the ideal partner mini case study brainly

• Relationships

What's Most Important When Choosing a Partner

... and why your list of must-have qualities may keep you from finding love..

Posted October 21, 2016

The list we’re going to talk about here is the one that contains the characteristics of the partner of your dreams —the person with whom you know you’d experience long-term happiness . The list includes all of your requirements for a perfect partner—looks, financial fitness, personality , education , health, personal and family history, religion, ethnicity , relationship history, and any other item you consider essential for a fulfilling relationship. Not everyone has a preference for all of these factors on their list. Many are irrelevant to some people, while other individuals have concerns that we have not mentioned here.

But this post is about what isn’t on your list—certain things that you need to have on your list, in addition to the priorities you're consciously aware of. These are our “shadow priorities”— needs and desires that we are less consciously aware of but that represent other commitments in competition with our more conscious preferences. It’s not that one set of preferences is correct and the other is not, but rather that they each represent compelling and competing interests and desires that need to be fulfilled in order to satisfy our different sets of needs.

We don't need to be completely similar to our partner—in fact, we generally aren’t even attracted to people who are very similar to us. However, there does need to be complementarity , meaning that we complement each other by providing strengths and enhancements in areas where our partner may be less developed. When this is present in a relationship, there is a strong likelihood that both partners will experience what we commonly refer to as chemistry .

Unconscious concerns have more to do with aspects of our life that relate to the potential that our partner represents. He or she may help us fulfill psychological needs and heal emotional wounds, support personal development, and, in general, be a good “fit” for our personality. When we are intimately connected to someone with whom we share the experience of complementarity, we feel a sense of being whole and complete that is not present otherwise. This is the feeling that frequently occurs during the “infatuation” phase of a relationship.

The experience of infatuation fades over time, because we experience this feeling vicariously through the other person, and haven’t yet fully cultivated and integrated the qualities and traits our partner brings to our life. The real work of a relationship begins after we find the partner of our dreams; it has to do with our willingness to see that what they bring into our life not only thrills us, but sometimes drives us to distraction.

These extremes are not a sign of instability, but are inherent in the process of coming to terms with one of the great paradoxes of relationships: They represent the hope of the fulfillment of our most cherished dreams, and the fears that inevitably underlie those hopes. Fears like losing ourselves, being controlled by another, re-experiencing painful feelings, being exploited or taken advantage of, being left or abandoned, or other disturbing possibilities.

When we fail to recognize and acknowledge the unconscious commitments that compete with our conscious preferences we run the risk of setting ourselves up to feel disappointed and unfulfilled. We may wrongly attribute those feelings to a deficiency in our partner or in ourselves when this isn’t necessarily the case. All too often, the problem is that even if we have successfully checked off all of the things on our list, we may have left off the most important items.

It isn’t necessary—nor is it even possible—to always be consciously aware of what is in the shadows of our desire system. It can be enough to understand that what draws us to others, and what draws others to us, includes characteristics that are important to our inner development and our healing into wholeness. When we more fully appreciate this aspect of our relationship, it becomes easier (but not necessarily easy) to trust the process enough to become less reactive to the upsets that arise when the heat of infatuation inevitably cools, whether after a week or several years.

Accepting the inevitability of these feelings, without mistaking them for indicators that we are just not meant to be, enables us to maintain a healthy relationship and resist the temptation to jump to conclusions or make impulsive judgments and decisions based on insufficient information.

Not all relationships are meant to be, and some should be ended when it becomes evident that there's a mismatch. Yet many potentially successful relationships are ended before they are given an adequate chance. It may be that it's only after sharing ordeals and spending time together—time that includes doing the work of learning to appreciate rather than condemn our differences—that we recognize the hidden gifts our partner brings to us, which may have initially shown up as problems to be eliminated.

By all means, hold on to your list, but don’t forget that your heart has another list that may not be quite as apparent to you. To quote Antoine de Saint-Exupéry, “It is only with the heart that one can see rightly; what is essential is invisible to the eye.”

Linda and Charlie Bloom are excited to announce the release of their third book, Happily Ever After…and 39 Other Myths about Love: Breaking Through to the Relationship of Your Dreams .

“Love experts Linda and Charlie shine a bright light, busting the most common myths about relationships. Using real-life examples, they skillfully, provide effective strategies and tools to create and grow a deeply loving and fulfilling long-term connection.” – Arielle Ford, author of Turn You Mate into Your Soulmate

If you like what you read, visit our website and subscribe to receive our free inspirational newsletters. And follow us on Facebook !

Linda Bloom, L.C.S.W. , and Charlie Bloom, M.S.W. , are the authors of Secrets of Great Marriages: Real Truths from Real Couples About Lasting Love .

• Find a Therapist
• Find a Treatment Center
• Find a Psychiatrist
• Find a Support Group
• Find Online Therapy
• United States
• Brooklyn, NY
• Chicago, IL
• Houston, TX
• Los Angeles, CA
• New York, NY
• Portland, OR
• San Diego, CA
• San Francisco, CA
• Seattle, WA
• Washington, DC
• Asperger's
• Bipolar Disorder
• Chronic Pain
• Eating Disorders
• Passive Aggression
• Personality
• Goal Setting
• Positive Psychology
• Stopping Smoking
• Low Sexual Desire
• Child Development
• Self Tests NEW
• Therapy Center
• Diagnosis Dictionary
• Types of Therapy

Sticking up for yourself is no easy task. But there are concrete skills you can use to hone your assertiveness and advocate for yourself.

• Emotional Intelligence
• Gaslighting
• Affective Forecasting
• Neuroscience

Ideal Partner Description Examples: Finding Your Perfect Match

How Do You Answer What’s Your Ideal Partner?

What are the 3 things people look for in an ideal partner, what are 5 positive characteristics in a relationship, how do you write an ideal partner list, how to communicate your ideal partner list to potential partners.

• Kind-hearted
• Good communicator
• Sense of humor
• Similar interests
• Emotionally mature
• Open-minded
• Family-oriented
• Physically active
• Financially responsible

What Are the Types of Life Partners?

Exploring the concept of “opposites attract” when it comes to life partners and whether this is a beneficial or detrimental approach..

You Might Also Like

How To Comfort A Girl With Family Problems – In Less Than Five Minutes

He Said He Will Hurt Me – Step By Step

Is Sharing A Dessert Intimate – In Less Than 5 Minutes

She Led Me on and Wants to Be Friends: Navigating Mixed Signals

• Intermediate
• Academic Listening
• Life Stories
• Language Games
• English Idioms
• Basic English Quizzes
• English Culture Videos
• Vocabulary Lessons
• ESL Vocabulary Quizzes
• Live Broadcasts
• Who's Randall?
• Terms of Use
• Speaking Events
• License ESL-Lab Content
• First-Time Users
• Audio/Video Help
• Self-Study Guide
• ESL Study Handouts
• Randall's ESL Blog
• Randall’s Favorites
• Tips for Teachers
• Recommended Products
• Contact Randall
• DailyESL.com
• Trainyouraccent.com
• EZslang.com

General Listening Quiz

“the ideal woman”.

Pre-Listening Exercise

In a small group, describe the “ideal” partner for you. Think in terms of personality, educational and family background, socioeconomic level, job, and personal values and beliefs.

Listening Exercise

A. Listen to the recording and answer the questions.

The Ideal Woman

Rocky was _______ at the beginning of the conversation., rocky likes women who _____., in addition to eating, rocky feels his household chores include ____., rocky’s views on women _____., what probably happens at the end of the conversation, post-listening exercise.

• What is your image of the ideal partner? Record your own opinion focusing on such factors as appearance, personality, character, and interests. Share your recording with another student and have them respond to your opinion.
• How do other cultures view the concept of the “ideal” partner differently from your own? 
• Easy Listening
• Intermediate Listening
• Difficult Listening
• Academic English Listening

Standout Traits for a Great Partner Case Study (With Examples)

It’s no surprise that partner case studies are a wee bit of a struggle to produce. Getting your customers to agree to a case study is one thing; getting your customer and your partner to agree to a case study is a miracle. On top of the fact that the partnerships world is still such a gray area for partner managers everywhere (let alone their leadership), partner case studies in SaaS are a rare sighting in the wild (think: the bat-eared fox. Do you even know what that is? 😝) . 

