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• Vol 8, No 13 (July 14, 2020) /

A bibliometric analysis using VOSviewer of publications on COVID-19

Yuetian Yu 1# , Yujie Li 1# , Zhongheng Zhang 2 , Zhichun Gu 3 , Han Zhong 3 , Qiongfang Zha 4 , Luyu Yang 5 , Cheng Zhu 6 , Erzhen Chen 6

1 Department of Critical Care Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University , Shanghai , China ; 2 Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine , Hangzhou , China ; 3 Department of Pharmacy, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University , Shanghai , China ; 4 Department of Respiratory and Critical Care Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University , Shanghai , China ; 5 Department of Intensive Care Unit, Wuhan Third Hospital, Wuhan University , Wuhan , China ; 6 Department of Emergency Medicine, Rui Jin Hospital, School of Medicine, Shanghai Jiao Tong University , Shanghai , China

Contributions: (I) Conception and design: Y Yu, L Yang, C Zhu; (II) Administrative support: Q Zha, Y Li; (III) Provision of study materials or patients: Y Yu, L Yang; (IV) Collection and assembly of data: All authors; (V) Data analysis and interpretation: Y Yu, C Zhu, H Zhong, Z Gu; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

# These authors contributed equally to this work.

Background: As a global pandemic, COVID-19 has aroused great concern in the last few months and a growing number of related researches have been published. Therefore, a bibliometric analysis of these publications may provide a direction of hot topics and future research trends.

Methods: The global literatures about COVID-19 published between 2019 and 2020 were scanned in the Web of Science collection database. “COVID-19” “Novel Coronavirus” “2019-nCoV” and “SARS-CoV-2” were used as the keywords to reach the relevant publications. VOSviewer was applied to perform the bibliometric analysis of these articles.

Results: Totally 3,626 publications on the topic of COVID-19 were identified and “COVID-19” with a total link strength of 2,649 appeared as the most frequent keyword, which had a strong link to “pneumonia” and “epidemiology”. The mean citation count of the top 100 most cited articles was 96 (range, 26–883). Most of them were descriptive studies and concentrated on the clinical features. The highest-ranking journal was British medical journal with 211 publications and the most cited journal was Lancet with 2,485 citation counts. Eleven articles written by Christian Drosten from Berlin Institute of Virology have been cited for 389 times and 40 articles from Chinese Academy of Sciences have been cited for 1,597 times which are the most cited author and organization. The number of collaborators with China is 44 and the total link strength is 487. The main partners of China are USA, England and Germany. The published literatures have focused on three topics: disease management, clinical features and pathogenesis.

Conclusions: The current growth trends predict a large increase in the number of global publications on COVID-19. China made the most outstanding contribution within this important field. Disease treatment, spike protein and vaccine may be hotspots in the future.

Keywords: Bibliometric analysis; novel coronavirus; coronavirus disease 2019 (COVID-19); SARS-CoV-2; trends

Submitted May 25, 2020. Accepted for publication Jun 11, 2020.

doi: 10.21037/atm-20-4235

Introduction

As a new acute infectious disease, coronavirus disease 2019 (COVID-19) was first reported in December 2019 in Wuhan, then spread to all the provinces of China and now has become a global pandemic ( 1 ). By 20 th May 2020, a total of 4,735,622 patients were confirmed in over 200 countries, including 307,537 death cases ( 2 ), which resulted in a great public concern. Thus, a series of descriptive researches about the clinical features of COVID-19 have been published by Chinese scholars at the end of 2019. With a deeper understanding of the pathophysiology, more studies focused on antiviral treatment and immune regulation were performed as well as those concentrated on pathology of the disease and vaccine research. In mid-May of this year, more than ten thousand articles have been published and many countries with pandemic have gained a lot of experience from them.

Bibliometrics is a statistical method which could quantitative analysis the research papers concerned about one special topic via mathematical ways ( 3 ). It could also access the quality of the studies, analysis the key areas of researches and predict the direction of future studies. The Web of Science (WOS) online database includes almost all the important research papers which also provides built-in analysis tools to produce representative figures. What is more, the search results from WOS could be exported to a software for further analysis like VOSviewer.

However, no bibliometric analysis of publications on COVID-19 has been published till now. As the COVID-19 pandemic has not been fully under control and more knowledge should be obtained from these reference, bibliometric analysis of it is in critical need. Therefore, our study was performed timely to provide a broad understanding of COVID-19 and future research directions.

The global literatures about COVID-19 published between 2019 to 2020 were scanned in the WOS collection database. The search terms applied to identify the closest matching publication included “COVID-19” or “Novel Coronavirus” or “SARS-CoV-2” or “2019-nCoV” which was used as the keyword in the title. As COVID-19 was first found in Wuhan and a fairly large number of the research papers were written in Chinese, language was not limited during the process of retrieval.

The information for the documents that meet the requirements contained year of publication, language, journal, title, author, affiliation, keywords, document type, abstract and counts of citation which were exported into CSV format. The date of the retrieval was 20 th May 2020. VOSviewer (version 1.6.10) was used to analyze the Co-authorship, Co-occurrence, Citation, Bibliographic coupling, Co-citation and themes. Two standard weight attributes are applied which are defined as “Links attribute” and “Total link strength attribute” ( 4 ).

Bibliometric analysis of publication output

Totally 15,805 publications on the topic of COVID-19 were identified in WOS database between 2019 and 2020 which included 10,601 (67.1%) original research articles, 1,189 (7.5%) review articles, 2,296 (14.5%) editorials and 1,719 other forms of publications including letters, case reports, etc. Among them, 15,619 (98.8%) papers were published in 2020 (till 20 th May) and the other 186 were published in December 2019. Almost all the publications (14,609, 92.4%) were written in English, followed by 623 Chinese publications and 11,575 (73.2%) papers were open access. In all the published papers, 3,626 could be indexed in the WOS core database.

Bibliometric analysis of the keywords

Keywords provided by authors of the paper and occurred for more than 5 times in the WOS core database were enrolled in the final analysis. Of the 4,532 keywords, 344 met the threshold. The keywords that appeared most were “COVID-19” (total link strength 2,649) and “coronavirus” (total link strength 2,024) which had a strong link to “pneumonia” and “epidemiology”. As comparisons of COVID-19, SARS and MERS were another two keywords and the total link strength of each were more than 300 ( Figure 1A ). A word cloud was also created to show the frequency of the keywords which occurred for more than 10 times. It was indicated that “COVID-19” was the most frequent followed by “pneumonia”, “outbreak” and “infection” ( Figure 1B ).

Bibliometric analysis of the citations and publications

The top 100 most cited articles in the field of COVID-19 were listed in Table S1 . Most of them were clinical studies including descriptive studies, case series and case report, the others were research articles which mainly focused on viral genomes and disease transmission. The mean citation count of the top 100 most cited articles was 96 (range, 26–883). All of the papers were published in 2020, and 54 of them were written by Chinese scholars. Thirteen articles were published on the special columns for COVID-19 of the Lancet .

Nine hundred and nineteen journals have published papers about COVID-19 and 141 of them have published more than 5 articles. In total, 606 papers were published in the top ten active journal which accounted for 16.7% of the publications in the WOS core database. The highest-ranking journal was British Medical Journal ( BMJ ), with 211 publications and an impact factor (IF) of 27.604. The most cited journal was the Lancet , with 2,485 citation counts and IF of 59.102 ( Figure 2 ).

