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Previous studies have often yielded mixed results in relation to the similar-to-me effect on extra-role behaviors. Based on social exchange theory, the purpose of this paper is to uncover the contribution of personality similarity to organizational citizenship behavior (OCB), a type of extra-role behaviors.

Questionnaire surveys were conducted in a multinational bank in Hong Kong. The participants were matched sample of 403 customer service representatives from 81 teams and their corresponding team supervisors.

Personality similarity to peers and supervisors had a positive impact on individual OCB (OCB-I) and organizational OCB (OCB-O), respectively, through better communication and social integration. Moreover, personality similarity to peers was related only to OCB-I, whereas personality similarity to supervisor was associated only with OCB-O.

Subordinates perform different facets of OCB depending on the subjects they are similar to in terms of personality. Being similar to others could facilitate communication and social integration, which in turn promote OCB targeted at similar individuals. The importance of distinguishing the similarity effects of peers and supervisors separately as well as scrutinizing the effects of different forms of OCB warrants future research attention.

Managers can promote OCB by enhancing communication and social integration among employees and supervisors.

As OCB enhances organizational effectiveness, the economic development of society in general will eventually benefit from having more effective organizations.

This study addresses the inconsistent findings of previous studies regarding the impact of similarity on OCB. It demonstrates the contribution of personality similarity to OCB beyond the confounding effects of judgment bias. It also advances theory by studying personality similarity to peers in addition to the commonly studied similarity to supervisors.

Followee recommendation is a problem rapidly gaining importance in Twitter as well as in other micro-blogging communities. To find interesting users to follow, most recommendation systems leverage different factors such as graph topology or user-generated content, among others. Those systems mostly disregard, however, the effect of psychological characteristics, such as personality, over the followee selection process. As personality is considered one of the primary factors that influence human behaviour, the purpose of this paper is to shed some light on the impact of personality traits on followee selection.

The authors performed a data analysis comparing the similarity among Twitter users and their followees regarding personality traits. The authors analysed three different similarity measures. First, the authors computed an overall similarity considering the five personality traits or dimensions of the Five-Factor model as a whole. Second, the authors computed the dimension-to-dimension similarity considering each individual personality trait independently of each other. Third, the authors computed a cross-dimension similarity considering each personality dimension in relation to the others.

This study showed that personality should be considered as a distinctive factor in the process of followee selection. However, personality dimensions should not be analysed as a whole as the overall personality similarity might not accurately assess the actual matching between individuals. Instead, the performed data analysis showed the existence of relations among the individual dimensions. Thus, the importance of considering each personality trait with respect to others is stated.

This study is among the firsts to study the impact of personality, one of the primary factors that influence human behaviour and social relationships, in the selection of followees in micro-blogging communities.

Improving the performance of recommender systems (RSs) has always been a major challenge in the area of e-commerce because the systems face issues such as cold start, sparsity, scalability and interest drift that affect their performance. Despite the efforts made to solve these problems, there is still no RS that can solve or reduce all the problems simultaneously. Therefore, the purpose of this study is to provide an effective and comprehensive RS to solve or reduce all of the above issues, which uses a combination of basic customer information as well as big data techniques.

The most important steps in the proposed RS are: (1) collecting demographic and behavioral data of customers from an e-clothing store; (2) assessing customer personality traits; (3) creating a new user-item matrix based on customer/user interest; (4) calculating the similarity between customers with efficient k-nearest neighbor (EKNN) algorithm based on locality-sensitive hashing (LSH) approach and (5) defining a new similarity function based on a combination of personality traits, demographic characteristics and time-based purchasing behavior that are the key incentives for customers' purchases.

The proposed method was compared with different baselines (matrix factorization and ensemble). The results showed that the proposed method in terms of all evaluation measures led to a significant improvement in traditional collaborative filtering (CF) performance, and with a significant difference (more than 40%), performed better than all baselines. According to the results, we find that our proposed method, which uses a combination of personality information and demographics, as well as tracking the recent interests and needs of the customer with the LSH approach, helps to improve the effectiveness of the recommendations more than the baselines. This is due to the fact that this method, which uses the above information in conjunction with the LSH technique, is more effective and more accurate in solving problems of cold start, scalability, sparsity and interest drift.