So, think of this roundup as snapshots of the elusive partner case studies that lurk in the depths of the SaaS ecosystem — a co-marketing material still so new that, just maybe, by producing one of your own, you’ll be ahead of the curve already. 

Below, we offer some partner case study standout traits, followed by a collection of examples located in (butler voice) the gallery , and a checklist for rolling out your own case study program.

1. Wow your readers by placing the results in the title.

While the rest of your case study should give the reader context, the results are what matter most to your potential buyers and their leadership teams. So, put the results at the top! SugarCRM kicks off its case study with Kyloe Partners and Bullhorn by sharing how they doubled lead-gen campaigns while cutting 60% of their customer’s workload.

Our suggestion: if someone were to ask you “What is the most impressive part of this case study?”, what is the first thing you’d say? That’s your headline.

2. Make the metrics obvious. 

If your customer has observed more than one area of growth, that’s awesome. Draw the reader’s eyes right to the numbers. In Facebook’s case study with Zapier and Wicked Good Cupcakes , they placed their metrics in a standalone box that makes the numbers the most important information on the page.

Meanwhile, Acquia’s case study with Third and Grove and King Arthur Baking Company features their results point-blank in a standalone line that reads “Results.” (Say what?)

3. Define the customer’s use case or challenge. 

It’s likely that your customers can use your integration for multiple use cases, so be clear about what this particular customer’s use case is from the start. In Microsoft Azure’s case study with Sourced Group and a Canadian bank , they clearly list out the challenge, the solution, and the result in three brief columns.

They also dive deeper into the bank’s challenges with a numbered list.

4. Define the audience or market. 

Your customers will want to know how you’ve solved challenges they’re facing internally or that their customers may be facing. Make an easy connection for them by pointing out the specific audience or market the case study applies to. 

Greenlight Guru’s case study with Rook Quality Systems explicitly describes how RQS’s clientele of medical professionals informs RQS’s product investments. 

5. Get customer quotes.

Tableau’s case study with AWS and ride-hailing app FREE NOW includes quotes from FREE NOW’s Head of Analytics showing how indispensable Tableau has been, in tandem with AWS, for their team’s daily operations. 

Tip: Repurpose your customer quotes by including them on your website, in press releases, and even in your outbound sales outreach. 

6. Put the results in perspective: Include a timeframe. 

Growth metrics don’t mean anything if they’re not tied to a before and after. Include the exact timeframe your analysis fits into.

And yes, Facebook’s case study with Zapier and Wicked Good Cupcakes is, indeed, cupcake-themed!

7. Get partner quotes.

You have quotes from your shared customer, why not also include a quote from your partner? Partner quotes can be especially useful for agencies who want to prove the value of their services to their customers and software vendors.

Cisco’s case study with Matternet and Stratus Information Systems includes quotes from individuals from Stratus Information Systems and Matternet — each of whom found the other to be invaluable while implementing Cisco’s software. 

8. Add personal stories.

Including brief personal stories can give extra life to an otherwise data-heavy document (think: the people behind the products and, more specifically, the customer service that makes working with a SaaS company so customer-friendly).

SugarCRM’s case study with Kyloe Partners and Bullhorn shares a meet-cute-ish story detailing how Kyloe Partners’ co-founder and director and Bullhorn’s co-founder met back in the day (Can’t you just see it in a movie?). 

9. Show them the people behind the product. 

Did I mention a big part of SaaS is that last “S”? It’s all about the service.

Greenlight Guru’s  case study with Rook Quality Systems talks about how much RQS values the company because of its relationship with GG employees. 

10. Avoid the “wall of text” effect. 

Grab your designer (Hi, Nick !), and develop a creative way to organize the benefits or data you’re showcasing in the case study.

Braze’s case study with Segment, Amplitude, and IBM includes a graphic displaying their in-platform activities. 

And Acquia’s case study with Third and Grove and King Arthur Baking Company includes the stakeholders, situation, challenge, solution, and results neatly laid out — bringing the good stuff front and center. 

11. Create video content.

For an extra special case study, and if your customer’s on board for the extra time commitment, consider creating a video. 

ActiveCampaign’s case study with Salesforce and the Museum of Science and Industry, Chicago , includes a video at the top that dives into what the MSI team’s work days look like, the challenges they experience, and how the ActiveCampaign-Salesforce integration has helped them. 

If you’re curious, we picked apart ActiveCampaign’s entire co-marketing playbook for getting to #1 in Salesforce’s marketing automation AppExchange .

From ActiveCampaign’s case study with Salesforce and the Museum of Science and Industry, Chicago 

Sensyne includes a case study video on their website , existing outside of their official case study with Microsoft and Cognizant , explaining how they’ve deployed patient monitoring capabilities during COVID-19. 

From Cognizant’s case study with Microsoft and Sensyne Health (video case study on Sensyne Health’s website) 

12. Talk up your partners.

Include context about your partners, and talk them up. This case study should make you and your partner shine! 

Tip: Include your partner case studies on the customer success section of your website and your partner page . It’s not just your potential customers reading these case studies, it’s also your potential partners. 

Amazon Web Services’ case study with Deluxe Entertainment Services and Capgemini features a description of Deluxe Entertainment Services in a standalone section on the right.

13. Include a CTA.

‘Nuff said.

14. Create ancillary content that promotes your case studies. 

Braze’s article in their Perspectives magazine links directly to their case study with Segment , Amplitude , and IBM .

If you’re developing partner case studies for the first time, or if you want to give your existing case studies a second life, check out our partner case study gallery below to gander everything we’ve mentioned thus far in a big picture view .

Partner Case Study Gallery: 

And now, a collection of examples to help inspire your own work.

1. Facebook, Zapier, and Wicked Good Cupcakes

Read the case study .

2. Braze, Segment, Amplitude, and IBM

3. greenlight guru and rook quality systems, 4. sugarcrm, kyloe partners, and bullhorn.

Read the case study . 

5. WPengine, BCF Agency, and Orangetheory Fitness 

6. activecampaign, salesforce, and the museum of science and industry, chicago, 7. microsoft azure, sourced group, and a canadian bank, 8. cisco, matternet, and stratus information systems, 9. aws, deluxe entertainment services, and capgemini , 10. boomi and workiva.

This case study is a little different. In Dell Boomi’s case study with Workiva , they talk about how Workiva’s developers use Boomi to develop integrations for a variety of customers. 

11. Tableau Software, AWS, and FREE NOW 

12. acquia, third and grove, king arthur baking company, 13. cognizant, microsoft, and sensyne health, your partner case study checklist.

Great, you have the fundamentals. But what now? To rollout successful case studies you’ll need to make a few decisions: Considerations for planning your partner case study strategy: 

• Will you develop joint case studies with some of your early adopters before going live with a given integration? (hint: case studies like this can help strengthen your press release and make the case for other customers interested in adopting) 
• Which customers do you have the best relationship with, who may be interested in participating in a case study?
• Is it okay to reach out to the above customers, or will it cause friction in their relationship with your sales or marketing team? (e.g. your team has already sent that customer a number of asks in the past month. Enough is enough!) 
• Are there specific use cases you’re looking to amplify through the case study? (e.g. an increase in revenue vs. a better leads to opportunities rate) 
• Will your case studies be more like a blog post-like or a fact-sheet-like? (note: Braze publishes case studies in their magazine, Perspectives ) 
• Will you create video case studies in addition to written case studies (like Cognizant’s case study with Microsoft and Sensyne Health )? 
• How long will your case studies be? ( ActiveCampaign and Salesforce’s case study with Museum of Science and Industry is quite extensive while Acquia, Third and Grove, and King Arthur Baking Company’s case study spans a single page.

Considerations for distributing your partner case studies:

• Where will your case studies live? Will they be gated with the goal of lead-gen? Or will they be available to the public? (Tip: If you make your case studies publicly available, you may want to consider a “Download PDF” button anyway so readers can pass the case study along to their team, just like Microsoft Azure does) 
• Will your case studies exist as standalone, downloadable documents, as dedicated pages on your site, or another format entirely?
• Will you pull quotes or pieces of analysis from your case studies as previews for a case study homepage — or for elsewhere on your site/marketing materials? (You’ll want to let your customer know your plans ahead of time)
• Will you use your case studies in nurture sequences to drive engagement with your leads?
• Will your case studies be part of a bigger campaign with the participating partner ?