The top ten most active countries, organizations and authors of COVID-19 publications are listed in Table 1 . Eleven articles written by Christian Drosten from Berlin Institute of Virology have been cited for 389 times and 40 articles from Chinese Academy of Sciences have been cited for 1,597 times which are the most cited author and organization. Eight hundred and thirty-eight papers from China have been cited for 7,273 times and the total link strength is 8,162 ( Figure 3 ).

Bibliometric analysis of the co-authorship

Totally 6,219 authors have participated in the publication of the COVID-19 papers. Among them, Andrei R. Akhmetzhanov from Hokkaido University of Japan has 7 papers which mostly focus on the transmission of COVID-19. The main collaborators with him are Natalie M. Linton and Hiroshi Nishiura from Japan Science and Technology Agency. The total link strength is 49.

Through the domestic and international literature search, it is revealed that 2,037 organizations have published the related papers and 140 of them have over 5 publications.

Huazhong University of Science and Technology has published 90 related papers with 1,268 citations. The main partner of the organization is Wuhan University and most of the researches mainly concentrate on the clinical features of COVID-19. Hongkong University is another important partner with a long-term study on the transmission of diseases.

The number of collaborators with China is 44 and the total link strength is 487 with 838 publications. The main partners of China are USA, England and Germany. Almost as remarkably, the total link strength of Saudi Arabia is 85 and the country cooperates with other 25 countries in the topic of sharing the experience of MERS treatment ( Figure 4 ).

Bibliometric analysis of the bibliographic coupling and co-citation

The bibliographic coupling map of documents and sources are shown in Figure 5A,B . Seven clusters were obtained from the analysis. Cluster 1 includes 67 items and the research area is clinical features (shown in blue). The representative paper was published in the Lancet in January 2020 by Huang Chaolin. Cluster 7 only has one item which discuss the influence of hypertension and diabetes mellitus on COVID-19 (shown in orange).

Eight clusters of the cited references were obtained by bibliometric analysis. The top three clusters represent the research fields of clinical feature, diseases transmission and treatment which are shown in the colour of red, green and blue. The two biggest clusters of cited sources include 79 and 58 items, respectively. The representative journals are the Lancet and Journal of Virology ( Figure 5C,D ).

Bibliometric analysis of themes and trend topics

As indicated in Figure 6A , three themes of COVID-19 studies were found. The blue cluster involved clinical trials investigating COVID-19 diagnosis and clinical features. The green cluster involved clinical trials investigating management and emergency preparedness. The red cluster involved clinical trials investigating risk factors and pathogenesis. Figure 6B demonstrates the network map of the trend topics according to the keywords used from December 2019 to April 2020. Indicator shows the current publications from purple to yellow. More studies focused on vaccine, disease treatment and spike protein have been published recently.

From our current study, 3,626 publications about COVID-19 indexed in WOS core database were analyzed. The published literatures include the following three aspects: disease management, clinical characteristics and pathogenesis. As the most frequent keyword, “COVID-19” has a strong link to “pneumonia” and “epidemiology”. China made the most outstanding contribution within this important field. Disease treatment, spike protein and vaccine may be hotspots in the future.

The COVID-19 epidemic continues to spread around the world till now and the new cases reported outside China have already exceeded the number of total confirmed cases in Wuhan. The current situation in Europe and America is still very worrisome. To fight against the pandemic, academia joined this “battlefield” as soon as possible to provide recommendations and suggestions to treat the disease. Medical journals with high impact such as the BMJ , Lancet and the New England Journal of Medicine have also opened special columns for COVID-19 ( 5 ), which have an advantage in the number of papers published.

COVID-19 is caused by SARS-CoV-2 and like other emerging diseases, the initial focus is often at the clinical characteristics and transmission ( 6 ). Thus, as the most commonly used keywords, “COVID-19” and “novel coronavirus” have a strong link to “clinical features” and “epidemiology”. Many articles about the comparation of SARS and MERS were published in order to provide lessons for treatment due to limited knowledge could be obtained at the early stage of the disease ( 7 ), and many articles concentrated on clinical features were also most cited ( 8 - 10 ). One of the most important articles was published in 24 th January 2020, which demonstrated the clinical characteristics and management of the disease ( 11 ). At the same day, person-to-person transmission of COVID-19 in hospital and family settings was verified in another family cluster study which has been cited for more than 300 times till now ( 12 ).

As the pandemic was first reported in Wuhan, Chinese scholars wrote almost all the articles published in 2019. With the in-depth study of the disease, more clinical studies were performed in Wuhan and other provinces of China ( 13 ). Studies of antiviral therapy like Chloroquine ( 14 ), Remdesivir ( 15 ), Arbidol ( 16 ) and Lopinavir-Ritonavir ( 17 ) have been published. However, because of the difference in the severity of the patients and the limited sample size, the results are still controversial ( 18 ). Effective drug treatment must be one of the research priorities in the future. As far as vaccines are concerned, monoclonal antibody therapy is still a potential therapeutic intervention to the infectious diseases. Global efforts should be paid on vaccines for COVID-19 and it still has a long way to go ( 19 ).

Publications on COVID-19 were retrieved from WOS and the data was analyzed objectively and comprehensively. Nonetheless, some limitations are still inevitable. Firstly, although a large number of new research papers are added to the WOS every day, only a part of them can be indexed in the core database. Thus, most of the non-English language articles were neglected or excluded. As the COVID-19 pandemic originated from Wuhan China, expert consensus written in Chinese might be important and helpful. Secondly, the current growth trends predict a large increase in the number of global publications on COVID-19 which leads to a fairly large number of papers were published in the preprint online database like medRxiv and they were not enrolled in our study.

Conclusions

With the spread of the pandemic, more and more academic papers have been published. It is particularly important to evaluate the quality of such a great number of research papers and obtain valuable information. Scientific and medical research plays a vital role in understanding COVID-19, as well as helping to find solutions to contain its transmission. Effective drug therapy and vaccine research are still future directions.

Acknowledgments

We are grateful to all the medical staffs of our medical rescue team for fighting against COVID-19 together in the last 2 months in Wuhan.

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/atm-20-4235 ). YY serves as an unpaid section editor of Annals of Translational Medicine from Oct 2019 to Sep 2020. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/ .

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Review article, value co-creation in business-to-business context: a bibliometric analysis using histcite and vos viewer.

• 1 Glorious Sun School of Business and Management, Donghua University, Shanghai, China
• 2 School of Business, Nanjing University, Nanjing, China

Abstract purpose: Value co-creation (VCC) recently displayed a significant increase in the frequency of publications in business studies and social sciences. Our study objects to explore the current state of VCC research in the business-to-business (B2B) context, principally in the marketing field.

Research design, approach, and methodology: This research article extracted research papers on VCC in the B2B context published in the last two decades through the Web of Science (WoS). Initially, we applied HistCite to determine the research dynamics of VCC articles and then VOS viewer to conduct bibliographic coupling and cartographic analysis. Furthermore, we found the most co-occurred keywords in the abstracts, titles, and keywords.

Findings: Our research explored that the United Kingdom was the most important country with 27 publications and 594 citations. Aarikka-Stenroos L was the most influential author, among his research is a systematic review which revealed that scholars of B2B journals adopted the term business “ecosystem” and studied the implications of ecosystem perspective in business and innovation networks and received the most citations. Industrial Marketing Management (IMM) was the most influential journal because it published 8 of the 10 most cited articles. One hundred and six out of 121 publications were in Business research and seventy-six were in management area, which made it the most hot and critical research area. Lappeenranta University was the most essential organization in VCC research based on the most records published and second-highest citations.

