews and archival data, the author compared the data with the propositions using the pattern-matching logic, which concluded in developing entrepreneurship theory.

2.3 Case study research design 3: social construction of reality

So far, the outlined case study research designs are based on positivist roots, but there is richness and variety in case study research stemming from different philosophical realms. The case study research design by Stake ( 1995 , 2000 , 2005 ), for example, is based on constructivist assumptions and aims to investigate the social construction of reality and meaning (Schwandt 1994 : 125).

According to this philosophical assumption, there is no unique “real world” that preexists independently of human mental activity and symbolic language. The world is a product of socially and historically related interchanges amongst people (social construction). The access to reality is given through social constructions, such as language and shared meanings: “The meaning-making activities themselves are of central interest to social constructionists/constructivists, simply because it is the meaning-making/sense making attributional activities that shape action or (inaction)” (Guba and Lincoln 2005 : 197). Therefore, the researcher is not looking for objective “facts”, nor does he aim at identifying and measuring patterns which can be generalized. Contrarily, the constructivist is researching into specific actions, in specific places, at specific times. The scientist tries to understand the construction and the sharing of meaning (Schwandt 1994 ).

According to Stake ( 2005 ), the direction of the case study is shaped by the interest in the case. In an intrinsic case study, the case itself is of interest. The purpose is not theory-building but curiosity in the case itself. In an instrumental case study, the case itself is of secondary interest. It plays a supportive role, as it facilitates the understanding of a research issue. The case can be typical of other cases. Multiple or collective case study research designs extend the instrumental case study. It is assumed that a number of cases will increase the understanding and support theorizing by comparison of the cases.

The differentiation by Stake ( 1995 , 2005 ) into intrinsic and instrumental cases guides the purposive sampling strategy. In intrinsic case studies, the case is, by definition, already selected. The researcher looks for specific characteristics, aiming for thick descriptions with the opportunity to learn. Representativeness or generalization is not considered. In instrumental case study design, purposive sampling leads to the phenomenon under investigation. In multiple case study designs, the ability to compare cases enhances the opportunity to theorize.

A case study requires an integrated, holistic comprehension of the case complexity. According to Stake ( 2005 ), the case study is constructed by qualitative data, such as observations, interviews, and documents. Triangulation first serves as clarification of meaning. Second, the researcher is interested in the diversity of perceptions.

Two methods of data analysis are considered in such qualitative case study design: direct interpretation and categorical aggregation (Stake 1995 : 74). The primary task of an intrinsic case study is to understand the case. This interpretation is offered to the reader, but the researcher has to provide the material in a sufficient way (thick descriptions), so that the reader can learn from the case as well as draw his or her own conclusions. Readers can thus make some generalizations based on personal and vicarious experiences (“naturalistic generalization”). In instrumental case studies, the understanding of phenomena and relationships leads to categorical aggregation, and the focus is on how the phenomenon exists across several cases.

Greenwood and Suddaby ( 2006 ), for example, used the instrumental case study design by Stake, combining network location theory and dialectical theory. They identified new dynamics creating a process model of elite institutional entrepreneurship.

Ituma et al. ( 2011 ) highlighted the social construction of reality in their study of career success. The majority of career studies have been conducted in Western countries and findings have been acknowledged as universally applicable. The authors demonstrated that realities of managers in other areas are constructed differently. As a result of their study, they provided a contextually sensitive frame for the analysis of career outcomes.

2.4 Case study research design 4: anomalies

Identifying anomalies as a basis for further research is common in management and organization research (Gilbert and Christensen 2005 ). In case study research, the extended case study method is used for this case study research design (Ridder 2016 ). Following Burawoy ( 1991 , 1998 , 2009 ), the research question derives from curiosity. Researchers normally look at what is “interesting” and what is “surprising” in a social situation that existing theory cannot explain. Initially, it is not important whether the expectations develop from some popular belief, stereotype, or from an academic theory. The extended case study research design is guided by anomalies that the previous theory was not able to explain through internal contradictions of theory, theoretical gaps, or silences. An anomaly does not reject theory, but rather demonstrates that the theory is incomplete. Theory is aimed to be improved by “… turning anomalies into exemplars” (Burawoy 1991 : 10).

The theoretical sampling strategy in this case study research design stems from the theoretical failure in confrontation with the site. According to the reflexive design, such cases do not favour individuals or isolated phenomena, but social situations in which a comparative strategy allows the tracing of differences across the cases to external forces.

In the extended case study, the researcher deals with qualitative data, but also considers the broader complex social situation. The researcher engages into a dialogue with the respondents (Burawoy ( 1991 , 1998 , 2009 ). An interview is an intervention into the life of a respondent. By means of mutual interaction it is possible to discover the social order under investigation. The observer has to unpack those situational experiences by means of participant observation and mutual interpretation. This situational comprehension aims at understanding divergent “voices”, reflecting the variety of respondents’ understandings of the social situation.

As in other sciences, these voices have to be aggregated. This aggregation of multiple readings of a single case is conducted by turning the aggregation into social processes: “The move from situation to process is accomplished differently in different reflexive methods, but it is always reliant on existing theory” (Burawoy 2009 : 41). Social processes are now traced to the external field as the conditions of the social processes. Consequently, this leads to the question concerning “… how those micro situations are shaped by wider structures” (Burawoy 1991 : 282). “Reflexive science insists, therefore, on studying the everyday world from the standpoint of its structuration, that is, by regarding it as simultaneously shaped by and shaping an external field of forces” (Burawoy 2009 : 42). Such social fields cannot be held constant, which undermines the idea of replication. The external field is in continuous flux. Accordingly, social forces that influence the social processes are identified, shaping the phenomenon under investigation. Extension of theory does not target representativeness as a relationship of sample and population. Generality in reflexive science is to reconstruct an existing theory: “We begin with our favorite theory but seek not confirmations but refutations that inspire us to deepen that theory. Instead of discovering grounded theory, we elaborate existing theory. We do not worry about the uniqueness of our case, since we are not as interested in its representativeness as its contribution to reconstructing theory. Our theoretical point of departure can range from the folk theory of participants to any abstract law. We consider only that the scientist consider it worth developing” (Burawoy 2009 : 43). Such elaboration stems from the identification of anomalies and offers new predictions with regard to the theory.

It is somewhat surprising that the extended case study design has been neglected in the management literature so far, and it appears that critical reflexive principles have to be resurrected as they have been in other disciplines (see the overview at Wadham and Warren 2014 ). Examples in the management and organization literature are rare. Danneels ( 2011 ) used the extended case study design to extend the dynamic capabilities theory. In his famous Smith Corona case, Danneels shows how a company tried to change its resource base. Based on detailed data, the Smith Corona case provides insights into the resource alteration processes and how dynamic capabilities operate. As a result, the paper fills a process gap in dynamic capability theory. Iterating between data collection and analysis, Danneels revealed resource cognition as an element not considered so far in dynamic capability theory. The use of the extended case study method is limited to the iteration of data and theory. First, there is “running exchange” (Burawoy 1991 : 10) between field notes and analysis. Second, there is iteration between analysis and existing theory. Unlike Burawoy, who aims to reconstruct existing theory on the basis of “emergent anomalies” (Burawoy 1991 : 11) considering social processes and external forces, Danneels confronts the dynamic capabilities literature with the Smith Corona case to extend the theory of dynamic capabilities.

2.5 A comparison of case study research processes

Commonalities and differences emerged from the comparison of the designs. Table  1 provides a brief summary of these main differences and the resulting portfolio of case study research designs which will be discussed in more detail.

There is an extensive range between the different designs regarding the research processes. In “no theory first”, there is a broad and tentative research question with some preliminary variables at the outset. The research question may be modified during the study as well as the variables. This design avoids any propositions regarding relationships.

On the contrary, the research question in “gaps and holes” is strongly related to existing theory, focusing on “how and why” questions. The existing theory contains research gaps which, once identified within the existing theory, lead accordingly to assumed relationships which are the basis for framework and propositions to be matched by empirical data. This broad difference is even more elaborated by a design that aims the “social construction of reality”. There is no research question at the outset, but a curiosity in the case or the case is a facilitator to understand a research issue. This is far away from curiosity in the “anomaly approach”. Here, the research question is inspired by questioning why an anomaly cannot be explained by the existing theory. What kind of gaps, silences, or internal contradictions demonstrates the insufficiency of the existing theory?

Various sampling strategies are used across these case study research designs, including theoretical sampling and purposeful sampling, which serve different objectives. Theoretical sampling in “no theory first” aims at selecting a case or cases that are appropriate to highlight new or extend preliminary constructs and reveal new relationships. There is a distinct difference from theoretical sampling in the “anomalies” approach. Such a sampling strategy aims to choose a case that is a demonstration of the failure of the theory. In “gaps and holes” sampling is highly focused on the purpose of the case study. Extreme and unusual cases have other purposes compared to common cases or revelatory cases. A single case may be chosen to investigate deeply into new phenomena. A multiple case study may serve a replication logic by which the findings have relevance beyond the cases under investigation. In “social construction of reality”, the sampling is purposeful as well, but for different reasons. Either the case is of interest per se or the case represents a good opportunity to understand a theoretical issue.

Although qualitative data are preferred in all of the designs, quantitative data are seen as a possible opportunity to strengthen cases by such data. Nevertheless, in “social construction of reality”, there is a strong emphasis on thick descriptions and a holistic understanding of the case. This is in contrast to a more construct- and variable- oriented collection of data in “no theory first” and “gaps and holes”. In addition, in contrast to that, the “anomaly” approach is the only design that receives data from dialogue between observer and participants and participant observation.

Finally, data analysis lies within a wide range. In “no theory first”, the research process is finalized by inspecting the emerging constructs within the case or across cases. Based on a priory constructs, systematic comparisons reveal patterns and relationships resulting in a tentative theory. On the contrary, in “gaps and holes”, a tentative theory exists. The final analysis concentrates on the matching of the framework or propositions with patterns from the data. While both of these approaches condense data, the approach of “social construction of reality” ends the research process with thick descriptions of the case to learn from the case or with categorical comparisons. In the “anomaly” approach, the data analysis is aggregation of data, but these aggregated data are related to its external field and their pressures and influences by structuration to reconstruct the theory.

As a result, it is unlikely that the specified case study designs contribute to theory in a homogeneous manner. This result will be discussed in light of the question regarding how these case study designs can inform theory at several points of a continuum of theory. This analysis will be outlined in the following sections. In a first step, I review the main elements of a theory continuum. In a second step, I discuss the respective contribution of the previously identified case study research designs to the theory continuum.

3 Elements of a theory continuum

What a theory is and what a theory is not is a classic debate (Sutton and Staw 1995 ; Weick 1995 ). Often, theories are described in terms of understanding relationships between phenomena which have not been or were not well understood before (Chiles 2003 ; Edmondson and McManus 2007 ; Shah and Corley 2006 ), but there is no overall acceptance as to what constitutes a theory. Theory can be seen as a final product or as a continuum, and there is an ongoing effort to define different stages of this continuum (Andersen and Kragh 2010 ; Colquitt and Zapata-Phelan 2007 ; Edmondson and McManus 2007 ; Snow 2004 ; Swedberg 2012 ). In the following section, basic elements of the theory and the construction of the theory continuum are outlined.

3.1 Basic elements of a theory

Most of the debate concerning what a theory is comprises three basic elements (Alvesson and Kärreman 2007 ; Bacharach 1989 ; Dubin 1978 ; Kaplan 1998 ; Suddaby 2010 ; Weick 1989 , 1995 ; Whetten 1989 ). A theory comprises components (concepts and constructs), used to identify the necessary elements of the phenomenon under investigation. The second is relationships between components (concepts and constructs), explaining the how and whys underlying the relationship. Third, temporal and contextual boundaries limit the generalizability of the theory. As a result, definitions of theory emphasize these components, relationships, and boundaries:

“It is a collection of assertions, both verbal and symbolic, that identifies what variables are important for what reasons, specifies how they are interrelated and why, and identifies the conditions under which they should be related or not related” (Campbell 1990 : 65).

“… a system of constructs and variables in which the constructs are related to each other by propositions and the variables are related to each other by hypotheses” (Bacharach 1989 : 498).

“Theory is about the connections among phenomena, a story about why acts, events, structure, and thoughts occur. Theory emphasizes the nature of causal relationships, identifying what comes first as well as the timing of such events” (Sutton and Staw 1995 : 378).

“… theory is a statement of concepts and their interrelationships that shows how and/or why a phenomenon occurs” (Corley and Gioia 2011 : 12).

The terms “constructs” and “concepts” are either used interchangeably or with different meanings. Positivists use “constructs” as a lens for the observation of a phenomenon (Suddaby 2010 ). Such constructs have to be operationalized and measured. Non-positivists often use the term “concept” as a more value neutral term in place of the term construct (Gioia et al. 2013 ; Suddaby 2010 : 354). Non-positivists aim at developing concepts on the basis of data that contain richness and complexity of the observed phenomenon instead of narrow definitions and operationalizations of constructs. Gioia et al. ( 2013 : 16) clarify the demarcation line between constructs and concepts as follows: “By ‘concept,’ we mean a more general, less well-specified notion capturing qualities that describe or explain a phenomenon of theoretical interest. Put simply, in our way of thinking, concepts are precursors to constructs in making sense of organizational worlds—whether as practitioners living in those worlds, researchers trying to investigate them, or theorists working to model them”.

In sum, theories are a systematic combination of components and their relationships within boundaries. The use of the terms constructs and concepts is related to different philosophical assumptions reflected in different types of case study designs.

3.2 Theory continuum

Weick ( 1995 ) makes an important point that theory is more a continuum than a product. In his view, theorizing is a process containing assumptions, accepted principles, and rules of procedures to explain or predict the behavior of a specified set of phenomena. In similar vein, Gilbert and Christensen ( 2005 ) demonstrate the process character of theory. In their view, a first step of theory building is a careful description of the phenomena. Having already observed and described the phenomena, researchers then classify the phenomena into similar categories. In this phase a framework defines categories and relationships amongst phenomena. In the third phase, researchers build theories to understand (causal) relationships, and in this phase, a model or theory asserts what factors drive the phenomena and under what circumstances. The categorization scheme enables the researchers to predict what they will observe. The “test” offers a confirmation under which circumstances the theory is useful. The early drafts of a theory may be vague in terms of the number and adequateness of factors and their relationships. At the end of the continuum, there may be more precise variables and predicted relationships. These theories have to be extended by boundaries considering time and space.

Across that continuum, different research strategies have various strengths. Several classifications in the literature intend to match research strategies to the different phases of a theory continuum (Andersen and Kragh 2010 ; Colquitt and Zapata-Phelan 2007 ; Edmondson and McManus 2007 ; Snow 2004 ; Swedberg 2012 ). These classifications, although there are differences in terms, comprise three phases with distinguishable characteristics.

3.2.1 Building theory

Here, the careful description of the phenomena is the starting point of theorizing. For example, Snow ( 2004 ) puts this phase as theory discovery, where analytic understandings are generated by means of detailed examination of data. Edmondson and McManus ( 2007 ) state the starting phase of a theory as nascent theory providing answers to new questions revealing new connections among phenomena. Therefore, research questions are open and researchers avoid hypotheses predicting relationships between variables. Swedberg ( 2012 ) highlights the necessity of observation and extensive involvement with the phenomenon at the early stage of theory-building. It is an attempt to understand something of interest by observing and interpreting social facts. Creativity and inspiration are necessary conditions to put observations into concepts and outline a tentative theory.

3.2.2 Developing theory

This tentative theory exists in the second phase of the continuum and has to be developed. Several possibilities exist. In theory extension, the preexisting constructs are extended to other groups or other contexts. In theoretical refinement, a modification of existing theoretical perspectives is conducted (Edmondson and McManus ( 2007 ). New antecedents, moderators, mediators, and outcomes are investigated, enhancing the explanation power of the tentative theory.

3.2.3 Test of theories

Constructs and relationships are well developed to a mature state; measures are precise and operationalized. Such theories are empirically tested with elaborate methods, and research questions are more precise. In the quantitative realm, testing of hypotheses is conducted and statistical analysis is the usual methodological foundation. Recently, researchers criticize that testing theories has become the major focus of scientists today (Delbridge and Fiss 2013 ); testing theories does not only happen to mature theory but to intermediate theory as well. The boundary between theory development and theory testing is not always so clear. While theory development is adding new components to a theory and elaborating the measures, testing a theory implies precise measures, variables, and predicted relationships considering time and space (Gilbert and Christensen ( 2005 ). It will be of interest whether case studies are eligible to test theories as well.

To summarize: there is a conversation as to where on a continuum of theory development, various methods are required to target different contributions to theory (methodological fit). In this discussion, case study research designs have been discussed as a homogeneous set that mostly contributes to theory-building in an exploratory manner. Hence, what is missing is a more differentiated analysis of how case study methodology fits into this conversation, particularly how case study research methodologically fits theory development and theory testing beyond its widely assumed explorative role. In the following section, the above types of case study research designs will be discussed with regard to their positions across the theory continuum.

This distinction adds to existing literature by demonstrating that case study research does not only contribute to theory-building, but also to the development of tentative theories and to the testing of theories. This distinction leads to the next question: is there any interplay between case study research designs and their contributions to the theory continuum? This paper aims at reconciling this interplay with regard to case study design by mirroring phases of a theory continuum with specific types of case study research designs as outlined above. The importance of the interplay between theory and method lies in the capacity to generate and shape theory, while theory can generate and shape method. “In this long march, theory and method surely matter, for they are the tools with which we build both our representations and understandings of organizational life and our reputations” (van Maanen et al. 2007 : 1145). Theory is not the same as methods, but a relationship of this interplay can broaden or restrict both parts of the equation (Swedberg 2012 : 7).

In the following, I discuss how the above-delineated case study research designs unfold their capacities and contribute differently to the theory continuum to build, develop, and test theory.

4 Discussion of the contribution of case study research to a theory continuum

Case study research is diverse with distinct contributions to the continuum of theory. The following table provides the main differences in terms of contributions to theory and specifically locates the case study research designs on the theory continuum (Table  2 ).

In the following, I outline how these specific contributions of case study designs provide better opportunities to enhance the rigor of building theory, developing theory, testing, and reconstructing theory.

4.1 Building theory

In building theory, the phenomenon is new or not understood so far. There is no theory which explains the phenomenon. At the very beginning of the theory continuum, there is curiosity in the phenomenon itself. I focus on the intrinsic case study design which is located in the social construction of reality approach on the very early phase of the theory continuum, as intrinsic case study research design is not theory-building per se but curiosity in the case itself. It is not the purpose of the intrinsic case study to identify abstract concepts and relationships; the specific research strategy lies in the observation and description of a case and the primary method is observation, enabling understanding from personal and vicarious experience. This meets long lasting complaints concerning the lack of (new) theory in management and organization research and signals that the gap between research and management practice is growing. It is argued that the complexity of the reality is not adequately captured (Suddaby et al. 2011 ). It is claimed that management and organization research systematically neglect the dialogue with practice and, as a result, miss new trends or recognize important trends with delay (Corley and Gioia 2011 ).

The specific case study research design’s contribution to theory is in building concrete, context-dependent knowledge with regard to the identification of new phenomena and trends. Openness with regard to the new phenomena, avoiding theoretical preconceptions but building insights out of data, enables the elaboration of meanings and the construction of realities in intrinsic case studies. Intrinsic case studies will enhance the understanding by researcher and reader concerning new phenomena.

The “No Theory First” case study research design is a classic and often cited candidate for building theory. As the phenomenon is new and in the absence of a theory, qualitative data are inspected for aggregation and interpretation. In instrumental case study design, a number of cases will increase the understanding and support building theories by description, aggregation, and interpretation (Stake 2000 ). New themes and concepts are revealed by case descriptions, interviews, documents, and observations, and the analysis of the data enables the specific contribution of the case study design through a constructivist perspective in theory-building.

Although the design by Eisenhardt ( 1989 ) stems from other philosophical assumptions and there are variations and developments in this design, there is still an overwhelming tendency to quote and to stick to her research strategy which aims developing new constructs and new relationships out of real-life cases. Data are collected mainly by interviews, documents, and observations. From within-site analysis and cross-case analysis, themes, concepts, and relationships emerge. Shaping hypotheses comprises: “… refining the definition of the construct and (…) building evidence which measures the construct in each case” (Eisenhardt 1989 : 541). Having identified the emerged constructs, the emergent relationships between constructs are verified in each case. The underlying logic is validation by replication. Cases are treated as experiments in which the hypotheses are replicated case by case. In replication logic cases that confirm the emergent relationships enhance confidence in the validity of the relationships. Disconfirmation of the relationships leads to refinement of the theory. This is similar to Yin’s replication logic, but targets the precision and measurement of constructs and the emerging relationships with regard to the emerging theory. The building of a theory concludes in an understanding of the dynamics underlying the relationship; the primary theoretical reasons for why the relationships exist (Huy 2012 ). Finally, a visual theory with “boxes and arrows” (Eisenhardt and Graebner 2007 ) may visually demonstrate the emerged theory. The theory-building process is finalized by iterating case data, emerging theory, and extant literature.

The “No Theory First” and “Social Construction of Reality” case study research designs, although they represent different philosophical assumptions, adequately fit the theory-building phase concerning new phenomena. The main contribution of case study designs in this phase of the theory continuum lies in the generation of tentative theories.

Case studies at this point of the theory continuum, therefore, have to demonstrate: why the phenomenon is new or of interest; that no previous theory that explains the phenomenon exists; how and why detailed descriptions enhance the understanding of the phenomenon; and how and why new concepts (constructs) and new relationships will enhance our understanding of the phenomenon.

As a result, it has to be demonstrated that the research strategy is in sync with an investigation of a new phenomenon, building a tentative theory.

4.2 Developing theory

In the “Gaps and Holes” case study research design, the phenomenon is partially understood. There is a tentative theory and the research strategy is theory driven. Compared to the theory-building phase, the existence and not the development of propositions differentiate this design along the continuum. The prediction comes first, out of an existing theory. The research strategy and the data have to be confronted by pattern-matching. Pattern-matching is a means to compare the theoretically based predictions with the data in the site: “For case study analysis, one of the most preferred techniques is to use a pattern-matching logic. Such a logic (…) compares an empirically based pattern–that is, one based on the findings from your case study–with a predicted one made before you collected your data (….)” (Yin 2014 : 143). The comparison of propositions and the rich case material is the ground for new elements or relationships within the tentative theory.

Such findings aim to enhance the scientific usefulness of the theory (Corley and Gioia 2011 ). To enhance the validity of the new elements or relationships of the tentative theory, literal replication is a means to confirm the new findings. By that, the theory is developed by new antecedents, moderators, mediators, or outcomes. This modification or extension of the theory contributes to the analytical generalization of the theory.

If new cases provide similar results, the search for regularities is based on more solid ground. Therefore, the strength of case study research in “Gaps and Holes” lies in search for mechanisms in their specific context which can reveal causes and effects more precisely.

The “Gaps and Holes” case study research design is an adequate candidate for this phase of the theory continuum. Case studies at this point of the theory continuum, therefore, have to outline the tentative theory; to demonstrate the lacks and gaps of the tentative theory; to specify how and why the tentative theory is aimed to be extended and/or modified; to develop theoretically based propositions which guide the investigation; and to evaluate new elements, relationships, and mechanisms related to the previous theory (analytical generalization).

As a result and compared to theory-building, a different research strategy exists. While in theory building the research strategy is based on the eliciting of concepts (constructs) and relationships out of data, in theory development, it has to be demonstrated that the research strategy aims to identify new elements and relationships within a tentative theory, identifying mechanisms which explain the phenomenon more precisely.

4.3 Test of theory

In “Gaps and Holes” and “Anomalies”, an extended theory exists. The phenomenon is understood. There is no search for additional components or relationships. Mechanisms seem to explain the functioning or processes of the phenomenon. The research strategy is focused on testing whether the theory holds under different circumstances or under different conditions. Such a test of theories is mainly the domain of experimental and quantitative studies. It is based on previously developed constructs and variables which are the foundation for stating specific testable hypotheses and testing the relations on the basis of quantitative data sets. As a result, highly sophisticated statistical tools enable falsification of the theory. Therefore, testing theory in “Gaps and Holes” is restricted on specific events.

Single case can serve as a test. There is a debate in case study research whether the test of theories is related to the falsification logic of Karl Popper (Flyvbjerg 2006 ; Tsang 2013 ). Another stream of the debate is related to theoretical generalizability (Hillebrand et al. 2001 ; Welch et al. 2011 ). More specifically, test in” Gaps and Holes” is analogous to a single experiment if a single case represents a critical case. If the theory has specified a clear set of propositions and defines the exact conditions within which the theory might explain the phenomena under investigation, a single case study, testing the theory, can confirm or challenge the theory. In sum Yin states: “Overall, the single-case design is eminently justifiable under certain conditions—where the case represents (a) a critical test of existing theory, …” (Yin 2014 : 56). In their survey in the field of International Business, Welch et al. conclude: “In addition, the widespread assumption that the role of the case study lies only in the exploratory, theory-building phase of research downplays its potential to propose causal mechanisms and linkages, and test existing theories” (Welch et al. 2011 : 755).

In multiple case studies, a theoretical replication is a test of theory by comparing the findings with new cases. If a series of cases have revealed pattern-matching between propositions and the data, theoretical replication can be revealed by new waves of cases with contrasting propositions. If the contrasting propositions reveal contrasting results, the findings of the first wave are confirmed. Several possibilities exist to test the initial findings of multiple case studies using different lenses from inside and outside the management realm (Corley and Gioia 2011 ; LePine and Wilcox-King 2010 ; Okhuysen and Bonardi 2011 ; Zahra and Newey 2009 ), but have not become a standard in case study research.

In rival explanations, rival theoretical propositions are developed as a test of the previous theory. This can be distinguished from theoretical replication where contrasting propositions aim to confirm the initial findings. This can, as well, be distinguished from developing theory where rival explanations might develop theory by the elimination of possible influences (interventions, implementations). The rich data enable one to identify internal and external interventions that might be responsible for the findings. Alternative explanations in a new series of cases enable to test, whether a theory “different from the original theory explains the results better (…)” (Yin 2014 : 141).

As a result, it astonishes that theoretical replication and rival explanations, being one of the strengths of case study research, are rarely used. Although the general debate about “lenses” has informed the discussion about theory contributions, this paper demonstrates that there is a wide range of possible integration of vertical or horizontal lenses in case study research design. Case study research designs aiming to test theories have to outline modes of replication and the elimination of rival explanations.

The “anomaly approach” is placed in the final phase of the theory testing, as well. In this approach, a theory exists, but the theory fails to explain anomalies. Burawoy goes a step further. While Yin ( 2014 ) sees a critical case as a test that challenges or contradicts a well formulated theory, in Burawoy’s approach, in contrast to falsification logic (Popper 2002 ), the theory is not rejected but reconstructed. Burawoy relates extended case study design to society and history. Existing theory is challenged by intervention into the social field. Identifying processes of historical roots and social circumstances and considering external forces by structuration lead to the reconstruction of the theory.

It is surprising that this design has been neglected so far in management research. Is there no need to reflect social tensions and distortions in management research? While case study research has, per definition, to investigate phenomena in its natural environment, it is hard to understand why this design has widely been ignored in management and organization research. As a result, testing theory in case study research has to demonstrate that an extended theory exists; a critical case or an anomaly can challenge the theory; theoretical replication and rival explanations will be means to contradict or confirm the theory; and societal circumstances and external forces explain the anomaly.

Compared to theory-building (new concepts/constructs and relationships out of data) and theory development (new elements and relationships within a tentative theory), testing theory challenges extended theory by empirical investigations into failures and anomalies that the current theory cannot explain.

5 Conclusion

Case studies provide a better understanding of phenomena regarding concrete context-dependent knowledge (Andersen and Kragh 2010 ; Flyvbjerg 2006 : 224), but as literature reviews indicate, there is still confusion regarding the adequate utilization of case study methodology (Welch et al. 2011 ). This can be interpreted in a way that authors and even reviewers are not always aware of the methodological fit in case study research. Case study research is mainly narrowed to its “explorative” function, neglecting the scope of possibilities that case study research provides. The claim for more homogeneity of specified rules in case study research misses the important aspect that a method is not a means in itself, but aims at providing improved theories (van Maanen et al. 2007 ). This paper contributes to the fit of case study research designs and the theory continuum regarding the following issues.

5.1 Heterogeneity of case study designs

Although case study research, overall, has similar characteristics, it incorporates various case study research designs that have heterogeneous theoretical goals and use various elements to reach these goals. The analysis revealed that the classical understanding, whereby case study research is adequate for the “exploration” of a theory and quantitative research is adequate for “testing” theory, is oversimplified. Therefore, the theoretical goals of case study research have to be outlined precisely. This study demonstrates that there is variety of case study research designs that have thus far been largely neglected. Case study researchers can utilize the entire spectrum, but have to consider how the phenomenon is related to the theory continuum.

Case study researchers have to demonstrate how they describe new or surprising phenomena, develop new constructs and relationships, add constructs (variables), antecedents, outcomes, moderators, or mediators to a tentative theory, challenge a theory by a critical case, theoretical replication or discarding rival explanations, and reconstruct a theory by tracking failures and anomalies to external circumstances.

5.2 Methodological fit

The rigor of the case study can be enhanced by considering the specific contribution of various case study research designs in each phase of the theory continuum. This paper provides a portfolio of case study research designs that enables researchers and reviewers to evaluate whether the case study arsenal has been adequately located:

At an early phase of the theory continuum, case studies have their strengths in rich descriptions and investigations into new or surprising empirical phenomena and trends. Researchers and readers can benefit from such rich descriptions in understanding and analyzing these phenomena.

Next, on the theory continuum, there is the well-known contribution of case study research in building tentative theory by eliciting constructs or concepts and their relationships out of data.