The research data were limited to only one e-clothing store.

In order to achieve an accurate and real-time RS in e-commerce, it is essential to use a combination of customer information with efficient techniques. In this regard, according to the results of the research, the use of personality traits and demographic characteristics lead to a more accurate knowledge of customers' interests and thus better identification of similar customers. Therefore, this information should be considered as a solution to reduce the problems of cold start and sparsity. Also, a better judgment can be made about customers' interests by considering their recent purchases; therefore, in order to solve the problems of interest drifts, different weights should be assigned to purchases and launch time of products/items at different times (the more recent, the more weight). Finally, the LSH technique is used to increase the RS scalability in e-commerce. In total, a combination of personality traits, demographics and customer purchasing behavior over time with the LSH technique should be used to achieve an ideal RS. Using the RS proposed in this research, it is possible to create a comfortable and enjoyable shopping experience for customers by providing real-time recommendations that match customers' preferences and can result in an increase in the profitability of e-shops.

In this study, by considering a combination of personality traits, demographic characteristics and time-based purchasing behavior of customers along with the LSH technique, we were able for the first time to simultaneously solve the basic problems of CF, namely cold start, scalability, sparsity and interest drift, which led to a decrease in significant errors of recommendations and an increase in the accuracy of CF. The average errors of the recommendations provided to users based on the proposed model is only about 13%, and the accuracy and compliance of these recommendations with the interests of customers is about 92%. In addition, a 40% difference between the accuracy of the proposed method and the traditional CF method has been observed. This level of accuracy in RSs is very significant and special, which is certainly welcomed by e-business owners. This is also a new scientific finding that is very useful for programmers, users and researchers. In general, the main contributions of this research are: 1) proposing an accurate RS using personality traits, demographic characteristics and time-based purchasing behavior; 2) proposing an effective and comprehensive RS for a “clothing” online store; 3) improving the RS performance by solving the cold start issue using personality traits and demographic characteristics; 4) improving the scalability issue in RS through efficient k-nearest neighbors; 5) Mitigating the sparsity issue by using personality traits and demographic characteristics and also by densifying the user-item matrix and 6) improving the RS accuracy by solving the interest drift issue through developing a time-based user-item matrix.

Facilitating members' continual participation in a community is crucial for ensuring the community's long-term survival. However, knowledge regarding whether member similarity is related to member participation and the mechanism underlying this relationship is limited. Drawing on similarity–attraction, social exchange and social identity theories, this study explored the influences of different facets of similarity (i.e. value, personality and goal similarity) on group norm conformity, group identity and social participation.

Data were collected from 444 Taiwanese members of social networking sites (SNSs), and structural equation modeling was employed to examine the hypothesized relationships.

The results revealed that value similarity directly affected group norm conformity but did not directly affect group identity; personality similarity influenced group identity but not group norm conformity. Goal similarity had positive influences on group norm conformity and group identity. Moreover, group norm conformity had direct and positive influences on group identity and social participation; group identity also had a positive influence on social participation.

On the basis of the aforementioned findings, this study contributes to the understanding of factors facilitating SNS members' participation from the perspective of similarity. These findings can serve as a reference for SNS administrators to facilitate social participation by emphasizing member similarity.

This paper aims to examine whether brands derive their personalities from their culture of origin, the stereotypes about their cultures of their origin or the cultures of their buyers. It also examines which of a culture’s personality traits are more transmittable to brand personalities (BPs), as well as the consequences of the BP resemblance to the personalities of the brand’s culture of origin and consumers’ culture on BP’s clarity and consumer attachment to the brand.

Hypotheses were developed and tested on survey data from a sample figure of 1,116 US consumers of luxury brands on 23 luxury brands originating from France, the USA, Britain, Italy and Germany. Trait by trait and personality profile analyses were performed using hierarchical model analysis (linear mixed effects models) and Cattell’s (1969) pattern similarity coefficient.