Research limitations/implications and future research: Four research streams have emerged which indicate the prominent role of VCC in the B2B context (1) VCC and relationships, (2) VCC and organizational capabilities, (3) VCC and actors’ engagement at various platforms, and (4) VCC and processes. Our research paper provided a base for conceptualizing publications related to business, management, operations research management science, and social sciences interdisciplinary on VCC in the B2B context. Content analysis has revealed that research work on VCC in the B2B context is at an early stage in the marketing arena. Along with bringing some sort of consensus regarding researchers’ opinion toward the nature and modality of VCC literature and process in the B2B context, we urge future research to focus on how relationships and their precursors can be efficiently utilized to co-create and enhance value within B2B interactions. We also request future research to focus on making the VCC process sustainable and viable both on a time and economical basis.

Practical implications: Organizations can involve customers and producers to work jointly to co-create value for their goods and services with negligible cost to achieve higher market shares and a competitive edge over rivals.

Originality/value: This might be the first bibliometric study conducted on VCC in the B2B context (there are some Bibliometric VCC publications, but they are not B2B-specific, our research is the first Bibliometric study conducted on VCC in the B2B context) in the marketing field and can expose novel avenues for future research.

Introduction

Value is probably an elusive and the most ambiguous concept in services marketing and management ( Carù and Cova, 2003 ; Woodall, 2003 ). Yet, various efforts were made to establish holistic conceptualizations of value ( Khalifa, 2004 ), mainly on the individual level ( Holbrook, 1999 ), ignoring the multiple stakeholder interactions. While investigating VCC, especially co-production as a construct that existed before 2000 in disciplines outside marketing Ranjan and Read (2016) , co-creation research emerged through the studies of Prahalad and Ramaswamy (2004a) service-dominant logic that evolved in the new millennium post-2000. Apriliyanti and Alon (2017) have argued that it is imperative and necessary to conduct a bibliometric analysis every 5 years or at least once in 10 years so that emerging constructs and research streams are highlighted. Current studies consider and align CB (Customer Based) VCC processes with several stakeholders, mainly focusing on CB relationships ( Cova et al., 2011 ; Merz et al., 2018 ). Very rarely have studies tried to investigate how CB value is co-created in an industrial environment (i.e., B2B, Business-to-Business) ( Gupta et al., 2017 ; Törmälä and Saraniemi, 2018 ; Iglesias et al., 2020 ). For this purpose, we conducted this study and used co-citation analysis via HistCite to achieve a thorough understanding of VCC research, especially in marketing; with cartography analysis through VOS viewer, we exposed novel research streams to achieve a better understanding of current research.

According to Sarkodie and Strezov (2019) , researchers mainly used HistCite and VOS Viewer in their bibliometric studies. Co-citation analysis is used as a meta-analytical tool in bibliometric studies to explore and demonstrate the interconnections among topics and research articles ( Kim and McMillan, 2008 ) by examining how frequently articles cite a research article. HistCite also shows novel and vital research dynamics (most influential journals, authors, institutions, countries, and cited references) of a topic under consideration ( Luukkonen, 1997 ; Nederhof and Satta, 2006 ). A research field’s genealogical antecedent could be explored swiftly through citation behavior because co-citation analysis highlights the most commonly cited articles ( Fetscherin, 2010 ). We conducted co-citation analysis through HistCite, bibliographic coupling, and cartographic analysis through VOS Viewer to discover essential keywords in the VCC research stream.

At last, this research has attempted to answer the following research questions through co-citation, cartography, bibliographic coupling, and content analysis. The principal research questions lectured in the study are as follows:

RQ1. Which are the most critical and influential channels (institutions, countries, authors, journals, and articles) in VCC in the B2B context literature?

RQ2. How are VCC in B2B publications clustered. Which are the most emerging research streams in marketing studies?

RQ3. Which research streams in VCC received the utmost attention?

RQ4. Which guidelines will expose new avenues for future research in VCC?

Theoretical background

Emergence of value co-creation in business-to-business.

According to Ranjan and Read (2016) , VCC investigations have revealed that co-production as a construct existed before 2000, while co-creation construct emerged through service-dominant logic ( Prahalad and Ramaswamy, 2004a ). McColl-Kennedy et al. (2012) have revealed that 22 out of 27 definitions of co-creation happened after 2000, while the remaining were specific to co-production. Value is perhaps the most ambiguous concept ( Carù and Cova, 2003 ; Woodall, 2003 ). Yet, various efforts were made to establish holistic conceptualization of value ( Khalifa, 2004 ). Co-creation happens when consumers collaborate with product/service providers to create value ( Prahalad and Ramaswamy, 2004b ). According to Grönroos et al. (2000) , Vargo and Lusch (2004) , the value gets more embedded in co-creation when customers transform from passive to more active audiences. Ramaswamy (2009) pointed out that organizations should involve employees in the co-creation of customer value; it must ensure employees’ interaction with customers. In the light of above-mentioned definitions, our study has defined VCC as a two-way process in which manufacturers and customers work together to co create and enhance the value of their products and services.

Prahalad and Ramaswamy (2004a) challenged Porter Michael (1985) traditional and conventional value chain concept; they argued that it did not consider the customer’s role in the process of VCC. Prahalad and Ramaswamy (2004b) proposed the DART Model, which provides the basic foundation by suggesting four necessary conditions for VCC: dialog, access, risk reduction, and transparency. Smith and Colgate (2007) proposed a value-creation strategies framework that classified value into four categories in literature: cost/sacrifice, experiential/hedonic, functional/instrumental, and symbolic/expressive. Payne et al. (2008) proposed a process-based framework that identified three significant processes (steps) in the VCC, first customer value-creation, second, supplier value-creation, and third the encounter process.

Web 2.0 allowed interactions of firms with customers, which reinforced VCC at the customer’s end ( Bell and Loane, 2010 ). Novel technology’s infusion in customer–firm interactions redefined the customer’s role in innovation and value creation ( Bitner et al., 2000 ; Dahan et al., 2001 ; Thomke and Von Hippel, 2002 ). In general, current studies have considered and aligned customer-based (CB) VCC processes with several stakeholders, mainly focusing on CB relationships ( Cova et al., 2011 ; Merz et al., 2018 ). Rare studies have investigated how CB value is co-created in the industrial environment (i.e., B2B, Business-to-Business) ( Gupta et al., 2017 ; Törmälä and Saraniemi, 2018 ; Iglesias et al., 2020 ). Yet, B2B and B2C do not represent all existing markets or business places; they can also function in another environment B2B2C (Business-to-Business-to-Consumer), which synchronously consider both consumers and industrial organizations as customers ( Iankova et al., 2019 ). With the increasing attention of practitioners’ Accenture (2014 , 2016) , and research scholars of marketing Brotspies and Weinstein (2019) , Iankova et al. (2019) , we don’t know how value is co-created in CB multiple stakeholders (B2B2C) markets. Furthermore, Iankova et al. (2019) believe “a treasure of research opportunity exists in the business models of B2B2C, and we know very little regarding the complementary of working in the traditional B2C and B2B sectors, which may yield novel insights.”