Third, development of theories is strongly related to literal replication. Strict comparisons, on the one hand, and controlled theoretical advancement, on the other hand, enable the identification of mechanisms, strengthen the notions of causality, and provide generalizable statements.

Fourth, there are specific circumstances under which case study approaches enable one to test theories. This is to confront the theory with a critical case, to test findings of pattern-matching by theoretical replication and discarding rival explanations. Therefore, “Gaps and Holes” provide the opportunity for developing and testing theories through case study design on the theory continuum.

Finally, testing and contradicting theory are not the final rejection of a theory, but is the basis for reconstructing theory by means of case study design. Anomalies can be traced to historical sources, social processes, and external forces.

This paper demonstrates that the precise interplay of case study research designs and theory contributions on the theory continuum is a prerequisite for the contribution of case study research to better theories. If case study research design is differentiated from qualitative research, the intended contribution to theory is stated and designs that fit the aimed contribution to theory are outlined and substantiated; this will critically enhance the rigor of case study research.

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Case Study | Definition, Examples & Methods

Published on 5 May 2022 by Shona McCombes . Revised on 30 January 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organisation, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating, and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyse the case.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

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Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

Unlike quantitative or experimental research, a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

If you find yourself aiming to simultaneously investigate and solve an issue, consider conducting action research . As its name suggests, action research conducts research and takes action at the same time, and is highly iterative and flexible. 

However, you can also choose a more common or representative case to exemplify a particular category, experience, or phenomenon.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews, observations, and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data .

The aim is to gain as thorough an understanding as possible of the case and its context.

In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis, with separate sections or chapters for the methods , results , and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyse its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

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Theories are formulated to explain, predict, and understand phenomena and, in many cases, to challenge and extend existing knowledge within the limits of critical bounded assumptions or predictions of behavior. The theoretical framework is the structure that can hold or support a theory of a research study. The theoretical framework encompasses not just the theory, but the narrative explanation about how the researcher engages in using the theory and its underlying assumptions to investigate the research problem. It is the structure of your paper that summarizes concepts, ideas, and theories derived from prior research studies and which was synthesized in order to form a conceptual basis for your analysis and interpretation of meaning found within your research.

Abend, Gabriel. "The Meaning of Theory." Sociological Theory 26 (June 2008): 173–199; Kivunja, Charles. "Distinguishing between Theory, Theoretical Framework, and Conceptual Framework: A Systematic Review of Lessons from the Field." International Journal of Higher Education 7 (December 2018): 44-53; Swanson, Richard A. Theory Building in Applied Disciplines . San Francisco, CA: Berrett-Koehler Publishers 2013; Varpio, Lara, Elise Paradis, Sebastian Uijtdehaage, and Meredith Young. "The Distinctions between Theory, Theoretical Framework, and Conceptual Framework." Academic Medicine 95 (July 2020): 989-994.

Importance of Theory and a Theoretical Framework

Theories can be unfamiliar to the beginning researcher because they are rarely applied in high school social studies curriculum and, as a result, can come across as unfamiliar and imprecise when first introduced as part of a writing assignment. However, in their most simplified form, a theory is simply a set of assumptions or predictions about something you think will happen based on existing evidence and that can be tested to see if those outcomes turn out to be true. Of course, it is slightly more deliberate than that, therefore, summarized from Kivunja (2018, p. 46), here are the essential characteristics of a theory.

• It is logical and coherent
• It has clear definitions of terms or variables, and has boundary conditions [i.e., it is not an open-ended statement]
• It has a domain where it applies
• It has clearly described relationships among variables
• It describes, explains, and makes specific predictions
• It comprises of concepts, themes, principles, and constructs
• It must have been based on empirical data [i.e., it is not a guess]
• It must have made claims that are subject to testing, been tested and verified
• It must be clear and concise
• Its assertions or predictions must be different and better than those in existing theories
• Its predictions must be general enough to be applicable to and understood within multiple contexts
• Its assertions or predictions are relevant, and if applied as predicted, will result in the predicted outcome
• The assertions and predictions are not immutable, but subject to revision and improvement as researchers use the theory to make sense of phenomena
• Its concepts and principles explain what is going on and why
• Its concepts and principles are substantive enough to enable us to predict a future

Given these characteristics, a theory can best be understood as the foundation from which you investigate assumptions or predictions derived from previous studies about the research problem, but in a way that leads to new knowledge and understanding as well as, in some cases, discovering how to improve the relevance of the theory itself or to argue that the theory is outdated and a new theory needs to be formulated based on new evidence.

A theoretical framework consists of concepts and, together with their definitions and reference to relevant scholarly literature, existing theory that is used for your particular study. The theoretical framework must demonstrate an understanding of theories and concepts that are relevant to the topic of your research paper and that relate to the broader areas of knowledge being considered.

The theoretical framework is most often not something readily found within the literature . You must review course readings and pertinent research studies for theories and analytic models that are relevant to the research problem you are investigating. The selection of a theory should depend on its appropriateness, ease of application, and explanatory power.

The theoretical framework strengthens the study in the following ways :

• An explicit statement of  theoretical assumptions permits the reader to evaluate them critically.
• The theoretical framework connects the researcher to existing knowledge. Guided by a relevant theory, you are given a basis for your hypotheses and choice of research methods.
• Articulating the theoretical assumptions of a research study forces you to address questions of why and how. It permits you to intellectually transition from simply describing a phenomenon you have observed to generalizing about various aspects of that phenomenon.
• Having a theory helps you identify the limits to those generalizations. A theoretical framework specifies which key variables influence a phenomenon of interest and highlights the need to examine how those key variables might differ and under what circumstances.
• The theoretical framework adds context around the theory itself based on how scholars had previously tested the theory in relation their overall research design [i.e., purpose of the study, methods of collecting data or information, methods of analysis, the time frame in which information is collected, study setting, and the methodological strategy used to conduct the research].

By virtue of its applicative nature, good theory in the social sciences is of value precisely because it fulfills one primary purpose: to explain the meaning, nature, and challenges associated with a phenomenon, often experienced but unexplained in the world in which we live, so that we may use that knowledge and understanding to act in more informed and effective ways.

The Conceptual Framework. College of Education. Alabama State University; Corvellec, Hervé, ed. What is Theory?: Answers from the Social and Cultural Sciences . Stockholm: Copenhagen Business School Press, 2013; Asher, Herbert B. Theory-Building and Data Analysis in the Social Sciences . Knoxville, TN: University of Tennessee Press, 1984; Drafting an Argument. Writing@CSU. Colorado State University; Kivunja, Charles. "Distinguishing between Theory, Theoretical Framework, and Conceptual Framework: A Systematic Review of Lessons from the Field." International Journal of Higher Education 7 (2018): 44-53; Omodan, Bunmi Isaiah. "A Model for Selecting Theoretical Framework through Epistemology of Research Paradigms." African Journal of Inter/Multidisciplinary Studies 4 (2022): 275-285; Ravitch, Sharon M. and Matthew Riggan. Reason and Rigor: How Conceptual Frameworks Guide Research . Second edition. Los Angeles, CA: SAGE, 2017; Trochim, William M.K. Philosophy of Research. Research Methods Knowledge Base. 2006; Jarvis, Peter. The Practitioner-Researcher. Developing Theory from Practice . San Francisco, CA: Jossey-Bass, 1999.

Strategies for Developing the Theoretical Framework

I.  Developing the Framework

Here are some strategies to develop of an effective theoretical framework:

• Examine your thesis title and research problem . The research problem anchors your entire study and forms the basis from which you construct your theoretical framework.
• Brainstorm about what you consider to be the key variables in your research . Answer the question, "What factors contribute to the presumed effect?"
• Review related literature to find how scholars have addressed your research problem. Identify the assumptions from which the author(s) addressed the problem.
• List  the constructs and variables that might be relevant to your study. Group these variables into independent and dependent categories.
• Review key social science theories that are introduced to you in your course readings and choose the theory that can best explain the relationships between the key variables in your study [note the Writing Tip on this page].
• Discuss the assumptions or propositions of this theory and point out their relevance to your research.

A theoretical framework is used to limit the scope of the relevant data by focusing on specific variables and defining the specific viewpoint [framework] that the researcher will take in analyzing and interpreting the data to be gathered. It also facilitates the understanding of concepts and variables according to given definitions and builds new knowledge by validating or challenging theoretical assumptions.

II.  Purpose

Think of theories as the conceptual basis for understanding, analyzing, and designing ways to investigate relationships within social systems. To that end, the following roles served by a theory can help guide the development of your framework.

• Means by which new research data can be interpreted and coded for future use,
• Response to new problems that have no previously identified solutions strategy,
• Means for identifying and defining research problems,
• Means for prescribing or evaluating solutions to research problems,
• Ways of discerning certain facts among the accumulated knowledge that are important and which facts are not,
• Means of giving old data new interpretations and new meaning,
• Means by which to identify important new issues and prescribe the most critical research questions that need to be answered to maximize understanding of the issue,
• Means of providing members of a professional discipline with a common language and a frame of reference for defining the boundaries of their profession, and
• Means to guide and inform research so that it can, in turn, guide research efforts and improve professional practice.

Adapted from: Torraco, R. J. “Theory-Building Research Methods.” In Swanson R. A. and E. F. Holton III , editors. Human Resource Development Handbook: Linking Research and Practice . (San Francisco, CA: Berrett-Koehler, 1997): pp. 114-137; Jacard, James and Jacob Jacoby. Theory Construction and Model-Building Skills: A Practical Guide for Social Scientists . New York: Guilford, 2010; Ravitch, Sharon M. and Matthew Riggan. Reason and Rigor: How Conceptual Frameworks Guide Research . Second edition. Los Angeles, CA: SAGE, 2017; Sutton, Robert I. and Barry M. Staw. “What Theory is Not.” Administrative Science Quarterly 40 (September 1995): 371-384.

Structure and Writing Style

The theoretical framework may be rooted in a specific theory , in which case, your work is expected to test the validity of that existing theory in relation to specific events, issues, or phenomena. Many social science research papers fit into this rubric. For example, Peripheral Realism Theory, which categorizes perceived differences among nation-states as those that give orders, those that obey, and those that rebel, could be used as a means for understanding conflicted relationships among countries in Africa. A test of this theory could be the following: Does Peripheral Realism Theory help explain intra-state actions, such as, the disputed split between southern and northern Sudan that led to the creation of two nations?

However, you may not always be asked by your professor to test a specific theory in your paper, but to develop your own framework from which your analysis of the research problem is derived . Based upon the above example, it is perhaps easiest to understand the nature and function of a theoretical framework if it is viewed as an answer to two basic questions:

• What is the research problem/question? [e.g., "How should the individual and the state relate during periods of conflict?"]
• Why is your approach a feasible solution? [i.e., justify the application of your choice of a particular theory and explain why alternative constructs were rejected. I could choose instead to test Instrumentalist or Circumstantialists models developed among ethnic conflict theorists that rely upon socio-economic-political factors to explain individual-state relations and to apply this theoretical model to periods of war between nations].

The answers to these questions come from a thorough review of the literature and your course readings [summarized and analyzed in the next section of your paper] and the gaps in the research that emerge from the review process. With this in mind, a complete theoretical framework will likely not emerge until after you have completed a thorough review of the literature .

Just as a research problem in your paper requires contextualization and background information, a theory requires a framework for understanding its application to the topic being investigated. When writing and revising this part of your research paper, keep in mind the following:

• Clearly describe the framework, concepts, models, or specific theories that underpin your study . This includes noting who the key theorists are in the field who have conducted research on the problem you are investigating and, when necessary, the historical context that supports the formulation of that theory. This latter element is particularly important if the theory is relatively unknown or it is borrowed from another discipline.
• Position your theoretical framework within a broader context of related frameworks, concepts, models, or theories . As noted in the example above, there will likely be several concepts, theories, or models that can be used to help develop a framework for understanding the research problem. Therefore, note why the theory you've chosen is the appropriate one.
• The present tense is used when writing about theory. Although the past tense can be used to describe the history of a theory or the role of key theorists, the construction of your theoretical framework is happening now.
• You should make your theoretical assumptions as explicit as possible . Later, your discussion of methodology should be linked back to this theoretical framework.
• Don’t just take what the theory says as a given! Reality is never accurately represented in such a simplistic way; if you imply that it can be, you fundamentally distort a reader's ability to understand the findings that emerge. Given this, always note the limitations of the theoretical framework you've chosen [i.e., what parts of the research problem require further investigation because the theory inadequately explains a certain phenomena].

The Conceptual Framework. College of Education. Alabama State University; Conceptual Framework: What Do You Think is Going On? College of Engineering. University of Michigan; Drafting an Argument. Writing@CSU. Colorado State University; Lynham, Susan A. “The General Method of Theory-Building Research in Applied Disciplines.” Advances in Developing Human Resources 4 (August 2002): 221-241; Tavallaei, Mehdi and Mansor Abu Talib. "A General Perspective on the Role of Theory in Qualitative Research." Journal of International Social Research 3 (Spring 2010); Ravitch, Sharon M. and Matthew Riggan. Reason and Rigor: How Conceptual Frameworks Guide Research . Second edition. Los Angeles, CA: SAGE, 2017; Reyes, Victoria. Demystifying the Journal Article. Inside Higher Education; Trochim, William M.K. Philosophy of Research. Research Methods Knowledge Base. 2006; Weick, Karl E. “The Work of Theorizing.” In Theorizing in Social Science: The Context of Discovery . Richard Swedberg, editor. (Stanford, CA: Stanford University Press, 2014), pp. 177-194.

Writing Tip

Borrowing Theoretical Constructs from Other Disciplines

An increasingly important trend in the social and behavioral sciences is to think about and attempt to understand research problems from an interdisciplinary perspective. One way to do this is to not rely exclusively on the theories developed within your particular discipline, but to think about how an issue might be informed by theories developed in other disciplines. For example, if you are a political science student studying the rhetorical strategies used by female incumbents in state legislature campaigns, theories about the use of language could be derived, not only from political science, but linguistics, communication studies, philosophy, psychology, and, in this particular case, feminist studies. Building theoretical frameworks based on the postulates and hypotheses developed in other disciplinary contexts can be both enlightening and an effective way to be more engaged in the research topic.

CohenMiller, A. S. and P. Elizabeth Pate. "A Model for Developing Interdisciplinary Research Theoretical Frameworks." The Qualitative Researcher 24 (2019): 1211-1226; Frodeman, Robert. The Oxford Handbook of Interdisciplinarity . New York: Oxford University Press, 2010.

Another Writing Tip

Don't Undertheorize!

Do not leave the theory hanging out there in the introduction never to be mentioned again. Undertheorizing weakens your paper. The theoretical framework you describe should guide your study throughout the paper. Be sure to always connect theory to the review of pertinent literature and to explain in the discussion part of your paper how the theoretical framework you chose supports analysis of the research problem or, if appropriate, how the theoretical framework was found to be inadequate in explaining the phenomenon you were investigating. In that case, don't be afraid to propose your own theory based on your findings.

Yet Another Writing Tip

What's a Theory? What's a Hypothesis?

The terms theory and hypothesis are often used interchangeably in newspapers and popular magazines and in non-academic settings. However, the difference between theory and hypothesis in scholarly research is important, particularly when using an experimental design. A theory is a well-established principle that has been developed to explain some aspect of the natural world. Theories arise from repeated observation and testing and incorporates facts, laws, predictions, and tested assumptions that are widely accepted [e.g., rational choice theory; grounded theory; critical race theory].

A hypothesis is a specific, testable prediction about what you expect to happen in your study. For example, an experiment designed to look at the relationship between study habits and test anxiety might have a hypothesis that states, "We predict that students with better study habits will suffer less test anxiety." Unless your study is exploratory in nature, your hypothesis should always explain what you expect to happen during the course of your research.

The key distinctions are:

• A theory predicts events in a broad, general context;  a hypothesis makes a specific prediction about a specified set of circumstances.
• A theory has been extensively tested and is generally accepted among a set of scholars; a hypothesis is a speculative guess that has yet to be tested.

Cherry, Kendra. Introduction to Research Methods: Theory and Hypothesis. About.com Psychology; Gezae, Michael et al. Welcome Presentation on Hypothesis. Slideshare presentation.

Still Yet Another Writing Tip

Be Prepared to Challenge the Validity of an Existing Theory

Theories are meant to be tested and their underlying assumptions challenged; they are not rigid or intransigent, but are meant to set forth general principles for explaining phenomena or predicting outcomes. Given this, testing theoretical assumptions is an important way that knowledge in any discipline develops and grows. If you're asked to apply an existing theory to a research problem, the analysis will likely include the expectation by your professor that you should offer modifications to the theory based on your research findings.

Indications that theoretical assumptions may need to be modified can include the following:

• Your findings suggest that the theory does not explain or account for current conditions or circumstances or the passage of time,
• The study reveals a finding that is incompatible with what the theory attempts to explain or predict, or
• Your analysis reveals that the theory overly generalizes behaviors or actions without taking into consideration specific factors revealed from your analysis [e.g., factors related to culture, nationality, history, gender, ethnicity, age, geographic location, legal norms or customs , religion, social class, socioeconomic status, etc.].

Philipsen, Kristian. "Theory Building: Using Abductive Search Strategies." In Collaborative Research Design: Working with Business for Meaningful Findings . Per Vagn Freytag and Louise Young, editors. (Singapore: Springer Nature, 2018), pp. 45-71; Shepherd, Dean A. and Roy Suddaby. "Theory Building: A Review and Integration." Journal of Management 43 (2017): 59-86.

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Abstract: The appropriateness of case studies as a tool for theory testing is still a controversial issue, and discussions about the weaknesses of such research designs have previously taken precedence over those about its strengths. The purpose of the paper is to examine and revive the approach of theory testing using case studies, including the associated research goal, analysis, and generalisability. We argue that research designs for theory testing using case studies differ from theory-building case study research designs because different research projects serve different purposes and follow different research paths.

Keywords: Case studies, theory testing, research paths

1. Introduction

Research based on case studies can take many forms. Case study research can depart in a positivist or interpretivist approach, it can be deductive or inductive, and it can rely on qualitative or quantitative methods. It can also be a mix of these extremes (Cavaye 1996). Using case studies is, however, still perceived as a less conventional manner of testing theories in many research communities (Cavaye 1996). This is so regardless of the fact that research capacities already in the 1970s made the following propositions: '[c]ase studies... are valuable at all stages of the theory building process, but most valuable at that stage of theory building where least value is generally attached to them: the stage at which candidate theories are "tested"' (Eckstein 1975: 80); and that case studies are useful 'particularly to examine a single exception that shows the hypothesis to be false' (Stake 1978: 7).

Today, we propose that case studies are still an overlooked source of theory refinement and development. Extending the value of case studies to that of theory development within a larger research programme is regrettably still a contested issue.

A research design based on case studies as a means for testing theories has not previously been examined comprehensively. Often the weaknesses of such research designs have taken precedence over reflections about its strengths. In this paper, we approach the debate from a different stance, arguing that case studies can indeed be a valuable tool for testing theories.

Thus, the purpose of the paper is to examine theory testing using case studies, including the associated research goal, analysis, and generalisability. In this respect, it is argued that the research design for theory testing using case studies differs from the design of theory building using case studies because different research projects serve different purposes and follow different research paths.

To promote the argument, we revitalise the notions of both 'testing' and 'theories' in a wider sense than is usually done. We suggest two specific research paths that serve as structured and legitimate frameworks for thinking about case research designs for theory testing. Finally, we elaborate on what consequences theory testing using case studies has on different elements of a research design, in particular the generalisability issues.

2. Theoretical Research Paths for Case Studies

Research based on a case study focuses on a single setting or unit that is spatially and temporally bounded (Eisenhardt 1989, Van Maanen 1979). Sometimes it can be difficult to specify where the case ends and the environment begins, but here boundedness, contexts, and experience can be useful concepts (Stake 2006).

Overall, the advantage of a case study is that it 'can "close-in" on real-life situations and test views directly in relation to phenomena as they unfold in practice' (Flyvbjerg 2004: 428).

Each case can contain embedded cases (Yin 2014). The essence of a case study is the case, understood as the choice of study object(s) and the framing of these (Stake 2000). In principle, any technique for collecting data is applicable, even if case studies are often mistakenly presented as a qualitative method (Eisenhardt 1989).

Case studies may serve different research goals (Maxwell 2005). For instance, Eisenhardt (1989) specifies three such goals: description, theory testing, and theory generation. The connection between elements in the research design is ensured by a research strategy (Maxwell 2005), which becomes 'a way of linking ideas and evidence to produce a representation of some aspect of social life' (Ragin 1994: 48).

Brinberg and McGrath (1985) suggest that research paths progress through three different domains: a substantive 'real-world' domain (S), a conceptual domain (C), and a methodological domain (M). Each domain can be a starting point for conducting research, and any study covers all three domains. Mapping out a research strategy thus starts with the choice of the primary domain of interest, then the second domain, and, finally, the third domain. The domains are interrelated and the researcher works iteratively between them, so the presentation in the following is a representation and not a cookbook recipe. Being clear about a study's starting point benefits researchers because it promotes the understanding of the study itself and gives an overview, as well as helps in expressing its results and contributions to a research programme.

For our purpose, we are interested in the type of research path that Brinberg and McGrath (1985) identify as a theoretical path leading to an end product of tested hypotheses. While many case studies take their starting point in the substantive domain, a theoretical research path also describes a situation where a study focuses on the conceptual domain and in which the cases are instrumental to the theoretical contribution. Theoretical paths are thus either concept-driven or system-driven (Brinberg and McGrath 1985). While we focus mainly on concept-driven paths in the following, the outcome of the two paths may appear similar, cf. Figure 1.

Concept-driven theoretical paths focus on understanding the explanation(s) underlying a phenomenon (Brinberg and McGrath 1985). Such a research path matches a research design built on, for instance, rival theories, a design in which multiple theories are compared in order to assess their relative value in terms of strengths, weaknesses, boundaries, and other relevant dimensions. Examples of research questions to this path could be 'Is the original theory correct? Does the original theory fit other circumstances? Are there additional categories or relationships?' (Crabtree and Miller 1999: 7).

System-driven theoretical paths focus on understanding an empirical system (Brinberg and McGrath 1985). For a system-driven theoretical path, we suggest a matching theory-testing case study research design using multiple theories to examine the system from different angles (triangulation).

Similar conceptualisations have been denoted analytic induction (Patton 2002) and explanatory case studies (Yin 2014). However, analytic induction builds on cross-case analyses, and explanatory studies examine how a particular situation or event may be explained by one or more theories. Only to a lesser degree does the latter focus on the theory as such, and therefore explanatory studies represent system-driven theoretical study paths. We argue that both types are subsets of theory-testing studies.

The line between system-driven and concept-driven case studies is blurred and several purposes may be served within the same study. A classic example from political science is the advent of revolutions and wars (George and Bennett 2005). Here the variables come partly from the cases and partly from prior theoretical explanations.

3. The Role of Theory for Theoretical Research Paths

In order to discuss the role of theories for theoretical research paths (c.f. Brinberg and McGrath 1985), of which theory testing using case studies is an example, we need to define both the concept of theory and theory-testing.

In the literature theory is defined more or less accurately (Andersen and Kragh 2010) and is often mistakenly refered to as models and propositions (Sutton and Staw 1995). Doty and Click (1994) define theory as 'a series of logical arguments that specifies a set of relationships among concepts, constructs, or variables'. Such a definition allows for theories to be conceptualised at different levels - for instance, conceptual, construct, and variable levels. The purpose of theories is to explain why (Sutton and Staw 1995) - which again explains how. So, theories are explanations.

Theories as explanations are important for case studies in several ways (c.f. Walsham 1995). First, they are always present as the researcher's implicit and explicit understanding of what is going on with the studied phenomenon. With minor differences, this role of theory is referred to as 'conceptual context' (Maxwell 2005), 'conceptual domain' (Brinberg and McGrath 1985), or 'analytical frames' (Ragin 1994).

Second, theories explicitly provide analytical guidelines and serve as 'a heuristic for collecting and organising data' (Colville et al. 1999). In a theory-testing case study, the researcher specifies a priori to data collection the types and content of data to be collected. These a priori-specified data requirements are the minimum amount of data satisfying the analytical needs. Theories are a useful tool for handling the large amounts of data in case studies because '[scanning all variables is not the same as including all variables' (Lijphart 1971: 690).

Third, theories as an object of interest can be developed, modified, and tested using case studies and thus serve as both input and output to the study (Campbell 1975, Eckstein 1975, Yin 2014). Theories-as-object is the special focus when case studies are used for theory testing, which distinguishes them from other types of case studies.

In this sense, theories allow for a focus on key variables, leading to the required parsimony of analysis. Thus, when the purpose of a case study is theory testing, not only in-depth knowledge of the case(s) and the methods is needed, but also knowledge of the theories involved.

Consider the meaning and implications of the terms 'test' and 'testing'. Many researchers seem to think of testing in a narrow sense: a specified and near-conclusive procedure for falsification or verification. We rely on a more inclusive definition. For instance, Crabtree and Miller specifically state that the goal of theory testing is 'to test explanatory theory by evaluating it in different contexts' (1999: 7). Likewise, Yin (2014) argues that theory testing is a matter of external validity and can be seen as the replication of case studies with the purpose of identifying whether previous results extend to new cases.

When a researcher conducts a theory test, then propositions, i.e., logical conclusions or predictions, are derived from the theory and are compared to observations, or data, in the case (Cavaye 1996). The more often and the more conclusively the theory is confirmed, the more faith in that the theory reflects reality (Cavaye 1996).

Theory testing is in contrast to theory-building case studies, where the latter are defined as 'the process through which researchers seek to make sense of the observable world by conceptualizing, categorizing and ordering relationships among observed elements' (Andersen and Kragh 2010). The case plays a different role whether it is used for theory testing or theory building, c.f. Figure 2. In theory testing using case studies, propositions are selected and articulated beforehand, as well as used dynamically in all other phases of the research process. The role of the case thus becomes instrumental, meaning that '[t]he case is of secondary interest, it plays a supportive role, and it facilitates our understanding of something else' (Stake 2000: 437).

The contributions from theory testing case studies can be diverse '...to strengthen or reduce support for a theory, narrow or extend the scope conditions of a theory, or determine which of two or more theories best explains a case, type, or general phenomenon' (George and Bennett 2005: 109). The classical study of theory testing using a case study is Allison's (1971) application of three different decision-making perspectives in the analysis of the Cuban Missile Crisis, but we find other types where case studies have been used for theory testing (e.g., Argyris 1979, Pinfield 1986, Jobber and Lucas 2000, Trochim 1985, Jauch et al. 1980, Brown 1999, Lee et al. 1996).

4. Theory Testing Case Study Design

When a researcher decides on theory testing using case studies, it affects different elements of a research design, as summarised in Table 1. A researcher doing a theory testing case study spends relatively more time preparing for data collection and analysis, making extant theories explicit and setting up the analytical framework.

4.1 Research goals

Consistent with the concept-driven theoretical path, testing of competing theories may be a research goal in itself. The competing perspectives approach aims to rule out less effective explanations, often looking for the one explanation that best explains a phenomenon, or to establish the boundaries of a theory's application.

The system-driven theoretical path is equivalent to theory triangulation. Comparing complementary theories is a form of triangulation (Brinberg and McGrath 1985): 'The point... is to understand how differing assumptions and premises affect findings and interpretations' (Patton 2002: 562). The complementary perspective thus sees each theory as contributing to understanding.

Identifying the relevant theories to include in a case study is a selection process: In some cases, the choice of theories to be included is unproblematic. In other instances, it may be difficult to distinguish distinct theories within a field, especially when a research field is emerging and everybody is trying to break new ground. Such diversity is one reason why theory testing using case studies is relevant, since the literature must be systematised prior to data collection.

4.2 Pre-data collection work on theories

Prior to data collection, theories are 'operationalised' in terms of the minimum data requirements and propositions to be matched with empirical data, thus addressing construct validity. Several levels and elements of the same theory, or rather the pattern that the theory constitutes, can be evaluated through multiple propositions and multiple theories because of the amount of data from the case study (Campbell 1975).

4.3 Analysis

Analytically, in-depth knowledge of theories facilitates moving from emic to etic accounts of a phenomenon. Ernie conceptualisations are those given by case informants, while etic conceptualisations are researchers' interpretations (Maxwell 2005). In terms of specific analytical techniques, Campbell (1975) suggested degrees- of-freedom analysis, which has been exemplified by, for example, Wilson and Woodside (1999). Ragin and co- workers (Ragin 1994) have developed techniques for analysing both crisp and fuzzy case data sets. Knowledge of prior theory also has potential risks. If, for instance, a researcher is too emotionally attached to certain explanations, (s)he runs the risk of ignoring conflicting information. Rival explanations might be a way of mitigating such a risk. However, knowledge of prior theory can also be argued to free 'mental' resources to look for alternative explanations and elements. Researchers will have excess information processing capacity to include additional thought experiments and iterations between theory and data (c.f. Campbell 1975), because familiar information can be processed faster and with less basic analytical work.

4.4 Validity and generalisation

The majority of the methodological literature describes quantitative and qualitative studies as associated with generalisation and particularisation, respectively. The result is that notions of theory testing, which are associated with generalisation purposes, in small-N studies, which are associated with particularisation purposes, are controversial topics in many research communities. Such scepticism includes theory testing using case studies. In a case study design, however, the methods applied for data collection do not determine whether the purpose is generalisation or particularisation. Therefore, the assumption that case studies cannot be applied for generalisation purposes is questionable.

Still, there are different views as to whether generalisations from case studies are possible. Some claim that inference is possible (e.g., Yin), whereas others reject this (e.g., Stake, Kennedy, Lincoln & Cuba) and argue that readers of case study reports are themselves responsible for whether there can be a 'transferability' of findings from one situation to another (Gomm et al. 2000).