The culture of a brand’s origin accounts for differences of different brands personalities. The personality profiles of a country’s brands are distinct from the BP profiles of brands from other countries. The conscientiousness trait of a culture is the most transmittable to BPs. BPs derive their characteristics from stereotypes of a culture’s personality than the actual personality of the culture. The assimilation of a brand’s personality to consumer’s culture is not supported. The similarity of a BP to both real and stereotypical personality of the culture of the brand’s origin enhance perceived clarity of the BP.

The study’s focus is limited to established luxury brands coming from countries that are the traditional producers of luxuries. Empirical evidence also comes only from American consumers of luxury brands. New luxury brands from countries that have recently emerged as luxury producers need to be included.

Brands retain a significant space to differentiate their personalities beyond the influence of their culture of origin on BPs. With the exception of conscientiousness, personality traits of culture are not automatically inherited or transmitted to the brands. Cultural stereotypes find their way into BPs easier than real personality traits and managers should focus on them. BP matching with the personality of a culture is a good way for managers to increase the perceived clarity of their brands’ personality.

To the best of the authors’ knowledge, this study is the first to examine the culture’s influence on BP using a compatible to the BP construct cultural framework, McCrae and Terracciano’s (2005a) personality of a culture framework. Three cultural meaning transfer processes are examined (cultural inheritance, cultural stereotyping and acculturation to the consumer’s culture) within the same study from a trait-by-trait and a configurational (i.e. personality profile) perspective. The consequences of BP similarity to the brand’s culture of origin as well as consumer’s culture on the BP’s appeal are also assessed.

This study aims to investigate the associations between organizational citizenship behaviors (OCBs), leader‐member exchange (LMX), perceived organizational justice, and similarity between subordinate and supervisor on the Big Five personality traits.

A research questionnaire was administered to 120 blue‐collar workers in a large industrial company in Israel. A structural equation model was conducted to test the proposed relations and mediating hypotheses.

OCBs were found to be related to LMX and organizational justice. In addition, LMX was found to mediate the relationship between organizational justice and OCBs. Contrary to expectations, a negative correlation was found between personality similarity and LMX.

Organizations may facilitate OCBs by improving LMX relationships and organizational justice. Supervisors should be encouraged to form high‐quality LMX relationships with dissimilar subordinates.

The study emphasizes the importance of LMX and organizational justice as motivational bases for OCBs. Among blue‐collar workers, LMX seems to be based on social exchange or reciprocity rather than attraction or personality similarity.

AI-driven product recommendation chatbots have markedly reduced operating costs and increased sales for marketers. However, previous literature has paid little attention to the effects of the personality of e-commerce chatbots. This study aimed to examine the ways that the interplay between the chatbot's and the user's personality can increase favorable product attitudes and future intentions to use the chatbot. Based on prior literature, we specifically focused on the degree of extroversion of both chatbot and user.

A total of 291 individuals participated in this study. Two different versions of chatbot were created for this study (i.e. extroversion: high vs. low). Participants self-reported their degree of extroversion. The PROCESS macro Model 1 and Model 7 with the Johnson–Neyman technique were employed to test the hypotheses.

The results showed that the high extroversion chatbot elicited greater user satisfactions and perceptions of chatbot friendliness among users with a high level of extroversion. On the contrary, the low extroversion chatbot resulted in greater user satisfactions and perceived chatbot friendliness among users with a low level of extroversion. This study further found that user satisfactions and perceived chatbot friendliness mediated the effects of the chatbot on greater intentions to use the chatbot and more favorable product attitudes.

By showing the effects of matching the personality of the chatbot and user, this study revealed that similarity-attraction effects also apply to human–chatbot interaction in e-commerce. Future studies would benefit by investigating the similarity-attraction effects in different characteristics, such as appearance, opinion and preference. This study also provides useful information for e-commerce marketers and chatbot UX/UI designers.