What makes a partner case study great? We called out the best attributes and developed a checklist for planning your case study strategy.

You Might Also Like

Your B2B SaaS Partner Page Checklist (with 50 Examples)

5 Signs Your Tech Partner's About to Get Acquired (And How to Prepare for Change)

This is a test comment.

This is a longer test comment to see how this looks if the person decides to ramble a bit. So they're rambling and rambling and then they even lorem ipsum.

Become an ELG Insider

ELG Insider is a not-so-secret club for driving revenue, growing your career, and staying ahead of the market with original research and analysis.

By checking this box you agree to the terms outlined in Crossbeam's Privacy Policy .

Something went wrong.

Thanks for subscribing!

Thanks for subscribing to ELG Insider, where you can enjoy the latest Ecosystem-Led Growth insights, analysis, and best practices all in one place. Plus, keep an eye on your inbox for new stories each week.

Check your email for a magic link to unlock all our exclusive content.

Need help? Email [email protected]

Magic Link Code Invalid

Please try signing in again.

Edit Profile

Successfully Updated Profile!

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Front Psychol
• PMC10019068

Singles' similarity preferences in an ideal partner: What, when, and why

1 Department of Education, Northeast Normal University, Changchun, Jilin, China

Yanyan Zhang

2 School of Philosophy and Sociology, Jilin University, Changchun, Jilin, China

Associated Data

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

This study investigated singles' similarity preferences concerning their ideal partner's personality traits, physical attractiveness, and social resources, as well as potential moderators (fear of being single and mate value) and mediators (forecasted satisfaction). With 1,014 Chinese singles, we found that singles preferred their ideal partner to share similarities in the HEXACO traits, physical attractiveness, and social resources, and they preferred higher similarity in Honesty–Humility and Openness to Experience. Fear of being single, mate value, and forecasted satisfaction did not affect similarity preferences concerning Honesty–Humility and Openness to Experience but had some mixed influence over similarity preferences for other features.

Introduction

In recent years, the topic of ideal partner preference has gained much attention from scholars (e.g., Thomas et al., 2020 ; Walter et al., 2020 ; Csajbók and Berkics, 2022 ). One line of studies primarily examined the similarity preferences for an ideal partner and have generally supported the idea that people prefer their ideal partner to be similar in many attributes, such as personality traits, attitudes, and affects. However, people with intimate relationships tend to adjust their ideal partner preferences based on the characteristics of their current partner (Fletcher et al., 2000 ; Overall et al., 2006 ). Liu et al. ( 2018b ) addressed this limitation by recruiting only singles when examining similarity preferences for personality traits in an ideal partner and found that the similarity preference was still held by singles. This study aims to extend the conclusions from Liu et al. ( 2018b ) to show that singles not only have similarity preferences for personality traits but also in physical attractiveness and social resources. In addition, this study explores potential moderators and mediators of such similarity preferences among singles.

Similarity preferences for ideal partner's features

It is well established that people prefer to have a similar partner from both theoretical and empirical perspectives. From an evolutionary perspective, having a similar partner can promote the passage of one's genes because when two parents share similarities, each parent can contribute more than 50% of their genetic material to their offspring (Thiessen et al., 1997 ). Niche construction theory indicates that having a similar partner can help people to form congenial and smooth relationships and to construct a desirable environment that fits their needs and facilitates their goals (Laland et al., 2001 ). From a psychological perspective, pairing with a similar partner is rewarding because similarity can satisfy one's demand for self-affirmation by validating their beliefs and values (Byrne and Clore, 1967 ) and because similarity can enhance mutual attraction between partners by fostering mutual liking (Condon and Crano, 1988 ). Besides the theoretical support, some empirical studies have also supported the importance of similarity between partners. For example, partners sharing similar personality traits and/or emotions tend to have more satisfying and stable relationships (Anderson et al., 2003 ; Luo and Klohnen, 2005 ; Gonzaga et al., 2007 ).

Given the importance of having a similar partner, people do depict their ideal partner based on their own characteristics. Past research has shown that people prefer their ideal partner to be similar to them in many aspects, including personality traits, physical attractiveness, attitudes, and values (Botwin et al., 1997 ; Figueredo et al., 2006 ; Dijkstra and Barelds, 2008 ; Watson et al., 2014 ). However, the relationship status of participants from these studies is either not clear or with some in relationships. Being in a relationship can influence one's ideal preference since people tend to adjust their ideal preference based on their current partner (Fletcher et al., 2000 ; Overall et al., 2006 ). Liu et al. ( 2018b ) addressed this issue by only recruiting singles and examining their ideal preference. They found that singles did prefer their ideal partner to share similar personality traits. But Liu et al. ( 2018b ) did not examine whether singles have similarity preferences regarding physical attractiveness and social resources. The current study aims to examine similarity preference among singles not only on personality traits but also on physical attractiveness and social resources. Based on prior literature, we hypothesize that singles prefer their ideal partner to be similar in personality traits, physical attractiveness, and social status (Hypothesis 1).

Previous research not only shows that people prefer their ideal partner to be similar on various attributes but also suggests that similarity preference is particularly pronounced for certain traits. Honesty-Humility and Openness to Experience (from here referred to as Openness) are two potential candidates (Liu et al., 2018b ; Liu and Ilmarinen, 2020 ). For example, Liu et al. ( 2018b ) reported that singles preferred their ideal partner to share a higher similarity in Honesty–Humility and Openness compared to the other HEXACO traits, with participants coming from across China, Denmark, Germany, and the USA. But Liu et al. ( 2018b ) did not examine singles' ideal partner preferences concerning physical attractiveness and social resources. Given that physical attractiveness and social resources are also important when depicting one's future partner as illustrated by ideal standards models, describing the ideal partner from three aspects, including physical attractiveness and social resources (Fletcher et al., 1999 ; Fletcher and Simpson, 2000 ), the relative importance of similarity preferences for these two features and personality traits is hard to judge. Some initial observations can be gleaned from studies examining the necessary attributes that people refuse to compromise on when choosing future partners. Li et al. ( 2002 ) found that both women and men considered kindness and intelligence as necessities compared to physical attractiveness (which men emphasized more) and social status (which women emphasized more). The two features—kindness and intelligence—nicely mirror some aspects of Honesty–Humility and Openness. Though Li et al. ( 2002 ) did not directly examine similarity preferences, their results that kindness and intelligence are prioritized over physical attractiveness and social status are likely to suggest the same when it comes to similarity preferences. Accordingly, we hypothesize that singles have a higher similarity preference concerning Honesty–Humility and Openness compared to the other HEXACO traits, physical attractiveness, and social resources (Hypothesis 2).

Moderators and mediators of similarity preferences in an ideal partner

Though it is well documented that singles prefer their ideal partner to be similar in many domains, the factors influencing such preferences remain largely unexplored. Liu and Ilmarinen ( 2020 ) tackled this issue by exploring the moderation effect of core self-evaluation (i.e., one's overall evaluation of oneself) on singles' similarity preferences in an ideal partner. They found that singles whose overall evaluation of themselves was high preferred their ideal partner to share a higher similarity in Emotionality, Extraversion, Agreeableness, and Conscientiousness, relative to singles whose overall evaluation of themselves was low, suggesting that higher similarity on these traits is deemed as more desirable and only people with more mate-attracting advantages can hope to achieve it. Liu and Ilmarinen ( 2020 ) also found that singles' similarity preferences for Honesty–Humility and Openness were not influenced by core self-evaluation, suggesting that similarity preferences for these two traits is less likely to be based on how one evaluates oneself.

In addition to core self-evaluation, other factors are likely to influence singles' similarity preferences in an ideal partner. In this study, we aim to explore not only moderators (i.e., fear of being single and mate value) but also mediators (i.e., forecasted satisfaction) of such preferences.

Fear of being single is defined as “concern, anxiety, or distress regarding the current or prospective experience of being without a romantic partner” (Spielmann et al., 2013 , p.1050). Spielmann et al. ( 2013 ) showed that people scoring high in fear of being single tend to have lower standards concerning their future partner and are less selective in expressing romantic interest at speed-dating events. Thus, people high in fear of being single might compromise more on their ideal standards.