Yin (2014) considers the case as an experiment and claims that case studies can lead to analytic generalisations, Le., a generalisation on a conceptual higher level than the case. Such analytical generalisation is based on 'a) corroborating, modifying, rejecting, or otherwise advancing theoretical concepts that you referenced in designing your case study or b) new concepts that arose upon the completion of your case study' (Yin 2014: 40). Thus, according to Yin, a case study is generalisable to theoretical propositions and not populations (Swanborn 2010: 66). Analytical generalisations involve a judgement about whether the findings of one study can be a guide to what occurs in another situation and include a comparison of the two situations (Brinkman and Kvale 2015).

Stake rejects a scientific induction from case studies but talks about a naturalistic generalizability which is developed within people based on their experience (Stake 1978, 1995). Often these generalisations are not predictions, but rather lead to expectations (Stake 1978). 'They may become verbalized, passing of course from tacit knowledge to propositional; but they have not yet passed the empirical and logical tests that characterize formal (scholarly, scientific) generalizations' (Gomm et al. 2000).

Kennedy (1979) claims that generalisation is a judgment of degree. The researcher should produce and share the information, and after this the receiver judges whether the findings can be generalised to the receiver's situation. Here it is of course essential that the researcher makes a detailed description of the specific case characteristics, because s(he) does not know who the receivers are (Kennedy 1979).

The logic behind theory testing supports the idea of generalisation from prior studies and their outcomes to an actual study, and from an actual study to theories (Lee and Baskerville 2003, Yin 2014). Two assumptions are present here. First, verification in the sense of 'ultimately true' is not possible except for trivial facts (Lakatos 1970). Second, verification and falsification are not opposites. The opposite of falsification is confirmation or corroboration-words that more accurately denote the outcome, namely an ongoing process of theory testing and theory development.

In terms of internal validity, rival explanations can be included because: 'the more rivals that your analysis addresses and rejects, the more confidence you can place in your findings' (Yin 2003: 113). Explicit consideration of alternative explanations for findings increases the credibility of a study, and here we use the entire range of rival explanations, not just theories (see Yin 2000, 2003).

The pursuit of generalisations typically goes together with a search for causes (Stake 2006). It is often claimed that case studies contribute by giving the opportunity of identifying causalities because cases are examined deeply and longitudinal (Gomm et al. 2000). Unlike an experiment, cases 'investigate causal processes "in the real world" rather than in artificially created settings' (Gomm et al. 2000).

However, we know that case studies are useful when the phenomenon under investigation is complex. Such complexity has many faces and can be seen, for instance, when phenomena interrelate, occur at multiple levels of analysis (e.g., span individual and group levels), or when they can only be understood as embedded in a larger context.

If the phenomenon being studied is too complex, a search for 'simple' causalities, however, becomes hopeless.

Nevertheless, cases can be seen as manifestations of more general phenomena and therefore embody the essence of those phenomena (c.f. Becker 1998, Gerring 2004).

4.4.1 Sampling

Generalisation in theory-testing case studies is closely related to the issue of sampling. It is, however, not merely a function of the number of cases observed, but rather the range of characteristics of the units and the range of conditions occurred under observation (Kennedy 1979). 'The range of characteristics included in a sample increases the range of population characteristics to which generalization is possible' (Kennedy 1979).

In line with this, we suggest that the number of cases is considered from what is added from each new case in terms of analytical benefits. Figure 3 outlines the relationship between the number of theories and the number of cases. When the number of theories and their propositions or 'variables' to be tested is small, multiple case studies are an obvious choice to investigate the boundaries of those theories in different settings. As the number of theories to be evaluated grows, a single case study may yield more credibility in the findings, because all theories are evaluated against the same material. The 'efficiency boundary' represents the interaction points where a thorough analysis is feasible and credible. It may be shifted outwards if more researchers are involved in a study, or if a researcher has special skills, experience, or insights with respect to the cases or the theories, because the pooled information processing capacity is increased and more relationships between theory and data can be handled.

Besides choosing the number of cases, strategic or purposeful case selection is essential for generalisation (Flyvbjerg 2004). Theory testing using case studies relies by definition on theoretical sampling where cases are chosen on the basis of theoretical criteria (Eisenhardt 1989, Patton 2002, Wilson and Vlosky 1997). In addition, we rely on information-oriented selection where '[cjases are selected on the basis of expectations about their information content' (Flyvbjerg 2004: 426), i.e., their potential for learning (Stake 2000: 446). Diverging ideas prevail regarding the benefits of one or multiple cases relative to generalisation. Yin argues that more cases provide stronger conclusions (2014), while Stake claims 'conclusions from differences between any two cases are less to be trusted than conclusions about one' and argues that comparisons might impede learning from the particular (Stake 2000: 444). In short, the number and type of cases relative to generalisability depends upon research questions and goals.

5. Theory Development

Case studies contribute to the development and refinement of research programmes along with other types of research. Much methodological literature seems to favour the use of cases for descriptive and explorative purposes, that is, early in the development of a research field or a study. Case studies are, however, sources of learning throughout the progress of a larger research programme (Campbell 1975, Eckstein 1975). For instance, case studies add depth to understanding that may arise from completed large-N studies (Patton 2002), they illuminate mechanisms and relations (Gerring 2004), and, of course, they are unique for learning from the particular (Stake 2000).

Research programmes 'connect' researchers through series of related theories and have a 'hard core' of assumptions which are not questioned and a protective belt of auxiliary hypotheses (Lakatos 1970). Findings in theory testing using case studies will often be related to the protective belt, but as fundamentally different ('paradigmatic') theories are evaluated, outcomes may also be related to the hard core.

Critiques have been made against case studies for 'having a bias towards verification, understood as a tendency to confirm the researcher's preconceived notions' (Flyvbjerg 2004: 428). The risk of confirming existing ideas and beliefs does not, however, seem to be an observed problem in case study research. Researchers often report that they change or discharge their original ideas as they gain additional insights during a case study (c.f. Campbell 1975, Flyvbjerg 2004, Lee and Baskerville 2003).

So rather than seeing one piece of counterevidence (or one case) as falsification, we use Lakatos' distinction between naïve and sophisticated falsification. Lakatos (1970: 120) suggests: 'falsification is not simply a relation between a theory and the empirical basis, but a multiple relation between competing theories, the original "empirical basis", and the empirical growth resulting from the competition'.

Lakatos nuances the issue of falsification by introducing the notion of sophisticated falsification, in which 'a theory is "acceptable" or "scientific" only if it has corroborated excess empirical content over its predecessor (or rival), that is, only if it leads to the discovery of novel facts' (Lakatos 1970:116).

In comparison, naïve falsificationists, following a Popperian argument, claim that a theory can be falsified by an 'observational' conflicting statement. To sophisticated falsificationists, a theory is falsified if another theory is proposed, fulfilling the requirements mentioned. Naïve falsification is therefore not a sufficient condition for eliminating a theory: 'in spite of hundreds of known anomalies we do not regard it as falsified (that is, eliminated) until we have a better one' (Lakatos 1970: 121).

When results in case studies indicate falsification or anomalies, we have two options: Either to suggest a new theory within a different research programme (abandon the hard core), or to explain anomalies using auxiliary hypotheses (modify the protective belt). In this sense theory testing using case studies is valuable at any stage in the theory development process as long as it has a positive and progressive effect on a research programme.

6. Concluding Remarks

We conclude that a research design built on theory testing using case studies contributes in several ways. Theory testing using case studies evaluates the explanatory power of theories and their boundaries, thus assessing external validity. In summary, the range of theories' applicability and usability is explored, thereby positioning such research in a stream of cumulative research that refines and develops the knowledge of a field. Theory testing using case studies is an overlooked and undervalued research strategy that can follow different paths. We seek to fill a gap in the literature to facilitate the understanding of this research strategy and to make it a legitimate research path. With this paper, we encourage researchers to experiment more with theory testing using case studies and to engage in the formulation of the epistemology of the particular.

Acknowledgements

We would like to thank the following people for their comments and feedback during the writing process: At Aalborg University, Professor Poul Houman Andersen; at the University of Southern Denmark, Associate Professors Bo Eriksen, Karsten Boye Rasmussen, and Per 0stergaard, as well as Head of Department Jeanette Lemmergaard; and, at Aarhus University, Associate Professor Emeritus Erik Maalpe.

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Ann-Kristina Lokke1 and Pernille Dissing S0rensenz

department of Economics and Business,School of Business and Social Sciences, Aarhus University

interdisciplinary Centre for Organizational Architecture (ICOA), School of Business and Social Sciences, Fuglesangs Allé 4

[email protected]

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Copyright Academic Conferences International Limited Jul 2014

The appropriateness of case studies as a tool for theory testing is still a controversial issue, and discussions about the weaknesses of such research designs have previously taken precedence over those about its strengths. The purpose of the paper is to examine and revive the approach of theory testing using case studies, including the associated research goal, analysis, and generalisability. We argue that research designs for theory testing using case studies differ from theory-building case study research designs because different research projects serve different purposes and follow different research paths.

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The Ultimate Guide to Qualitative Research - Part 1: The Basics

• Introduction and overview
• What is qualitative research?
• What is qualitative data?
• Examples of qualitative data
• Qualitative vs. quantitative research
• Mixed methods
• Qualitative research preparation
• Theoretical perspective
• Theoretical framework
• Literature reviews
• Research question
• Conceptual framework
• Introduction

Revisiting theoretical frameworks

Revisiting conceptual frameworks, differences between conceptual and theoretical frameworks, examples of theoretical and conceptual frameworks, developing frameworks for your study.

• Data collection
• Qualitative research methods
• Focus groups
• Observational research
• Case studies
• Ethnographical research
• Ethical considerations
• Confidentiality and privacy
• Power dynamics
• Reflexivity

Conceptual vs. theoretical framework

Theoretical and conceptual frameworks are both essential components of research, guiding and structuring the research. Although they are closely related, the conceptual and theoretical framework in any research project serve distinct purposes and have different characteristics. In this section, we provide an overview of the key differences between theoretical and conceptual frameworks.

Theoretical and conceptual frameworks are foundational components of any research study. They each play a crucial role in guiding and structuring the research, from the formation of research questions to the interpretation of results .

While both the theoretical and conceptual framework provides a structure for a study, they serve different functions and can impact the research in distinct ways depending on how they are combined. These differences might seem subtle, but they can significantly impact your research design and outcomes, which is why it is important to think through each one of them.

The theoretical framework describes the broader lens through which the researcher views the topic and guides their overall understanding and approach. It connects the theoretical perspective to the data collection and data analysis strategy and offers a structure for organizing and interpreting the collected data.

On the other hand, the conceptual framework describes in detail and connects specific concepts and variables to illustrate potential relationships between them. It serves as a guide for assessing which aspects of the data are relevant and specifying how the research question is being answered. While the theoretical framework outlines how more abstract-level theories shape the study, the conceptual framework operationalizes the empirical observations that can be connected to theory and broader understanding.

Understanding these differences is crucial when designing and conducting your research study. In this chapter, we will look deeper at the distinctions between these types of frameworks, and how they interplay in qualitative research . We aim to provide you with a solid understanding of both, allowing you to effectively utilize them in your own research.

Theoretical frameworks play a central role in research, serving as the bedrock of any investigation. This section offers a refresher on the essential elements and functions of theoretical frameworks in research.

A theoretical framework refers to existing theory, concepts, and definitions that you use to collect relevant data and offer meaningful empirical findings. Providing an overall orientation or lens, it guides your understanding of the research problem and directs your approach to data collection and analysis .

Your chosen theoretical framework directly influences your research questions and methodological choices . It contains specific theories or sets of assumptions drawn from relevant disciplines—such as sociology, psychology, or economics—that you apply to understand your research topic. These existing models and concepts are tools to help you organize and make sense of your data.

The theoretical framework also plays a key role in crafting your research questions and objectives. By determining the theories that are relevant to your research, the theoretical framework shapes the nature and direction of your study. It's essential to note, however, that the theoretical framework's role in qualitative research is not to predict outcomes. Instead, it offers a broader structure to understand and interpret your data, enabling you to situate your findings within the broader academic discourse in a way that makes your research findings meaningful to you and your research audience.

Conceptual frameworks , though related to theoretical frameworks , serve distinct functions within research. This section reexamines the characteristics and functions of conceptual frameworks to provide a better understanding of their roles in qualitative research .

A conceptual framework, in essence, is a system of concepts, assumptions, and beliefs that supports and informs your research. It outlines the specific variables or concepts you'll examine in your study and proposes relationships between them. It's more detailed and specific than a theoretical framework, acting as a contextualized guide for the collection and interpretation of empirical data.

The main role of a conceptual framework is to illustrate the presumed relationships between the variables or concepts you're investigating. These variables or concepts, which you derive from your theoretical framework, are integral to your research questions , objectives, and hypotheses . The conceptual framework shows how you theorize these concepts are related, providing a visual or narrative model of your research.

A study's own conceptual framework plays a vital role in guiding the data collection process and the subsequent analysis . The conceptual framework specifies which data you need to collect and provides a structure for interpreting and making sense of the collected data. For instance, if your conceptual framework identifies a particular variable as impacting another, your data collection and analysis will be geared towards investigating this relationship.

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Though interconnected, theoretical and conceptual frameworks have distinct roles in research and contribute differently to the research. This section will contrast the two in terms of scope, purpose, their role in the research process, and their relationship to the data analysis strategy and research question .

Scope and purpose of theoretical and conceptual frameworks

Theoretical and conceptual frameworks differ fundamentally in their scope. Theoretical frameworks provide a broad and general view of the research problem, rooted in established theories. They explain phenomena by applying a particular theoretical lens. Conceptual frameworks, on the other hand, offer a more focused view of the specific research problem. They explicitly outline the concrete concepts and variables involved in the study and the relationships between them.

While both frameworks guide the research process, they do so in different ways. Theoretical frameworks guide the overall approach to understanding the research problem by indicating the broader conversation the researcher is contributing to and shaping the research questions.

Conceptual frameworks provide a map for the study, guiding the data collection and interpretation process, including what variables or concepts to explore and how to analyze them.

Study design and data analysis

The two types of frameworks relate differently to the research question and design. The theoretical framework often inspires the research question based on previous theories' predictions or understanding about the phenomena under investigation. A conceptual framework then emerges from the research question, providing a contextualized structure for what exactly the research will explore.

Theoretical and conceptual frameworks also play distinct roles in data analysis. Theoretical frameworks provide the lens for interpreting the data, informing what kinds of themes and patterns might be relevant. Conceptual frameworks, however, present the variables concepts and variables and the relationships among them that will be analyzed. Conceptual frameworks may illustrate concepts and relationships based on previous theory, but they can also include novel concepts or relationships that stem from the particular context being studied.

Finally, the two types of frameworks relate differently to the research question and design. The theoretical framework basically differs from the conceptual framework in that it often inspires the research question based on the theories' predictions about the phenomena under investigation. A conceptual framework, on the other hand, emerges from the research question, providing a structure for investigating it.

Using case studies , we can effectively demonstrate the differences between theoretical and conceptual frameworks. Let’s take a look at some real-world examples that highlight the unique role and function of each framework within a research context.

Consider a study exploring the impact of classroom environments on student learning outcomes. The theoretical framework might be grounded in Piaget's theory of cognitive development, which offers a broad lens for understanding how students learn and process information.

Within this theoretical framework, the researcher formulates the conceptual framework. The conceptual framework identifies specific variables to study such as classroom layout, teacher-student ratio, availability of learning materials, and student performance as the dependent variable. It then outlines the expected relationships between these variables, such as proposing that a lower teacher-student ratio and well-equipped classrooms positively impact student performance.

Another study might aim to understand the factors influencing the job satisfaction of employees in a corporate setting. The theoretical framework could be based on Maslow's hierarchy of needs, interpreting job satisfaction in terms of fulfilling employees' physiological, safety, social, esteem, and self-actualization needs.

From this theoretical perspective, the researcher constructs the conceptual framework, identifying specific variables such as salary (physiological needs), job security (safety needs), teamwork (social needs), recognition (esteem needs), and career development opportunities (self-actualization needs). The conceptual framework proposes relationships among these variables and job satisfaction, such as higher salaries and more recognition being related to higher job satisfaction.

After understanding the unique roles and functions of these types of frameworks, you might ask: How do I develop them for my study? It's essential to remember that it's not a question of choosing one over the other, as both frameworks can and often do coexist within the same research project.

The choice of a theoretical and a conceptual framework often depends on the nature of your research question . If your research question is more exploratory and requires a broad understanding of the problem, a theoretical framework can provide a useful lens for interpretation. However, your conceptual framework may end up looking rather different to previous theory as you collect data and discover new concepts or relationships.

Consider the nature of your research problem as well. If you are studying a well-researched problem and there are established theories about it, using a theoretical framework to interpret your findings in light of these theories might be beneficial. But if your study explores a novel problem or aims to understand specific processes or relationships, developing a conceptual framework that maps these specific elements could prove more effective.

Your research methodology could also inform your choice. If your study is more interpretive and aims to understand people's experiences and perceptions, a theoretical framework can outline broader concepts that are relevant to approaching your study. Your conceptual framework can then shed light on the specific concepts that emerged in your data. By carefully thinking through your theoretical and conceptual frameworks, you can effectively utilize both types of frameworks in your research, ensuring a solid foundation for your study.

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• v.21(3); Fall 2022

Literature Reviews, Theoretical Frameworks, and Conceptual Frameworks: An Introduction for New Biology Education Researchers

Julie a. luft.

† Department of Mathematics, Social Studies, and Science Education, Mary Frances Early College of Education, University of Georgia, Athens, GA 30602-7124

Sophia Jeong

‡ Department of Teaching & Learning, College of Education & Human Ecology, Ohio State University, Columbus, OH 43210

Robert Idsardi

§ Department of Biology, Eastern Washington University, Cheney, WA 99004

Grant Gardner

∥ Department of Biology, Middle Tennessee State University, Murfreesboro, TN 37132

Associated Data

To frame their work, biology education researchers need to consider the role of literature reviews, theoretical frameworks, and conceptual frameworks as critical elements of the research and writing process. However, these elements can be confusing for scholars new to education research. This Research Methods article is designed to provide an overview of each of these elements and delineate the purpose of each in the educational research process. We describe what biology education researchers should consider as they conduct literature reviews, identify theoretical frameworks, and construct conceptual frameworks. Clarifying these different components of educational research studies can be helpful to new biology education researchers and the biology education research community at large in situating their work in the broader scholarly literature.

INTRODUCTION

Discipline-based education research (DBER) involves the purposeful and situated study of teaching and learning in specific disciplinary areas ( Singer et al. , 2012 ). Studies in DBER are guided by research questions that reflect disciplines’ priorities and worldviews. Researchers can use quantitative data, qualitative data, or both to answer these research questions through a variety of methodological traditions. Across all methodologies, there are different methods associated with planning and conducting educational research studies that include the use of surveys, interviews, observations, artifacts, or instruments. Ensuring the coherence of these elements to the discipline’s perspective also involves situating the work in the broader scholarly literature. The tools for doing this include literature reviews, theoretical frameworks, and conceptual frameworks. However, the purpose and function of each of these elements is often confusing to new education researchers. The goal of this article is to introduce new biology education researchers to these three important elements important in DBER scholarship and the broader educational literature.

The first element we discuss is a review of research (literature reviews), which highlights the need for a specific research question, study problem, or topic of investigation. Literature reviews situate the relevance of the study within a topic and a field. The process may seem familiar to science researchers entering DBER fields, but new researchers may still struggle in conducting the review. Booth et al. (2016b) highlight some of the challenges novice education researchers face when conducting a review of literature. They point out that novice researchers struggle in deciding how to focus the review, determining the scope of articles needed in the review, and knowing how to be critical of the articles in the review. Overcoming these challenges (and others) can help novice researchers construct a sound literature review that can inform the design of the study and help ensure the work makes a contribution to the field.

The second and third highlighted elements are theoretical and conceptual frameworks. These guide biology education research (BER) studies, and may be less familiar to science researchers. These elements are important in shaping the construction of new knowledge. Theoretical frameworks offer a way to explain and interpret the studied phenomenon, while conceptual frameworks clarify assumptions about the studied phenomenon. Despite the importance of these constructs in educational research, biology educational researchers have noted the limited use of theoretical or conceptual frameworks in published work ( DeHaan, 2011 ; Dirks, 2011 ; Lo et al. , 2019 ). In reviewing articles published in CBE—Life Sciences Education ( LSE ) between 2015 and 2019, we found that fewer than 25% of the research articles had a theoretical or conceptual framework (see the Supplemental Information), and at times there was an inconsistent use of theoretical and conceptual frameworks. Clearly, these frameworks are challenging for published biology education researchers, which suggests the importance of providing some initial guidance to new biology education researchers.

Fortunately, educational researchers have increased their explicit use of these frameworks over time, and this is influencing educational research in science, technology, engineering, and mathematics (STEM) fields. For instance, a quick search for theoretical or conceptual frameworks in the abstracts of articles in Educational Research Complete (a common database for educational research) in STEM fields demonstrates a dramatic change over the last 20 years: from only 778 articles published between 2000 and 2010 to 5703 articles published between 2010 and 2020, a more than sevenfold increase. Greater recognition of the importance of these frameworks is contributing to DBER authors being more explicit about such frameworks in their studies.

Collectively, literature reviews, theoretical frameworks, and conceptual frameworks work to guide methodological decisions and the elucidation of important findings. Each offers a different perspective on the problem of study and is an essential element in all forms of educational research. As new researchers seek to learn about these elements, they will find different resources, a variety of perspectives, and many suggestions about the construction and use of these elements. The wide range of available information can overwhelm the new researcher who just wants to learn the distinction between these elements or how to craft them adequately.

Our goal in writing this paper is not to offer specific advice about how to write these sections in scholarly work. Instead, we wanted to introduce these elements to those who are new to BER and who are interested in better distinguishing one from the other. In this paper, we share the purpose of each element in BER scholarship, along with important points on its construction. We also provide references for additional resources that may be beneficial to better understanding each element. Table 1 summarizes the key distinctions among these elements.

Comparison of literature reviews, theoretical frameworks, and conceptual reviews

This article is written for the new biology education researcher who is just learning about these different elements or for scientists looking to become more involved in BER. It is a result of our own work as science education and biology education researchers, whether as graduate students and postdoctoral scholars or newly hired and established faculty members. This is the article we wish had been available as we started to learn about these elements or discussed them with new educational researchers in biology.

LITERATURE REVIEWS

Purpose of a literature review.

A literature review is foundational to any research study in education or science. In education, a well-conceptualized and well-executed review provides a summary of the research that has already been done on a specific topic and identifies questions that remain to be answered, thus illustrating the current research project’s potential contribution to the field and the reasoning behind the methodological approach selected for the study ( Maxwell, 2012 ). BER is an evolving disciplinary area that is redefining areas of conceptual emphasis as well as orientations toward teaching and learning (e.g., Labov et al. , 2010 ; American Association for the Advancement of Science, 2011 ; Nehm, 2019 ). As a result, building comprehensive, critical, purposeful, and concise literature reviews can be a challenge for new biology education researchers.

Building Literature Reviews

There are different ways to approach and construct a literature review. Booth et al. (2016a) provide an overview that includes, for example, scoping reviews, which are focused only on notable studies and use a basic method of analysis, and integrative reviews, which are the result of exhaustive literature searches across different genres. Underlying each of these different review processes are attention to the s earch process, a ppraisa l of articles, s ynthesis of the literature, and a nalysis: SALSA ( Booth et al. , 2016a ). This useful acronym can help the researcher focus on the process while building a specific type of review.

However, new educational researchers often have questions about literature reviews that are foundational to SALSA or other approaches. Common questions concern determining which literature pertains to the topic of study or the role of the literature review in the design of the study. This section addresses such questions broadly while providing general guidance for writing a narrative literature review that evaluates the most pertinent studies.

The literature review process should begin before the research is conducted. As Boote and Beile (2005 , p. 3) suggested, researchers should be “scholars before researchers.” They point out that having a good working knowledge of the proposed topic helps illuminate avenues of study. Some subject areas have a deep body of work to read and reflect upon, providing a strong foundation for developing the research question(s). For instance, the teaching and learning of evolution is an area of long-standing interest in the BER community, generating many studies (e.g., Perry et al. , 2008 ; Barnes and Brownell, 2016 ) and reviews of research (e.g., Sickel and Friedrichsen, 2013 ; Ziadie and Andrews, 2018 ). Emerging areas of BER include the affective domain, issues of transfer, and metacognition ( Singer et al. , 2012 ). Many studies in these areas are transdisciplinary and not always specific to biology education (e.g., Rodrigo-Peiris et al. , 2018 ; Kolpikova et al. , 2019 ). These newer areas may require reading outside BER; fortunately, summaries of some of these topics can be found in the Current Insights section of the LSE website.

In focusing on a specific problem within a broader research strand, a new researcher will likely need to examine research outside BER. Depending upon the area of study, the expanded reading list might involve a mix of BER, DBER, and educational research studies. Determining the scope of the reading is not always straightforward. A simple way to focus one’s reading is to create a “summary phrase” or “research nugget,” which is a very brief descriptive statement about the study. It should focus on the essence of the study, for example, “first-year nonmajor students’ understanding of evolution,” “metacognitive prompts to enhance learning during biochemistry,” or “instructors’ inquiry-based instructional practices after professional development programming.” This type of phrase should help a new researcher identify two or more areas to review that pertain to the study. Focusing on recent research in the last 5 years is a good first step. Additional studies can be identified by reading relevant works referenced in those articles. It is also important to read seminal studies that are more than 5 years old. Reading a range of studies should give the researcher the necessary command of the subject in order to suggest a research question.

Given that the research question(s) arise from the literature review, the review should also substantiate the selected methodological approach. The review and research question(s) guide the researcher in determining how to collect and analyze data. Often the methodological approach used in a study is selected to contribute knowledge that expands upon what has been published previously about the topic (see Institute of Education Sciences and National Science Foundation, 2013 ). An emerging topic of study may need an exploratory approach that allows for a description of the phenomenon and development of a potential theory. This could, but not necessarily, require a methodological approach that uses interviews, observations, surveys, or other instruments. An extensively studied topic may call for the additional understanding of specific factors or variables; this type of study would be well suited to a verification or a causal research design. These could entail a methodological approach that uses valid and reliable instruments, observations, or interviews to determine an effect in the studied event. In either of these examples, the researcher(s) may use a qualitative, quantitative, or mixed methods methodological approach.

Even with a good research question, there is still more reading to be done. The complexity and focus of the research question dictates the depth and breadth of the literature to be examined. Questions that connect multiple topics can require broad literature reviews. For instance, a study that explores the impact of a biology faculty learning community on the inquiry instruction of faculty could have the following review areas: learning communities among biology faculty, inquiry instruction among biology faculty, and inquiry instruction among biology faculty as a result of professional learning. Biology education researchers need to consider whether their literature review requires studies from different disciplines within or outside DBER. For the example given, it would be fruitful to look at research focused on learning communities with faculty in STEM fields or in general education fields that result in instructional change. It is important not to be too narrow or too broad when reading. When the conclusions of articles start to sound similar or no new insights are gained, the researcher likely has a good foundation for a literature review. This level of reading should allow the researcher to demonstrate a mastery in understanding the researched topic, explain the suitability of the proposed research approach, and point to the need for the refined research question(s).

The literature review should include the researcher’s evaluation and critique of the selected studies. A researcher may have a large collection of studies, but not all of the studies will follow standards important in the reporting of empirical work in the social sciences. The American Educational Research Association ( Duran et al. , 2006 ), for example, offers a general discussion about standards for such work: an adequate review of research informing the study, the existence of sound and appropriate data collection and analysis methods, and appropriate conclusions that do not overstep or underexplore the analyzed data. The Institute of Education Sciences and National Science Foundation (2013) also offer Common Guidelines for Education Research and Development that can be used to evaluate collected studies.

Because not all journals adhere to such standards, it is important that a researcher review each study to determine the quality of published research, per the guidelines suggested earlier. In some instances, the research may be fatally flawed. Examples of such flaws include data that do not pertain to the question, a lack of discussion about the data collection, poorly constructed instruments, or an inadequate analysis. These types of errors result in studies that are incomplete, error-laden, or inaccurate and should be excluded from the review. Most studies have limitations, and the author(s) often make them explicit. For instance, there may be an instructor effect, recognized bias in the analysis, or issues with the sample population. Limitations are usually addressed by the research team in some way to ensure a sound and acceptable research process. Occasionally, the limitations associated with the study can be significant and not addressed adequately, which leaves a consequential decision in the hands of the researcher. Providing critiques of studies in the literature review process gives the reader confidence that the researcher has carefully examined relevant work in preparation for the study and, ultimately, the manuscript.

A solid literature review clearly anchors the proposed study in the field and connects the research question(s), the methodological approach, and the discussion. Reviewing extant research leads to research questions that will contribute to what is known in the field. By summarizing what is known, the literature review points to what needs to be known, which in turn guides decisions about methodology. Finally, notable findings of the new study are discussed in reference to those described in the literature review.

Within published BER studies, literature reviews can be placed in different locations in an article. When included in the introductory section of the study, the first few paragraphs of the manuscript set the stage, with the literature review following the opening paragraphs. Cooper et al. (2019) illustrate this approach in their study of course-based undergraduate research experiences (CUREs). An introduction discussing the potential of CURES is followed by an analysis of the existing literature relevant to the design of CUREs that allows for novel student discoveries. Within this review, the authors point out contradictory findings among research on novel student discoveries. This clarifies the need for their study, which is described and highlighted through specific research aims.

A literature reviews can also make up a separate section in a paper. For example, the introduction to Todd et al. (2019) illustrates the need for their research topic by highlighting the potential of learning progressions (LPs) and suggesting that LPs may help mitigate learning loss in genetics. At the end of the introduction, the authors state their specific research questions. The review of literature following this opening section comprises two subsections. One focuses on learning loss in general and examines a variety of studies and meta-analyses from the disciplines of medical education, mathematics, and reading. The second section focuses specifically on LPs in genetics and highlights student learning in the midst of LPs. These separate reviews provide insights into the stated research question.