The emergence of HistCite and VOS viewer

According to Zupic and Čater (2015) , HistCite use a robust quantitative technique to analyze literature reviews systematically. Pan et al. (2018) investigated 481 research articles through VOS Viewer and HistCite for bibliometric mapping. According to Apriliyanti and Alon (2017) , 336 articles followed HistCite for co-citation purposes, and 2088 articles used VOS Viewer for cartographic analysis to segregate literature for absorptive capacity into five research streams.

By following bibliometric analysis, researchers can swiftly identify a specific concept’s current state, significance and origin ( Fellnhofer, 2019 ). Literature intensive examination has revealed that VOS viewer and HistCite are extensively used; hence, we followed both. HistCite is primarily used for bibliometric analysis to generate chronological tables which provide information about essential authors, institutions, countries, journals, and cited references ( Levitt and Thelwall, 2008 ). Meanwhile, VOS Viewer is frequently used in bibliometric studies, mostly in thematic, cartographic, and cluster analysis ( Llanos-Herrera and Merigo, 2019 ; Noor et al., 2020c ). While using VOS viewer, researchers can promptly investigate and analyze bibliometric networks such as authors, publications, countries, organizations, and journals ( van Eck and Waltman, 2017 ).

Bibliometric analysis has the following five ways, i.e., bibliographic coupling, cartographic analysis, co-occurrence of keywords, co-citation, and co-author. Olczyk (2016) used VOS viewer and HistCite to study and identify growth patterns in international competitiveness literature through bibliometric citation data (1945−2015) of the Web of Science (WoS). VOS viewer uses the text-mining method for keyword analysis to extract keywords content, abstracts, and titles to assist us in finding clusters of closely associated items. The significance of the items demonstrated depends upon the item’s size; a larger item size means higher significance ( Perianes-Rodriguez et al., 2016 ).

Our research is stirred from the research work of Vargo (2011) , O’Cass and Viet (2012) , Shah et al. (2019) , González-Torres et al. (2020) . This study also follows the methodology used by Shah et al. (2021a) . The methodology was used in studies to conduct bibliometric analyses for specific research areas such as brand personality ( Llanos-Herrera and Merigo, 2019 ), Twitter ( Noor et al., 2020b , d ), music therapy ( Li et al., 2021 ), social media role in knowledge management ( Noor et al., 2020a ), maping trends in Moyamoya Angiopathy research ( Chen et al., 2021 ), autism research ( Whyatt and Torres, 2018 ), bibliometric analysis of scientific publications ( Chriki et al., 2020 ), trends of postpartum depression ( Bai et al., 2021 ), and podocyte injury research ( Liu et al., 2021 ). It was also used in the marketing field to study its different aspects like global branding ( Chabowski et al., 2013 ), global value chain ( González-Torres et al., 2020 ), Prosumption ( Shah et al., 2020 ), business-to-business branding ( Seyedghorban et al., 2016 ), and VCC ( Alves et al., 2016 ; Shah et al., 2021a ).

This article searched “value co-creation” and “B2B” as keywords in the WoS, a top-quality database, and found 138 results, as shown in Figure 1 (September 2022). We selected 121 publications from business, management, operations research management science, and social sciences interdisciplinary. WoS is used for searching and tracking top journals of social science, arts, humanities, and basic science ( Fetscherin and Heinrich, 2015 ). It has access to more than 50 million research publications in 70 languages, 151 categories, and 22,000 journals ( Merigó et al., 2015 ). We preferred WoS over SciELO, Google Scholar, SCOPUS, and other search engines based on its competitiveness and quality.

Figure 1. Total publications. Reproduced with permission of Clarivate.

About 4,409 studies used PLS-SEM (partial least square, structural equation modeling) in WoS core collection (October 2022), the most prominent studies were conducted by Henseler et al. (2015) who assessed the discriminant validity in variance-based structural equation modeling and Hair et al. (2011) who studied the use of PLS-SEM in the field of marketing. SEM is a technique used to study, measure, and analyze the relationship between or among observant and latent variables. Another important study was by Hair et al. (2019) , they discussed when and how to use and report and interpret the results of PLS-SEM. About 115 studies on VCC within WoS core collection used SEM, among which 98 (85%) were published post-2017. While among the studied conducted in VCC in the B2B context, only seven research papers have used SEM.

Among the 121 VCC-B2B publications, 100 were articles, 10 were literature reviews, 6 were early access articles, 3 were editorial material and 1 were proceeding papers and corrections each.

The 121 results showed 1880 total citations at an average of 19.81 per year, as shown in Figure 2 . The graph has shown an increasing trend in annual citations specifying the importance and emergence of research work in VCC. During cartographic analysis, we chose co-occurrence for the type of analysis and all keywords for the unit of analysis.

Figure 2. Citations and publications per year. Reproduced with permission of Clarivate.

Methods and analytical tools

We searched “HistCite” and “VOS Viewer” in the core collection of WoS (September 2022). One hundred forty-six bibliometric studies used HistCite; 109 (74.65%) were from the last 5 years. Two hundred thirty-four studies used VOS Viewer, of which 221 (94.44%) were from the last 5 years, which illustrates its emergence and significance in contemporary bibliometric studies. In the bibliographic coupling analysis, the level and degree of authors citing the same research papers show the connection between their research. The nature of relatedness between unrelated authors depends on the number of times they cite a specific article; the higher the citation means higher the relatedness ( Waltman et al., 2010 ). Unlike HistCite numerical representation in its citation graph, VOS Viewer can highlight author names and publication years. We can also use it to cluster publications based on a similar theme, topic, or field ( Ding et al., 2001 ). Hence, with cartographic analysis, research streams of VCC were confirmed, as shown in Figure 3 .

Figure 3. Cartography analysis using VOS viewer.

The procedure of analysis of data

We extracted 121 papers from WoS published on VCC in the B2B context and saved them in a text document correctly to be used by HistCite later (September 2022). The document possessed the article’s titles, document’s type, abstract, authors and journals names, and language used. Then, we exported that file to HistCite and processed it to extract the most influential authors and journals names, articles, language, document types, countries, and institutes names. Furthermore, we performed a VCC citation mapping analysis to obtain a tabular form output ( Garfield et al., 2003 ). Afterward, we took the services of VOS Viewer to conduct bibliographic coupling and cartographic analysis. The tabular and visual data were beneficial for assisting us in sighting and discovering the future research streams of VCC in the B2B context.

Discussion and findings

Value co-creation articles analysis through histcite, influential authors, articles, and journals.

This study discovered that 339 researchers authored 121 articles. TGCS was the formula for sorting out the most influential and renowned authors. TGCS demonstrates the number of times articles reference a specific article globally. The total local citations score (TLCS) shows the number of times an article is referenced within a retrieved set of articles. The most prominent author was Aarikka-Stenroos L, with 193 TGCS, 6 TLCS score, and three records ( Table 1 ). Second on the list was Ritala P, with 150 TGCS. Zolkiewski J with 138 was spotted third, Breidbach CF and Maglio PP ( Breidbach and Maglio, 2016 ) with 127 TGCS were listed fourth and fifth, respectively. Baumann J and Keranen J were listed sixth and seventh. Chowdhury IN and Gruber T with the same TGCS and TLCS were placed eighth and ninth. Despite being listed at tenth Rajala R is still an essential author for showing the highest TLCS among the top 10 authors as shown in Table 1 .