Mate value describes one's value as a mate to a potential or actual partner (Landolt et al., 1995 ). Edlund and Sagarin ( 2010 ) found that people with high mate value tend to have higher standards when visualizing a future partner (e.g., the partner must be highly attractive, more humorous, livelier, and richer). Accordingly, people high in mate value might be more demanding concerning their ideal standards.

Overall, past research suggests that people low in fear of being single or high in mate value tend to have higher standards concerning their ideal partner. Relating to similarity preferences for personality traits, higher standards indicate higher similarity in Emotionality, Extraversion, Agreeableness, and Conscientiousness (Liu et al., 2018b ; Liu and Ilmarinen, 2020 ). Consequently, we hypothesize that fear of being single and mate value moderate similarity preferences for Emotionality, Extraversion, Agreeableness, and Conscientiousness in the way that people low in fear of being single or high in mate value have higher similarity preference for these traits (Hypothesis 3a). This also applies to physical attractiveness and social resources (Hypothesis 3b). Noticeably, Liu and Ilmarinen ( 2020 ) show that similarity preferences for Honesty–Humility and Openness were not affected by moderators. Accordingly, we hypothesize that both moderators had no influence over similarity preferences for Honesty–Humility and Openness (Hypothesis 4).

In addition to examining moderators, we also explore mediators of similarity preferences in an ideal partner. We propose that forecasted satisfaction might be one mediator. Forecasted satisfaction is defined as “anticipated fulfillment and pleasure associated with the relationship in the future” (Lemay, 2016 , p.35). Perhaps, people prefer a similar ideal partner due to the belief that they could have good relationships when being with such a partner (Fletcher et al., 2013 ). Therefore, we hypothesize that forecasted satisfaction mediates singles' similarity preferences for personality traits, physical attractiveness, and social resources (Hypothesis 5).

The current study

To recap, the current study aims to examine all these hypotheses by recruiting singles who are not currently involved in any kind of intimate relationship. We not only try to replicate previous studies where singles prefer their ideal partner to share similarities concerning personality traits, and such similarity preferences are most pronounced in Honesty–Humility and Openness, but also aim to extend previous studies by examining singles' similarity preferences for physical attractiveness and social resources, determining the relative importance of similarity preferences for these two features and Honesty–Humility and Openness. In addition, we explore two moderators (fear of being single and mate value) and one mediator (forecast relationship satisfaction) of similarity preferences.

Participants and procedure

Singles were recruited from advertisements posted on online social media platforms (e.g., WeChat). Participants were informed that the study would involve participating in an online survey about personality and ideal partner preference. Participants took part in this study voluntarily without monetary compensation but with personalized personality feedback. A total of 1566 participants started our survey and 1078 completed it. Sixty-four participants were deleted because of their patterned response (i.e., reporting 1 or 5 for all personality items). The final sample comprised 1014 participants (81% female), aged between 18 and 46 ( M = 20.8, SD = 2.75).

Personality

The personality of participants was assessed with the 60-item HEXACO Personality Inventory–Revised (Ashton and Lee, 2009 ). One sample item is “I would be quite bored by a visit to an art gallery.” These items were answered with a 5-point Likert scale ranging from 1 ( strongly disagree ) to 5 ( strongly agree ). The personality of the ideal partner was measured by an adapted version of the HEXACO inventory about oneself by replacing the first-person pronoun with “my ideal partner” and making grammatical changes only when necessary. Corresponding to the earlier sample item in the measures concerning self-evaluation, the sample item in the ideal partner version is “My ideal partner would be quite bored by a visit to an art gallery.”

Physical attractiveness

The physical attractiveness of a participant and their ideal partner was assessed by the vitality–attractiveness dimension from Fletcher et al. ( 1999 ). Six descriptions are used, including “nice body” and “attractive.” Participants were instructed to describe their self-perceived physical attractiveness and their ideal partner's physical attractiveness based on these descriptions with a 5-point Likert scale ranging from 1 ( strongly disagree ) to 5 ( strongly agree ).

Social status

The social status of participants and their ideal partner was assessed by the status–resources dimension identified by Fletcher et al. ( 1999 ). Five descriptions 1 are used, including “good job” and “financially secure.” Participants were instructed to describe themselves and their ideal partner based on these descriptions with a 5-point Likert scale ranging from 1 ( strongly disagree ) to 5 ( strongly agree ).

Fear of being single

Fear of being single was measured by a scale from Spielmann et al. ( 2013 ) and was answered on a 9-point Likert scale (1 = strongly disagree , 9 = strongly agree ). One sample item is, “It scares me to think that there might not be anyone out there for me.”

Participants reported their self-perceived mate value by three items from Landolt et al. ( 1995 ). These items include “Men/women notice me” and “Men/women feel attracted to me.” They were measured on a 9-point Likert scale (1 = strongly disagree , 9 = strongly agree ).

Forecasted satisfaction

Forecasted satisfaction was measured by an adapted version of the satisfaction scale from Rusbult et al. ( 1998 ) and was answered on a 9-point Likert scale (1 = strongly disagree , 9 = strongly agree ). One sample item is “With my ideal partner, our relationship is much better than others' relationships.” An overview of all assessments, datasets, and analyses can be found at https://osf.io/xemyj/ .

Similarity preference

Table 1 presents the correlations of our main variables. The correlations between self and ideal partner HEXACO traits, physical attractiveness, and social resources ranged from 0.17 to 0.61 ( ps < 0.001), indicating the existence of similarity preferences. These results remain unchanged after controlling for age and sex (refer to Table 2 ). Thus, Hypothesis 1, that singles prefer their ideal partner to share similarities in HEXACO traits, physical attractiveness, and social resources, is supported.

Descriptive statistics and correlations for main variables.

S, Self-evaluation of personality; HH, Honesty–Humility; EM, Emotionality; EX, Extraversion; AG, Agreeableness; CO, Conscientiousness; OP, Openness to Experience; PA, physical attractiveness; SR, social resources; P, ideal partner report personality; FoS, fear of being single; MA, mate value; FS, forecasted satisfaction. Reliabilities are printed in a diagonal line.

Partial similarity preference and higher similarity preference for Honesty–Humility and Openness to Experience.

Next, we examine Hypothesis 2, that similarity preference for Honesty–Humility and Openness is more important than the other features, by comparing the correlations of these two traits with that of the other features (Liu et al., 2018b ). Specifically, we used the method of comparing two non-overlapping correlations from the same group via the cocor package in R (Diedenhofen and Musch, 2015 ). This method is appropriate because all correlations (e.g., the correlation between self-ratings and ideal partner ratings for Honesty–Humility and the respective correlation for Agreeableness) were from the same participants but shared no common variables (e.g., there is no overlap in the items assessing Honesty–Humility and Agreeableness, respectively). Age and sex were also controlled in these comparisons. The results show that the similarity preference is higher for Honesty–Humility and Openness not only relative to the other HEXACO traits but also to physical attractiveness and social resources (7.37 ≤ z ≤ 11.82, ps < 0.001; refer to Table 2 ) supporting Hypothesis 2.

Fear of being single and mate value as moderators

We examine Hypotheses 3a and 3b, using linear regressions, that fear of being single and mate value moderate similarity preferences for Emotionality, Extraversion, Agreeableness, Conscientiousness, physical attractiveness, and social resources. For each moderator, six regression models were performed with each of the features of self (e.g., self-Emotionality), the moderator (e.g., fear of being single), the interaction (e.g., Emotionality * fear of being single), and control variables (i.e., age and gender) as predictors, and the corresponding feature of ideal partner (e.g., ideal partner's Emotionality) as an outcome. The results show that fear of being single moderated similarity preference for Agreeableness and social resources but not on the other characteristics (Refer to Table 3 ). Simple effects show that singles high in fear of being single showed lower similarity preferences for Agreeableness ( b = 0.21, β = 0.24, t = 5.90, p < 0.001) and social resources ( b = 0.10, β = 0.11, t = 2.80, p = 0.005) compared to singles low in fear of being single ( b = 0.32, β = 0.37, t = 8.90, p < 0.001 for Agreeableness; b = 0.23, β = 0.25, t = 6.26, p < 0.001 for social resources; refer to Figures 1 , ​ ,2 2 ).

Moderation effects of fear of being single and mate value on HEXACO traits, physical attractiveness, and social resources.