Suggestions and Advice

A well-conceptualized, comprehensive, and critical literature review reveals the understanding of the topic that the researcher brings to the study. Literature reviews should not be so big that there is no clear area of focus; nor should they be so narrow that no real research question arises. The task for a researcher is to craft an efficient literature review that offers a critical analysis of published work, articulates the need for the study, guides the methodological approach to the topic of study, and provides an adequate foundation for the discussion of the findings.

In our own writing of literature reviews, there are often many drafts. An early draft may seem well suited to the study because the need for and approach to the study are well described. However, as the results of the study are analyzed and findings begin to emerge, the existing literature review may be inadequate and need revision. The need for an expanded discussion about the research area can result in the inclusion of new studies that support the explanation of a potential finding. The literature review may also prove to be too broad. Refocusing on a specific area allows for more contemplation of a finding.

It should be noted that there are different types of literature reviews, and many books and articles have been written about the different ways to embark on these types of reviews. Among these different resources, the following may be helpful in considering how to refine the review process for scholarly journals:

• Booth, A., Sutton, A., & Papaioannou, D. (2016a). Systemic approaches to a successful literature review (2nd ed.). Los Angeles, CA: Sage. This book addresses different types of literature reviews and offers important suggestions pertaining to defining the scope of the literature review and assessing extant studies.
• Booth, W. C., Colomb, G. G., Williams, J. M., Bizup, J., & Fitzgerald, W. T. (2016b). The craft of research (4th ed.). Chicago: University of Chicago Press. This book can help the novice consider how to make the case for an area of study. While this book is not specifically about literature reviews, it offers suggestions about making the case for your study.
• Galvan, J. L., & Galvan, M. C. (2017). Writing literature reviews: A guide for students of the social and behavioral sciences (7th ed.). Routledge. This book offers guidance on writing different types of literature reviews. For the novice researcher, there are useful suggestions for creating coherent literature reviews.

THEORETICAL FRAMEWORKS

Purpose of theoretical frameworks.

As new education researchers may be less familiar with theoretical frameworks than with literature reviews, this discussion begins with an analogy. Envision a biologist, chemist, and physicist examining together the dramatic effect of a fog tsunami over the ocean. A biologist gazing at this phenomenon may be concerned with the effect of fog on various species. A chemist may be interested in the chemical composition of the fog as water vapor condenses around bits of salt. A physicist may be focused on the refraction of light to make fog appear to be “sitting” above the ocean. While observing the same “objective event,” the scientists are operating under different theoretical frameworks that provide a particular perspective or “lens” for the interpretation of the phenomenon. Each of these scientists brings specialized knowledge, experiences, and values to this phenomenon, and these influence the interpretation of the phenomenon. The scientists’ theoretical frameworks influence how they design and carry out their studies and interpret their data.

Within an educational study, a theoretical framework helps to explain a phenomenon through a particular lens and challenges and extends existing knowledge within the limitations of that lens. Theoretical frameworks are explicitly stated by an educational researcher in the paper’s framework, theory, or relevant literature section. The framework shapes the types of questions asked, guides the method by which data are collected and analyzed, and informs the discussion of the results of the study. It also reveals the researcher’s subjectivities, for example, values, social experience, and viewpoint ( Allen, 2017 ). It is essential that a novice researcher learn to explicitly state a theoretical framework, because all research questions are being asked from the researcher’s implicit or explicit assumptions of a phenomenon of interest ( Schwandt, 2000 ).

Selecting Theoretical Frameworks

Theoretical frameworks are one of the most contemplated elements in our work in educational research. In this section, we share three important considerations for new scholars selecting a theoretical framework.

The first step in identifying a theoretical framework involves reflecting on the phenomenon within the study and the assumptions aligned with the phenomenon. The phenomenon involves the studied event. There are many possibilities, for example, student learning, instructional approach, or group organization. A researcher holds assumptions about how the phenomenon will be effected, influenced, changed, or portrayed. It is ultimately the researcher’s assumption(s) about the phenomenon that aligns with a theoretical framework. An example can help illustrate how a researcher’s reflection on the phenomenon and acknowledgment of assumptions can result in the identification of a theoretical framework.

In our example, a biology education researcher may be interested in exploring how students’ learning of difficult biological concepts can be supported by the interactions of group members. The phenomenon of interest is the interactions among the peers, and the researcher assumes that more knowledgeable students are important in supporting the learning of the group. As a result, the researcher may draw on Vygotsky’s (1978) sociocultural theory of learning and development that is focused on the phenomenon of student learning in a social setting. This theory posits the critical nature of interactions among students and between students and teachers in the process of building knowledge. A researcher drawing upon this framework holds the assumption that learning is a dynamic social process involving questions and explanations among students in the classroom and that more knowledgeable peers play an important part in the process of building conceptual knowledge.

It is important to state at this point that there are many different theoretical frameworks. Some frameworks focus on learning and knowing, while other theoretical frameworks focus on equity, empowerment, or discourse. Some frameworks are well articulated, and others are still being refined. For a new researcher, it can be challenging to find a theoretical framework. Two of the best ways to look for theoretical frameworks is through published works that highlight different frameworks.

When a theoretical framework is selected, it should clearly connect to all parts of the study. The framework should augment the study by adding a perspective that provides greater insights into the phenomenon. It should clearly align with the studies described in the literature review. For instance, a framework focused on learning would correspond to research that reported different learning outcomes for similar studies. The methods for data collection and analysis should also correspond to the framework. For instance, a study about instructional interventions could use a theoretical framework concerned with learning and could collect data about the effect of the intervention on what is learned. When the data are analyzed, the theoretical framework should provide added meaning to the findings, and the findings should align with the theoretical framework.

A study by Jensen and Lawson (2011) provides an example of how a theoretical framework connects different parts of the study. They compared undergraduate biology students in heterogeneous and homogeneous groups over the course of a semester. Jensen and Lawson (2011) assumed that learning involved collaboration and more knowledgeable peers, which made Vygotsky’s (1978) theory a good fit for their study. They predicted that students in heterogeneous groups would experience greater improvement in their reasoning abilities and science achievements with much of the learning guided by the more knowledgeable peers.

In the enactment of the study, they collected data about the instruction in traditional and inquiry-oriented classes, while the students worked in homogeneous or heterogeneous groups. To determine the effect of working in groups, the authors also measured students’ reasoning abilities and achievement. Each data-collection and analysis decision connected to understanding the influence of collaborative work.

Their findings highlighted aspects of Vygotsky’s (1978) theory of learning. One finding, for instance, posited that inquiry instruction, as a whole, resulted in reasoning and achievement gains. This links to Vygotsky (1978) , because inquiry instruction involves interactions among group members. A more nuanced finding was that group composition had a conditional effect. Heterogeneous groups performed better with more traditional and didactic instruction, regardless of the reasoning ability of the group members. Homogeneous groups worked better during interaction-rich activities for students with low reasoning ability. The authors attributed the variation to the different types of helping behaviors of students. High-performing students provided the answers, while students with low reasoning ability had to work collectively through the material. In terms of Vygotsky (1978) , this finding provided new insights into the learning context in which productive interactions can occur for students.

Another consideration in the selection and use of a theoretical framework pertains to its orientation to the study. This can result in the theoretical framework prioritizing individuals, institutions, and/or policies ( Anfara and Mertz, 2014 ). Frameworks that connect to individuals, for instance, could contribute to understanding their actions, learning, or knowledge. Institutional frameworks, on the other hand, offer insights into how institutions, organizations, or groups can influence individuals or materials. Policy theories provide ways to understand how national or local policies can dictate an emphasis on outcomes or instructional design. These different types of frameworks highlight different aspects in an educational setting, which influences the design of the study and the collection of data. In addition, these different frameworks offer a way to make sense of the data. Aligning the data collection and analysis with the framework ensures that a study is coherent and can contribute to the field.

New understandings emerge when different theoretical frameworks are used. For instance, Ebert-May et al. (2015) prioritized the individual level within conceptual change theory (see Posner et al. , 1982 ). In this theory, an individual’s knowledge changes when it no longer fits the phenomenon. Ebert-May et al. (2015) designed a professional development program challenging biology postdoctoral scholars’ existing conceptions of teaching. The authors reported that the biology postdoctoral scholars’ teaching practices became more student-centered as they were challenged to explain their instructional decision making. According to the theory, the biology postdoctoral scholars’ dissatisfaction in their descriptions of teaching and learning initiated change in their knowledge and instruction. These results reveal how conceptual change theory can explain the learning of participants and guide the design of professional development programming.

The communities of practice (CoP) theoretical framework ( Lave, 1988 ; Wenger, 1998 ) prioritizes the institutional level , suggesting that learning occurs when individuals learn from and contribute to the communities in which they reside. Grounded in the assumption of community learning, the literature on CoP suggests that, as individuals interact regularly with the other members of their group, they learn about the rules, roles, and goals of the community ( Allee, 2000 ). A study conducted by Gehrke and Kezar (2017) used the CoP framework to understand organizational change by examining the involvement of individual faculty engaged in a cross-institutional CoP focused on changing the instructional practice of faculty at each institution. In the CoP, faculty members were involved in enhancing instructional materials within their department, which aligned with an overarching goal of instituting instruction that embraced active learning. Not surprisingly, Gehrke and Kezar (2017) revealed that faculty who perceived the community culture as important in their work cultivated institutional change. Furthermore, they found that institutional change was sustained when key leaders served as mentors and provided support for faculty, and as faculty themselves developed into leaders. This study reveals the complexity of individual roles in a COP in order to support institutional instructional change.

It is important to explicitly state the theoretical framework used in a study, but elucidating a theoretical framework can be challenging for a new educational researcher. The literature review can help to identify an applicable theoretical framework. Focal areas of the review or central terms often connect to assumptions and assertions associated with the framework that pertain to the phenomenon of interest. Another way to identify a theoretical framework is self-reflection by the researcher on personal beliefs and understandings about the nature of knowledge the researcher brings to the study ( Lysaght, 2011 ). In stating one’s beliefs and understandings related to the study (e.g., students construct their knowledge, instructional materials support learning), an orientation becomes evident that will suggest a particular theoretical framework. Theoretical frameworks are not arbitrary , but purposefully selected.

With experience, a researcher may find expanded roles for theoretical frameworks. Researchers may revise an existing framework that has limited explanatory power, or they may decide there is a need to develop a new theoretical framework. These frameworks can emerge from a current study or the need to explain a phenomenon in a new way. Researchers may also find that multiple theoretical frameworks are necessary to frame and explore a problem, as different frameworks can provide different insights into a problem.

Finally, it is important to recognize that choosing “x” theoretical framework does not necessarily mean a researcher chooses “y” methodology and so on, nor is there a clear-cut, linear process in selecting a theoretical framework for one’s study. In part, the nonlinear process of identifying a theoretical framework is what makes understanding and using theoretical frameworks challenging. For the novice scholar, contemplating and understanding theoretical frameworks is essential. Fortunately, there are articles and books that can help:

• Creswell, J. W. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Los Angeles, CA: Sage. This book provides an overview of theoretical frameworks in general educational research.
• Ding, L. (2019). Theoretical perspectives of quantitative physics education research. Physical Review Physics Education Research , 15 (2), 020101-1–020101-13. This paper illustrates how a DBER field can use theoretical frameworks.
• Nehm, R. (2019). Biology education research: Building integrative frameworks for teaching and learning about living systems. Disciplinary and Interdisciplinary Science Education Research , 1 , ar15. https://doi.org/10.1186/s43031-019-0017-6 . This paper articulates the need for studies in BER to explicitly state theoretical frameworks and provides examples of potential studies.
• Patton, M. Q. (2015). Qualitative research & evaluation methods: Integrating theory and practice . Sage. This book also provides an overview of theoretical frameworks, but for both research and evaluation.

CONCEPTUAL FRAMEWORKS

Purpose of a conceptual framework.

A conceptual framework is a description of the way a researcher understands the factors and/or variables that are involved in the study and their relationships to one another. The purpose of a conceptual framework is to articulate the concepts under study using relevant literature ( Rocco and Plakhotnik, 2009 ) and to clarify the presumed relationships among those concepts ( Rocco and Plakhotnik, 2009 ; Anfara and Mertz, 2014 ). Conceptual frameworks are different from theoretical frameworks in both their breadth and grounding in established findings. Whereas a theoretical framework articulates the lens through which a researcher views the work, the conceptual framework is often more mechanistic and malleable.

Conceptual frameworks are broader, encompassing both established theories (i.e., theoretical frameworks) and the researchers’ own emergent ideas. Emergent ideas, for example, may be rooted in informal and/or unpublished observations from experience. These emergent ideas would not be considered a “theory” if they are not yet tested, supported by systematically collected evidence, and peer reviewed. However, they do still play an important role in the way researchers approach their studies. The conceptual framework allows authors to clearly describe their emergent ideas so that connections among ideas in the study and the significance of the study are apparent to readers.

Constructing Conceptual Frameworks

Including a conceptual framework in a research study is important, but researchers often opt to include either a conceptual or a theoretical framework. Either may be adequate, but both provide greater insight into the research approach. For instance, a research team plans to test a novel component of an existing theory. In their study, they describe the existing theoretical framework that informs their work and then present their own conceptual framework. Within this conceptual framework, specific topics portray emergent ideas that are related to the theory. Describing both frameworks allows readers to better understand the researchers’ assumptions, orientations, and understanding of concepts being investigated. For example, Connolly et al. (2018) included a conceptual framework that described how they applied a theoretical framework of social cognitive career theory (SCCT) to their study on teaching programs for doctoral students. In their conceptual framework, the authors described SCCT, explained how it applied to the investigation, and drew upon results from previous studies to justify the proposed connections between the theory and their emergent ideas.

In some cases, authors may be able to sufficiently describe their conceptualization of the phenomenon under study in an introduction alone, without a separate conceptual framework section. However, incomplete descriptions of how the researchers conceptualize the components of the study may limit the significance of the study by making the research less intelligible to readers. This is especially problematic when studying topics in which researchers use the same terms for different constructs or different terms for similar and overlapping constructs (e.g., inquiry, teacher beliefs, pedagogical content knowledge, or active learning). Authors must describe their conceptualization of a construct if the research is to be understandable and useful.

There are some key areas to consider regarding the inclusion of a conceptual framework in a study. To begin with, it is important to recognize that conceptual frameworks are constructed by the researchers conducting the study ( Rocco and Plakhotnik, 2009 ; Maxwell, 2012 ). This is different from theoretical frameworks that are often taken from established literature. Researchers should bring together ideas from the literature, but they may be influenced by their own experiences as a student and/or instructor, the shared experiences of others, or thought experiments as they construct a description, model, or representation of their understanding of the phenomenon under study. This is an exercise in intellectual organization and clarity that often considers what is learned, known, and experienced. The conceptual framework makes these constructs explicitly visible to readers, who may have different understandings of the phenomenon based on their prior knowledge and experience. There is no single method to go about this intellectual work.

Reeves et al. (2016) is an example of an article that proposed a conceptual framework about graduate teaching assistant professional development evaluation and research. The authors used existing literature to create a novel framework that filled a gap in current research and practice related to the training of graduate teaching assistants. This conceptual framework can guide the systematic collection of data by other researchers because the framework describes the relationships among various factors that influence teaching and learning. The Reeves et al. (2016) conceptual framework may be modified as additional data are collected and analyzed by other researchers. This is not uncommon, as conceptual frameworks can serve as catalysts for concerted research efforts that systematically explore a phenomenon (e.g., Reynolds et al. , 2012 ; Brownell and Kloser, 2015 ).

Sabel et al. (2017) used a conceptual framework in their exploration of how scaffolds, an external factor, interact with internal factors to support student learning. Their conceptual framework integrated principles from two theoretical frameworks, self-regulated learning and metacognition, to illustrate how the research team conceptualized students’ use of scaffolds in their learning ( Figure 1 ). Sabel et al. (2017) created this model using their interpretations of these two frameworks in the context of their teaching.

Conceptual framework from Sabel et al. (2017) .

A conceptual framework should describe the relationship among components of the investigation ( Anfara and Mertz, 2014 ). These relationships should guide the researcher’s methods of approaching the study ( Miles et al. , 2014 ) and inform both the data to be collected and how those data should be analyzed. Explicitly describing the connections among the ideas allows the researcher to justify the importance of the study and the rigor of the research design. Just as importantly, these frameworks help readers understand why certain components of a system were not explored in the study. This is a challenge in education research, which is rooted in complex environments with many variables that are difficult to control.

For example, Sabel et al. (2017) stated: “Scaffolds, such as enhanced answer keys and reflection questions, can help students and instructors bridge the external and internal factors and support learning” (p. 3). They connected the scaffolds in the study to the three dimensions of metacognition and the eventual transformation of existing ideas into new or revised ideas. Their framework provides a rationale for focusing on how students use two different scaffolds, and not on other factors that may influence a student’s success (self-efficacy, use of active learning, exam format, etc.).

In constructing conceptual frameworks, researchers should address needed areas of study and/or contradictions discovered in literature reviews. By attending to these areas, researchers can strengthen their arguments for the importance of a study. For instance, conceptual frameworks can address how the current study will fill gaps in the research, resolve contradictions in existing literature, or suggest a new area of study. While a literature review describes what is known and not known about the phenomenon, the conceptual framework leverages these gaps in describing the current study ( Maxwell, 2012 ). In the example of Sabel et al. (2017) , the authors indicated there was a gap in the literature regarding how scaffolds engage students in metacognition to promote learning in large classes. Their study helps fill that gap by describing how scaffolds can support students in the three dimensions of metacognition: intelligibility, plausibility, and wide applicability. In another example, Lane (2016) integrated research from science identity, the ethic of care, the sense of belonging, and an expertise model of student success to form a conceptual framework that addressed the critiques of other frameworks. In a more recent example, Sbeglia et al. (2021) illustrated how a conceptual framework influences the methodological choices and inferences in studies by educational researchers.

Sometimes researchers draw upon the conceptual frameworks of other researchers. When a researcher’s conceptual framework closely aligns with an existing framework, the discussion may be brief. For example, Ghee et al. (2016) referred to portions of SCCT as their conceptual framework to explain the significance of their work on students’ self-efficacy and career interests. Because the authors’ conceptualization of this phenomenon aligned with a previously described framework, they briefly mentioned the conceptual framework and provided additional citations that provided more detail for the readers.

Within both the BER and the broader DBER communities, conceptual frameworks have been used to describe different constructs. For example, some researchers have used the term “conceptual framework” to describe students’ conceptual understandings of a biological phenomenon. This is distinct from a researcher’s conceptual framework of the educational phenomenon under investigation, which may also need to be explicitly described in the article. Other studies have presented a research logic model or flowchart of the research design as a conceptual framework. These constructions can be quite valuable in helping readers understand the data-collection and analysis process. However, a model depicting the study design does not serve the same role as a conceptual framework. Researchers need to avoid conflating these constructs by differentiating the researchers’ conceptual framework that guides the study from the research design, when applicable.

Explicitly describing conceptual frameworks is essential in depicting the focus of the study. We have found that being explicit in a conceptual framework means using accepted terminology, referencing prior work, and clearly noting connections between terms. This description can also highlight gaps in the literature or suggest potential contributions to the field of study. A well-elucidated conceptual framework can suggest additional studies that may be warranted. This can also spur other researchers to consider how they would approach the examination of a phenomenon and could result in a revised conceptual framework.

It can be challenging to create conceptual frameworks, but they are important. Below are two resources that could be helpful in constructing and presenting conceptual frameworks in educational research:

• Maxwell, J. A. (2012). Qualitative research design: An interactive approach (3rd ed.). Los Angeles, CA: Sage. Chapter 3 in this book describes how to construct conceptual frameworks.
• Ravitch, S. M., & Riggan, M. (2016). Reason & rigor: How conceptual frameworks guide research . Los Angeles, CA: Sage. This book explains how conceptual frameworks guide the research questions, data collection, data analyses, and interpretation of results.

CONCLUDING THOUGHTS

Literature reviews, theoretical frameworks, and conceptual frameworks are all important in DBER and BER. Robust literature reviews reinforce the importance of a study. Theoretical frameworks connect the study to the base of knowledge in educational theory and specify the researcher’s assumptions. Conceptual frameworks allow researchers to explicitly describe their conceptualization of the relationships among the components of the phenomenon under study. Table 1 provides a general overview of these components in order to assist biology education researchers in thinking about these elements.

It is important to emphasize that these different elements are intertwined. When these elements are aligned and complement one another, the study is coherent, and the study findings contribute to knowledge in the field. When literature reviews, theoretical frameworks, and conceptual frameworks are disconnected from one another, the study suffers. The point of the study is lost, suggested findings are unsupported, or important conclusions are invisible to the researcher. In addition, this misalignment may be costly in terms of time and money.

Conducting a literature review, selecting a theoretical framework, and building a conceptual framework are some of the most difficult elements of a research study. It takes time to understand the relevant research, identify a theoretical framework that provides important insights into the study, and formulate a conceptual framework that organizes the finding. In the research process, there is often a constant back and forth among these elements as the study evolves. With an ongoing refinement of the review of literature, clarification of the theoretical framework, and articulation of a conceptual framework, a sound study can emerge that makes a contribution to the field. This is the goal of BER and education research.

Supplementary Material

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Theories, theoretical and conceptual frameworks, models and constructs: Limiting research outcomes through misconceptions and misunderstandings

Contributing to knowledge or theory is generally a standard requirement for research and doctoral studies. Whether that contribution should be from a research, policy or practice perspective is often not specifically stated as a requirement, yet one or all are certainly possible. A doctoral study (or indeed any research study) is usually quite firmly cast or framed within a form of theoretical or conceptual framework. Yet, even the definition, selection and formulation of a framework that is appropriate and that can inform a study throughout its various phases and stages is sometimes considered a ‘doctoral or research challenge’ in itself. This paper will argue that the way models, frameworks or theories - all of which in this current paper are collectively termed underpinnings - are conceived and used could well determine whether, how and to what extent a thesis or research study might contribute to a wider knowledge base. The paper offers a theoretical strategic analysis of the issue. It will explore what a conceptual or theoretical framework for a doctoral or wider research study is, what role or roles it can take, and whether, how and to what extent a study might contribute to knowledge or theory. The paper will conclude with ways to question approaches to roles of conceptual or theoretical underpinnings that do not limit the potential of a thesis or study to contribute to theory. Keywords: theories; theoretical frameworks; conceptual frameworks; models; research studies; underpinning constructs Part of the Special Issue Debating the status of ‘theory’ in technology enhanced learning research

1. Introduction

This initial section asks what a conceptual or theoretical framework for a research study might be. The ways that universities define a doctoral study’s contribution to knowledge or theory can vary quite widely. The United Kingdom (UK) Quality Assurance Agency (2014, p.30) states that a student for a doctoral degree should demonstrate “the creation and interpretation of new knowledge, through original research or other advanced scholarship… at the forefront of an academic discipline or area of professional practice”. This statement clearly supports new knowledge contribution that could be in professional or policy fields as well as in the research field. It is not surprising then, perhaps, that different universities might state different requirements in this respect. For example, in the UK, Lancaster University’s regulations for a doctoral thesis state that, “A successful candidate for the degree of PhD shall show convincing evidence of the capacity to pursue scholarly research or scholarship in his or her field of study... The results of this research shall then be embodied in a thesis which makes an original contribution to knowledge” (Lancaster University, 2018, p.3). However, a much more detailed description is given by Manchester Metropolitan University, UK, stating that, “Doctorates are awarded for creating, interpreting and communicating knowledge that extends the forefront of a discipline or of professional practice, through original research and critical thinking” (Manchester Metropolitan University, 2019, n.p.). It is clear from these different statements that the latter institution is clearly supporting a focus of developing knowledge that can be research, policy or practice focused. From a theoretical or conceptual perspective, this means that the underpinning in the latter case might be founded on a conception, framework or model that could be policy or practice based, rather than it necessarily being research based.

Underpinnings (a term used throughout this paper to collectively include models, frameworks and theories) for research can take a number of different forms. Indeed, distinctions between different forms of underpinnings might provide a quite different conceptual or theoretical basis for a study – if differences between models, conceptual frameworks, theoretical frameworks or theories are considered (Grant & Osanloo, 2014). These different forms of underpinnings can all arise from previous published research, but they can arise from and have quite different contextual bases. In general, the contexts of the four different forms arising from previous studies that are described in the research literature can be outlined (Passey, 2019), and will be defined in the remainder of this paper, as:

a model holds for a given case or stated population, arising from context-specific research, often indicating main features of influence or contribution;

a conceptual framework tends to be more flexible and descriptive, as it usually identifies factors or criteria that have influence on a particular field within the more major features, which might be, for example, social learning, discovery learning, or experiential learning;

a theoretical framework arises from outcomes beyond a single study, based on one or more theories, which might be, for example, social constructivism, constructionism, or behaviourism; while

a theory considers a broader and deeper concern or context, suggesting the detail of what might be more general, beyond one or a number of contexts.

This distinction between different forms of underpinnings is fundamentally important, as it can determine the applicability of any choice of underpinning to a specific study. For example, if a model has been developed from research in one context, then whether it could be applied in another different context is in itself a significant question. Additionally, if a model is gained from a limited context and range of participants, whether using such a model as it stands would then limit the findings of another piece of research just to the major features of influence that have been identified is another notable question. These concerns form some of the basis of the debate that has arisen when thinking about approaches that might be taken with case study research, where the focus is on a real-life context, where the “case will be complex and bounded… with the analysis undertaken seeking to be holistic” (Tight, 2017, p.17). Considering whether outcomes from those cases have potential or wider applicability, and how any wider generalisation might be viewed and gained, can be a key question. Indeed, in the context where a model from a single case is used, where only major features of influence are identified, there is the question of whether taking an alternative grounded theory approach, defined as “a general abstract theory of a process, action or interaction grounded in the views of the participants in a study” (Creswell, 2009, p.243), might not release opportunity that would not be offered when using an existing model. Indeed, this concern might also similarly apply if major features of influence are only used even when a framework or conception is adopted as an underpinning for a research study.

In the context of technology enhanced learning, it is perhaps pertinent to think about distinctions of different forms of underpinning constructs (a term used in this paper to indicate how ideas can be formulated through conceptions that may be subjective or believed or even imaged or imaginary) through a number of examples (shown in Table 1). These examples will be illustrated and discussed subsequently, in terms of their context, scope and potential interpretation.

Table 1: Examples of forms of underpinning constructs

In terms of models, three are offered as examples in Table 1. The origin of these models is quite different, but they all relate to the field of technologies (in the widest sense). The first of these, the Technology Acceptance Model (TAM) of Davis (1989) is a very well-known model, yet it is often incorrectly cited as being a theory. The original TAM was indeed a model, and Davis stated this quite clearly in the title he gave to it. As a model, it provides a structure and a set of features; in this form, using this as an underpinning for a research study is clearly attractive, as it provides clear hooks for both developing research questions and for analysing research evidence. However, it should certainly be recognised that it has limitations if and when it is to be considered for use as a fundamental or strong underpinning to a study, as it has no theoretical credibility as it stands. Diffusion of Innovation (Rogers, 2003) is also often incorrectly cited as a theory – yet Rogers was clear in his original description in calling it a model (or process). It is often used in its model form as a research instrument for conceptualising or analysing stages of diffusion or implementation, without referring to the important text that contextualises and surrounds more descriptive factors that detail the model further. The third model, Pathways to Implementing Change (Corbett & Rossman, 1989) was also described as a model by the authors. But, as in the two preceding examples, the surrounding text that the authors provide offers crucially important factors that offer additional details within its major features. These factors enable this model to be more adequately considered for the purposes of underpinning a study (or elements of it). In all of these three cases, while these models might provide for a complete underpinning to a study, studies that have used these models have tended to apply them to elements of studies, concerned often with the elements of data collection and data analysis.

In terms of conceptual frameworks, three examples are shown in Table 1. The Technological, Pedagogical and Content Knowledge framework (Mishra & Koehler, 2006) is a well-known and well-used framework in technology enhanced learning research. Despite its widespread use, and the fact that the framework is supported by descriptions of the elements of that framework, some researchers have noted that the descriptions are what they describe as being somewhat vague, not allowing easy analysis of their outcome data. As such, it is found that this framework provides a conceptual base, and it is in this form that researchers have tended to use this for their own studies. The second example, Discovery Learning, described by Bruner (1961) for example, has not been classed as a theory, or as a model. Rather, it is presented as a concept, or a practice that is based upon certain principles. As such, and using those principles, it is possible to use this as a framework, but it is not constituted as a theory. The third example, Experiential Learning, in a paper by Kolb (1984) is described as a model that is then elaborated and proposed as a theory. Certainly, given the level of elaboration, experiential learning is undoubtedly provided as a framework, and is in itself underpinned by a concept of learning. Whilst it could be used as theory, therefore, it is certainly possible to use it as a conceptual framework.

In terms of theoretical frameworks, two examples are offered. The first, Social Creative Constructionism (Passey et al., 2019), is a theoretical framework developed from an analysis of a number of existing theories and frameworks, including Social Constructivism (Vygotsky, 1978) and Constructionism (Papert, 1986). As these two existing theories and frameworks do not accommodate and provide for a contemporary perspective on the development of young people with creative uses of digital technologies, the creation of an integrated theoretical framework through analysis of earlier and more contemporary theories and frameworks sought to address this gap. This example illustrates that underpinnings do not need to be ‘taken off the shelf’, and indeed that underpinnings need to be questioned in terms of their applicability. Rather, underpinnings should be selected carefully or even developed to relate to contexts and circumstances. The second example, Human Motivation, was a theoretical framework that was developed by Maslow (1943), based upon a number of existing theories. This framework is perhaps best recognised through what has been called Maslow’s model of a hierarchy of needs, and this is often the form in which the theoretical framework is used in research studies. The creation and use of this model for underpinning research has been strongly questioned (Bridgman, Cummings, & Ballard, 2019); again, the background theories that led to this framework contextualise it in important ways.