Table 1. Most influential authors.

The article published by Aarikka-Stenroos L and Ritala P was on top, with a TGCS score of 150. The runner-up study was Breidbach and Maglio (2016) with 127 TGCS. We ranked Chowdhury et al. (2016) third with a 102 TGCS score. The study conducted by Marcos-Cuevas et al. (2016) was placed fourth with a TGCS score of 94 and Kohtamäki and Rajala (2016) was placed fifth. Articles of Bruhn et al. (2014) with 89 TGCS, Singaraju et al. (2016) , Nguyen QA, Niininen O, and Sullivan-Mort G with 86 TGCS value and Hilton T, Hughes T, Little E, and Marandi E with 75 TGCS were ranked sixth, seventh, and eighth, respectively. The article of Hein A, Weking J, Schreieck M, Wiesche M, and Bohm M with 72 TGCS was listed ninth and Zhang et al. (2015) with 70 TGCS was tenth. Based on TLCS value Kohtamäki and Rajala (2016) showed the highest value of 25. From Table 2 our study also found that all the top ten research articles were published in one-decade post 2012, among which one was published in 2013, 2014, and 2015 each, five in 2016, one in 2017 and 2019 each. This shows the emergence and novelty of the topic.

Table 2. Most influential articles.

We sorted the rankings of the journals based on the number of publications and the TGCS value. Our study found that the selected 121 research articles were published in 33 journals. As shown in Table 3 , 41 out of 121 research articles were published in IMM having TGCS value of 1417, which shows the importance of IMM for its publications in the relevant research. The TGCS value of other journals was comparatively less because IMM published eight out of the top ten (most-cited) research articles. We also found that 31 research articles were published in the Journal of Business and Industrial Marketing , having a TGCS value of 278. Similarly, the Journal of Business Research , and Journal of Marketing Management showed four publications each, with 61 and 43 TGCS value were ranked third and fourth respectively. European Journal of Marketing and Journal of Hospitality and Tourism Management with the same publications were ranked fifth and sixth, respectively. Furthermore, all the remaining four journals showed two publications.

Table 3. Most influential journals.

Most prominent institutions and countries

Our study found that 200 institutions participated in 121 publications. We sorted the top 10 most influential and prominent institutions in Table 4 based on publications and then TGCS value. We found the Lappeenranta University of Technology on top of the list with six publications and a TGCS value of 266. Aalto University showed five records and 165 TGCS. The University Valencia and Lebanese Amer University showed four publications each and were listed third and fourth, respectively. All the remaining six universities published three research papers each. Despite Aalto University being ranked second, it showed the highest TLCS value of 28.

Table 4. Most influential institutions.

A total of 37 countries were involved in publishing the 121 VCC in B2B research papers. We ranked the Countries based on the number of records published and then TGCS value; Table 5 shows the top ten countries publishing these 121 research papers. The United Kingdom was on top of the list with 27 publications and 594 TGCS values. The United States with 21 publications and a TGCS value of 385 was listed second. Finland with 18 publications and a TGCS value of 619 was ranked third. The people’s republic of China was fourth with 15 publications and a TGCS value of 217. Australia with 11 records was listed fifth. Sections “Influential authors, articles, and journals” and “Bibliographic coupling using VOS viewer” are an attempt to answer the research question (RQ1).

Table 5. Most influential countries.

Research streams of 121 value co-creation research papers

Citation mapping analysis.

Figure 4 shows HistCite co-citation analysis. HistCite graph maker revealed 15 links (relationships among articles) from 30 articles (nodes) as the most cited. The graphs displayed the interconnection between these articles and how these articles have cited other articles. The citation mapping of HistCite also displayed the existing situation of all these 30 articles. It exposed two central and most crucial research articles, which were the epicenter of most of the connections among the top 30 articles. Kohtamäki and Rajala (2016) (number 26) on HistCite graph with 25 TLCS and 92 TGCS and Singaraju et al. (2016) (number 23) with six TLCS and 86 TGCS value as shown in Figure 5 .

Figure 4. HistCite citation mapping analysis. Reproduced with permission of Clarivate.

Figure 5. Bibliographic couplings using VOS viewer.

Based on TLCS value, the study by Kohtamäki and Rajala (2016) with 25 was ranked first, Breidbach and Maglio (2016) with 14 was spotted at second and Komulainen (2014) with 11 scores grabbed the third position. On the basis of TGCS value, the study by Breidbach and Maglio (2016) was first, Chowdhury et al. (2016) was second and Kohtamäki and Rajala (2016) was third with a score of 127, 102, and 92, respectively.

Bibliographic coupling using VOS viewer

In our study, bibliographic coupling was used for citation analysis. It offers a variety of analyses such as authors, journals, and publications ( van Eck and Waltman, 2017 ). Circle size determines an article’s importance; a larger circle indicates more significance ( van Eck and Waltman, 2010 ). During the analysis, for the type of analysis, we selected bibliographic coupling for the unit of analysis, we selected publications and full counting as the method in the VOS viewer. We selected a threshold value of 10 (citations) to bring rigor and precision to the analysis of VCC research streams. In total, we received 56 publications that emerged into four clusters, 1200 links, and a total link strength value of 3965. Represented by red color (having 18 articles) cluster 1 was the largest. The study by Breidbach and Maglio (2016) with 127 was the most cited article, while Chowdhury et al. (2016) with 102 the second, and Marcos-Cuevas et al. (2016) with 94 the third most cited article. Marcos-Cuevas et al. (2016) showed the highest links value of 52 while Chowdhury et al. (2016) showed the highest value of 288 for total links strength. Cluster 1 showed a total of 844 citations, 779 links, and total links strength value of 2657. Cluster 2 was represented by green color and possessed 14 articles and was the second largest. Bruhn et al. (2014) with 89 citations was the most cited article, Singaraju et al. (2016) with 86 was second and the Zhang et al. (2015) with 70 citations was the third most cited article in Cluster 2. Singaraju et al. (2016) showed the highest number of links, with 52, and Zhang et al. (2015) showed the highest value for total links strength. Cluster 2 showed 541 total citations and 1515 total links strength value.

Cluster 3 was represented by blue color containing 13 articles. Aarikka-Stenroos et al. (2017) showed 150 citations, Hollebeek (2019) with 62 was the second and Drummond et al. (2020) with 50 was the third most cited article in Cluster 3. Hollebeek (2019) displayed the highest value of links, with 52, and 230 total links strength. Cluster 3 showed 512 citations, 555 links and 1826 of total links strength value. Cluster four, represented by a yellow color, possessed 11 articles and was the smallest cluster. Komulainen (2014) showed the highest citation value of 49, Keränen and Jalkala (2013) with 48 was the second and Mencarelli and Rivière (2015) with 38 was the third most cited article in Cluster 4. La Rocca and Snehota (2014) , Baumann and Le Meunier-FitzHugh (2015) , Mencarelli and Rivière (2015) , Park and Lee (2018) showed the highest links value of 50, while Baumann and Le Meunier-FitzHugh (2015) showed the total links strength value of 225. Cluster 4 showed 276 total citations, 513 links, and 1936 of total links strength value. Graphical representation and tabular explanation can be seen in Figure 5 and Table 6 .

Table 6. Keywords co-occurrences in respective clusters.