S, Self-evaluation of personality; HH, Honesty–Humility; EM, Emotionality; EX, Extraversion; AG, Agreeableness; CO, Conscientiousness; OP, Openness to Experience; PA, physical attractiveness; SR, social resources; P, ideal partner report personality. Moderator refers to the fear of being single or mate value.

The moderation effect of fear of being single of agreeableness. AG, Agreeableness.

The moderation effect of fear of being single of agreeableness. SR, Social resources.

Mate value moderated similarity preferences for Extraversion Conscientiousness, physical attractiveness, and social resources. Simple effects indicate that singles scoring high in mate value have higher similarity preference for Extraversion ( b = 0.23, β = 0.32, t = 7.09, p < 0.001), Conscientiousness ( b = 0.27, β = 0.31, t = 7.63, p < 0.001), physical attractiveness ( b = 0.29, β = 0.36, t = 8.29, p < 0.001), and social resources ( b = 0.23, β = 0.25, t = 6.27, p < 0.001), relative to their counterparts low in mate value ( b = 0.07, β = 0.09, t = 2.28, p = 0.023 for Extraversion; b = 0.17, β = 0.19, t = 4.87, p < 0.001 for Conscientiousness; b = 0.14, β = 0.17, t = 3.73, p < 0.001 for physical attractiveness, and b = 0.04, β = 0.05, t = 1.18, p = 0.240 for social resources; Refer to Figures 3 – 6 ). These results partially supported Hypotheses 3a and 3b.

The moderation effect of mate value on similarity preference on extraversion. EX, Extraversion.

The moderation effect of mate value on similarity preference on social resources. SR, Social resources.

The moderation effect of mate value on similarity preference on conscientiousness. CO, Conscientiousness.

The moderation effect of mate value on similarity preference on physical attractiveness. PA, physical attractiveness.

We then examine Hypothesis 4 that fear of being single and mate value have no impact over similarity preference for Honesty–Humility and Openness. Results from Table 3 show that these moderators did not influence similarity preference for Honesty–Humility and Openness, supporting Hypothesis 4.

Forecasted satisfaction as a mediator

Hypothesis 5 forecasted that satisfaction may explain the similarity preferences that singles have in their ideal partner, which was examined with mediation models. These mediation models were performed with the Mediation package in R (Tingley et al., 2014 ). The indirect effect of forecasted satisfaction was significant for similarity preference for Extraversion (β = 0.03, 95% CI [0.01, 0.04]), Conscientiousness (β = 0.01, 95% CI [0, 0.03]), physical attractiveness (β = 0.04, 95% CI [0.02, 0.06]), and social resources (β = 0.04, 95% CI [0.02, 0.06]), indicating that the similarity preferences for these features can be partially explained by forecasted satisfaction, partially supporting Hypothesis 5.

This study examined singles' similarity preferences regarding ideal partner's personality traits, physical attractiveness, and social resources, and we found that singles had similarity preferences for all features, most pronounced in Honesty–Humility and Openness. In addition, we examined the moderation effect of fear of being single and mate value on similarity preference, and the results indicated that neither of these two moderators influenced individuals' preferences for Honesty-Humility and Openness. However, both of the moderators affected similarity preferences for some other features. Specifically, fear of being single moderated similarity preference for Agreeableness and social resources, indicating that singles low in fear of being single preferred their ideal partner to share higher similarity in both features; mate value moderated similarity preference for Extraversion, Conscientiousness, physical attractiveness, and social resources, indicating that singles high in mate value preferred their ideal partner to share higher similarity on these features. Finally, we examined the mediation effect of forecasted satisfaction on similarity preferences and found forecasted satisfaction mediated similarity preference for Extraversion, Conscientiousness, physical attractiveness, and social resources, indicating that expecting a good relationship in the future partially explained why people prefer similarity in these features with an ideal partner.

The results that singles prefer their ideal partner to share similarities in all the HEXACO traits perfectly mirror the conclusion from previous studies (Liu et al., 2018b ; Liu and Ilmarinen, 2020 ). In addition, our results show that similarity preferences are present for physical attractiveness and social resources. Resonating suggestions from Almeida ( 2004 ) that people have principles when choosing a romantic partner, our results reflect that similarity between individuals and their ideal partner is one important principle concerning ideal criteria. However, even though it is critical for one to depict a similar partner in a hypothetical way, results from examining established couples have provided a quite mixed picture. Some studies show that couples indeed share similarities with each other (e.g., Watson et al., 2000 ; McCrae et al., 2008 ; Leikas et al., 2018 ), whereas other studies suggest the opposite (e.g., Watson et al., 2014 ; Liu et al., 2018a , 2022 ). The seemingly paradoxical phenomenon might be explained by the complication of real-life partner choice. This is because, except for ideal partner preference, there might be some other factors influencing one's actual partner choice, such as the availability of potential partners, family interference, and pursued relationship types. For example, when there are few potential partners available, people are very likely to settle down with partners that do not quite resemble themselves. Future studies could examine how these factors influence similarity preferences in an ideal partner and the relative importance of these factors together with similarity preference when visualizing one's potential future partner.

Furthermore, we found that the similarity preferences were particularly strong for Honesty–Humility and Openness compared to the other four HEXACO traits, which perfectly replicate results from Liu et al. ( 2018b ). Broadly speaking, similarities in Honesty–Humility and Openness can be explained by their close associations with personal values, and people expect to have close relationships with someone who shares their values (Lee et al., 2009 ). More related to intimate relationships, the emphasis on similarity in Honesty–Humility and Openness might be due to their association with relationship satisfaction and commitment, and people tend to believe that similarity in these two traits is beneficial to relationships (Liu et al., 2022 ). Furthermore, singles' similarity preferences for Honesty–Humility and Openness outweigh physical attractiveness and social resources, suggesting similarity is more important in key personality traits than more socially desirable features. Future research could use other methods to examine this idea. For example, researchers can use the budget allocation paradigm (e.g., Li et al., 2002 ) to ask participants to allocate a limited amount of money to indicate similarity preference for HEXACO traits, physical attractiveness, and social resources and observe what feature people allocate the largest portion of the money. Furthermore, it is unclear how individuals make a trade-off between competing preferences such as preference for similarity in certain traits and preference for an absolute level of various characteristics, such as physical attractiveness. Actually, similarity in personality in established heterosexual couples tends to be quite low, even in Honesty–Humility and Openness (Liu et al., 2018a , 2022 ). Accordingly, people may trade the similarity of these two traits with other individual features when choosing a real-life partner. It would be interesting to examine whether men tend to trade similarities in Honesty–Humility and Openness with physical attractiveness while women trade similarities in these two traits with social resources, as men and women are shown to emphasize different aspects in their future partner from evolutionary perspectives (Buss, 1989 ). Future studies could further explore these issues.

Though Liu et al. ( 2022 ) found that similarity in Honesty–Humility and Openness in intimate couples from China tends to be quite low, a recent study by Kandler et al. ( 2019 ) has shown the opposite. Indeed, Kandler et al. ( 2019 ) found that their participants, 228 German couples, presented quite a high similarity in Honesty–Humility ( r =0.225) and Openness ( r =0.277). Therefore, similarities in Honesty–Humility and Openness might be different depending on different relationship types (e.g., married vs. unmarried) and different cultures (e.g., collectivism vs. individualism). For example, it is possible that similarities in Honesty–Humility and Openness in married couples is more significant than in unmarried intimate couples. Future studies could further explore these possibilities.

We found that similarity preferences for Honesty–Humility and Openness was not moderated by fear of being single, and mate value also indirectly reflects the particular importance of similarity in these two traits. These results nicely echo the conclusion from Liu and Ilmarinen ( 2020 ) that similarity preferences for these two traits was not moderated by core self-evaluation. Together, these results indicate that singles' similarity preferences for Honesty–Humility and Openness are quite strong and immune from potential moderators relating to individual differences. Future research could examine whether social factors, such as the availability of potential partners and relational factors, such as relationship types (e.g., long-term vs. short-term relationships), have an influence on similarity preferences for these two traits.