For theories, four examples are listed. The Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003) was developed through a series of models arising initially from TAM. Following reviews of research using TAM and using subsequent models that were developed, not only did the major features of TAM become expanded, but additional factors and influences were identified and integrated. With wider application in a range of contexts, this level of applicability was considered strong enough to posit the framework as a theory. TAM started out with a much more focused view from the individual user’s perspective, while UTAUT viewed acceptance and use from a wider range of social and societal influences on the individual. UTAUT, therefore, can provide a wider and more detailed contextual view if used as an underpinning for a research study. The same holds true for the second example, the theory of Social Constructivism (Vygotsky, 1978), in that it was posited on the basis of a wide range of perspectives that had been tested in different contexts over time. This theory considers the role of social influences on learning, as well as the earlier cognitive influences that had been identified, so considers external dimensions on learning in addition to the internal dimensions; as a consequence, the theory is not limited to internal cognitive features alone. Piaget’s (1952) theory of cognitive constructivism, based on a more focused exploration of cognitive features, and taking a more developmental approach to learning, is more limited in terms of its accommodation of social influences (especially when the very limited range of originating participants that led to the findings of the research are considered – in this case, Piaget’s three children and children of some of his colleagues). The third example, the theory of Constructionism (Papert, 1986), was based on Piaget’s theory, but took into account influences of the handling and creating of artefacts by learners. Within a context of digital technologies, this theory, therefore, tends to relate strongly to learning contexts where artefacts are involved, as is the case within contemporary situations of digital technology use. However, as discussed earlier, the forms of digital technology that were used at the time of Papert’s development of the theory were not developed to the same extent in terms of communication uses, or how programming could be used to create the current width of technological outputs by the user. Taking another earlier theory, the fourth example, the theory of Behaviourism (Skinner, 1953), is often now not taken as a serious contender for theoretical underpinning of research studies. Yet, a focal feature of that theory, operant conditioning, undoubtedly arises in contemporary situations – such as the response to stimuli by social media users from received emails or WhatsApp messages, for example.

From the discussion of the different forms of underpinning presented above, one point that emerges is a shift in the parts of the research process that might be supported by models to those that might be supported by theories. Across the four forms of underpinnings, there tends to be an identifiable shift in focus towards elements of the entire research approach and design. This movement concerns the ways that the different forms might be applied to elements of a research study - from ways that models might support the underpinning of elements such as data collection and analysis, to the ways that theories might support the overall underpinning of approaches and research position or stance taken.

2. Role or roles of underpinning theories or conceptions

The ways that models, frameworks or theories might support a research study (as discussed above), relate to conclusions and discussions that have been drawn from other research literature. For example, Oliver (2002) identified different ways that theories (rather than all conceptual or theoretical underpinnings) can be conceived, and how they might be used in research. When each of these different ways is considered from a critical perspective, they give rise to different questions about implications arising. As an example, for a theory, some implications and questions arising are outlined in Table 2 (using Oliver’s four ways to use theory – as a tool, as a principle, for building, and for using – shown in the left-hand column).

Table 2: Role or roles a theory can take, and implications arising

Linked to these implications and questions arising, some common myths also need to be considered when choosing and using an underpinning (going beyond considering only a theory) in a study:

A model, conceptual or theoretical framework or theory is independent of its originating context. Well, this is not true, of course – but if an underpinning is dependent on an originating context, then what are the implications for a study that is being undertaken within another context? To what extent can that underpinning be of value or appropriate or relevant in that new context? For example, Piaget’s theory of cognitive constructivism (1952) was based on observation of his children and those of some of his colleagues. Clearly, the theory relates, therefore, to a specific cultural group in a specific temporal, social and societal setting. The application of this theory to other quite different contexts clearly needs to be questioned, rather than unquestionably accepted.

A theory should not be questioned. Of course, this is certainly not true – and if a theory is to be questioned, then what are the implications for how a study is to be set up? In essence, if to contribute to theory is an outcome of a study, as is often stated for doctoral studies, for example, then how can the theory that underpins the study be framed in such a way as to enable ‘new’ theory to arise? If the theory that is used only takes those features and factors that are already identified by an existing literature into account, and this drives the data collection and analysis, then to what extent is it enabling only the same theory to be re-identified, (albeit perhaps in a different context), rather than questioning or adding to it?

Taking further forward the idea of implications arising from the roles that underpinning theory might take, it is possible to consider what the form of contribution of a research study might be in each case. Table 3 begins to explore how role and contribution might be viewed in terms of linkage or relationship.

Table 3: Roles of underpinning theory and relationship to contribution to knowledge

The questions raised in Table 3 are certainly not meant to be exhaustive. Rather, they should be taken as examples of the forms of questions that can be asked if there are implications that are identified when using a theory in specific contexts or ways. How these questions relate to other forms of underpinnings also need to be considered carefully in any specific research context.

3. Choosing one or more underpinnings for a study

It is perfectly feasible, of course, to select more than one model, framework, concept or theory to underpin a research study. In the context of marketing strategy, Varadarajan (2019) considers reasons and identifies trends in adopting single or multiple–theory approaches in this research field over time, as well as discussing outcomes and implications arising from taking specific approaches. It is certainly possible to take a multi-theory approach even if a study does not seek to develop a new model, framework, concept or theory from a number that exist already. Whilst some researchers come with fairly well-developed ideas of models, frameworks, concepts or theories that align with their own concerns, approaches and position as a researcher, other researchers do not start with this stance, but recognise the possibility and values that different models, frameworks, concepts and theories might bring to their research endeavour. In this latter case, it is more likely that a researcher is concerned with thinking through the study to be undertaken, and identifying methodological stance and approach, and how this might benefit from the use of one or more models, frameworks, concepts and theories. Some researchers might argue that a combination can be conflicting, or would argue for adoption of a single underpinning framework that conceptualises the basis of the study (for example, Passey, 2010) or for a single theory building approach to support wider generalisability (for example, Eisenhardt, 1989). On the other hand, others would argue a different case, that multi-theory approaches provide for a better sense of situational contexts (for example, Berman, 2013), and establish how more than one form of underpinning would be associated, related and of value. In research, strength of argument often determines possibility in these respects.

For example, can it be argued that both behaviourism and social constructivism could be used as forms of underpinning in a single study? It might at first appear that these two theories are incompatible – that behaviourism is concerned with responses arising from stimuli through operant conditioning, while social constructivism is concerned with the way the learner engages with the external environment, learning through social interaction. It might be inferred, therefore, that behaviourism is defined as learning that is driven through conditioned response - what has become associated in certain ways with passive learning, or ‘drill and practice’ approaches. For social constructivism, this might be defined in terms of the learner exercising control over learning through engagement and interaction with the environment (what has become associated in other ways with active learning approaches). Ertmer and Newby (1993) provide a useful discussion about the relationship and differences between behaviourism, cognitivism and constructivism. They state that “we have consciously chosen not to advocate one theory over the others, but to stress instead the usefulness of being well versed in each. This is not to suggest that one should work without a theory” (p.62). From a learner’s perspective, they also quote Drucker’s statement (cited in Snelbecker, 1983, p.203): “These old controversies have been phonies all along. We need the behaviorist’s triad of practice/reinforcement/feedback to enlarge learning and memory. We need purpose, decision, values, understanding—the cognitive categories—lest learning be mere behavioral activities rather than action” (p. 203).

The question that we are left with, then, is perhaps more concerned with why and how we would want to include and integrate more than one form of underpinning. In the case above, social constructivism can be argued as a contextual approach to learning, whilst behaviourism can be argued as a (short- or long-term) response to learning. A note of caution here is to say that considering single or multi-theory approaches should not be confused with taking multi- or mixed-methods approaches. Multi- or mixed-methods approaches are concerned with the gathering and forms of data, and with how questions about reliability and generalisability - or credibility - might be addressed. Multi- or mixed-methods provide evidence to inform research questions, whereas single or multi-theory approaches provide the underpinning and conceptual basis of the study or key elements of it.

4. Overall research design and approach, and relationship of underpinnings

One way to consider the reasons why theoretical or conceptual underpinnings might be used, and the practice of how, is to explore different elements of a study, and how they are related. For this purpose, five elements will be considered: ontological and epistemological position, methodological approach, methodological design, data collection methods, and data analysis methods.

Taking each one of these in turn, initially, ontological and epistemological position are concerned with the stance of the researcher. Ontology has been described as “the study of being” (Crotty, 1998, p.10). This clearly “raises basic questions about the nature of reality and the nature of the human being in the world” (Denzin & Lincoln, 2005, p.183). Ontological position, therefore, can take a view that reality exists independently outside consciousness, or that reality exists only in the interpretation that individual consciousness brings to it. These different positions then tend to lean towards a view of reality that is either objective (a world that can be positively identified) or subjective (a world that is perceived as being different by different individuals). From a research perspective, it is then a question of how evidence can be gathered to support either one of these positions. Epistemology has, in that context, been described as “a way of understanding and explaining how I know what I know” (Crotty, 1998, p.3). Denzin and Lincoln (2005) explore this further, considering associations between the knower and the knowledge, and they ask a crucial question: “how do I know the world?” (p.183). Epistemology in a research context is concerned with making sense of our world through a methodological approach, where the researcher is aware of their ontological and epistemological position, or they are aware of the possibility to associate with one position or another, according to the nature of the study being undertaken. For any research study, underpinnings clearly need to accommodate the position or stance taken with regard to ontology and epistemology.

Methodological approaches should then be related to ontological and epistemological position. There are different ways in which methodological approaches and philosophical paradigms can be defined and categorised. For example, Kivunja and Kuyini (2017) explore four categories – positivist, interpretivist/constructivist, critical/transformative, and pragmatic. In this paper, three methodological approaches will be explored in the context of relationship to underpinnings, but it should be noted that these are selected as examples, and do not represent the entirety of possibilities within the field. The first of these approaches is post-positivism. Although this paradigm (approach) is often related to an objectivist position, it usually takes a more critical realist perspective, in that identifying an absolute truth is not possible (Letourneau & Allen, 2006). Rather than taking a position that objectivism can lead to truth, post-positivism is concerned with how to research in order to move closer to truth. There is also a recognition here that knowledge can be questioned, and that such critical realist perspectives through objective study can enable a movement towards truth. The second paradigm (approach) considered here is interpretivism. Often related to a more subjectivist position, it is usually recognised that knowledge is highly contextual, in terms of relationship through participants (either individual or groups) to, for example, time, place, culture and external or internal factors. Hence, interpretivism considers the importance of multiple meanings. The meanings of human experiences are a focal concern for researchers taking this approach (Fossey, Harvey, McDermott & Davidson, 2002). The third paradigm (approach) considered here is constructionism. This approach is concerned with the relationship of the interpreter with what is being interpreted (Crotty, 1998). The interpreter, rather than taking an unconnected view, considers the context strongly, in terms of external and internal influences (Charmaz, 2006). The influence of the context is taken into consideration in this approach, and it is recognised that this can affect interpretation. In this way, knowledge is considered to be a construct rather than providing a truth; knowledge through interpretation is itself a construct rather than something to be identified. The recognition or choice of even these three different paradigms (approaches) can clearly influence the appropriateness of any underpinning conceptual or theoretical framework that might be chosen.

Methodological design is concerned with the structural and overarching scope and practices of a research study. It is not possible in this paper to discuss all methodological designs – that is covered far more effectively in texts dedicated to that arena (for example, Cohen, Manion, & Morrison, 2007; Creswell, 2014). For the purposes of this paper, three examples will be highlighted – case study, phenomenography, and design-based research. In terms of a case study design, as Harrison, Birks, Franklin and Mills (2017) state, case study “has a practical versatility in its agnostic approach… case study research can be orientated from a realist or positivist perspective where the researcher holds the view that there is one single reality, which is independent of the individual and can be apprehended, studied and measured, through to a relativist or interpretivist perspective” (n.p.). Alignment with an epistemological and ontological position or stance, therefore, is more concerned with the strength of argument made to demonstrate that alignment, rather than alignment arising from a simple choice of known appropriateness. Taking a phenomenographic design, the alignment that is possible here is more distinctive. Richardson (1999) posits that phenomenography aligns with “realist” interpretation. Indeed, Marton, a key leader in developing this form of methodological design, stated that the aim of this design is to identify different conceptions of reality (Marton, 1986). If these conceptions are constructed by those using or associated with a phenomenon, then this focus aligns with “constructionism”. By comparison, with a design-based methodological design, the alignment is again not necessarily distinctive. Cross (1999) discussed three concerns with design-based research – design epistemology, design praxeology, and design phenomenology. In terms of design epistemology, Cross referred to “designerly ways of knowing”, which was defined as the ways that designers think about design (Cross, 1999; Cross, 2007). He referred to design praxiology as practices and processes in creating outcomes, while for design phenomenology this was concerned with the connection of a phenomenon created with the users. Whilst it could be possible to argue alignment with a post-positivistic approach, it could also be argued that a constructionist approach could be taken. Here again, the alignment is concerned with form and strength of argument and discussion, rather than it being determined by a distinct alignment of the methodological design itself.

So far, concerns about choice and application of forms of underpinning that are related to the discussions above tend to focus on theoretical or conceptual underpinnings, through theories or frameworks. However, when data collection methods are considered, whilst underpinnings need to associate with those same background philosophies, there is some scope to look to how other forms of underpinnings might work in addition to those already considered and selected. Taking a case study design as an example, forms of data collection that are suggested by key researchers in this field, such as Yin (2003), Stake (1995) or Merriam (1998), cover multiple forms. These might include interviews, observations, questionnaires, artefacts and relevant background documents. However, interview questions, observation details to be identified, questions in a questionnaire, artefacts to be collected and specific background documents that might be relevant, can be informed by an appropriate underpinning model, framework or conception that aligns with the wider theoretical and philosophical stance of the study. In the case of a study looking at implementation of a digital technology, for example, TAM (Davis, 1989) or UTAUT (Venkatesh et al., 2003) might well provide a model or framework for this purpose.

An underpinning construct used to support or inform data collection might also apply to data analysis methods. Taking the example of a case study informed by the UTAUT framework (Venkatesh et al., 2003), it would be just as appropriate to use this framework for data analysis. Indeed, researchers have used such frameworks to undertake both qualitative analyses and quantitative analyses. For example, Abualbasal, Abu-Shanab and Al-Quraan (2016) undertook a quantitative analysis using the UTAUT framework within a case study of use of Microsoft Project by students, while Biljon and Renaud (2008) undertook a qualitative study using the UTAUT framework with a case study exploring applicability to senior mobile telephone users. So, although the same framework was used, it was clear that it was used in a quite different way in each of these studies; the role of the framework was quite different (see Table 3), and this means that the ontological and epistemological position, methodological approach and deign could also be quite different.

In a single study, if different models, frameworks or theories are chosen, then they must, of course, align, so that their relationship is understood, and so that they align paradigmatically. An example to illustrate this is shown in Table 4.

Table 4: An example of multiple forms of underpinning constructs for a study

The example shown in Table 4 is, on the one hand, complex in terms of the number of underpinning conceptions and theories that are involved, but on the other hand, it indicates the degree of concern that is needed when developing a proposal for a research study that is based through a particular and identified epistemological and ontological position. Alignment of theoretical and conceptual underpinning is important, how it is argued is important, the way it might then contribute to the literature and future research is to some extent determined, but none of this invalidates the possibility of questioning elements of underpinnings that are involved. During and at the end of a study, it is still possible to ask questions about the efficacy of underpinning theories and conceptions, and their relationship to findings at a methodological level.

Table 5 offers some further examples of how studies that have been undertaken over the past few years in the field of technology enhanced learning (TEL) have been underpinned by models, frameworks or theories.

Table 5: Examples of studies in TEL that have used a range of underpinning constructs

As can be seen from Table 5, using models, frameworks or theories to underpin research studies neither involves a singular approach, nor is it necessarily a simple choice. In all these cases, the use of models, frameworks and theories has been argued by the authors, and relates to their specific studies and the needs of that research. In the case of Almpanis (2015), for example, it was the argument for epistemological and ontological position that formulated the argument for subsequent uses of underpinning models and frameworks to support the research methods of data collection and analysis. In the case of Topol (2016), it was the argument arising from a concern for understanding the philosophical underpinning that led to subsequent uses of models and frameworks for the research design. By contrast, Essam (2019) and Kotsovoulou (2020) focused the majority of their argument on the underpinnings of their research design and methods.

Reading the range of research studies that are listed in Table 5, it is clear that at doctoral level, and for theses, a great deal of detail and associated word count is devoted to the description and argument associated with enabling the reader to understand their choices and uses of model, framework, conceptual or theoretical underpinnings. Journal articles, whilst commonly considered to be a main source of research background, do not usually provide for this same level of detail and allow for a word count that can be devoted to this element or level of description. It could be argued that this might be a reason why so many journal articles do not give so much attention to the detailed discussion and description of this element, and, consequently, appear to be devoid of conceptual or theoretical underpinnings. Some journals do specifically aim their paper selection and focus on conceptual and theory development, and on theoretical concerns, such as Theory and Research in Education (Sage Journals, n.d.), or Educational Theory (Wiley, 2020). In the field of technology enhanced learning, there are authors who focus strongly on theoretical concerns, and draw attention to the importance of developing scholarship more fundamentally in this direction (for example, Oliver, 2002; Bennett & Oliver, 2011).

5. How a study might contribute to knowledge or theory

Going back to the original discussion about contributions to research, policy and practice, the question remains as to what contribution a study can make when it is based on theoretical and conceptual underpinnings. A part of this contribution must, of course, come from addressing a gap in the literature – but to what extent that gap is related to or reliant on theoretical or conceptual underpinnings is an important question to ask. Certainly, Bennett and Oliver (2011) argue that contribution can come from more focused studies that explore the very nature of underpinning theoretical conceptions of technology enhanced learning. Whilst it is possible to see how contributions could arise, it is also important to consider how the use of underpinnings might lead to limitations. Passey (2019), for example, argues that the concept of technology enhanced learning itself has not been developed in contemporary contexts and that this in itself is a potential limitation to understanding how underpinnings can be appropriately considered and selected. One way to consider these concerns (although it should be recognised that this is not the only way that this could be done), is as follows.

For a model, contributions to research knowledge might be either understanding how the model might apply to other contexts (as in Tam, 2014, for example), or understanding whether the elements in the model apply, the extent to which they apply, or whether some should be added or amended. Contributions to policy or practice knowledge might be understanding how the model applies to a specific policy or practice area not previously researched, or understanding how the model supports specific actors involved in policy or practitioner actions and decisions. In some circumstances, a model might not be found to be highly applicable, and whilst this can in itself be a contribution rather than a limitation, a study might provide evidence that the model is more contextual than had been initially considered. Alternatively, in some cases, the model might limit the factors that are considered, so that others that are pertinent are not recognised – so, data collection and analysis methods need to accommodate for the possibility of drawing out additional factors that go beyond those in the initial model or framework. In the field of research in technology enhanced learning, contributions that can arise from and limitations that apply to the use of underpinning models is of particular importance. As technologies continue to be developed, their functionality shifts over time, their uses shift over time, and the ways they are integrated into social practices shift over time. This means that models arising from research in one technological and temporal context need to be regularly checked for applicability to other contexts. The way in which the TAM (Davis, 1989) was checked and developed into the UTAUT (Venkatesh et al., 2003) shows how an initial concern with identifying user acceptance (of temporal importance in the 1980s) was shifted to a later concern on identifying use within social practices (of greater concern in the 2000s). In this regard, if research studies that are undertaken continue to focus on challenges that are linked to temporality and focus on matters of technological development and their outcomes rather than on longer-term patterns of development that apply to social and societal concerns, then applicability is likely to be focused much more on a ‘new’ technology than it would be on the movement to a contemporary social practice.

For a conceptual framework, the same contributions as those in the point above could apply. For contributions to policy or practice knowledge, giving recommendations to those in policy or practice, based on the findings of the research using the conceptual framework might also apply (as was the case in McDowell, 2018, for example). Not in this case, but it is always worth noting that a chosen framework might similarly limit the factors that are considered, so that others that are pertinent are not recognised. Again, data collection and analysis methods need to accommodate for the possibility of drawing out additional factors that go beyond those in the initial framework (as in Alenezi, 2014, for example). In the field of research in technology enhanced learning, contributions that can arise from the use of underpinning conceptual frameworks may address some of the limitations of using models for underpinning purposes. A conceptual framework can be used in a time-bounded way, but it can be used in ways that also consider shifts and developments over time. It might be argued that understanding a shift over time might offer a more predictive possibility in terms of outcomes. For technology enhanced learning, therefore, this could mean that whilst a model might offer ideas for implementation into practice over a short time period (if it is contextually bounded), a conceptual framework might offer a wider policy and practice perspective that would enable predictions applying to implementation and uses over longer projected periods of time. An example of this form of predictive potential would be the case of networked learning. Findley (1988) developed initial concepts of Collaborative Networked Learning in a seminal research project. The term and concept have endured, nevertheless, over time and context. Nearly 20 years later, Goodyear, Banks, Hodgson and McConnell (2004) clarified and defined the concept in terms of educational practices. Nearly 20 years after that, the concept is still pertinent, and applicability in contemporary contexts is regularly researched, revisited and applied - for example, in the practices used to support doctoral student engagement on programmes at Lancaster University in the Department of Educational Research (2020).

For a theoretical framework, the same contributions as those in the point above could apply. For contributions to research knowledge, understanding how the different theories that provide the basis for the theoretical framework work together, or offering a potentially different methodological approach that uses the theoretical framework, might also apply (as in Topol, 2016, for example). The framework might again limit the factors that are considered, so that others that are pertinent are not recognised, implying that data collection and analysis methods should accommodate for the possibility of drawing out additional factors that go beyond those in the initial framework. The ways that the different theoretical elements relate should undoubtedly be questioned as a part of the study, and one way to address this would be through the research questions, which might include one that explores the relationship of the different theoretical elements within the study approach taken. In the field of research in technology enhanced learning, contributions that can arise from the use of underpinning theoretical frameworks may similarly potentially address some of the limitations of using conceptual frameworks for underpinning purposes. While conceptual frameworks offer longer-term perspectives compared to models, they can also be limited in terms of wider social context. Networked learning, for example, is aligned to the context of learning and education. A theoretical framework can go beyond a single context, and cover wider social practices. Ngai, Tao and Moon (2015), for example, explored how previous research into social media and its applications had been underpinned by theory. Contextually, their review and findings went beyond a single subject context, but their conclusions nevertheless highlighted important areas for further research. The authors stated that “important areas, such as organization orientation, social power, cultural differences, and impacts of social media, have not received sufficient research attention” (p.42). In terms of the focus of their contribution, this was clearly focused as a research contribution. If they had been seeking a practice or policy contribution, their research questions, selection of literature, and specificity of context would have been quite different, and this might well have led them to take a focus underpinned more at a model or conceptual level (see Kotsovoulou, 2020, for example).

For a theory, the same contributions as those in the point above that relate to a conceptual framework could similarly apply. Additionally, for contributions to research knowledge, understanding whether the features in the theory apply, or whether some features should be added or amended could also apply. If the theory is not questioned as a part of the study, its applicability to that context will not be questioned. To address this limitation, research questions should include one that explores the validity of the theory within the study context. In the field of research in technology enhanced learning, contributions that can arise from the use of theories may similarly address some of the limitations of using theoretical frameworks for underpinning purposes. Bower (2019), for example, develops and argues the case for adopting technology-mediated learning theory, basing this contemporary theory on a wide variety of background frameworks and prior theories. Theories of this form provide the widest forms of contextual underpinnings, but at the same time, those theories can still be based on limited geographic and cultural contexts (see Lee, 2018, for example).

Forms of contribution from research clearly relate to the ways that models, frameworks or theories are applied within the overall research study and design. In the example in Table 4, social constructivism as an ontological and epistemological position might be considered at the end of the study in terms of how far or at what levels it is matched or applied, whereas contextual constructivism could perhaps be more questioned as to its validity within the study, and whether there were strengths or weaknesses related to its use. In the same example, regarding the use of self-determination theory and self-theories of motivation, the ways that these are linked, the appropriateness of their use, and whether any features or factors emerged that would be particularly highlighted, added or redundant, could certainly add to a theoretical contribution, related to the context of the study.

When considering contribution, limitations should be considered in terms of the ways that theory and other underpinnings are used. Going back to the categorisation of uses of theory by Oliver (2012), limitations vary according to intended use, whether it is intended that theory be used as a tool, a principle, whether it is intended for theory building, or for theory using. From this categorisation, using theory for theory building is clearly the most likely to avoid limitations of theoretical contribution (see Bower, 2019, for example).

6. Conclusions

The key conclusion that arises from the discussion and argument presented in this paper is that choice of underpinning and choice of role that models, frameworks or theories play can both provide for and potentially limit the opportunity for a study to question and, therefore, to develop theory as a contribution arising from that study. The role of questioning and argument (criticality) is paramount in addressing these concerns.

When considering using models, conceptual and theoretical frameworks, and theories to underpin a research study, to avoid limitations when considering appropriate underpinnings, the analysis from this paper highlights and recommends:

For any underpinning considered, its status from the originating research should be identified and recognised. From this understanding, an appropriate focus through research questions, design and methods can draw out particular areas of contribution, which can be different in each of the cases for a model, framework or theory. This is particularly important for research in technology enhanced learning as the field is relatively new, so many models, frameworks or theories are often taken from different contexts. For example, Kim and Hannafin (2011) explored the appropriateness of the basis of constructs of problem-solving and scaffolding (both developed outside the technology enhanced learning field) when they studied the scaffolding of problem-solving in technology enhanced learning environments.

Similarly, the context from which any underpinning is generated should be identified and recognised. Questions about applicability within other contexts, and in the context of a specific study, should be raised. For example, Lytras, Sarirete and Damiani (2020) explored technology-enhanced learning from a transformative perspective, but as this was in the context of higher education, how far their model would apply to training, compulsory or vocational education sectors is not clear.

Criticality is a key concept that should be applied as much to models, frameworks and theories as it is to the focal concern or the problem of the study to be investigated itself. This criticality should apply through a study’s research questions and methods as much as through any review of literature or previous research. For example, how far does Laurillard’s conversational framework (2002) enable the practice of teacher professional development in creating e-books for reluctant readers to be assessed as effective by an observer?

Epistemological and ontological stance within a study may shape the choice and role(s) of models, frameworks and theories. This does not eliminate a concern to question how those with other epistemological and ontological stances might still gain in terms of contribution arising from a study that is based on a specific stance and appropriate underpinnings. For example, how far do the findings of a study about uses of social media to support peer learning through an interpretivist approach enable recommendations to be viewed as feasible by policy makers with positivist stances?

Methodological design that is underpinned by appropriate models, frameworks or theories does not mean that the design itself cannot be questioned. Critical questioning of methodological design (underpinned by appropriate models, frameworks or theories) can lead to developments that contribute to research in major ways. For example, Collins, Joseph and Bielaczyc (2004) questioned whether a methodological approach using design research, underpinned by pragmatism, was appropriate and could be developed for analysing evaluative needs to support developments such as communities of learners. Similarly, Wang and Collins (2005) questioned appropriateness and future challenges in using a design-based research approach in developing technology-enhanced learning environments.

Research questions should be framed in ways that allow alternative ways to view factors and features relating to underpinning models, frameworks or theories. Finding contextual matches, shifts, amendments or additions can all offer important contributions to the field. For example, Varga-Atkins (2019) used research questions that allowed her study to identify an additional element to Shulman’s underpinning concept of signature pedagogies (2005a), in the form of signature assessments.

Contributions to policy and practice should be considered in the context of underpinning models, frameworks or theories. The generation of recommendations to policy and practice can be important contributions in themselves, which can evolve from research findings that have been underpinned by previous policy or practice. For example, Alenezi (2013), by reviewing underpinning concepts in a Saudi context, was able to offer recommendations for policy that aligned specifically with that context.

Concerns for underpinning of our studies through an appropriate conceptual and theoretical base can present a challenge for us as researchers. It is clear that our research knowledge in the areas of epistemological and ontological positions, methodological approaches and design, research data collection and analysis methods, have all relied upon critical perspectives by previous researchers through their published works. Taking models, frameworks and theories for granted will only limit our ultimate knowledge; we must be prepared to question these from the inside (when and during use) as well as from the outside (before we use them).

Acknowledgements

I would like to thank the PhD students I have supervised over the years, who have all, in their own ways, thoughtfully considered, selected and used models, frameworks, and theories to underpin their studies. Through their concerns and initiatives, I have gained insight into this area. Doctoral studies should always offer contribution to knowledge, and the students I have supervised have never failed to provide that for me. I am delighted to have had chance to acknowledge their work in this paper. My thanks also to the reviewers of this paper; their insights and careful reading have undoubtedly added to the finished product.

About the author

Don Passey , Centre for Technology Enhanced Learning, Department of Educational Research, Lancaster University, United Kingdom.

Don is Professor of Technology Enhanced Learning in the Department of Educational Research at Lancaster University, UK, and an Honorary Professor of the Institutes of Education and of Information Technology at Amity University, Uttar Pradesh, India. He is a current staff member of the Centre for Technology Enhanced Learning in the Department of Educational Research, and was a previous director and co-director of the Centre. He is currently the Director of Studies for the Doctoral Programme in e-Research and Technology Enhanced Learning. His research investigates how digital technologies support learning and teaching. Recent studies have explored innovative and inclusive practices, in and outside educational institutions and classrooms, in off-site, home and community settings. His findings have informed policy and practice, for international institutions and groups, government departments and agencies, regional and local authorities, companies and corporations. His publications span theoretical as well as empirical studies, and the methodological approaches he adopts widely range across bespoke mixed methods. He is currently chair of the International Federation for Information Processing (IFIP) Technical Committee on Education, has chaired a number of international conferences in his academic field, and is the recipient of Outstanding Service and Silver Core Awards from IFIP for his international contributions to his field in education.