Cartography analysis through VOS viewer

By exploring the research streams of 121 VCC articles through bibliographic coupling analysis, we categorized research streams through the cartography analysis technique of VOS Viewer, as displayed in Figure 3 . During the analysis process, a map was constructed for frequently occurring keywords in 121 VCC research papers. We selected co-occurrence for the type of analysis and all keywords for the unit of analysis. Furthermore, our study selected five as a minimum threshold for shared keywords to bring rigor and precision to the analysis. Consequently, we got 56 frequently occurring keywords in VCC in B2B research ( Figure 3 ). VOS Viewer classified keywords into four main clusters and transferred them into visual form in the network visualization view. The size of the circle and label shows the significance of the keywords; a larger circle means more significance. Furthermore, keywords of the same color belong to the same cluster ( van Eck and Waltman, 2010 ; Figure 3 ).

Among the total 56 keywords, Cluster 1 (marked in red) possessed 20 keywords. The keyword “value co-creation” had the highest co-occurrence value of 103, the highest links value of 55 and total links strength value of 505. Cluster 1 showed 270 total co-occurrences of keywords, 553 links, and 1426 total links strength value. Cluster 2, represented by green color was the second largest, and it possessed 15 keywords. “B2B” and “innovation” showed 26 co-occurrences each. Similarly, the keyword “B2B” showed the highest links value of 47 and total links strength value of 156. Cluster 2 displayed 200 co-occurrences of keywords, 452 links, and 1071 total links strength value. Cluster 3, shown in blue, possessed 13 keywords and was the third largest. Keyword “performance” showed the highest co-occurrences of 25, while the keyword “management” showed the highest links value of 47 and total links strength value of 139. Cluster 3 showed 152 total co-occurrences of keywords, 372 links, and 818 total links strength. Cluster four represented in yellow color was the smallest of all clusters and possessed 8 keywords. “Customer engagement” and “Social media” showed the highest co-occurrences value of 11 each. Keywords “Sales” and “Social media” showed 31 links while “customer engagement” showed 68 total links strength value. Keywords of cluster four exhibited 60 co-occurrences of keywords, 207 links, and 357 total links strength value. With the discussion in Sections “Citation mapping analysis,” “Bibliographic coupling using VOS viewer,” and “Cartography analysis through VOS viewer,” we have answered the research question (RQ2).

Cluster analysis

We found 56 research articles that fulfilled the criteria of having at least 10 citations in 121 VCC in B2B publications. These were categorized into four clusters ( Tables 7 – 10 ) having details about author names, titles, weighting (number of links and total link strength), and TGCS. The significance and importance of each research paper depend upon its weight in the particular cluster ( Rodrigues et al., 2014 ; van Eck and Waltman, 2017 ). We followed two standard weighting features (total link strength and number of links), highlighting the article’s significance. In bibliographic coupling analysis, a link shows the connection or relation between two articles. Every link possesses a number value which explains its strength, which is higher when the link is stronger ( van Eck and Waltman, 2017 ). VOS Viewer calculated links of specific articles and their strength values into one value of total link strength. We ranked the articles within the clusters based on the number of links and TGCS value. The higher the number of links and TGCS value, the higher the ranks. We ranked articles with similar links and TGCS values according to their respective total links strength value, the higher the total links strength value, the higher the ranking.

Table 7. Cluster 1.

Table 8. Cluster 2.

Table 9. Cluster 3.

Table 10. Cluster 4.

Cluster 1 value co-creation and relationships

Cluster one possessed 18 articles as listed below, including the title, author’s name, links, total link strength, and TGCS score. Research articles authored by Marcos-Cuevas et al. (2016) , Altuntas Vural (2017) showed 52 links each and were ranked first and second, respectively, while Chowdhury et al. (2016) with 51 links was listed 3rd. Breidbach and Maglio (2016) , Kohtamäki and Rajala (2016) , Mingione and Leoni (2020) , Leone et al. (2021) displayed 50 links each and were ranked, respectively. Chowdhury et al. (2016) exhibited the highest value for total links strength 288 followed by Mingione and Leoni (2020) with 234 and Kohtamäki and Rajala (2016) with 216. Breidbach and Maglio (2016) showed the highest TGCS value of 127, Altuntas Vural (2017) showed 120 and Chowdhury et al. (2016) displayed 102, being the third. The ranking is given based on the links value and then in alphabetical order.

Altuntas Vural (2017) conducted a literature review of service-dominant logic in B2B marketing and supply chain management studies. This research identified five key research streams, (1) value-in-use and VCC, (2) integration and relationship management, (3) service supply chains, (4) resource sharing, and (5) Servitization. Chowdhury et al. (2016) focused on the dark side of VCC and studied how role conflict, role ambiguity, opportunism, and power impacted the VCC process negatively. Breidbach and Maglio’s (2016) empirical study focused on the information technology (IT) role in the co-creation of value in complex B2B service systems of consulting industry. Kohtamäki and Rajala (2016) reviewed the theories and methods used in VCC and co-production literature. They covered numerous viewpoints of economic and social exchange theory within multi-actor service ecosystems. Petri and Jacob (2016) termed customers as enablers. This cluster mostly focused on precursors (trust, commitment) and their outcomes (satisfaction, relationship quality and competitive advantage) in the relationships (buyer- seller, B2B, buyer- supplier relation, relationship marketing) and the resources needed for them in various industries (services and supply chain, etc.).

Cluster 2 value co-creation and organizational capabilities

Cluster 2 contains 14 articles, as shown in Table 8 . Singaraju et al. (2016) showed 52 links and was first in the ranking. Chang et al. (2018) , Jayashankar et al. (2018) showed 50 links each and were placed second and third. Zhang et al. (2015) displayed 49 links occupying the fourth place. Zhang and Zhu (2019) showed 47, Zolkiewski et al. (2017) showed 46, and Ferguson et al. (2016) showed 41 links and were ranked fifth, sixth, and seventh, respectively. Zhang et al. (2015) showed the highest links strength value of 215, followed by Singaraju et al. (2016) , Chang et al. (2018) with 186 and 184, respectively. Bruhn et al. (2014) exhibited the highest TGCS value of 89, Singaraju et al. (2016) 86, and Jayashankar et al. (2018) 62.

Singaraju et al. (2016) reviewed the literature on the actor-to-actor (A2A) model and SD logic and studied the significance of social media platforms as system resource integrators between firms and customers interactions. Chang et al. (2018) revealed that marketing capability and entrepreneurial orientation are vital and positively affect a firm’s brand orientation, influencing brand performance by facilitating customer VCC activities. Jayashankar et al. (2018) studied the influence of trust in technology adoption by farmers in the agriculture sector. The study also revealed that perceived value is positively related to trust and negatively affiliated with perceived risk. Zhang et al. (2015) study unveiled that networking and marketing capability via customer value and VCC both, directly and indirectly, create brand equity, while innovation capability positively and indirectly impacts brand equity by enhancing and facilitating customer value and VCC.

This cluster mainly focused on how and which organizational capabilities can bring changes like innovation, the role of technology in increasing the value of service-dominant logic, and how to engage and utilize networks in today’s world of technology. It also discussed how all these factors influence value in B2B interaction in different industries.