This study examines opinion leadership's personal and social characteristics to see which one is more effective in opinion leadership in four different industries: fashion, travel and tourism, wellness and book and literature. The specific subject of this investigation is how largely openness, exhibitionism and competence in interpersonal relationships and status and attitude homophily affect the opinion leadership and the decision-making of opinion leaders' followers.

The proposed model was tested with the questionnaire shared via stories featured on Instagram among followers of four micro-influencers in different industries. For the purpose of testing the offered hypotheses of this study, the partial least squares method was used.

The findings show that openness, exhibitionism and competence in interpersonal relationships have a substantial effect on opinion leadership. It was also evident that status and attitude homophily impact opinion leadership. The model supports the effect of both personal and social characteristics on opinion leadership; however, based on the results, the effect of personal characteristics on opinion leadership is more remarkable, both in a direct relationship and through the mediating role of para-social interaction.

This study is novel in categorizing opinion leaders' attributes in two different extents of personal and social characteristics. The authors defined a model of the effectiveness of each personal and social characteristic on opinion leaders. The model investigates whether the personal or social characteristics have the most effect on opinion leadership, particularly with the mediating role of para-social interaction.

Self-report questionnaires are the predominant method used in human resource management (HRM) research to assess employees’ work-related psychological constructs (e.g., processes, states, and attributes). However, this method is associated with significant shortcomings, including the introduction of self-serving bias and common method variance when used exclusively. In this chapter, the authors challenge the assumption that individuals themselves are the only accurate source of the self-focused information collected in HRM research. Instead, the authors propose that other-ratings – ratings of a target individual that are provided by a workplace observer, such as a coworker, supervisor, or subordinate – can accurately assess commonly measured work-related psychological constructs. The authors begin by explaining the advantages of other-ratings for HRM research and practice, reviewing the history of other-ratings and how they emerged in the personality and person-perception literature, and outlining how they have been used in HRM research to date. Then, the authors build upon Funder’s (1995) realistic accuracy model to develop a theoretical argument detailing why workplace others should be able to accurately judge how another employee thinks and feels about work. Next, the authors highlight existing evidence in the literature on the accuracy of other-ratings and present the results of a preliminary meta-analysis on the ability of other-ratings to predict self-ratings of work-related psychological constructs. Finally, the authors discuss potential moderators of other-rating accuracy and reflect on a number of practical considerations for researchers looking to use other-ratings in their own work. The authors intend for this chapter to meaningfully contribute to the larger conversation on HRM research methods. Other-ratings are a simple, yet powerful, addition to the methodological toolkit of HRM researchers that can increase flexibility in research design and improve the overall quality of research.

Purpose: This study investigates how couple similarity in various aspects affects their life satisfaction and how these impacts vary across educational groups among the young married couples in Shanghai.

Methodology: This study employs the pooled data from three waves of the Fudan Yangtze River Delta Social Transformation Survey which sampled Shanghai youths born between 1980 and 1989, the first single-child generation. Couple similarity is evaluated through the comparison in age, hukou status, education, and income quartile between the husband and wife. Ordered logistic regression model is applied to assess the impacts of couple similarity on life satisfaction.

Findings: Marriage hypergamy in age, education, and income barely have any impacts on couples’ life satisfaction, while hukou comparison, as an important indication of social stratification in Shanghai, is strongly associated with life satisfaction. The couple in which husband holds the urban hukou and wife rural hukou as well as the couple in which both partners hold the urban hukou are significantly happier than those in which both partners hold the rural hukou. Such a positive impact is partially explained by the higher husband’s decision-making power in male-advantaged families. Moreover, husband’s urban hukou status is especially important for those without college education, but not for those with college education.

Values: This chapter highlights the importance of hukou hypergamy in life satisfaction for married couples, in particular, lower-educated couples in Shanghai. These findings reveal an implicit but persistent preference for male-dominated family model, where husbands retain a higher decision-making power that, in turn, promotes life satisfaction for both partners.