Email : [email protected]

ORCID : 0000-0002-9205-502X

Article information

Article type: Full paper, double-blind peer review.

Publication history: Received: 01 June 2020. Revised: 22 June 2020. Accepted: 22 June 2020. Published: 24 June 2020.

Cover image: LTDatEDU via Pixabay.

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What is a Theoretical Framework? How to Write It (with Examples) 

Theoretical framework 1,2 is the structure that supports and describes a theory. A theory is a set of interrelated concepts and definitions that present a systematic view of phenomena by describing the relationship among the variables for explaining these phenomena. A theory is developed after a long research process and explains the existence of a research problem in a study. A theoretical framework guides the research process like a roadmap for the research study and helps researchers clearly interpret their findings by providing a structure for organizing data and developing conclusions.   

A theoretical framework in research is an important part of a manuscript and should be presented in the first section. It shows an understanding of the theories and concepts relevant to the research and helps limit the scope of the research.  

Table of Contents

What is a theoretical framework ?  

A theoretical framework in research can be defined as a set of concepts, theories, ideas, and assumptions that help you understand a specific phenomenon or problem. It can be considered a blueprint that is borrowed by researchers to develop their own research inquiry. A theoretical framework in research helps researchers design and conduct their research and analyze and interpret their findings. It explains the relationship between variables, identifies gaps in existing knowledge, and guides the development of research questions, hypotheses, and methodologies to address that gap.  

Now that you know the answer to ‘ What is a theoretical framework? ’, check the following table that lists the different types of theoretical frameworks in research: 3

Developing a theoretical framework in research can help in the following situations: 4

• When conducting research on complex phenomena because a theoretical framework helps organize the research questions, hypotheses, and findings  
• When the research problem requires a deeper understanding of the underlying concepts  
• When conducting research that seeks to address a specific gap in knowledge  
• When conducting research that involves the analysis of existing theories  

Summarizing existing literature for theoretical frameworks is easy. Get our Research Ideation pack  

Importance of a theoretical framework  

The purpose of theoretical framework s is to support you in the following ways during the research process: 2  

• Provide a structure for the complete research process  
• Assist researchers in incorporating formal theories into their study as a guide  
• Provide a broad guideline to maintain the research focus  
• Guide the selection of research methods, data collection, and data analysis  
• Help understand the relationships between different concepts and develop hypotheses and research questions  
• Address gaps in existing literature  
• Analyze the data collected and draw meaningful conclusions and make the findings more generalizable  

Theoretical vs. Conceptual framework  

While a theoretical framework covers the theoretical aspect of your study, that is, the various theories that can guide your research, a conceptual framework defines the variables for your study and presents how they relate to each other. The conceptual framework is developed before collecting the data. However, both frameworks help in understanding the research problem and guide the development, collection, and analysis of the research.  

The following table lists some differences between conceptual and theoretical frameworks . 5

How to write a theoretical framework  

The following general steps can help those wondering how to write a theoretical framework: 2

• Identify and define the key concepts clearly and organize them into a suitable structure.  
• Use appropriate terminology and define all key terms to ensure consistency.  
• Identify the relationships between concepts and provide a logical and coherent structure.  
• Develop hypotheses that can be tested through data collection and analysis.  
• Keep it concise and focused with clear and specific aims.  

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Examples of a theoretical framework  

Here are two examples of a theoretical framework. 6,7

Example 1 .   

An insurance company is facing a challenge cross-selling its products. The sales department indicates that most customers have just one policy, although the company offers over 10 unique policies. The company would want its customers to purchase more than one policy since most customers are purchasing policies from other companies.  

Objective : To sell more insurance products to existing customers.  

Problem : Many customers are purchasing additional policies from other companies.  

Research question : How can customer product awareness be improved to increase cross-selling of insurance products?  

Sub-questions: What is the relationship between product awareness and sales? Which factors determine product awareness?  

Since “product awareness” is the main focus in this study, the theoretical framework should analyze this concept and study previous literature on this subject and propose theories that discuss the relationship between product awareness and its improvement in sales of other products.  

Example 2 .

A company is facing a continued decline in its sales and profitability. The main reason for the decline in the profitability is poor services, which have resulted in a high level of dissatisfaction among customers and consequently a decline in customer loyalty. The management is planning to concentrate on clients’ satisfaction and customer loyalty.  

Objective: To provide better service to customers and increase customer loyalty and satisfaction.  

Problem: Continued decrease in sales and profitability.  

Research question: How can customer satisfaction help in increasing sales and profitability?  

Sub-questions: What is the relationship between customer loyalty and sales? Which factors influence the level of satisfaction gained by customers?  

Since customer satisfaction, loyalty, profitability, and sales are the important topics in this example, the theoretical framework should focus on these concepts.  

Benefits of a theoretical framework  

There are several benefits of a theoretical framework in research: 2  

• Provides a structured approach allowing researchers to organize their thoughts in a coherent way.  
• Helps to identify gaps in knowledge highlighting areas where further research is needed.  
• Increases research efficiency by providing a clear direction for research and focusing efforts on relevant data.  
• Improves the quality of research by providing a rigorous and systematic approach to research, which can increase the likelihood of producing valid and reliable results.  
• Provides a basis for comparison by providing a common language and conceptual framework for researchers to compare their findings with other research in the field, facilitating the exchange of ideas and the development of new knowledge.  

Frequently Asked Questions 

Q1. How do I develop a theoretical framework ? 7

A1. The following steps can be used for developing a theoretical framework :  

• Identify the research problem and research questions by clearly defining the problem that the research aims to address and identifying the specific questions that the research aims to answer.
• Review the existing literature to identify the key concepts that have been studied previously. These concepts should be clearly defined and organized into a structure.
• Develop propositions that describe the relationships between the concepts. These propositions should be based on the existing literature and should be testable.
• Develop hypotheses that can be tested through data collection and analysis.
• Test the theoretical framework through data collection and analysis to determine whether the framework is valid and reliable.

Q2. How do I know if I have developed a good theoretical framework or not? 8

A2. The following checklist could help you answer this question:  

• Is my theoretical framework clearly seen as emerging from my literature review?  
• Is it the result of my analysis of the main theories previously studied in my same research field?  
• Does it represent or is it relevant to the most current state of theoretical knowledge on my topic?  
• Does the theoretical framework in research present a logical, coherent, and analytical structure that will support my data analysis?  
• Do the different parts of the theory help analyze the relationships among the variables in my research?  
• Does the theoretical framework target how I will answer my research questions or test the hypotheses?  
• Have I documented every source I have used in developing this theoretical framework ?  
• Is my theoretical framework a model, a table, a figure, or a description?  
• Have I explained why this is the appropriate theoretical framework for my data analysis?  

Q3. Can I use multiple theoretical frameworks in a single study?  

A3. Using multiple theoretical frameworks in a single study is acceptable as long as each theory is clearly defined and related to the study. Each theory should also be discussed individually. This approach may, however, be tedious and effort intensive. Therefore, multiple theoretical frameworks should be used only if absolutely necessary for the study.  

Q4. Is it necessary to include a theoretical framework in every research study?  

A4. The theoretical framework connects researchers to existing knowledge. So, including a theoretical framework would help researchers get a clear idea about the research process and help structure their study effectively by clearly defining an objective, a research problem, and a research question.  

Q5. Can a theoretical framework be developed for qualitative research?  

A5. Yes, a theoretical framework can be developed for qualitative research. However, qualitative research methods may or may not involve a theory developed beforehand. In these studies, a theoretical framework can guide the study and help develop a theory during the data analysis phase. This resulting framework uses inductive reasoning. The outcome of this inductive approach can be referred to as an emergent theoretical framework . This method helps researchers develop a theory inductively, which explains a phenomenon without a guiding framework at the outset.  

Q6. What is the main difference between a literature review and a theoretical framework ?  

A6. A literature review explores already existing studies about a specific topic in order to highlight a gap, which becomes the focus of the current research study. A theoretical framework can be considered the next step in the process, in which the researcher plans a specific conceptual and analytical approach to address the identified gap in the research.  

Theoretical frameworks are thus important components of the research process and researchers should therefore devote ample amount of time to develop a solid theoretical framework so that it can effectively guide their research in a suitable direction. We hope this article has provided a good insight into the concept of theoretical frameworks in research and their benefits.  

References  

• Organizing academic research papers: Theoretical framework. Sacred Heart University library. Accessed August 4, 2023. https://library.sacredheart.edu/c.php?g=29803&p=185919#:~:text=The%20theoretical%20framework%20is%20the,research%20problem%20under%20study%20exists .  
• Salomao A. Understanding what is theoretical framework. Mind the Graph website. Accessed August 5, 2023. https://mindthegraph.com/blog/what-is-theoretical-framework/  
• Theoretical framework—Types, examples, and writing guide. Research Method website. Accessed August 6, 2023. https://researchmethod.net/theoretical-framework/  
• Grant C., Osanloo A. Understanding, selecting, and integrating a theoretical framework in dissertation research: Creating the blueprint for your “house.” Administrative Issues Journal : Connecting Education, Practice, and Research; 4(2):12-26. 2014. Accessed August 7, 2023. https://files.eric.ed.gov/fulltext/EJ1058505.pdf  
• Difference between conceptual framework and theoretical framework. MIM Learnovate website. Accessed August 7, 2023. https://mimlearnovate.com/difference-between-conceptual-framework-and-theoretical-framework/  
• Example of a theoretical framework—Thesis & dissertation. BacherlorPrint website. Accessed August 6, 2023. https://www.bachelorprint.com/dissertation/example-of-a-theoretical-framework/  
• Sample theoretical framework in dissertation and thesis—Overview and example. Students assignment help website. Accessed August 6, 2023. https://www.studentsassignmenthelp.co.uk/blogs/sample-dissertation-theoretical-framework/#Example_of_the_theoretical_framework  
• Kivunja C. Distinguishing between theory, theoretical framework, and conceptual framework: A systematic review of lessons from the field. Accessed August 8, 2023. https://files.eric.ed.gov/fulltext/EJ1198682.pdf  

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Writing a Counselling Case Study

As a counselling student, you may feel daunted when faced with writing your first counselling case study. Most training courses that qualify you as a counsellor or psychotherapist require you to complete case studies.

Before You Start Writing a Case Study

However good your case study, you won’t pass if you don’t meet the criteria set by your awarding body. So before you start writing, always check this, making sure that you have understood what is required.

For example, the ABC Level 4 Diploma in Therapeutic Counselling requires you to write two case studies as part of your external portfolio, to meet the following criteria:

• 4.2 Analyse the application of your own theoretical approach to your work with one client over a minimum of six sessions.
• 4.3 Evaluate the application of your own theoretical approach to your work with this client over a minimum of six sessions.
• 5.1 Analyse the learning gained from a minimum of two supervision sessions in relation to your work with one client.
• 5.2 Evaluate how this learning informed your work with this client over a minimum of two counselling sessions.

If you don’t meet these criteria exactly – for example, if you didn’t choose a client who you’d seen for enough sessions, if you described only one (rather than two) supervision sessions, or if you used the same client for both case studies – then you would get referred.

Check whether any more information is available on what your awarding body is looking for – e.g. ABC publishes regular ‘counselling exam summaries’ on its website; these provide valuable information on where recent students have gone wrong.

Selecting the Client

When you reflect on all the clients you have seen during training, you will no doubt realise that some clients are better suited to specific case studies than others. For example, you might have a client to whom you could easily apply your theoretical approach, and another where you gained real breakthroughs following your learning in supervision. These are good ones to choose.

Opening the Case Study

It’s usual to start your case study with a ‘pen portrait’ of the client – e.g. giving their age, gender and presenting issue. You might also like to describe how they seemed (in terms of both what they said and their body language) as they first entered the counselling room and during contracting.

If your agency uses assessment tools (e.g. CORE-10, WEMWBS, GAD-7, PHQ-9 etc.), you could say what your client scored at the start of therapy.

Free Handout Download

Writing a Case Study: 5 Tips

Describing the Client’s Counselling Journey

This is the part of the case study that varies greatly depending on what is required by the awarding body. Two common types of case study look at application of theory, and application of learning from supervision. Other possible types might examine ethics or self-awareness.

Theory-Based Case Studies

If you were doing the ABC Diploma mentioned above, then 4.1 would require you to break down the key concepts of the theoretical approach and examine each part in detail as it relates to practice. For example, in the case of congruence, you would need to explain why and how you used it with the client, and the result of this.

Meanwhile, 4.2 – the second part of this theory-based case study – would require you to assess the value and effectiveness of all the key concepts as you applied them to the same client, substantiating this with specific reasons. For example, you would continue with how effective and important congruence was in terms of the theoretical approach in practice, supporting this with reasoning.

In both, it would be important to structure the case study chronologically – that is, showing the flow of the counselling through at least six sessions rather than using the key concepts as headings.

Supervision-Based Case Studies

When writing supervision-based case studies (as required by ABC in their criteria 5.1 and 5.2, for example), it can be useful to use David Kolb’s learning cycle, which breaks down learning into four elements: concrete experience, reflective observation, abstract conceptualisation and active experimentation.

Rory Lees-Oakes has written a detailed guide on writing supervision case studies – entitled How to Analyse Supervision Case Studies. This is available to members of the Counselling Study Resource (CSR).

Closing Your Case Study

In conclusion, you could explain how the course of sessions ended, giving the client’s closing score (if applicable). You could also reflect on your own learning, and how you might approach things differently in future.

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• Published: 05 August 2024

Public participation in the conservation and management of canal cultural heritage worldwide: a case study of the Rideau Canal and Erie Canal

• Zhengqing Gu 1 &
• Dexin Tian   ORCID: orcid.org/0000-0002-7361-5140 2  

Humanities and Social Sciences Communications volume  11 , Article number:  1005 ( 2024 ) Cite this article

Metrics details

• Business and management
• Cultural and media studies
• Development studies

To shed light on the conservation and management of canal cultural heritage worldwide, this paper examines the relevant experience and implications acquired from the US Erie Canal and Canadian Rideau Canal from the perspective of public participation in terms of four dimensions: subject, concept, content, and horizon. The study findings are fourfold: first, the factors such as residents of the Heritage Corridor, non-governmental organizations, non-profit enterprises, private forces, tourists, and individual volunteers constitute the subject of public participation. Second, both sides concur that extensive public involvement is the driving force behind the success of cultural heritage conservation and management. This wide involvement is conducive to promoting education and shaping national identity. Third, for both sides, public participation is integral to the Heritage Corridor project management plan, spanning the entire process of drafting, revising, implementing, and evaluating. Finally, both sides have been leveraging modern information technology and social media, such as web home pages, databases, virtual discussions, Facebook, Twitter, and Instagram, to promote public participation, and achieving double the results with half the effort. The implications of the findings lie in four aspects: first, the canal community committees assume leadership responsibilities with relevant laws and regulations in place as legal backup; second, both the US and Canadian sides take effective measures to organize, recognize, and appreciate participants; third, they demonstrate the spirit of democratic participation and exemplary deliberation throughout the cultural heritage canal conservation and management process; and finally, both sides maximize the use of modern information technologies for efficient conservation and management of their respective Canal Cultural Heritage Corridors.

Introduction

In the information age featuring digitalization, big data, and artificial intelligence (AI), public participation has become increasingly essential in all social sectors, including the conservation and management of cultural heritage worldwide. Public participation, which is used interchangeably as public engagement, public involvement, citizen participation, or public democracy in this paper, refers to “any of the several mechanisms intentionally instituted to involve the lay public or their representatives in administrative decision-making” (Beierle and Cayford, 2002 , p. 6). As Kumpu ( 2022 ) notes, “civic engagement, public participation, and public involvement” all underscore the significance of “involving citizens, customers, employees, and stakeholders in the activities of governments, businesses, scientific and arts institutions, and organizations of various kinds in policy making processes” (p. 306). Pierroux et al. ( 2020 ) also remark that “at the crux of all citizen projects are the volunteers…who dedicate their senses, passions, and knowledge to ongoing research in natural, cultural, and science heritage” (p. 5). Thus, we not only understand what public participation means but also appreciate its significance.

Regarding the significance of public participation in environmental conservation, the United Nations Economic Commission for Europe (UNECE) adopted the convention on access to information, public participation in decision-making and access to justice in environmental matters at its fourth Ministerial Conference in Denmark from 23 to 25 June 1998 (Economic Commission for Europe Secretariat, 1998 , p. 3). Specifically, concerning the significance of conserving and managing cultural heritage, UNESCO ( 2022 ) rules that “within the framework of its safeguarding activities of the intangible cultural heritage, each country shall endeavor to ensure the widest possible participation of communities, groups and, where appropriate, individuals that create, maintain and transmit such heritage so as to involve them actively in its management” (p. 12). Since the beginning of the 21st century, with the rapid development of modern civil society, the “public participation community” composed of governments, citizens, experts, and the media has initially emerged. It can be seen that the effect of public participation in the conservation and management of cultural heritage has received attention from all parties.

However, while the concept of heritage conservation continues to evolve, the content of heritage conservation is also becoming increasingly complex, and it is challenging for government-led static management to meet today’s dynamic conservation needs. In the overall management system of conservation, inheritance, and utilization of canal tangible and intangible cultural heritage in the world, the overall degree of community participation in some developing countries is not high enough, and the dominant position of communities in the intangible cultural heritage conservation system has not yet been established. In the case of China, the lack of public participation makes the conservation of the cultural heritage of the Grand Canal insufficiently supervised, coupled with its development bottlenecks and “destructive construction” pressure, resulting in the excessive commercial development of the Grand Canal heritage and serious loss of original residents (Fu, Cao and Huo, 2021 ). Clearly, in the conservation and management of canal cultural heritage worldwide, establishing an effective path and mechanism of public participation has become an urgent issue and responsibility of relevant government departments, academic circles, and the general public.

Since public participation in the conservation and management of cultural heritage is still in its infancy in quite a number of developing countries, lessons and experience can be drawn from those developed countries that have witnessed hundreds of years herein. Meanwhile, little has been written about the experience and implications of advanced countries in their conservation and management of cultural heritage for the sake of shedding light on other canals in the rest of the world, especially those listed on the World Heritage List. Therefore, this paper first summarizes the cultural heritage content of the Heritage Canals of the World and then elaborates on the theoretical basis and conceptual evolution of public participation. Furthermore, the significance of public participation in environmental issues is discussed. Finally, this paper investigates the experience and implications that can be learned from the Erie Canal in the US and the Rideau Canal in Canada from the four dimensions of subject, concept, content, and horizon. To this end, the following research questions (RQ) are raised:

RQ1: What experience can be drawn from the Erie Canal in the US and the Rideau Canal in Canada in their respective conservation and management of canal cultural heritage?

RQ2: What implications do the above experience hold for the bottleneck issues in the conservation and management of canal cultural heritage worldwide?

Literature review

Research on the world heritage canals.

Globalization is creating new perspectives on social and cultural spaces, which leads to changes in the expression of culture, identity, and belonging, as well as the role of heritage today (Colomer, 2017 ). In the preface to the Convention concerning the Protection of the World Cultural and Natural Heritage, UNESCO ( 1972 ) emphasizes that those “parts of the cultural or natural heritage of outstanding interest…need to be preserved as part of the world heritage of mankind as a whole”, and “it is incumbent on the international community as a whole to participate in the protection of the cultural and natural heritage” (p. 1). The 2005 Faro Convention underscores the importance of citizens’ responsibilities in assigning heritage values, thereby introducing the concept of “heritage communities” that encompass individuals who cherish particular elements of cultural heritage and aspire to preserve and pass them down to future generations through public action (Council of Europe, 2005 ). Based on the information from the UNESCO World Heritage Centre ( 2022 ) and the research results of scholar Liu ( 2020 ), the names of the eight World Heritage Canals, their location countries, the time of inclusion in the World Heritage List, the standard serial number, and the evaluation summary of the World Heritage Committee can be listed as follows:

In Table 1 , except for Iran, China, and Mexico, the other five World Heritage canals are all located in western developed countries and belong to the products of industrial civilization. According to the Operational Guidelines for the Implementation of the World Heritage Convention issued by UNESCO ( 2023 ), all heritage sites listed in the World Heritage List must have long-term and sufficient legislative and normative measures to ensure the conservation of the heritage sites. From the practice of its legislation, most western world heritage canals have formulated a relatively exemplary heritage conservation law system. For instance, Canada has issued the Historic Sites and Monuments Act, which has played a substantial role in the effective management of the Rideau Canal by the coordination of the Parks Canada Agency and other relevant authorities. The other four Western countries have established similar working mechanisms in their respective conservation and management of the cultural heritage of their world heritage canals. This study has singled out the Erie Canal in the US as a representative of the non-world heritage canals and the Rideau Canal in Canada as a representative of the world heritage canals for detailed explorations.

At present, there are >520 canals in the world, distributed across >50 countries, involving >3000 cities along the route. Carrying the history and culture, the canals, as a unique living cultural heritage, have always been the spiritual home of people from all over the world, and have accumulated profound and long cultural deposits (Fan and Shi, 2022 ). As important cultural heritage globally, the canals have garnered the general attention of scholars at home and abroad with their unique historical and cultural connotations and tourism development values. In the process of conserving, managing, and developing tourism for canal cultural heritage worldwide, a series of problems have emerged. For instance, in the early development of the European canal cultural heritage, there were many problems such as single canal tourism products, lack of tourism image brand, and uneven distribution of interests (Gfeller and Eisenberg, 2016 ). Flemsæter et al. ( 2020 ) use the rhythm analysis to explore the rhythm of the tourist experience of the Telemark Canal in Norway and believe that the lack of connection between tourists and the host community has caused a serious disorder in local and regional economic, social, and cultural development. Through research on the Amsterdam Canal, Pinkster and Boterman ( 2017 ) have found that as more tourists arrive, the dissatisfaction of residents living in the canal area is growing, but in the face of many troubles brought by tourism, residents are unable to change the status quo. As a world heritage canal, the Grand Canal of China is a large-scale linear multi-functional cultural ecology with the largest space-time span, the highest technical content, and the most colorful content among all canals in the world. However, the awareness and concept of the general public to participate in the conservation of canal heritage is still in its embryonic stage, which cannot provide sufficient human, material, and financial support for organized development at a higher level (Chu, 2016 ).

Thus, we observe such issues in most developing countries as the lack of collaboration between tourists and host communities on both sides of the canals, the increasing dissatisfaction of residents living in canal areas, and the general public’s weak awareness of canal heritage protection. All this has made public participation in the conservation and management of canal cultural heritage worldwide an important topic for further research.

The theoretical basis and conceptual evolution of public participation

The theoretical basis.

In the process of social governance, the public is the most critical interest subject. Therefore, public participation in the management of public affairs is not only the basic right of citizens but also an important way to realize democratic politics. Specifically, public participation refers to “the ability of individual citizens and groups to influence environmental decisions through (1) access to relevant information, (2) public comments to the agency responsible for a decision, and (3) the right, through the courts, to hold public agencies and businesses accountable for their environmental decisions and behaviors” (Cox, 2006 , p. 84). Three rights can be delineated from Cox’s definition: the right to know as transparency, the right to comment as direct participation, and the right of standing as accountability (Walker, 2007 ). In the Internet age, the information transmission chain and transactional model of communication constructed by the mobile Internet, mobile phone SMS, blog, microblog, WeChat, APP client, etc., are profoundly changing the traditional political ecology and the logic of social operation (Ni, 2017 ). The term “public participation” originates from the West. Traditional public participation refers to the activities of civic voting, while public participation in the modern sense refers to the social behavior that individuals or social organizations outside the government are trying to influence the decision-making and governance of public affairs by law (Cheng, 2017 ). In the city-state society of ancient Greece, democracy is mainly the direct participatory management of public life. As a representative of classical democratic theory, Rousseau believes that civic participation in the political decision-making process could not only make the democratic system possible but also promote individual responsible social action and political action (Wang, 2008 ). In modern social governance, Spanish scholar Barnes has proposed the concept of the third generation of administrative procedures for national governance in the context of risk society. The third generation of administrative procedures emphasizes: first, to improve the quality of decision-making and implementation by enhancing the understanding of real risk and risk decisions; second, the decision with multiple subjects has a higher formal rationality for the public; third, the public’s deep participation in the process of risk decision consultation also has a declaration and educational effect. Compared with traditional administrative procedures, the third generation of administrative procedures is more open, multi-orderly, and consultative (Wu and Zhang, 2023 ).

In the digitalized information age of media generalization, technology empowerment makes the relationship between the communication subject and the object tend to generalize. The generalization of information production and consumption participants activates the user’s autonomy and selectivity. The direct conversion from behavioral data to content production clearly shows that user production tends to be subjective. As Castells ( 2018 ) believes, one of the reasons for the transformation of the traditional social power model to the network social power model is the “presence” of people’s spatial power, that is, the development of the Internet and wireless communication supports and strengthens the audience’s independent practice, including uploading user-created content on the Internet. In the era of digital artificial intelligence, the logic of information is user-based, and the starting point of the collection, processing, generation, and dissemination of all data is the network behavior of the public. The information sharing will be continuously improved and iterated along the logic of user needs (Lv and Huang, 2022 ). To give full play to the utility of network technology innovatively, the public network participants can ensure the essence and effect of their public participation from the aspects of public opinion expression, technology drive, and system guarantee. Besides, Roberts ( 2004 ) emphasizes that public participation may involve deliberation, which means that the involved parties make their decisions through dialog, exchange of ideas, and mutual learning. It can be seen that public network participation is not only a political phenomenon involving state power and interest relations but also an act of citizens carrying out political complaints and participating in social management through interactive communication and mutual learning.

As the integrator of the theory of public participation, the ladder of citizen participation proposed by the American scholar Arnstein in 1969 still has guiding significance in the digital age of technology empowered. Specifically, Arnstein ( 1969 ) divides the public participation ladder into three levels, namely, from low to high, including no participation model, representation participation model, and active participation model. It goes without saying that under the no-participation model, the public does not enjoy the right to participate or passively participate in governance activities in social governance. Under the representation participation model, public participation behavior is more of a form of amusement. And only under the active participation model, the public has gained more rights to participate, reflecting the overall participation and substantial participation effect.

Evolution of the concept of public participation

As a historical category, public participation has undergone a process of evolution, enrichment, and expansion. Because public participation encompasses a wide range of fields, its definition varies across different fields. To Friedmann ( 1987 ), public participation refers to the fact that the public participates in the decision-making process in the form of groups. Glass ( 1979 ) interprets it as a process or opportunity for the public to participate in government decision-making and planning.

In the “Internet +” era, public participation is characterized by the following features: First, in terms of the subjects, government agencies, the general public, including individuals, experts and scholars, social organizations, non-governmental organizations, and non-profit enterprises constitute the main body of public participation. Second, in terms of the concept, from the obligation standard to the right standard, citizens in modern society bear not only the duty to participate in the management of state and social affairs but also the due right. Third, in terms of the content, public participation is expanded from state affairs to social affairs. This means that the public has shifted from pure political participation to involvement in various public affairs. Finally, in terms of the horizon, it extends from real life to the virtual world. In today’s digital information age, the development of the Internet has provided an unprecedented free and equal communication public space for public participation, making it shift from “absence” to “presence”, and then through the “legal and orderly” path, to ensure the “civilized and effective” virtual public participation activities (Cheng, 2017 ). Therefore, public participation essentially comprises such components as the subject, concept, content, and horizon.

In short, with the drastic changes in social structure and profound changes in ideas, non-profit enterprises, the general public, and non-governmental organizations consciously participate in public governance in various forms, which is becoming a norm, and public participation is also becoming a trend in the conservation of cultural heritage worldwide. Some developed countries, such as the US and Canada, have a history of hundreds of years of protecting cultural heritage, which can provide a lot of valuable experience worth learning from. Now that the research on public participation in the conservation of cultural heritage is still in its infancy, it is not comparable in many aspects. The main body of public participation in the US and Canada is mostly the same; however, the situation is somewhat different in China. The public in the US and Canada refers to tourists, indigenous people, volunteers, related experts and scholars, and technical personnel, but the public of the Grand Canal of China refers to the canal coast residents, relevant experts, professional and technical personnel, users or consumers, and volunteers (Zhang and Qiu, 2019 ).

To sum up, public participation has shifted from the political field to a wider range of social public affairs such as legislation, urban planning, environmental governance, and heritage conservation. The period from 1970 to 1990 has been the embryonic stage of the public value concept of heritage. The Amsterdam Declaration , issued in 1975, has emphasized that the survival of architectural heritage depends on public attention, particularly among young people. In 1976, the Nairobi Proposal , adopted by UNESCO, encourages individuals, groups, and heritage users to contribute to heritage conservation. Since 1990, it has been the rise and application stage of the public value concept of heritage. Through the reflection of authoritative heritage discourse, people begin to explore the transformation of heritage conservation power from authority to the public, thus giving birth to the emergence of the public value concept of heritage. This concept links heritage with daily public life and pays attention to effective interaction between them, so that more people care about and protect heritage, promoting the formation of the heritage conservation force and conservation mechanism (Fu et al. 2021 ). This is why, in 2007, the World Heritage Committee has added “community involvement” to the original “4C” principles of credibility, conservation, capacity-building, and communication to highlight the importance of community people in heritage conservation and sustainable development, thus forming the ground and strategic framework for heritage conservation in the 21st century (Wei, 2022 ). In this paper, we adopt the four dimensions of subject, concept, content, and horizon of public publication as the theoretical framework.