Cluster 3 value co-creation in actor’s engagement at various platforms

Cluster 3 exhibited 13 articles with Hollebeek LD showing the highest links value of 52. Jonas et al. (2018) , Möller and Halinen (2018) showed 48 links each and were placed second and third, respectively. Laczko et al. (2019) , Blasco-Arcas et al. (2020) exhibited 47 links and were ranked fourth and fifth, respectively. Hollebeek (2019) showed the highest links strength value of 230, Möller and Halinen (2018) with 220 was second, and Blasco-Arcas et al. (2020) with 167 was third. Jaakkola and Aarikka-Stenroos (2019) showed the highest TGCS value of 150, followed by Hollebeek (2019) with 62, and Drummond et al. (2018) with 50.

Hollebeek (2019) focused on how important social media platforms and customer engagement are for businesses, and how can businesses engage their customers, while Jonas et al. (2018) studied the precursors of engagement and the role of stake holders’ engagement in intra- and interorganizational innovation within service ecosystems. This cluster focused on how to engage customers, Stakeholders, business actors, networks, purchasers, etc. It also studied how to enhance engagement at each level (social media and digital platforms, business platforms, and industrial environment). It also studied the role of management, knowledge, and information sharing in enhancing performance.

Cluster 4 value co-creation and processes

La Rocca and Snehota (2014) , Baumann and Le Meunier-FitzHugh (2015) , Mencarelli and Rivière (2015) , Park and Lee (2018) all showcased 50 links and were ranked, respectively. Pinnington et al. (2016) showed 47 and was ranked fifth. Keränen and Jalkala (2013) , Komulainen (2014) displayed 47 links each and were ranked sixth and seventh. Baumann and Le Meunier-FitzHugh (2015) showed the highest value for total links strength of 225 followed by Mencarelli and Rivière (2015) with 219 and Keränen and Jalkala (2013) with 215. Komulainen (2014) presented the highest TGCS value of 49, Keränen and Jalkala (2013) 48, and Mencarelli and Rivière (2015) 38.

Baumann and Le Meunier-FitzHugh (2015) explored the VCC process through in-depth interviews of salespersons and their customer interactions. During the co-creative interaction, both parties played different roles that were driven by characteristics, like sharing interests, establishing equitable dialog and commitment to common goal achievement. La Rocca and Snehota (2014) explored the organizational issues involved in implementing value programs in B2B firms and explored the required managerial actions. Keränen and Jalkala (2013) empirically studied the customer value assessment process from three solution suppliers’ perspectives. They proposed a five-step process framework (potential value identification, baseline assessment, performance evaluation, long-term value realization, and systematic data management). Mencarelli and Rivière (2015) compared the understanding of the perceived value in B2B and B2C spheres and adopted a micro-analytical (zoom-in) approach. Komulainen (2014) focused on customer sacrifices and motivation toward learning and involvement in VCC with the service provider. Section “Cluster analysis” provides an answer to the research question RQ3.

Research guidelines for future studies

This research paper’s final objective was to propose guidelines for further studies, explore and advance VCC’s role in the marketing discipline. Our research paper followed Apriliyanti and Alon (2017) , Shah et al. (2019) methodology using content analysis or the conventional literature review method. We proposed future research guidelines from research articles having comparatively high links and total links strength. We selected 17 research papers and their guidelines, eight from Cluster 1, four from Cluster 2, two from Cluster 3, and three from Cluster 4, as shown in Table 11 .

Table 11. Future research guidelines.

The research guidelines suggested by the first cluster highlighted concepts, like communication skills and dynamic capabilities, leadership and management role, and customer value. The future research direction from Cluster 1 urged future research to focus on the concepts mentioned above and find their association with VCC ( Marcos-Cuevas et al., 2016 ; Petri and Jacob, 2016 ). VCC is a new field, and along with B2B research should also focus on B2C ( Breidbach and Maglio, 2016 ). Kohtamäki and Rajala (2016) focused on service-dominant logic and urged to focus on bridging the gap in SD-Logic and institutional approach. Cluster 2 emphasized concepts like organizational and dynamic capabilities and the role of management in utilizing these capabilities to create and enhance VCC. It also focused on the knowledge management application effectiveness in marketing and on establishing and developing systems perspective, utilization of big data in multi stake holder systems ( Singaraju et al., 2016 ), and the role of CSR in VCC ( Tuan et al., 2019 ).

Cluster 3 is about how the performance, trust, commitment, interaction, and relationship between buyer and seller (producer and customer) create and augment VCC. It endorses future research to focus on how to engage customers, actors, buyers, and stakeholders in a way that improves their interaction among the parties to enhance VCC and performance. Cluster 4 was the smallest cluster; however it mostly focused on the process of VCC and urges future researches to focus on extending the existing framework for VCC in B2B ( Keränen and Jalkala, 2013 ), how does value co-destruction work ( Berenguer-Contrí et al., 2020 ) as shown in Table 11 . Appendix Table 1 in the appendix section at the end of the paper show the future research guidelines of some research papers. Despite showing low citations these research papers are still important based on their relevance and nature of research work.

Our research article contributed to the understanding of the literature on VCC in the B2B context by grouping the articles into clusters systematically and exploring future research streams. Our study identified influential authors, articles, journals, institutions, and countries through HistCite, which contributed to VCC research in the B2B context. We received 138 publications in “VCC” in “B2B” September (2022). We refined the publications to 121 by selecting articles from Business, management, operations research management science, and social sciences interdisciplinary. Furthermore, we categorized the top fifty-six research articles into four clusters through VOS viewer’s cartographic analysis. We studied each cluster in-depth through content analysis and proposed future research guidelines as well. Our research work will guide researchers in the marketing discipline to investigate various aspects of VCC and determine the research work’s growth by title, topic, measurement, and context.

Theoretical implications

This study was assisted by bibliometric analysis to provide meaningful insight for other researchers. From content analysis, we have achieved certain novel aspects and understanding about this concept. Some scholars believe that VCC is still an ambiguous concept, and scholars have a difference of opinion regarding VCC’s nature and modality. Existing models of VCC in B2B perspectives purposed by Chen and Nath (2004) , Prahalad and Ramaswamy (2004b) , Andersson et al. (2007) provide a wide range of conceptual differences. A group of scholars believes that further research is needed to bridge the gap between the new institutional approach and S-D logic. They urge, that there is a need for studies of VCC in the service network, service ecosystem, and service value system ( Kohtamäki and Rajala, 2016 ). Another group of scholars believes, that current studies of customer-based VCC processes in multiple stakeholders environments focus on CB relationships ( Cova et al., 2011 ; Merz et al., 2018 ). While only a few researchers have tried to investigate how customer-based value is co-created in the industrial environment ( Gupta et al., 2017 ; Törmälä and Saraniemi, 2018 ; Iglesias et al., 2020 ). So, another venue of future academia could focus on how CB relationships co-create value in B2B interactions. While a group of authors believes that despite practitioners’ ( Accenture, 2014 , 2016) and scholars’ attention ( Brotspies and Weinstein, 2019 ; Iankova et al., 2019 ), nothing is known on how value is co-created in customer-based A2A interactions and multiple stakeholders in B2B2C markets. Moreover, Iankova et al. (2019) call for future research that a wealth of research opportunities exist in B2B2C models.