The moderation hypotheses are only partially supported. Fear of being single and mate value had mixed moderation effects on Extraversion, Agreeableness, Conscientiousness, physical attractiveness, and social resources, but overall they suggest that people low in fear of being single or high in mate value are more demanding concerning similarity preferences in an ideal partner. These results not only echoed the results from Liu and Ilmarinen ( 2020 ) that people with high self-evaluation tend to have high ideal standards but also confirmed that some personality traits (e.g., Extraversion, Agreeableness, and Conscientiousness) are more socially desirable.

The mediation effects of forecasted satisfaction were only supported by similarity preference for Extraversion, Conscientiousness, physical attractiveness, and social resources, indicating that expecting a satisfying relationship in the future is the reason why singles prefer a similar partner. This actually mirrors the main idea of niche construction theory that people are motivated to build an environment that is congenial, fluent, and low in conflict (Laland et al., 2001 ). In the setting of an intimate relationship, our study shows that the reason why people initially prefer to have a similar partner is because they presume that such a partner can help to form a satisfying relationship in the future. For example, if Sally is high in Extraversion, she would like to have a partner who is high in Extraversion; this is because she could easily imagine a happy relationship with such a partner, not only more pleasures and joys (e.g., going to parties together) but also fewer disagreements and conflicts (e.g., negotiating being alone vs. socially active) in future. However, since the partial mediation models suggest the existence of other mediators, future research could explore other potential mediators, such as intimacy, responsiveness, and commitment.

The current study also has some limitations. First, most participants in our study were female, which may prevent us from generalizing our conclusions to more gender-balanced samples. Future research should strive for a gender-balanced sample to further examine this topic. Second, our participants are relatively young, meaning our study is limited in its representation of older individuals. Future research could explore whether older singles still exhibit the same patterns. Third, we mainly used the method where a participant only reports information about themselves to collect our data. Accordingly, our results might be affected by some response biases, such as acquiescence response style, social desirability bias, and self-enhancement bias. For example, self-rated physical attractiveness might not be that objective due to self-enhancement bias, and people are likely to think of themselves as more attractive than they actually are (Epley and Whitchurch, 2008 ). Future researchers could combine self-rated and other-rated methods to measure these variables in a more comprehensive and objective way to further test these hypotheses. Finally, though the moderation and mediation effects in our study add some important insights to the current literature concerning similarity preference in an ideal partner, they are only partially supported. Future research could continue examining these moderation and mediation effects to further test their robustness.

Overall, this study examined singles' similarity preferences concerning their ideal partner's personality traits, physical attractiveness, and social resources, as well as potential moderators (fear of being single and mate value) and mediators (forecasted satisfaction). Our results show that singles had similarity preferences in their ideal partner for the HEXACO traits, physical attractiveness, and social resources. This preference was higher for Honesty–Humility and Openness to Experience relative to the other features. In addition, fear of being single, mate value, and forecasted satisfaction did not affect similarity preference for Honesty–Humility and Openness to Experience but had some mixed influence over similarity preferences for other features.

Data availability statement

Ethics statement.

The studies involving human participants were reviewed and approved by IRB Board, Department of Psychology, School of Philosophy and Sociology, Jilin University. The patients/participants provided their written informed consent to participate in this study.

Author contributions

JL prepared the manuscript and performed the analyses. JL and YZ helped in interpreting the results and editing the manuscript. All authors contributed to the article and approved the submitted version.

Funding Statement

The work of YZ was supported by the National Social Science Fund of China (No. 22ASH016).

1 The original status–resources dimension has six descriptions, with “appropriate ethnicity” included. We excluded this one because it is not meaningful in China.

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.