Cultural heritage value and significance of public participation

Adopted by the Australia International Council on Monuments and Sites (ICOMOS), a non-governmental organization that focuses on cultural heritage conservation, the Burra Charter “provides guidance for the conservation and management of places of cultural significance” (ICOMOS Australia, 2013 , p. 1). In terms of conservation principles, the Burra Charter has stressed the importance of public participation in Article 12, namely “conservation, interpretation and management of a place should provide for the participation of people for whom the place has significant associations and meanings, or who have social, spiritual or other cultural responsibilities for the place” (ICOMOS Australia, 2013 , p. 5). In the conservation processes and practice, the cultural heritage value has been fully considered in ICOMOS New Zealand Charter. The cultural heritage value means “possessing esthetic, archeological, architectural, commemorative, functional, historical, landscape, monumental, scientific, social, spiritual, symbolic, technological, traditional, or other tangible or intangible values, associated with human activity” (ICOMOS New Zealand, 2010 , p. 9). The conservation plans and projects about different aspects of cultural heritage value are intertwined with public participation, involving “interested parties and connected people” (ICOMOS New Zealand, 2010 , p. 5). The ICCROM report means that particularly “artistic, historic, and typological value” could be taken into account as the outstanding universal value of cultural heritage (Jokilehto and Cameron, 2008 , p. 11). The ICOMOS report notes that cultural heritage should also include properties “with great potential for esthetic, educational and scientific value” (Jokilehto and Cameron, 2008 , p. 11). The social value of cultural heritage is shaped by the combined efforts of people and non-human factors, such as technology, through the use of social media platforms (Bonacchi et al. 2023 ).

Among the various aspects of cultural heritage values, authenticity is of great importance in the process of conservation. According to the Operational Guidelines for the Implementation of the World Heritage Convention, to be of outstanding universal value, a cultural property must meet the requirement of authenticity in “design, materials, workman ship and setting” (Jokilehto and Cameron, 2008 , p. 43). The Nara document provides a full discussion of the concept of authenticity and has a profound impact on modern conservation history and conservation practices (Stovel, 2008 ). The research on the comparative analysis of China and Scotland shows a more comprehensive understanding of the relationship between authenticity and heritage conservation (Gao and Jones, 2021 ). Besides emphasizing material authenticity, people’s experience of authenticity is also necessary for heritage conservation and heritage management. Another essential element for identifying the significance of cultural heritage is the requirement of integrity. Integrity is defined as “a measure of the wholeness and intactness of the natural and/or cultural heritage and its attributes”, including “the social-functional integrity”, “the historical-structural integrity”, and “the visual/esthetic integrity” (Jokilehto and Cameron, 2008 , p. 44). Both authenticity and integrity form the pivot of cultural heritage values and provide guidance for public participation in cultural heritage conservation.

Adopted on 25 June 1998, at the meeting of the United Nations Economic Commission for Europe (UNECE) held in the Danish city of Aarhus, the Aarhus Convention has come into effect on 30 October 2001. As a legally binding global instrument on environmental democracy, the Aarhus Convention gives the public more rights, including the ability to seek justice, access information, and participate in environmental decision-making (UNECE, 2023 ). Kumpu ( 2022 ) argues that public participation underscores the involvement of “citizens, customers, employees, and stakeholders in the activities of governments, businesses, scientific and arts institutions, and organizations of various kinds” (p. 306) in the process of policy-making. Pierroux et al. ( 2020 ) note that “this movement promoting public participation and engagement is built around the concept of deliberative democracy” (p. 51) which is “based on the equality of interlocutors and the reciprocity of their exchanges as well as a greater transparency” (p. 56).

With an eye toward communication-centered research, Norton ( 2017 ) has theorized a structuration model for environmental public participation, highlighting in particular issues of agency, “which involves ontological security and ontological competence, social systems, and various elements within duality of structure” (p. 146). Walker ( 2007 ) highlights participatory communication as a crucial strategy for public participation and stresses Collaborative Learning (CL) as an important approach in participatory communication. He uses the case of the 2006 Region 10 EPA Tribal Leaders Summit to illustrate the worksheet technique in the CL community workshops. In addition, Martin ( 2007 ) holds that increasing public participation can enhance the democratic nature, legitimacy, and quality of environmental decisions and believes that the involvement of citizens in both “how decisions are made” and “what decisions are made” are “meaningful public participation” (p. 12). Thus, public participation is seen as an essential aspect of democratic governance in a collaborative way or in other words “deliberative democracy” (Nabatchi, 2010 ). Accordingly, the need for collaborative efforts should give special importance to “an integrated approach among civil society organizations (CSOs), news media, research institutions, and the public” (Ittefaq and Kamboh, 2023 , p. 49).

Research methods

This paper has adopted the research methods of online field observation and comparative case study. As for the online field observation, the two authors have visited and revisited the home pages of the Erie Canal in the US and the Rideau Canal in Canada, as well as the relevant websites in the forms of homepage introductions, online survey results, and official documents, etc., on and about the two said canals. In this way, we have satisfactorily collected our first-hand data. Regarding the comparative case study, Sturman ( 1997 ) defines a case study as “the exploration of an individual, group, or phenomenon” (p. 61). Similarly, but further, Hartley ( 2004 ) holds that case study has been recognized as more than merely a research method, but as a design in its own right. The case study allows researchers to explore complex issues and their underlying mechanisms by focusing on the unique characteristics and context of the studied case. Yin ( 2014 ) believes that case study research preserves “the holistic and meaningful characteristics of real-life events” while enabling an in-depth examination of novel or ambiguous phenomena. He argues that case studies are particularly useful for exploring “what works” in real-world settings and for generating new theoretical insights. Case studies are often examined using a qualitative approach, a quantitative approach, or a mixed methodology, relying upon the cases’ accessibility and the goals of the study. In this paper, a qualitative comparative case study has been conducted to compare and contrast the main features of the two canals by the four dimensions of subject, concept, content, and horizon of public participation.

Experience and implications in the conservation and management of canal cultural heritage in the US and Canada

As a combination of water bodies and the birth of the US, the Erie Canal has transformed from the management model of “government → community → aboriginals” to “community →aboriginals→ government”, which can be a classic example. As one of the World Heritage canals, the Rideau Canal has formulated a short-term, medium-term, and long-term action plan for the strategic objectives of public participation in heritage management plan, which has achieved remarkable results. By following the rules of authenticity and integrity to cultural heritage values, the remainder of the paper explores the fruitful experience and insightful implications of public participation in the cultural heritage conservation and management of the above two canals from the four dimensions of subject, concept, content, and horizon. In the process of comparative case analysis, public participation contributes to unfolding these cultural spaces and their values and revealing their influence on conservation.

The subject

The public participants of the Erie Canalway National Heritage Corridor (ECNHC) in the US are mainly composed of corridor residents, local communities, regional representatives, political leaders, private or non-profit heritage resource managers, as well as tourists, volunteers, non-governmental organizations, non-profit enterprises, and civil society organizations related to the Erie Canal. Under the ECNHC Act, published in December 2000, the Erie Canalway National Heritage Corridor Committee (ECNHCC) was established. The committee consists of 27 members, 19 of whom are local people from within the scope of the ECNHC. While receiving consultations from the National Park Service (NPS), the committee is responsible for coordinating partnerships between relevant federal and state government agencies, municipalities, university research centers, nonprofit organizations, and citizens, and actively organizing their joint participation in the conservation and management of the ECNHC Act (Goodstadt et al. 2020 ). According to the above Act, the groups and persons of the public participants should have relevant knowledge and experience in tourism, economic and community development, regional planning, historical conservation, cultural or natural resource management, conservation, entertainment, education, or museum services. Participant diversity embodies “the multivocality of the stakeholders involved in the heritage management process in an effective way” (Pastor and Colomer, 2024 , p. 226).

At the same time, the New York State Historic Preservation Plan stipulates that the ECNHC project should be open to the public from planning to implementation and evaluation. In determining the direction and scope of the corridor project, discussion and review of the plan, and the implementation and completion of management planning, there has been public participation throughout the entire process. According to statistics, the number of public participants in the ECNHC project has been increasing. Since 2000, institutions have participated in the project as partners, from fewer than 50 people at the beginning to >200 people in 2007, 400 in 2018, and 2901 formal partners as well as 5,102 informal partners in 2021. Individual public participation has increased from single digit starting in 2011 – 400 visits in 2018, and then increased to 21,803 in 2021 (National Parks Service, 2021 ). It can be seen that the scale of public participation in the ECNHC project has soared from 50 in 2000 to 21,803 in 2021, giving great impetus to the driving force of community cultural heritage conservation. On one hand, national and state governments have issued relevant bills and programs to legally ensure public participation in cultural heritage conservation. On the other hand, the project is open and transparent in planning, implementation, evaluation, and other relevant links, and public participation occurs throughout the process, as an essential component of the mechanism.

Likewise, the public participants in the conservation and management of the Rideau Canal in Canada are composed of individuals, experts, scholars, social organizations, non-governmental organizations, and non-profit enterprises. Parks Canada Agency is responsible for the mutual liaison and normal operation of its members. The Agency builds the natural, cultural, shipping, and community resources related to the Rideau Canal into an interdependent, coexisting, and symbiotic mechanism. In order to ensure the orderly, normal, and efficient operation of the cooperation among the members, a review team for the cultural heritage of the Rideau Canal was established in 1995. According to the operation rules and management plans for the conservation and inheritance of canal heritage, the opinions of relevant people have been extensively considered, and eight implementation rules have been formulated. Among the eight rules, the following ones concern public participation:

(4) An advisory committee should be formed immediately for each canal. It should report to the superintendent and advise on subjects of mutual concern. (5) Membership should be drawn from business and community leaders, and the group should be convened a minimum of four times a year. (6) It is suggested that the committees should be voluntary and be provided with administrative support. (7) The terms of reference for committees, their membership, tenure, and size should be developed in consultation with interest groups on each canal. (8) The advisory committee should monitor the implementation of the corridors of change report. (Keenan et al. 1995 )

It can be seen that, as the competent department of the Rideau Canal, Parks Canada Agency creatively coordinates all forces, actively solicits opinions from grassroots people and tourists, and regularly updates the activities related to cultural heritage. At the same time, the original residents and stakeholders around the Rideau Canal have signed agreements with the government, so that they can actively participate in various volunteer activities involving the public. In short, the public participants of the US and Canada are much the same, mainly composed of residents of the Heritage Corridor, non-governmental organizations, non-profit enterprises, private forces, tourists, and individual volunteers. However, the former emphasizes the role of grassroots partners, while the latter relies on the phased goals of the Heritage Corridor program. Participatory processes are considered “a democratic tool in the field of cultural heritage” (Pastor and Colomer, 2024 , p. 226), where democratizing participation creates spaces for negotiation and interaction among stakeholders. The participating subjects of the US and Canada reflect that democracy, especially deliberative democracy is placed in a very important position in the process of public participation. Deliberative democracy strives to empower citizens in the decision process of public participation and redirect decision-making processes toward core ethical and social principles (Bohman and Rehg, 1997 ). One of the key elements of deliberative democracy stipulates that the participants should represent all sectors of the community (Dryzek, 2000 ). The diversity of public participants and their actual decision rights in the process of legislation, regulation, and report drafting demonstrate apparent and typical deliberative democracy in the public participation of the Erie Canal and the Rideau Canal.

The concept

As the National Historic Preservation Act of 1966 explained: “The preservation of our irreplaceable heritage is in the public interest so that its vital legacy of cultural, educational, esthetic, inspirational, economic, and energy benefits will be maintained and enriched for future generations of Americans” (Bsarnum et al. 2021 ). Based on this concept, the ECNHC Committee reiterated that heritage conservation is both a movement and a land use law. It maximizes the interests of the masses and their communities when it inspires the masses to find a relationship with historical sites, natural resources, or cultural traditions. This is the best embodiment of the trend that public participation is “changing from obligation standard to right standard, and citizens in the modern society bear not only the duty to participate in the management of state and social affairs but also the due right” (Cheng, 2017 ) as pointed out in the above theoretical framework.

Therefore, the formulation of the New York State Historic Preservation Plan (2021–2026) focuses on the importance of public participation, based on extensive surveys and interviews. Given the partnership and the education and publicity of the public, the plan has introduced clear goals and measures, which to a large extent guarantee the public’s right to know, participate in the government, and supervise the conservation and management of the cultural heritage. In short, to reflect the rooted opinions of the community group, academic institutions, non-profit enterprises, or local government agencies, the management of the ECNHC project adheres to the consistent and clear concept to ensure that the public has the opportunity to understand the project, actively participate in related heritage conservation work, and creatively shape the spiritual world of the present and future of New Yorkers, and even of Americans.

Similarly, as the national wealth and living cultural heritage of Canada, the Rideau Canal is not only a waterway but also a part of the identity construction of Canadians in coastal communities. To this end, the Parks Canada Agency and its liaison members, such as the Friends of the Rideau organization hope to work together “to enhance and conserve the irreplaceable charm of the Rideau Corridor and to increase public awareness and enjoyment of the Rideau Corridor and to develop strong public support for the long term well-being of the Rideau Corridor” (Thomson, 2009 ). To implement the above concepts, the Agency has been developing the Rideau Canal National Historic Site of Canada Management Plan since 1990 and re-evaluating and updating it every 6 years. According to the existing plan, there are the following four concepts related to public participation:

(1) Canadians, residents, and visitors cherish the Rideau Canal as a symbol of Canada’s identity and take pride in their contribution to preserving this national treasure for future generations. (3) Residents of the Canal corridor value and protect the unique cultural and natural heritage character and scenic beauty of the Canal corridor through the cooperative efforts of stakeholder groups, government agencies, public and private sector partnerships, municipal land use policies, and private stewardship. (4) The Canal’s tradition as a fully functional navigable historic waterway is maintained. (7) The values of the Rideau Waterway, Canadian Heritage River, are widely understood and protected through public and private stewardship. (8) The staff of the Rideau Canal are proud of their stewardship role and, through their actions, display leadership in resource conservation, sustainable use, and heritage presentation. (Chief Executive Officer of Parks Canada, 2005 )

Thus, it can be seen that there is a consensus among Canadians on their concept, which states that by passing on the cultural heritage to future generations, they can receive education, appreciate, and identify with the splendid culture of their own country, and the cultural heritage can be more effectively valued and protected. Public participation becomes not only an asset that needs to be protected and valued but also an effective means of promoting and enhancing social-cultural identity and cohesion (Parks Canada Agency, 2016 ). Just as Martin ( 2007 ) remarks, meaningful public participation requires (1) access to information, education, and technical assistance; (2) possessing civic legitimacy so that public concerns can be given authentic consideration; and (3) having the real potential to affect the decision-making process because “who decides usually determines what is decided” (p. 172). In short, both the US and Canada believe that extensive public participation is the driving force for the successful conservation and management of cultural heritage in their concepts. However, the former pays more attention to the role of heritage conservation in shaping the identity of Americans, while the latter places more emphasis on the inheritance and educational function of heritage.

The content

With regards to content, first of all, there are two relevant articles in the ECNHC Act on the US side:

(1) The information on the scale, construction blueprint, management plan, and other information of this corridor (see Fig. 1 ) is subordinate to the NPS, but remains open and transparent and subject to public supervision at all times; (2) In the process of formulating its management plan, conservation plan, and evaluation report, the committee must extensively solicit public opinions through the form of hearings and interviews. (Goodstadt et al. 2020 )

Then, among the six objectives of the ECNHC Preservation and Management Plan, there are also two relevant aspects of content: (4) The Corridor’s current and future generations of residents and visitors will value and support the preservation of its heritage; (6) The Corridor will be a “must do” travel experience for regional, national, and international visitors (Goodstadt et al. 2020 ). Finally, among the eight goals of the New York State Historic Preservation Plan (2021–2026), the relevant content includes: (1) Inclusion, Diversity, Equity, and Access; (7) Partnerships; (8) Public Outreach and Education (Bsarnum, 2021 ). The specific implementation measures include: (1) advisory groups; (2) public meetings; and (3) round-table meetings or academic seminars. As can be seen, there have been particular articles in the relevant Federal, state, and local laws, to conserve and manage the Erie Cultural Heritage Corridor well. Thus, the scope of conservation and management is clear and specific, and the legitimacy and authority of the laws ensure the expected implementation of what has been stipulated or planned.

The Erie Canalway National Heritage Corridor ( 2006 ).

Apart from the legal stipulations and strategic plans, there have been practical measures to promote the prosperity and development of the corridor community and cultural tourism. The Corridor Committee holds >400 cultural and tourism promotion activities every year, attracting >500,000 people to participate in various activities of the corridor heritage conservation. At least 40 venues have been set up in the corridor for residents and invited experts to display and share the special exhibits, programs, and stories related to the corridor’s cultural heritage. About 35,000 primary school students from 110 school districts have been sponsored to visit the corridor heritage sites to experience the beauty of the corridor and the cultural connotation of the heritage. At the same time, more than 400 people from Europe and the US have attended the World Canal Symposium held in Syracuse, New York, to discuss research projects and innovative arguments leading to the discovery and transformation of the canal in the world (Goodstadt et al. 2020 ). Public participation is explicitly stipulated in both federal laws and state government documents in the US, so whether it is a non-profit organization in a partnership, an academic group, or an individual, their respective responsibilities are very clear. As a result, they can achieve duty-bound and voluntary participation, fully reflecting the multiple attributes of obligations, rights, and responsibilities that public participation possesses.

Regarding content on the Canadian side, Canada’s Rideau Corridor (see Fig. 2 ) project was officially launched in 2006, aiming to develop, package, and market the cultural tourism experience along the Rideau Canal and its coastline from Ottawa to Kingston. The concept of the Heritage Corridor originated in the US by integrating special cultural resources into a linear landscape. It is an approach to regional heritage conservation, characterized by a clear economic center, thriving tourism, reuse of old buildings, and environmental improvement (Flink and Searns, 1993 ).

Canada’s Rideau corridor (Whytock, 2013 ).

Authenticity is an indispensable factor when it comes to the management and conservation of cultural heritage. In September 1994, an expert World Heritage meeting was held to discuss how the authenticity of heritage canals might be best measured. An annex to the technical analysis of authenticity in the meeting report was submitted to the World Heritage Committee (UNESCO, 1994 ). The goal of this Rideau Corridor project is to position Ottawa, Kingston, and the entire Rideau area as a cultural destination to promote authenticity in the region, offering art, heritage, cuisine, agricultural tourism, and natural history experiences. This corridor project aims to promote the development of a diversified market for the Rideau tourism industry in the short and long term, increasing visitors and incomes for corridor suppliers and local communities. In order to provide tourists with a tourism experience that embodies the unique elements of the region of the Rideau Canal Cultural Heritage Corridor, the Parks Canada Agency and relevant organizations, including public participation groups and personnel, brainstormed and finally identified and launched seven themes closely related to the corridor:

(1) Tell regional or national stories based on the Canal; (2) experience adventures related to home stay, fishing, camping, hunting, and adventure; (3) spend various festivals of towns and villages; (4) enjoy the music and art feasts of dozens of theaters, concert halls, and dance pools; (5) visit nearly 100 art galleries, studios, and exhibition halls with strong art color; (6) enjoy the natural scenery along the canal; (7) enjoy “peaceful” trips of 16 gardens, botanical gardens, and wetland parks. (Flink and Searns, 1993 )

From the above, it can be seen that the Rideau Cultural Heritage Corridor integrates the world’s top art and heritage experiences, focusing on exploring, integrating, and showcasing the marketable art, heritage, cuisine, agricultural tourism, and natural history of the Rideau Canal itself and its adjacent towns, villages, and nature. It also provides visitors with unique cultural tourism resources from the American continent. In summary, public participation runs throughout the entire process of drafting, modifying, implementing, and evaluating the management plan for the Heritage Corridor project between the US and Canada. Just as Cheng ( 2017 ) notes, in the present day, public participation has expanded from state affairs to social affairs, or from pure political participation to involvement in various public affairs. The above accounts of the Cultural Heritage Corridors of both the Erie Canal and Rideau Canal well match the development trajectory. However, the former tends to present a management trajectory that starts from top to bottom and then from bottom to top, while the latter is more expansive, diverse, and local.

The horizon

By horizon, we mean that public participation extends from real life to the virtual world in today’s digital information age, which makes public participation from “absence” to “presence” in an unprecedented free and equal communication public space via the Internet-connected social media (Cheng, 2017 ). Social media creates a new sphere of participants and provides a new platform for public participation (Papacharissi, 2010 ). For heritage research, the use of social media and big data helps digital heritage transform “from a more informational web to a more interactive and collaborative one” (Bonacchi, 2022 , p. 9). Cameron ( 2021 ) describes digital cultural heritage as “composed, conjoined and transformed by the co-evolving interrelatedness of a broad range of actors from people to technologies, algorithms, materials, infrastructures, energy systems, ideas and so forth” (p. 129). The process of creating digital cultural heritage involves more than just human effort; it is a collaborative endeavor that encompasses a variety of actors and elements. This perspective affects the way we understand and investigate the values that are inherent in this type of heritage.

In the case of the US, firstly, the Erie Canal National Heritage Corridor has a dedicated ARCBridge database, which provides services for the collection, analysis, and management of a large amount of information and materials in the management of natural and cultural heritage in the region, especially the access to video records of experts and scholars and other promotional activities as well as the retrieval of information from corridor committee partners. Secondly, the network homepage ( www.eriecanalway.org ) of the corridor project regularly updates the content, images, and interactive maps of heritage conservation and management. At the same time, the home page provides an average of tens of thousands of tourists and public volunteers with detailed corridor tour resources, in-depth explanations of the historical evolution of corridor heritage, corridor heritage conservation and inheritance of the rich and colorful aspects of pictures, game interactions, audio-visual materials, and other multi-modal display content. Finally, the Corridor project also uses popular new social media and we-media platforms such as Facebook, Twitter, and Instagram to maintain interaction and communication with various stakeholders, partners, corridor visitors, and individual public participation volunteers (Goodstadt et al. 2020 ).

With the assistance of the ever-updated technology, the management team of the Erie Canalway National Heritage Corridor Project can keep up with the times, fully utilizing databases, online homepages, and trendy social media to ensure smooth communication of information on corridor heritage conservation and management, and effective question-and-answer (Q&A) interaction between project management and corridor visitors. In fact, in addition to participating in activities such as on-site visits and research, attending meetings, and conducting academic exchanges, the corridor management team has also completed important tasks related to the drafting, modification, implementation, promotion, and evaluation of corridor heritage conservation and management plans through the operation of internet platforms with high efficiency. Therefore, the conservation and management of the Erie Canalway National Heritage Corridor has been becoming increasingly standardized, clear, and systematic, presenting a management model that transitions from government → community → aboriginals to community → aboriginals → government. Through the accumulation of practical experience, the management model of the Erie Canalway National Heritage Corridor illustrates the gradual transition from initial government leadership to the dominant roles of the residents’ committees along the canal, assisted by the government with various non-profit or extensive participation of civil organizations. Given public participation in the conservation and management of canal cultural heritage, the relevant departments of other countries have issued a series of canal management regulations and implementation measures, which to some extent reflect the importance of national competent departments to public participation. However, most of them are led by the government to promulgate various regulations and decrees, which usually make it difficult to fully implement cultural heritage conservation and management measures in the jurisdiction, due to the lack of extensive, voluntary, and systematic public participation. Therefore, the management model of the Erie Canal provides a timely and valuable practical reference.

In the case of Canada, the Parks Canada Agency ( 2022 ) released What We Heard—Management Plan Review, Public Consultation Report (hereinafter referred to as the Report), which divided the public participation in the management of the Rideau Cultural Heritage Corridor into two phases. The first phase is from 2016 to 2019, and the main forms of public participation include open days for cultural heritage conservation, and evaluation discussions held four times a year, cultural heritage conservation seminars attended by all stakeholders three times a year, and occasional consultation meetings with indigenous peoples to seek advice on improving the management plan of the Rideau Cultural Heritage Corridor. The second phase is from 2020 – 2021, during which the form of public participation mainly consisted of virtual meetings of stakeholders for public consultation, via email, social media, and other online platforms (Parks Canada Agency, 2022 ).

It can be seen that in the management of the Rideau Cultural Heritage Corridor, public participation has shifted from face-to-face contact and communication in real life to the trend of online virtual meetings and consultations, ensuring that more relevant individuals move from “absence” to “presence” and then to legal, orderly, civilized, and effective “participation” (Cheng, 2017 ). The following is a summary of public participation on the online platform for the conservation and management of the Rideau Cultural Heritage Corridor from January 2021–May 2021 (see Table 2 ):

From Table 2 , it can be seen that Parks Canada Agency attaches great importance to the long-term, stable, and efficient cooperation and participation of cooperating institutions, non-profit organizations, stakeholders, indigenous peoples, and the relevant public in the development and implementation of the Rideau Cultural Heritage Corridor Project. In just 3–4 months, over 9,145 relevant people participated in different forms of public activities through online platforms. Among them, 50% of the respondents live along the Rideau Canal, while 89.1% of the respondents are over 30 years old. Thus, it can be seen that only with broad and active public participation can the management plan and implementation goals of projects similar to the Rideau Cultural Heritage Corridor Project be implemented and become a reality. In short, both the US and Canada can fully utilize modern information technologies and social media, such as online homepages, databases, simulation seminars, Facebook, Twitter, and Instagram, to promote public participation efficiently.

Discussion and conclusion

In this study, through online field observations and comparative case studies, we have explored the experience and implications of public participation that can be learned from the Erie Canal in the US and the Rideau Canal in Canada from the four dimensions of subject, concept, content, and horizon. To this end, we raised two research questions. As the answer to the first question: What experience can be drawn from the Erie Canal in the US and the Rideau Canal in Canada in their respective conservation and management of canal cultural heritage? The relevant experience of the US and Canada can be summarized in four dimensions: first, from the subject dimension, the public participation subjects on both sides are similar, mainly composed of Heritage Corridor residents, non-governmental organizations, non-profit enterprises, civil forces, tourists, and individual volunteers. However, the former emphasizes the role of grassroots partners, while the latter relies more on the phased goals of the Heritage Corridor plan. Second, in terms of the concept dimension, both sides firmly believe that broad public participation is the driving force for the success of cultural heritage conservation and management. However, the former focuses more on the role of heritage conservation in shaping American identity, while the latter focuses more on the inheritance and educational functions of heritage. Third, in terms of the content dimension, public participation runs through the whole process of drafting, modification, implementation, and evaluation of the conservation and management plan in both the US and Canadian Heritage Corridor projects. However, the former presents a more top-down and then bottom-up management trajectory, while the latter is more expansive, diverse, and local. Finally, regarding the horizon dimension, both countries can fully utilize modern information technologies and social media, such as online homepages, databases, simulation seminars, Facebook, Twitter, and Instagram, to efficiently promote public participation.

As the answer to the second question: What implications do the above experience hold for the bottleneck issues in the conservation and management of the canal cultural heritage worldwide? The canals in this paper refer to those world heritage canals in developing countries such as Iran, China, and Mexico, as well as other canals mainly in less industrialized countries and regions. Since the experience has been drawn from four dimensions, the implications can be discussed accordingly about the bottleneck issues with canals worldwide. First, in the dimension of subject, most developing countries still tend to rely on the roles of governments at various levels, which have been generally top-down, one-way, and thus ineffective. With implications from both the US and Canada, on the one hand, the initial leadership role of the government proceeds to be shifted to community committees, and the composition of public participants aims to be diverse and inclusive, targeting not only residents along the canals but also visitors or even tourists from home and abroad. On the other hand, necessary national legal acts or local regulations are in place to make public participation both a duty and an obligation for the involved individuals and organizations in the conservation and management of canal cultural heritage.

Second, in the dimension of concept, cultural heritage conservation and management have constantly been updated, deepened, and refined. Therefore, the static management model led by the government has been becoming increasingly difficult to adapt to new and challenging needs. To face the challenge, both the US and Canada have successfully revitalized the role of public participation in close association with the shaping of national identity and the functioning of school education. In other words, both sides keep the concept of their respective Canal Cultural Heritage Corridors abreast with the developmental trajectories of the modern age by getting the relevant public participants organized, their positions recognized, and, most importantly, their critical voices heard and constructive suggestions taken.

Third, in the dimension of content, in most developing countries and regions, public participation is still at the initial stage; the educational content of public participation tends to be outdated, and the dissemination is often one-way with little or insufficient feedback. Although the US and Canada have adopted different approaches in this regard, one common feature here is that both sides have fully demonstrated the spirit of democratic participation and exemplary deliberation with major decisions made through dialog, exchange, and mutual learning throughout the whole process of drafting, modification, implementation, and evaluation of the conservation and management plans.

Finally, in the dimension of horizon, it is true that in the digitalized information age, the conservation and management of canals worldwide have witnessed various applications of Internet-connected media platforms, including social media or new media. Nevertheless, due to the differences in the construction of the overall management system for the conservation, inheritance, and utilization of the tangible and intangible cultural heritage of canals worldwide, access to modern information technologies for public participation is surprisingly insufficient. Moreover, issues with the above three dimensions of subject, concept, and content have resulted in further obstacles to popularize up-to-date information technologies. Fortunately, the experience of the US and Canada in their extensive utilization of online homepages, databases, simulation seminars, Facebook, Twitter, and Instagram for public participation can shed light on this regard.

The limitations of this study are twofold: first, this study has relied on only two cases, so the findings may not be representative enough. Second, the two authors both come from China. Although they have studied and lived in the US and Canada for some years, the two authors may have revealed some subjectivity in their analyses of and discussions about the primary data. For future research, more cases of both the world heritage canals and other categories of exemplary canals can be targeted, and more authors from the host countries of the selected canals can be invited for a more representative and triangulated study.

Data availability

Data sharing was not required to this research as no data were generated or analysed.

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Acknowledgements

This work was supported by National Social Science Fund Project “Research on the Path to Enhance the International Image of the Grand Canal of China from the Perspective of Cultural Game” under Grant No. 18BGJ086; and Postgraduate Research & Practice Innovation Program of Jiangsu Province “A Study on the Path of Constructing China’s Image in the Discourse of International Chinese Friends from the Perspective of Discourse Analysis” under Grant No. KYCX23_3486.