Practical implication

Value co-creation research in the B2B environment is in the incubation stage; as presented by bibliometric and content analysis, this study reveals that most papers were published in the last decade specifically post-2018. With web 2.0 rise, business firms can easily achieve a competitive advantage, market share, and VCC ( Cova and Cova, 2012 ; Shah et al., 2021b ). Organizations can involve customers in the value creation process to add desired features and changes to products and services to increase their value and organizational value, eventually leading to performance and competitive edge. According to Campbell (2003) , Harkison (2018) , Wu et al. (2018) , organizations gain knowledge from specific customers and then utilize this information to gain competitive advantage through delivering a unique and personalized set of services. Thus, VCC can help get a competitive advantage if organizations learn to manage the process correctly ( Prahalad and Ramaswamy, 2004b ; Navarro et al., 2015 ; Oyner and Korelina, 2016 ; Harkison, 2018 ).

Limitations and future research

From content analysis, we learned that VCC is a new construct, especially in the B2B context, and both have their significance in today’s business environment. Our first limitation is that we did not study VCC in other multi-stake holder environment (B2C and B2B2C context); so, we recommend future research to study VCC in the B2C and B2B2C context. Second, in this study, for content analysis, we ignored articles having less than 10 citations during cluster and co-citation analysis. Thus, the recently published research papers were not considered for contribution as their citation index was less than 10.92 out of 121 research articles were published in the past 5 years after 2018 which is 76 percent of the total, which shows the novelty of the concept and is a hot research area. Apriliyanti and Alon (2017) argue that it is essential to conduct bibliometric analysis every 5 years or once in 10 years so that emerging research constructs are highlighted. Thirdly, this study ignored research articles from sources other than WoS. Questions may be raised on our research paper for preferring high-quality publications and ignoring non-WoS journal articles. We recommend future researchers to study research articles from SCOPUS and other data bases as well. Future researchers should also use other Bibliometric software tools to analyze non-WoS journal articles related to VCC in the B2B context. However, this study possesses novel research insights into VCC in B2B contexts for research academia.

As some scholars believe that value and VCC are still ambiguous concepts and there lies a difference of opinion regarding VCC’s nature and modality, so we urge future research to establish some sort of accord. Relationships and its precursors are vital resources and aspects that when efficiently utilized by organizations can give fruitful results in enhancing brand loyalty, customer retention, VCC, competitive edge, and organizational performance. However, there is also a lack of empirical studies which can show us how CB value is co-created in multiple stakeholder and industrial environments (B2B, B2C, and B2B2C). There is a dire need for future studies to focus on how business relationships could be best utilized for co-creating costumer and organizational-based value in B2B interactions. We also urge future research to put an effort in bridging the gap between the service-dominant logic and new institutional approach. The existent proposed models by various researchers within VCC in B2B have a wide range of differences among them, we request future research to propose a model which in unanimously accepted. Achieving VCC is not the ultimate target, for achieving a long-term competitive edge future research need to find a way how can organizations make the process of VCC both sustainable and economically viable.

With the discussion, we have made in Sections “Research guidelines for future studies” and “Limitations and future research” we have answered our fourth and final research question (RQ4).

Author contributions

All authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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APPENDIX TABLE 1. Future research guidelines of some important articles.

Keywords : Web of Science, VOS viewer, bibliometric review, HistCite, value co-creation, B2B

Citation: Ullah F, Shen L and Shah SHH (2023) Value co-creation in business-to-business context: A bibliometric analysis using HistCite and VOS viewer. Front. Psychol. 13:1027775. doi: 10.3389/fpsyg.2022.1027775

Received: 25 August 2022; Accepted: 14 October 2022; Published: 11 January 2023.

Reviewed by:

Copyright © 2023 Ullah, Shen and Shah. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Fawad Ullah, [email protected] ; Lei Shen, [email protected]

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Bibliometric Analysis and Visualization

• Bibliometrics
• Journal level metrics
• Author-level metrics
• Article-level metrics
• Bibliometric resources

About VOSviewer

Obtaining content from databases, bibliometric analysis using vosviewer, create a thesaurus, definitions.

• CitNet Explorer

VOSviewer is a software tool for constructing and visualizing bibliometric networks. These networks may for instance include journals, researchers, or individual publications, and they can be constructed based on citation, bibliographic coupling, co-citation, or co-authorship relations. VOSviewer also offers text mining functionality that can be used to construct and visualize co-occurrence networks of important terms extracted from a body of scientific literature.

Download VOSviewer from  https://www.vosviewer.com/

Scopus – CSV – most options for analysis (co-authorship, co-occurrence, citation, co-citation, bibliographic coupling)

• search by topic or desired publications
• select citations and click export – select CSV
• limited to 2000 articles
• Citation information 
• Affiliations
• Abstract and keywords
• Include references 

Scopus – RIS – limited to author and co-occurrence (keyword)

• select citations and click export – select RIS

Web of Sciences – plain text (txt) – most options for analysis (co-authorship, co-occurrence, citation, co-citation, bibliographic coupling)

• select citations and click export – select plain text
• limited to 500 articles
• include records from 1 to ???
• Record content – Full Record and Cited References

Web of Science – RIS – limited to author and co-occurrence (keyword)

• limited to 1000 articles
• Record content – Author, Title, Source, Abstract

Create a map based on bibliographic data

Export in CSV format (Scopus) or TXT (Web of Science)

• Choose this option to create a co-authorship, keyword co-occurrence, citation, bibliographic coupling, or co-citation map based on bibliographic data  -- click next
• Choose data source - select Read data from bibliographic database files  -- click next
• Select files - click on tab of database source and select file from computer (.csv) - click next
• Click Co-authorship and Full counting  & Unit of analysis (Authors, Organization, Countries) and - click next
• Choose threshold - make choice -- click next
• Choose number of authors - make choice - click next
• you can use this table to create a thesaurus to clean up names.  (i.e. same author but name variations) or exclude names
• Click Finish

Export in RIS format

• Choose this option to create a co-authorship or keyword co-occurrence-- click next
• Choose data source - select Read data from reference manager files  -- click next
• Under RIS tab, select file from computer - click next
• Click Co-authorship (or co-occurrence) and Full counting - change other setting you would like - click next

Create a map based on text data

• Choose this option to create a term co-occurrence map based on text data - click next
• Choose data source - select Read data from a bibliographic databases (Scopus – CSV; WOS -txt) or read data from reference manager files (RIS) -- click next
• Choose fields – Title and abstract fields, Title field  or abstract field)- click next   (if download included abstracts - abstract & title will be an option)
• Choose counting method - choose binary or full - click next
• Choose number of terms - make choice - click next
• you can use this table to create a thesaurus to clean up terms.  (i.e. same author but name variations) or exclude names

A thesaurus can be created to remove "stop" words or to standardize terms or names or affiliations

A thesaurus must be in a plain .txt table format

• by putting an alternative term in the replace by column the system will replace the label term with the replace by term
• by leaving replace by blank, the system will replace the label with a blank, removing the term from analysis (stop word)
• Co-authorship – authors writing in the same network, whether directly or indirectly
• Co-occurrence - Keyword co-occurrence
• Citation – which article cites another article (or which authors of the articles cites authors of author articles)
• Co-citation - Two publications are co-cited if there is a third publication
• that cites both publications (Marshakova, 1973; Small, 1973). The larger the number of publications by which two publications are co-cited, the stronger the co-citation relation between the two publications. (3rd pub newer)
• Bibliographic coupling is the opposite of co-citation. Two publications are bibliographically coupled if there is a third publication that is cited by both publications (Kessler, 1963). In other words, bibliographic coupling is about the overlap in the reference lists of publications. (3rd pub older)
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