• Almeida T. (2004). A gênese e a escolha no amor romântico: alguns princípios regentes . Revista de Psicologia (Fortaleza) 22 , 15–22. Available online at: http://www.repositorio.ufc.br/handle/riufc/12765 [ Google Scholar ]
• Anderson C., Keltner D., John O. P. (2003). Emotional convergence between people over time . J. Personal. Soc. Psychol. 84 , 1054–1068. 10.1037/0022-3514.84.5.1054 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Ashton M., Lee K. (2009). The HEXACO-60: A short measure of the major dimensions of personality . J. Personal. Assess. 91 , 340–345. 10.1080/00223890902935878 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Botwin M. D., Buss D. M., Shackelford T. K. (1997). Personality and mate preferences: five factors in mate selection and marital satisfaction . J. Personal. 65 , 107–136. 10.1111/j.1467-6494.1997.tb00531.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Buss D. M. (1989). Sex differences in human mate preferences: Evolutionary hypotheses tested in 37 cultures . Behav. Brain Sci. 12 , 1. 10.1017/S0140525X00023992 [ CrossRef ] [ Google Scholar ]
• Byrne D., Clore G. L. (1967). Effectance arousal and attraction . J. Personal. Soc. Psychol. 6 , 1–18. 10.1037/h0024829 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Condon J. W., Crano W. D. (1988). Inferred evaluation and the relation between attitude similarity and interpersonal attraction . J. Personal. Soc. Psychol. 54 , 789–797. 10.1037/0022-3514.54.5.789 [ CrossRef ] [ Google Scholar ]
• Csajbók Z., Berkics M. (2022). Seven deadly sins of potential romantic partners: the dealbreakers of mate choice . Personal. Individ. Differen. 186 , 111334. 10.1016/j.paid.2021.111334 [ CrossRef ] [ Google Scholar ]
• Diedenhofen B., Musch J. (2015). cocor: A comprehensive solution for the statistical comparison of correlations . PLoS One 10 , e0121945. 10.1371/journal.pone.0121945 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Dijkstra P., Barelds D. P. (2008). Do people know what they want: a similar or complementary partner? Evol. Psychol. 6 , 595–602. 10.1177/147470490800600406 [ CrossRef ] [ Google Scholar ]
• Edlund J. E., Sagarin B. J. (2010). Mate value and mate preferences: an investigation into decisions made with and without constraints . Personal. Individ. Differen. 49 , 835–839. 10.1016/j.paid.2010.07.004 [ CrossRef ] [ Google Scholar ]
• Epley N., Whitchurch E. (2008). Mirror, mirror on the wall: enhancement in self-recognition . Personal. Soc. Psychol. Bull. 34 , 11591170. 10.1177/0146167208318601 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Figueredo A. J., Sefcek J. A., Jones D. N. (2006). The ideal romantic partner personality . Personal. Individ. Differen. 41 , 431–441. 10.1016/j.paid.2006.02.004 [ CrossRef ] [ Google Scholar ]
• Fletcher G. J. O., Simpson J. A. (2000). Ideal standards in close relationships: their structure and functions . Curr. Direct. Psychologic. Sci. 9 , 102–105. 10.1111/1467-8721.00070 [ CrossRef ] [ Google Scholar ]
• Fletcher G. J. O., Simpson J. A., Campbell L., Overall N. C. (2013). The Science of Intimate Relationships . Malden, MA: Wiley-Blackwell. [ Google Scholar ]
• Fletcher G. J. O., Simpson J. A., Thomas G. (2000). Ideals, perceptions, and evaluations in early relationship development . J. Personal. Soc. Psychol. 79 , 933–940. 10.1037/0022-3514.79.6.933 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Fletcher G. J. O., Simpson J. A., Thomas G., Giles L. (1999). Ideals in intimate relationships . J. Personal. Soc. Psychol. 76 , 72–89. 10.1037/0022-3514.76.1.72 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Gonzaga G. C., Campos B., Bradbury T. (2007). Similarity, convergence, and relationship satisfaction in dating and married couples . J. Personal. Soc. Psychol. 93 , 34–48. 10.1037/0022-3514.93.1.34 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kandler C., Richter J., Zapko-Willmes A. (2019). The nature and nurture of HEXACO personality trait differences . Zeitschrift für Psychologie 227 , 195–206. 10.1027/2151-2604/a000378 [ CrossRef ] [ Google Scholar ]
• Laland K. N., Odling-Smee J., Feldman M. W. (2001). Cultural niche construction and human evolution . Journal of Evolutionary Biology 14 , 22–33. 10.1046/j.1420-9101.2001.00262.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Landolt M. A., Lalumière M. L., Quinsey V. L. (1995). Sex differences in intra-sex variations in human mating tactics: an evolutionary approach . Ethol. Sociobiol. 16 , 3–23. 10.1016/0162-3095(94)00012-V [ CrossRef ] [ Google Scholar ]
• Lee K., Ashton M. C., Pozzebon J. A., Visser B. A., Bourdage J. S., Ogunfowora B. (2009). Similarity and assumed similarity in personality reports of wellacquainted persons . J. Personal. Soc. Psychol. 96 , 460–472. 10.1037/a0014059 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Leikas S., Ilmarinen V.-J., Verkasalo M., Vartiainen H.-L., Lonnqvist J.-E. (2018). Relationship satisfaction and similarity of personality traits, personal values, and attitudes . Personal. Individ. Differen. 123 , 191–198. 10.1016/j.paid.2017.11.024 [ CrossRef ] [ Google Scholar ]
• Lemay E. P. (2016). The forecast model of relationship commitment . J. Personal. Soc. Psychol. 111 , 34–52. 10.1037/pspi0000052 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Li N. P., Bailey J. M., Kenrick D. T., Linsenmeier J. A. W. (2002). The necessities and luxuries of mate preferences: testing the tradeoffs . Journal of Personality and Social Psychology 82 , 947–955. 10.1037/0022-3514.82.6.947 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Liu J., Ilmarinen V.-J. (2020). Core self-evaluation moderates distinctive similarity preference in ideal partner's personality . J. Res. Personal. 84 , 103899. 10.1016/j.jrp.2019.103899 [ CrossRef ] [ Google Scholar ]
• Liu J., Ilmarinen V.-J., Lehane C. (2022). Seeing you in me: Moderating role of relationship satisfaction and commitment on assumed similarity in honesty-humility and openness to experience . J. Res. Personal. 97 , 104209. 10.1016/j.jrp.2022.104209 [ CrossRef ] [ Google Scholar ]
• Liu J., Ludeke S., Haubrich J., Gondan-Rochon M., Zettler I. (2018b). Similar to and/or better than oneself? Singles' ideal partner personality descriptions. Euro. J. Personal. 32 , 443–458. 10.1002/per.2159 [ CrossRef ] [ Google Scholar ]
• Liu J., Ludeke S., Zettler I. (2018a). Assumed similarity in personality within intimate relationships . Personal Relationships 25 , 316–329. 10.1111/pere.12246 [ CrossRef ] [ Google Scholar ]
• Luo S., Klohnen E. C. (2005). Assortative mating and marital quality in newlyweds: a couple-centered approach . J. Personal. Soc. Psychol. 88 , 304–326. 10.1037/0022-3514.88.2.304 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• McCrae R. R., Martin T. A., Hrebíckov'a M., Urb'anek T., Boomsma D. I., Willemsen G., et al.. (2008). Personality trait similarity between spouses in four cultures . J. Personal. 76 , 1137–1164. 10.1111/j.1467-6494.2008.00517.x [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Overall N. C., Fletcher G. J. O., Simpson J. A. (2006). Regulation processes in intimate relationships: the role of ideal standards . J. Personal. Soc. Psychol. 91 , 662–685. 10.1037/0022-3514.91.4.662 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Rusbult C. E., Martz J. M., Agnew C. R. (1998). The investment model scale: Measuring commitment level, satisfaction level, quality of alternatives, and investment size . Personal Relationships 5 , 357–387. 10.1111/j.1475-6811.1998.tb00177.x [ CrossRef ] [ Google Scholar ]
• Spielmann S. S., MacDonald G., Maxwell J. A., Joel S., Peragine D., Muise A., et al.. (2013). Settling for less out of fear of being single . J. Person. Soc. Psychol. 105 , 1049–1073. 10.1037/a0034628 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Thiessen D., Young R. K., Delgado M. (1997). Social pressures for assortative mating . Personal. Individ. Differen. 22 , 157–164. 10.1016/S0191-8869(96)00181-X [ CrossRef ] [ Google Scholar ]
• Thomas A. G., Jonason P. K., Blackburn J. D., Kennair L. E. O., Lowe R., Malouff J., et al.. (2020). Mate preference priorities in the East and West: a cross-cultural test of the mate preference priority model . J. Personal. 88 , 606–620. 10.1111/jopy.12514 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Tingley D., Yamamoto T., Hirose K., Keele L., Imai K. (2014). Mediation: R package for causal mediation analysis . J. Statistic. Softw. 59 , 1–38. 10.18637/jss.v059.i05 [ CrossRef ] [ Google Scholar ]
• Walter K. V., Conroy-Beam D., Buss D. M., Asao K., Sorokowska A., Sorokowski P., et al.. (2020). Sex differences in mate preferences across 45 countries: a large-scale replication . Psychologic. Sci. 31 , 408–423. 10.1177/0956797620904154 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Watson D., Beer A., McDade-Montez E. (2014). The role of active assortment in spousal similarity: active assortment and spousal similarity . J. Personal. 82 , 116–129. 10.1111/jopy.12039 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Watson D., Hubbard B., Wiese D. (2000). Self–other agreement in personality and affectivity: the role of acquaintanceship, trait visibility, and assumed similarity . J. Personal. Soc. Psychol. 78 , 546–558. 10.1037/0022-3514.78.3.546 [ PubMed ] [ CrossRef ] [ Google Scholar ]

• Español – América Latina
• Português – Brasil

Brainly: Democratizing education by giving students worldwide access to expert study help, 24/7

About Brainly

When they’re stuck on a problem, more than 350 million students and parents turn to Brainly. The Kraków-based technology company democratizes education with a collaborative online learning platform where students can ask questions and get answers instantly. Parents can link their accounts to the ones of their kids. Today, Brainly is supported in multiple languages in more than 35 countries.

Tell us your challenge. We're here to help.

Using vision ai, brainly built a “snap to solve” feature for mobile that helps students find answers via photo queries, achieving a 70% satisfaction rate while increasing paid subscription numbers., google cloud results.

• Bolsters user engagement with intuitive photo query feature for smartphones, achieving 6x more engagement than traditional typed queries
• Supports students in different languages across 35 countries with multilingual capabilities of Google Vision AI
• Increases revenues, boosting paid subscription numbers, thanks to high satisfaction with “Snap to Solve” searches
• Enables 10x increase in instant answers to queries by improving machine learning algorithms with TensorFlow
• Ensures stable service even during record peaks thanks to automatic scaling to the demand with Google Cloud

70% of users happy with “Snap to Solve” search results

In education, technology is a game changer. With the world at their fingertips, the students have become the masters. But while tech is changing the way we learn, it’s not a silver bullet. Classrooms are constantly evolving, and teachers are using smart technology to drive engagement or personalize learning plans. However, not all learning happens in the classroom. When students are doing their homework or studying for exams, there’s not always someone around to ask for advice. Enter Brainly .

For more than 350 million students, teachers and parents worldwide, Brainly is the place they go to when there’s a problem they can’t solve by themselves. The knowledge-sharing community crowdsources answers to any question, helping students tackle their toughest assignments with expert guidance, 24/7. Parents can create their own accounts to follow their kids’ educational progress and help them find the right answers.

Brainly was founded in 2009, long before COVID-19 swept the globe and forced students and teachers to rediscover what it means to learn and teach without a classroom. In this new world, Brainly’s services suddenly became even more popular than ever before.

“The pandemic has been tough on all of us, but in many ways, students were the ones who were left behind,” explains Bill Salak, CTO at Brainly. “That’s why students turned to our platform in record numbers. This didn’t just challenge us in terms of the sheer traffic, but also made us think about features to help our students get back on track with their education.”

“The kinds of problems students encounter are pretty similar around the world, but we need to make sure that we can solve them in multiple languages. Other AI solutions we looked at focused mainly on English and a few additional languages, whereas Vision AI enables us to support our students in the language they prefer. That’s why Google Cloud was the right choice for us.”

Mobile learning done right with Vision AI

Students increasingly use their mobile devices to help them learn and access support, but queries on a smartphone are more cumbersome than simple desktop searches. That’s why the Brainly team came up with its Snap to Solve feature: instead of typing in questions manually, students can simply take a photo of them with the Brainly app and select from a set of relevant answers from the Brainly database.

Because Brainly is active in 35 countries, every new solution needs to cover a variety of languages and work natively in all of them. Besides scalability, performance, accuracy, and price, the multilingual capabilities of Google Cloud made the Vision AI platform a perfect fit for Brainly.