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Gu, Z., Tian, D. Public participation in the conservation and management of canal cultural heritage worldwide: a case study of the Rideau Canal and Erie Canal. Humanit Soc Sci Commun 11 , 1005 (2024). https://doi.org/10.1057/s41599-024-03516-1

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Translating theory into practice: A flexible decision-making tool to support the design and implementation of climate-smart agriculture projects

• Walsh, Conor
• Klauser, Dominik
• de Pinto, Alessandro
• Haggar, Jeremy
• Abdur, Rouf
• Hopkins, Richard J.
• Zamil, Farhad

Climate-smart agriculture (CSA) is a conceptual framework for responding climate-related risk in agriculture across the three pillars of Mitigation, Resilience, and Production. Existing tools have been developed which seek to operationalise the CSA concept to evaluate and benchmark progress; each of which have their own relative strengths and weaknesses. The translation of this concept into actionable projects/portfolios hence requires the careful evaluation of potential trade-offs and synergies between these three pillars. The hereby presented decision-making tool aims to offer a basis for a structured evaluation of such trade-offs and synergies. It does so by assessing five different outcome pathways on how they contribute to a project's performance across the three pillars of CSA. We aspire that the use of this tool will allow for more deliberate design and implementation of projects in agricultural development, increasing the resilience and productivity of farming systems whilst ensuring the sustainable use of the environmental resource-based agriculture depends on. This tool was applied in a workshop setting to evaluate the relative strengths and weaknesses of two distinct projects; demonstrating the utility in visualising the same performance in different ways. Of particular importance was ability to demonstrate how focusing on productivity and adaptation may trade-off mitigation activities. The results of the case study application demonstrated the challenge in meeting all the CSA requirements; particularly where the main objective of a project is to enhance and increase productivity. This reinforces how supporting all three pillars is challenging for a single project and therefore CSA is arguably more achievable when viewed in terms of a portfolio of activities which can collectively compensate for the limitations of a single project.

• Climate smart agriculture;
• Trade-offs;

• Open access
• Published: 29 July 2024

From pre-test and post-test probabilities to medical decision making

• Michelle Pistner Nixon 1 ,
• Farhani Momotaz 1 ,
• Claire Smith 2 ,
• Jeffrey S. Smith 3 , 4 , 5 ,
• Mark Sendak 6 ,
• Christopher Polage 7 &
• Justin D. Silverman 1 , 8 , 9  

BMC Medical Informatics and Decision Making volume  24 , Article number:  210 ( 2024 ) Cite this article

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A central goal of modern evidence-based medicine is the development of simple and easy to use tools that help clinicians integrate quantitative information into medical decision-making. The Bayesian Pre-test/Post-test Probability (BPP) framework is arguably the most well known of such tools and provides a formal approach to quantify diagnostic uncertainty given the result of a medical test or the presence of a clinical sign. Yet, clinical decision-making goes beyond quantifying diagnostic uncertainty and requires that that uncertainty be balanced against the various costs and benefits associated with each possible decision. Despite increasing attention in recent years, simple and flexible approaches to quantitative clinical decision-making have remained elusive.

We extend the BPP framework using concepts of Bayesian Decision Theory. By integrating cost, we can expand the BPP framework to allow for clinical decision-making.

We develop a simple quantitative framework for binary clinical decisions (e.g., action/inaction, treat/no-treat, test/no-test). Let p be the pre-test or post-test probability that a patient has disease. We show that \(r^{*}=(1-p)/p\) represents a critical value called a decision boundary. In terms of the relative cost of under- to over-acting, \(r^{*}\) represents the critical value at which action and inaction are equally optimal. We demonstrate how this decision boundary can be used at the bedside through case studies and as a research tool through a reanalysis of a recent study which found widespread misestimation of pre-test and post-test probabilities among clinicians.

Conclusions

Our approach is so simple that it should be thought of as a core, yet previously overlooked, part of the BPP framework. Unlike prior approaches to quantitative clinical decision-making, our approach requires little more than a hand-held calculator, is applicable in almost any setting where the BPP framework can be used, and excels in situations where the costs and benefits associated with a particular decision are patient-specific and difficult to quantify.

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Introduction

The Bayesian Pre-test/Post-test Probability (BPP) framework provides a quantitative framework for expressing diagnostic uncertainty and updating that uncertainty given clinical signs or test results. The BPP framework is used as a tool at the bedside, in the classroom, and as part of medical research [ 1 ]. Yet the BPP framework is only one part of what could be a much larger toolkit that clinicians, educators, and researchers could employ.

Though often discussed in the context of clinical decision-making [ 2 , 3 ], the BPP framework is insufficient for it: while pre- and post-test probabilities represent beliefs in the disease state of a patient, clinical decision-making requires that diagnostic uncertainty be balanced against various cost and benefit factors. For example, a decision to treat must consider not only the probability that a patient has the disease in question but also the safety and efficacy of the proposed treatment. Yet these costs and benefits are often difficult to quantify, e.g., consider quantifying the psycho-social costs of a prophylactic bilateral mastectomy in a BRCA1 carrier. In short, the BPP framework can be used for quantifying diagnostic uncertainty, but it is not a tool for clinical decision-making; the latter requires that diagnostic uncertainty be balanced with patient-specific, difficult-to-quantify cost and benefit factors.

Despite the challenges, there is a rich history of methods that have been developed for quantitative clinical decision-making. Yet most of these methods have either required complex computational models that cannot be easily performed at the bedside [ 4 , 5 , 6 ] or are specialized to a particular decision task (such as aspirin treatment for pre-eclampsia prevention [ 7 ]). As forewarned by Albert [ 8 ], these limitations can hinder adoption as the time and effort required to implement these support tools can outweigh their clinical benefit. However, the key exception is the almost 50-year-old work by Pauker and Kassirer [ 9 ] which provides a flexible, general-purpose approach to action/inaction (e.g., treat/no-treat or test/no-test) decisions that is simple enough to be applied at the bedside or discussed easily in a classroom. The Pauker and Kassirer (PK) framework combines diagnostic uncertainty with quantified costs and benefits to determine a treatment threshold based on probability: a decision boundary between action and inaction stated in terms of diagnostic uncertainty. Despite the maturity of that work, it has not seen widespread adoption beyond certain educational settings (e.g., Newman and Kohn [ 10 ], Chapter 2). We argue that the major limitation of the PK framework, which has limited its adoption, is its requirement that all costs and benefits be pre-specified and explicitly quantified. In fact, this limitation, namely combining hard-to-quantify costs on separate scales, had been noted in the literature shortly after the introduction of the PK framework [ 8 ].

Contributions

The purpose of this article is to review the PK framework and to propose a simple reformulation that addresses its major limitation. In brief, the PK framework requires that all costs and benefits be specified a priori. With these specified costs, a decision boundary \(p^{*}\) can be calculated which represents the probability of disease at which action and inaction are equally optimal. A clinician-calculated probability p can then be compared to \(p^{*}\) to determine whether action or inaction are warranted. Here, we show that the decision boundary \(p^{*}\) can be reformulated in such a way that it can be calculated without requiring pre-specification of all costs and benefits. We call this the Simplified PK (SPK) framework and present more details in The SPK framework  section. In the  Applications  section, we discuss the SPK framework in clinical and educational contexts through a series of hypothetical case studies. In addition, we illustrate its use as a research tool through a reanalysis of a study which found widespread overestimation of disease probabilities among clinicians in the section titled Reevaluating the source of inflated probability estimates among clinicians [ 11 ]. For reference, we provide a complete list of abbreviations and notation used throughout the manuscript in Table 1 .

While the SPK framework is not the first tool to use concepts from Bayesian decision theory, it provides a simple extension of the existing BPP framework which has clearly found a home in modern medicine (see Fig.  1 ). In contrast to the PK framework, the SPK framework requires no additional user input and returns a single decision boundary which can be used in clinical decision-making. As the SPK framework is so simple, it could be viewed as a previously unrecognized feature of the BPP framework.

Summary of the Bayesian Pre-test/Post-test (BPP) and Simplified Pauker-Kassirer (SPK) framework. Odds can be calculated from probabilities and vice-versa. In the BPP framework, post-test odds are calculated by multiplying the pre-test odds by the likelihood ratio of a test or sign. The SPK framework centers on the decision boundary \(r^{*}\) which can be calculated as the inverse of either pre-test or post-test odds (leading to a pre-test or post-test version of the boundary). \(r^{*}\) is the critical value at which the cost of under-treating ( \(c_{\text {under-acting}}\) ) is equal to the cost of over-treating ( \(c_{\text {over-acting}}\) ). This value can be compared to the ratio of the cost of under-acting (the additional cost of inaction when action is warranted) versus the cost of over-acting (the additional cost of action when no action is warranted) to make treatment decisions

Background information

Probabilities and odds.

We use p to denote the probability that a patient is in an actionable state . The precise definition of actionable state will depend on the clinical decision under question. For example, when deciding whether or not to treat with an antibiotic, p could represent the probability that a patient has an infection treatable with the antibiotic. At times, it will be more natural to state our results in terms of odds rather than probabilities. Probabilities ( p ) can be calculated from odds ( o ) and vice versa using the following two relationships:

Review of the BPP framework

Bayesian statistics provides a quantitative tool for updating prior beliefs (quantified as probabilities or odds) based on observed data. Compared to the full framework of Bayesian statistics, the BPP framework includes a critical simplification: the patient state is binary (e.g., disease or health as opposed to mild/moderate/severe disease). Under this simplification, Bayesian statistics reduces to the BPP framework.

Let \(o_{\text {pre}}\) (or \(o_{\text {post}}\) ) denote the odds of an actionable state before (or after) observing a particular diagnostic test or clinical sign. With this notation, the BPP framework can be written as

where \(\ell\) is the likelihood ratio of the test or sign (a quantity capturing the evidence provided by the observed data). In short, given a clinician-specified pre-test odds and given the likelihood ratio of a particular sign or test, the BPP framework computes an updated (post-test) odds. More discussion on the BPP framework in the context of medical decision-making can be found in Mark and Wong [ 12 ] or Armstrong and Metlay [ 13 ].

A note on notation: Much of what follows can be applied equally well to pre-test probabilities (or pre-test odds) as to post-test probabilities (or post-test odds). Therefore, we will often drop the subscript pre or post and simply write p or o .

BDT and the Pauker-Kassirer (PK) framework

Bayesian Decision Theory (BDT) extends Bayesian statistics and provides a principled approach to making decisions under uncertainty. Compared to Bayesian statistics, BDT requires an additional user input: a cost function which takes two inputs and outputs a number between negative and positive infinity. The two inputs are the patient state and a potential action. The numerical output represents the cost or loss incurred by a given action and state of patient combination. Costs are a general concept and may incorporate medical, monetary, psycho-social, or even opportunity costs that may result from a given action. Negative costs are often called benefits. Were the patient state known exactly, BDT would reduce to finding the action that minimizes cost. Uncertainty in the state of the patient complicates the problem. To address this, BDT defines an optimal action (the “Bayes action”) as the action that minimizes the expected cost : the cost weighted by the probability of disease or no disease.

Optimizing expected cost often involves advanced numerical techniques, as seen in many prior articles in medicine [ 4 , 5 , 6 ]. We follow Pauker and Kassirer [ 9 ] and take a simpler approach. Beyond the standard simplifying assumption of the BPP framework (that the patient state is binary), we also assume that the considered action is binary (e.g., test/no test or treat/no treat). This implies that there are four combinations of action and patient state, each with an associated cost: accurate action ( \(c_{\text {accurate action}}\) , e.g., treating with disease), accurate inaction ( \(c_{\text {accurate inaction}}\) , e.g., not treating with no disease), inaccurate action ( \(c_{\text {inaccurate action}}\) , e.g., treating with no disease), and inaccurate inaction ( \(c_{\text {inaccurate inaction}}\) , e.g., not treating with disease). Using shorthand, we denote these as \(c_{aa}\) , \(c_{ai}\) , \(c_{ia}\) , and \(c_{ii}\) , respectively. Letting that p denote the probability of an actionable state (e.g., disease), the expected cost of action (or inaction) decisions is then given by:

The Bayes action is action or inaction depending on whether \(\text {Expected Cost(action)}\) or \(\text {Expected Cost(inaction)}\) is less.

Given the four cost values \(\{c_{\text {aa}}, c_{\text {ia}}, c_{\text {ai}}, c_{\text {ii}}\}\) , Pauker and Kassirer [ 9 ] suggest calculating the threshold probability \(p^*\) needed to warrant action. That is, \(p^{*}\) is the specific probability at which \(\text {Expected Cost(action)}\) and \(\text {Expected Cost(inaction)}\) are equal. A physician calculated probability p (e.g., calculated using the BPP framework) can be compared to \(p^{*}\) to determine if action or inaction is optimal. They showed that this threshold was equal to:

The term \(c_{\text {under-action}}\) represents difference in costs between inaccurate and accurate action when a patient is in a state that warrants action. Similarly, the term \(c_{\text {over-action}}\) represents the difference in costs between inaccurate and accurate action when the patient is in an state that warrants no action. In essence, these two terms represents the additional cost of choosing the wrong action over the correct. We refer to these two terms as the cost of under-action and over-action, respectively.

Overall, what we call the PK framework consists of first quantifying the four cost values, calculating the ratio of the costs of under- to over-action and then comparing the resulting action threshold \(p^*\) against a physician-calculated (or specified) probability of an actionable state p .

The SPK framework

The major limitation of the PK framework is the need to pre-specify the four cost values in order to calculate the decision boundary \(p^*\) . Especially when the costs or benefits of a potential action are patient-specific or even qualitative, it can be impossible to use the PK framework. Yet, we can mitigate this limitation of the PK framework by framing the same decision boundary in terms of a critical value for the ratio \(r=c_{\text {under-action}}/c_{\text {over-action}}\) rather than a critical value for the probability p :

Equation ( 3 ) (SPK Framework) represents the same decision boundary as Eq. ( 2 ) (PK Framework) but is presented differently (see Supplementary Section 1, Additional file 1 for derivation). Yet, we expect Eq. ( 3 ) will be substantially easier to use than Eq. ( 2 ). Consider that Eq. ( 2 ) requires that all four costs values be specified in order to calculate \(p^{*}\) . In contrast, Eq. ( 3 ) requires only that a probability p or odds o be specified. Given the ubiquity of the BPP framework, we expect the latter will be substantially easier than the former: any clinician already using the BPP framework can essentially calculate \(r^{*}\) for free (without further input).

There are two main ways to use Eq. ( 3 ) depending on whether or not the four cost values \(\{c_{aa}, c_{ia}, c_{ai}, c_{ii}\}\) can be quantified. If those cost values cannot be specified, e.g., if the costs are fundamentally qualitative and patient-specific, then Eq. ( 3 ) can be used as a qualitative tool to help incorporate diagnostic uncertainty into the decision-making process. As an example, consider a patient with a \(20\%\) probability of being in an actionable state. This implies a decision boundary \(r^{*}=4\) . In words, regardless of the particular action in question, the cost of under-treating must be at least 4 times higher than the cost of over-treating in order to warrant action in this patient . Even if the actual cost of under- and over-treating cannot be calculated, we expect this result may help frame the decision and catalyze discussions about costs and benefits. When costs can be quantified, clinicians can calculate r and compare it to \(r^{*}\) to determine whether action or inaction is warranted. In Supplementary Section 1 (Additional file 1 ), we discuss how to compare r and \(r^{*}\) in more detail.

Applications

We illustrate the SPK framework through a hypothetical case study of asymptomatic bacteriuria and a reanalysis of a recent study which found widespread misestimation of pre- and post-test probabilities by clinicians [ 11 ]. In Supplementary Section 2 (Additional file 1 ), we provide an additional case study designed to illustrate how subjective and objective cost factors can be combined within the SPK framework. All three of these applications are designed to highlight the use of the SPK framework in situations where the PK framework cannot be applied: where it is difficult to specify the four cost values a priori.

Case study: antibiotics for asymptomatic bacteriuria

An otherwise healthy, non-pregnant, pre-menopausal 40-year-old woman presents to the emergency department complaining of chest pain. As a part of a standard work-up, a urinalysis is performed. The urine culture results indicate the presence of Escherichia coli in excess of 100,000 CFUs/mL, resulting in a diagnosis of asymptomatic gram negative bacteriuria. The patient has no recent history of Urinary Tract Infections (UTIs) nor any other presenting symptoms consistent with UTI. Based on this presentation, prior work suggests that this patient has an approximately 6% probability of progressing from asymptomatic bacteriuria to symptomatic bacteriuria [ 14 , 15 ]. Let this probability denote a post-test probability, where the state in question is whether the patient’s pathology will progress to symptomatic bacteriuria. We must decide whether to treat this patient with antibiotics at this time or wait and reevaluate if symptoms present.

Regardless of whether this 6% represents a pre-test or post-test probability, it is enough to calculate the decision boundary: \(r^{*}=\frac{1-0.06}{0.06}=16\) . In words: Given our diagnostic uncertainty, the cost of under-treating must be at least 16 times greater than the cost of over-treating to warrant treatment .

In this situation, we expect that many clinicians will find it difficult to apply the PK framework directly: it is difficult to quantify the cost of under- and over-treating as there are many considerations including morbidity, monetary, and public-health (e.g., antibiotic resistance) costs. Even if all these costs could be specified exactly, combining them into an overall cost of over- and under-treating is not straightforward. Despite these challenges, we show that the decision boundary, particularly its translation into words, provides insights for contextualizing the decision in terms of diagnostic uncertainty. As a starting point, we suggest considering each type of cost individually (e.g., monetary, morbidity, and public health), from most to least important. If these costs agree on which decision is optimal, the choice of treatment decision is obvious. If they do not agree, we suggest careful consideration of which costs are most important and how strongly each cost supports its preferred decision.

In this case, we consider morbidity, public health, and monetary costs in that order. Either individually, or in concert with the patient, we would consider the following question: “Is the morbidity associated with under-treating at least 16 times greater than that of over-treating?” In our reading of the literature [ 16 , 17 ], we expect that the morbidity associated with under-treating is likely higher than the morbidity associated with over-treating, yet we expect it is not 16 times greater especially when the low probability of progression to pyelonephritis and the probability of adverse reactions to antibiotics are considered. Therefore, considering morbidity alone we consider that no-treatment is warranted at this time. Additionally, after asking analogous questions about the monetary and public health costs, we believe the costs are higher in the case of over-treating. In sum, our suggestion would be to not treat this patient at this time but to pursue watchful waiting. This conclusion is supported by current treatment recommendations for asymptomatic bacteriuria in healthy non-pregnant persons [ 18 ].

Reevaluating the source of inflated probability estimates among clinicians

In a study of 553 medical practitioners presented with four different clinical scenarios, Morgan et al. [ 11 ] found widespread over-estimation of both pre-test and post-test probabilities compared to objective probability estimates. The results of this study are significant and led to a conversation about potential biases affecting the observed inflation (for example, see Chaitoff [ 19 ]; Patel and Goodman [ 20 ]). Current hypotheses include various factors that confound physicians’ perceptions and interpretations of medical tests [ 11 , 21 ]. For example, Kellner [ 21 ] suggests this over-estimation comes from less-experienced physicians included in the study cohort. While we do not doubt that such factors are at play, we hypothesize that the bluntness of the survey instrument used to elicit physician probability estimates is another source of potential error in the survey estimates. What if the physicians surveyed included consideration of various cost factors in their reported probabilities: e.g., a physician asked to quantify the probability of disease might modify their probability estimates based the risk of missing a diagnosis. Assuming that the cost of under-treatment is greater than the cost of over-treatment, we expect that such conflation would lead reported probability estimates to exceed objective probability estimates, exactly as reported in Morgan et al. [ 11 ].

The SPK framework can be used to gauge the plausibility of this hypothesis. Let us suppose that our hypothesis is true: the Morgan et al. [ 11 ] survey elicited a physician’s probability to act ( \(p_{\text {act}}\) ) rather than their estimation of the probability of disease ( \(p_{\text {disease}}\) ). Further, let us assume that clinicians’ perceptions about disease probabilities are accurate: physicians’ true estimates of \(p_{\text {disease}}\) are equal to their objective values. Let us assume that the probability that a physician will act is proportional to their perceptions about the expected cost of action. Using this later assumption, we can calculate the physicians’ perceptions about the relative cost of under- to over-treating (the implied cost-ratio ) as:

See Supplementary Section 3.1, Additional file 1 for derivation.

Below, we reanalyze the results of Morgan et al. [ 11 ] and calculate implied cost-ratios for three diseases studied in that work. We argue that the implied cost ratios are defensible given current evidence. In short, we provide a hypothesis for the inflated probability estimates observed in Morgan et al. [ 11 ] based only on a bluntness of the survey instrument and without requiring overt errors in clinical perception.

Re-analyzing Morgan et al.

We calculated implied cost ratios for three of the four clinical scenarios studied in Morgan et al. [ 11 ]: pneumonia, breast cancer, and coronary artery disease. We excluded the asymptomatic bacteriuria scenario from our reanalysis due to concerns about the accuracy of the survey data (see Supplementary Section 3.2, Additional file 1 for details). The resulting cost-ratios are 15.8 for the pneumonia scenario, 16.7 for the breast-cancer scenario, and 21.4 for the coronary artery disease scenario.

We argue that these implied cost ratios could represent realistic clinical attitudes towards risk. To justify our opinion, we provide an example clinical argument justifying the 16.7 breast-cancer cost-ratio in Supplementary Section 3.3, Additional file 1 . Moreover, we can compare to prior literature which studied physicians’ attitudes towards the risk of over- and under-treating patients with pneumonia [ 22 ]. Based on that prior literature, we estimate a pneumonia cost-ratio of 14.7 (see Supplementary Section 3.4, Additional file 1 ). We suggest that the correspondence between that result and the estimated results from Morgan et al. [ 11 ] is a strong argument that these implied cost ratios reflect potentially realistic clinician attitudes towards risk. Together, this suggests that the bluntness of the survey instrument could lead to the inflated probability estimates reported by Morgan et al. [ 11 ]. While testing this hypothesis in a clinical setting is outside the scope of this work, our results do suggest that future research should consider that physicians may conflate probabilities of disease with factors affecting decisions to act.

We introduced the Simplified PK (SPK) Framework as a flexible and easy-to-use tool for medical decision-making when there is uncertainty in the state of the patient. This SPK framework translates disease probabilities into quantitative statements about the ratio of benefits to costs. For a clinician already using the BPP framework, our approach is essentially free: simply invert an odds of disease.

The SPK framework does not replace more advanced decision support models such as Parmigiani [ 4 ], Kornak and Lu [ 5 ], or Skaltsa et al. [ 6 ]. Those methods address more complex decision tasks where either the patient state or the potential action is not binary. However, the SPK framework is meant to fill a need unmet by those tools: a flexible framework for quantitative decision-making that matches the simplicity and ease of use of the BPP framework. In this way, the SPK framework occupies the same niche as the PK framework [ 9 ], yet we believe the SPK framework is a more natural extension of the BPP framework as it does not require the relevant costs and benefits be specified a priori. More broadly, the SPK framework is complimentary to more complex decision theory models which are often specifically designed for more specialized tasks. We leave empirical evaluation of the relative strengths and weaknesses of these different decision support tools to future research.

Beyond clinical practice, we expect that the SPK Framework could be used in medical education. Much as the BPP framework provides a formal language for interpreting the value of a medical test, the SPK framework provides a formal language for medical decision-making. Educators can use this language to discuss the intricacies of medical decision-making and to explain their own decisions to students. Moreover, this framework will clarify the distinction between quantifying the state of a patient and quantifying costs associated with over- and under-treating.

Finally, we proposed a new interpretation of the results of Morgan et al. [ 11 ]. Beyond the factors already suggested, we propose that physicians may conflate the probability of disease with the costs of over- and under-treating which would appear as over-estimation of pre- and post-test probabilities. While a clinical trial is required to test this hypothesis, given the present evidence, we suggest that future studies looking to elicit clinician-estimated pre-test or post-test probabilities also survey attitudes towards costs and actions (see Heckerling et al. [ 22 ] and Baghdadi et al. [ 23 ] for practical examples). Notably, this recommendation has been made elsewhere albeit due to different concerns [ 20 ].

There are countless avenues for future study of the SPK framework; we highlight three. First, many papers support the BPP framework by providing quantitative estimates for likelihood ratios of different clinical signs and tests (e.g., Coburn et al. [ 24 ]). In fact, these papers can be useful in estimating decision boundary for the SPK framework. Future studies can similarly support both the PK and SPK framework by providing clear statements and quantification of cost-ratios. Beyond this, we note that more objective measures such as hazard ratios or odds ratios represent forms of cost-ratios that can be used in the SPK framework. Second, we have only demonstrated a very restricted set of tools for evaluating cost-ratios. A wide literature on eliciting decision makers preferences could be applied to quantify clinicians’ and patients’ attitudes towards costs [ 25 , 26 ]. Finally, we have not addressed potential conflicts between clinicians’ and patients’ attitudes towards cost though such conflicts exist. We imagine that future studies may find the SPK framework useful in mitigating these conflicts as it may catalyze discussions about costs.

Availability of data and materials

Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

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JDS and MPN were supported by NIH 1 R01GM 148972-01. The funding bodies played no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

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MPN, JDS, and FM conceptualized the SPK framework and its supporting mathematical details. JDS, CS, and JSS developed the arguments for bacteriuria and breast cancer case studies. MS and CP suggested the connection to Morgan et al. which was further developed by MPN and JDS. MPN and FM found and analyzed the necessary data to support the case studies and implemented any necessary software code. MPN and JDS prepared the original draft. All authors read and approved the final manuscript.

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Nixon, M.P., Momotaz, F., Smith, C. et al. From pre-test and post-test probabilities to medical decision making. BMC Med Inform Decis Mak 24 , 210 (2024). https://doi.org/10.1186/s12911-024-02610-3

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Understanding dual effects of social network services on digital well-being and sustainability: a case study of xiaohongshu (red).

1. Introduction

2. literature review, 2.1. sustainability and research related to social networking services, 2.1.1. sustainability and its dimensions, 2.1.2. research on the correlation between social networking services and sustainability, 2.2. social networking services, well-being, and resonance, 2.3. social networking services and alienation, 3. theoretical perspective, 3.1. rosa’s theory of resonance, 3.2. resonance theory and sustainability, 4. methodology, 4.1. virtual fieldwork, 4.2. data collection, 4.3. data analysis, 5. findings and discussion, 5.1. three types of resonance in red, 5.1.1. material resonance.

• Commodity consumption
• Experiential consumption

5.1.2. Spiritual Resonance

• Mental self-care
• Cultural communication
• Aestheticization of everyday life

5.1.3. Social Resonance

• Interest group
• Emotion community

5.2. Three Types of Alienation in RED

5.2.1. material alienation, 5.2.2. spiritual alienation, 5.2.3. social alienation, 6. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

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Wu, Q.; Gu, L.; Zhang, M.; Liu, H. Understanding Dual Effects of Social Network Services on Digital Well-Being and Sustainability: A Case Study of Xiaohongshu (RED). Sustainability 2024 , 16 , 6709. https://doi.org/10.3390/su16156709

Wu Q, Gu L, Zhang M, Liu H. Understanding Dual Effects of Social Network Services on Digital Well-Being and Sustainability: A Case Study of Xiaohongshu (RED). Sustainability . 2024; 16(15):6709. https://doi.org/10.3390/su16156709

Wu, Qingyue, Lei Gu, Mingxiao Zhang, and Huimei Liu. 2024. "Understanding Dual Effects of Social Network Services on Digital Well-Being and Sustainability: A Case Study of Xiaohongshu (RED)" Sustainability 16, no. 15: 6709. https://doi.org/10.3390/su16156709

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• Preprint egusphere-2024-2133

Assessing the adequacy of traditional hydrological models for climate change impact studies: A case for long-short-term memory (LSTM) neural networks

Abstract. Climate change impact studies are essential for understanding the effects on water resources under changing climate conditions. This paper assesses the effectiveness of Long Short-Term Memory (LSTM) neural networks versus traditional hydrological models for these studies. Traditional hydrological models, which rely on historical climate data and simplified process parameterization, are scrutinized for their capability to accurately predict future hydrological streamflow in scenarios of significant warming. In contrast, LSTM models, known for their ability to learn from extensive sequences of data and capture temporal dependencies, present a viable alternative. This study utilizes a domain of 148 catchments to compare four traditional hydrological models, each calibrated on individual catchments, against two LSTM models. The first LSTM model is trained regionally across the study domain of 148 catchments, while the second incorporates an additional 1,000 catchments at the continental scale, many of which are in climate zones indicative of the future climate within the study domain. The climate sensitivity of all six hydrological models is evaluated using four straightforward climate scenarios (+3 °C, +6 °C, -20 %, and +20 % mean annual precipitation), as well as using an ensemble of 22 CMIP6 GCMs under the SSP5-8.5 scenario. Results indicate that LSTM-based models exhibit a different climate sensitivity compared to traditional hydrological models. Furthermore, analyses of precipitation elasticity to streamflow and multiple streamflow simulations on analogue catchments suggest that the continental LSTM model is most suited for climate change impact studies, a conclusion that is also supported by theoretical arguments.

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https://doi.org/10.5194/egusphere-2024-2133-supplement

HYSETS - A 14425 watershed Hydrometeorological Sandbox over North America R. Arsenault, F. Brissette, J. L. Martel, M. Troin, G. Lévesque, J. Davidson-Chaput, M. Castañeda Gonzalez, A. Ameli, and A. Poulin https://doi.org/10.17605/OSF.IO/RPC3W

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LSTM climate change paper codes and data R. Arsenault, J.-L. Martel, and F. Brissette https://osf.io/5yw4u/

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Jean-Luc Martel

François brissette, richard arsenault, richard turcotte, mariana castañeda-gonzalez, william armstrong, edouard mailhot, jasmine pelletier-dumont, gabriel rondeau-genesse, louis-philippe caron.

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