“The kinds of problems students encounter are pretty similar around the world, but we need to make sure that we can solve them in multiple languages,” explains Gabriel Habryn, Domain Lead at Brainly. “Other AI solutions we looked at focused mainly on English and a few additional languages, whereas Vision AI enables us to support our students in the language they prefer. That’s why Google Cloud was the right choice for us.”

“At launch, only a small percentage of queries delivered an instant answer in the US region. By improving our machine learning algorithms with TensorFlow, we’re achieving ten times more, and that number is growing. More than 70% of our users are very happy with the results they’re getting, which is even higher than for text queries.”

Answers within seconds, in two languages

With help from Brainly’s Snap to Solve feature, students and parents can tackle any written question, but also math problems. Here’s how it works: with the Brainly app, users simply snap a photo of the question, and Vision AI’s optical character recognition (OCR) analyzes the image’s content to extract words and sentences. If there’s a perfect match for the query, Brainly delivers an instant answer within seconds, if not, the app falls back to a full text search, combing through Brainly’s entire knowledge base to find a selection of relevant answers.

Snap to Solve is a hit with students. They love its convenience and the fact that they no longer have to type in questions manually on their phones. “As soon as we introduced the Snap to Solve solution, we experienced a huge shift from typed queries to photos,” says Grzegorz Kućma, Senior Manager, Mobile at Brainly. “Today, we’re observing engagement that’s significantly higher for photo queries compared to text queries.”

High accuracy, high satisfaction

Brainly is constantly optimizing its search algorithms and machine learning models, but the progress has already been astounding. Using TensorFlow ’s Multilingual Universal Sentence Encoder, the team developed an in-house solution to find instant answers for queries. “At launch, only a small percentage of queries delivered an instant answer in the US region,” says Kućma. “By improving our machine learning algorithms with Tensorflow, we’re achieving ten times more, and that number is growing. More than 70% of our users are very happy with the results they’re getting, which is even higher than for text queries.”

While Brainly’s services can be used for free, there’s a Brainly Plus subscription that gives users an ad-free experience and access to all answers and more. The happier students are with the Snap to Solve results, the more likely they are to use it, explains Kućma: “We’ve observed that users who received instant answers are more likely to buy our subscription, because they see the value of our product. The better our solution, the better we can monetize our services.”

And photo searches aren’t Brainly’s only novelty. While Snap to Solve queries are the most popular way to find answers, voice search is also gathering steam. Using Android’s speech to text features, the Brainly app can deliver answers to audio queries as well, giving students another way to avoid typed queries. “While Snap to Solve is definitely going to be the most popular way of searching in the future, audio queries may overtake and replace regular typed searches,” says Kućma. “With Google Cloud, we can deliver excellent quality on both.”

Scaling to the needs of students

When COVID-19 closed down classrooms around the world, Brainly quickly gained tens of millions of new users. Meanwhile, existing students were more dependent on the platform than ever before, leading to peaks in traffic. Thanks to the scalability of Google Cloud, the team didn’t need to worry about availability and performance issues.

“During the pandemic, we really had to raise the quota to meet the demand,” says Habryn. “Because Google Vision scales to our needs automatically, there was no technical effort necessary from our side. Even during record peaks, we were able to focus on improving our solution, rather than make sure that it’s working.”

Scaling up resources is also a cost question, and the flexibility of Google Cloud helps Brainly make better spending decisions in line with the company’s budget. For example, Android enables online OCR processing while ML Kit enables this offline, the latter being more cost-efficient. “Scaling up generates more cost, and the ability to switch between the online and offline OCR solution gives us an additional opportunity to control costs,” says Michał Leszek, Director of Information Technology and Data Protection Officer at Brainly.

“Everyone who’s ever been to school knows what it’s like to be stuck on a problem you just can’t solve, but not everyone has the same resources to get the right help. At Brainly, we’re using Google Cloud technology to build a solution that democratizes access to education and helps students who often get left behind.”

Democratizing education with Google Cloud

Students worldwide already love Brainly’s new Snap to Solve capabilities, but the team is constantly thinking about ways to make it even better. In the future, it might recognize handwriting as well, which is supported by Vision AI. Because every language is different, developers at Brainly also work hard to optimize text recognition in different languages.

Much like its users, Brainly will never stop learning. But every new answer, every new feature, and every gain in accuracy is in service of a larger goal: democratizing education. “Everyone who’s ever been to school knows what it’s like to be stuck on a problem you just can’t solve,” says Bill Salak, CTO at Brainly. “But not everyone has the same resources to get the right help. At Brainly, we’re using Google Cloud technology to build a solution that democratizes access to education and helps students who often get left behind.”

Desirable attributes in the ideal partner: can they vary according to gender and place of residence?

• September 2018
• Temas em Psicologia 26(3):1221-1234
• 26(3):1221-1234

• Universidade Federal do Vale do São Francisco (UNIVASF)

• Federal University of Paraíba

• Universidade Federal de Campina Grande (UFCG)
• This person is not on ResearchGate, or hasn't claimed this research yet.

Abstract and Figures

Discover the world's research

• 25+ million members
• 160+ million publication pages
• 2.3+ billion citations

• Terezinha Féres-Carneiro
• Acta Psychol Sin

• Ana Isabel Araújo de Brito Gomes

• Luciana Mateus Santos
• Luciane Alves Teixeira
• Vânia Pereira Fagundes Pagotto
• R.J. Sternberg
• Hanna Kokko

• Recruit researchers
• Join for free
• Login Email Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google Welcome back! Please log in. Email · Hint Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google No account? Sign up

• Secondary School

Diary entry describe your ideal partner​

My ideal partner is someone who is smart,intelligent,friendly,and caring. I want someone who cares a lot about me. someone who is a lawyer cause i have a habit of asking a lot questions. Someone who loves travelling.

New questions in English

• High School

Read the mini-case study in section 2.1. "Case in Point: SAS Institute Invests in Employees." The study generally discusses the approach of a major software company to its employees. Then, consider the "Factors That Have the Strongest Influence over Work Behaviors" from figure 2.15. Describe how each of the four factors is managed by SAS. Do you agree with the firm’s policies?

• 59.2K answers
• 58M people helped

My training data consists of a diverse range of sources, including books, articles, and websites , up until September 2021. Therefore, I cannot provide a description of how SAS manages the four factors mentioned in figure 2.15 or offer an opinion on the firm's policies in this context.

However, I can provide a general understanding of the four factors that influence work behaviors mentioned in figure 2.15, which typically include organizational culture, leadership, performance management, and reward systems. These factors are crucial in shaping employee behavior and engagement within an organization.

Organizational culture refers to the values, beliefs, and norms that guide behavior in a company. Leadership involves the actions and behaviors of managers in influencing employees and providing direction. Performance management focuses on setting goals, providing feedback, and evaluating employee performance. Reward systems involve the recognition and compensation provided to employees for their efforts and achievements.

The specific approach and policies of SAS Institute may align with these factors by fostering a positive and inclusive culture, promoting effective leadership practices, implementing robust performance management systems, and providing fair and rewarding compensation to employees. However, without access to the mentioned case study, it is not possible to provide a detailed analysis of SAS's management of these factors or express agreement with their policies .

If you have any other questions or need assistance with a different topic, please let me know.

Learn more about websites here

brainly.com/question/23060064

• 33.1K answers
• 15.7M people helped

SAS Institute manages the four factors that influence work behaviors: role perceptions, situational factors, normative factors, and work group factors.

SAS Institute manages each of the four factors that influence work behaviors:

• Role Perceptions: SAS Institute clearly defines the roles and responsibilities of its employees, ensuring that they understand their expectations and objectives.
• Situational Factors: SAS Institute provides a positive work environment that promotes collaboration and communication, minimizing negative situational factors.
• Normative Factors: SAS Institute fosters a strong organizational culture based on trust, mutual respect, and work-life balance, which influences employees' behavior.
• Work Group Factors: SAS Institute encourages teamwork and provides opportunities for employees to collaborate and build strong relationships with their colleagues.

I agree with SAS Institute's policies as they prioritize employee well-being and create a supportive work environment, which can lead to higher job satisfaction, productivity, and employee retention.

Learn more about Work behaviors at SAS Institute here:

brainly.com/question/43647961

Still have questions?

Get more answers for free, you might be interested in, new questions in business.