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This study's purpose is to investigate the antecedents of an employee's remedy‐seeking behavioral intentions in response to wrongful dismissal.

Hypotheses generated by two paradigms are tested, the similarity‐attraction and the similarity‐betrayal paradigms, using Tobit regression and data from a scenario‐based survey of employees.

Consistent with the similarity‐attraction paradigm, the management team's racial and deep‐level similarity to the employee both were negatively related to the employee's propensity to consult a lawyer. Consistent with the similarity‐betrayal paradigm, the employee's propensity to consult a lawyer increased with the supervisor's deep‐level similarity to the employee; among men, the propensity to complain to regulatory agencies increased with the management team's gender similarity and the propensity to not seek a remedy declined with the supervisor's gender similarity.

Limitations of the study include the use a single‐source, cross‐sectional, convenience sample; the small size and heterogeneity of the non‐white sub‐sample; and the limited number of control variables. Future research should explore whether the findings are robust when tested using alternative types of data; alternative wrongful dismissal scenarios; a more extensive set of controls for organizational, job, and personal characteristics; and larger, more diverse sub‐samples of non‐whites.

Organizations should manage dismissals in a manner that encourages employees to favor internal remedy‐seeking over external remedy‐seeking options.

This study is the first to investigate the antecedents of a wrongfully dismissed employee's propensity to engage in internal as well as external remedy‐seeking and to explore the effects of management's similarity to the employee on the employee's remedy‐seeking actions.

We investigate the effects of management-employee similarity on mistreated employees’ propensities to engage in legal and organizational claiming, to quit, and to not seek a remedy in ongoing employment relationships.

We test hypotheses generated by the similarity-attraction and similarity-betrayal paradigms using Tobit regression and data from vignette-based employee surveys.

Mistreated employees with same-sex supervisors are more likely to initiate legal claims and to quit than those with opposite-sex supervisors, but less likely to initiate legal claims and to quit when they have a same-race supervisor than when they have a different-race supervisor. The effects of management-employee similarity on mistreated employees’ remedy-seeking responses exhibit asymmetries by gender and by race. The presence of same-race supervisors or other managers appears to diminish the greater reluctance of nonwhite employees, compared to white employees, to use organizational claiming mechanisms.

We know of no prior published research that has investigated the determinants of employees’ propensities to engage in multiple forms of remedy seeking, as well as the propensity to not seek a remedy, in response to plausibly illegal mistreatment not involving dismissal.

Buyers (renters) and sellers (hosts) on peer-to-peer (P2P) room-sharing websites make purchasing/selling decisions based on each other’s demographic information published in the cyber marketplace. Nevertheless, how this reciprocal selection based on the similarities between renters and hosts may lead to a successful P2P transaction of such services has not yet been discussed. Building on the similarity–attraction paradigm, this study assessed the similarity effects between renters and hosts on the likelihood of a P2P room-sharing transaction.

A logistical regression model was employed in analysis, using a large-scale, granular online observational data set collected from Xiaozhu.com, a primary home-sharing platform in China.

Renter–host similarities in age and education significantly affect the likelihood of a P2P room-sharing transaction. As the number of listings managed by a host increases, the effect of age similarity decreases. While a renter’s experience with a room-sharing website negatively moderates the similarity effect of age, it is a factor positively moderating the similarity effect of education.

Other possible host–renter similarities were not analyzed due to the limitation of the data source. The reciprocal selection process for room-sharing services was acknowledged by integrating buyers’ and sellers’ data into one analysis.

Implications are advanced for the stakeholders of room-sharing business, including entrepreneurs running a room-sharing website, operators of short-term residential rentals and hoteliers.

This study represents a first attempt to research the buyer–seller similarity effects on the likelihood of a P2P transaction in sharing economy.

This study aims to investigate whether and how strongly cultural (mis)matches influence immigrant customers’ satisfaction, as well as if this relationship is mediated by cultural or service employee performance attributions. In addition, the authors test whether attributions differ depending on the service delivery outcome (success vs failure).

The 2 (origin of service employee: Austria or Turkey) × 2 (service delivery outcome: success or failure) scenario-based experiment includes 120 Turkish immigrant customers in Austria.

Contrary to previous research, the results indicate that in an immigrant customer context, cultural (mis)match does not influence customer satisfaction. The service delivery outcome is a boundary condition. With a positive service delivery outcome, immigrant customers attribute the results to the cultural background of the employee if it is the same as their own, but they attribute success to employees’ performance if they belong to the immigration destination culture. For negative service delivery outcomes, neither cultural nor performance attributions arise.

This study is the first to focus specifically on immigrant customer behavior in a high-involvement service context. The results challenge the predictions of social identity theory and the similarity-attraction paradigm and highlight that the immigrant context is unique. In this context, attributions play a key role in determining customer satisfaction.

In this chapter, we review relational demography literature underpinned by the similarity–attraction paradigm and status characteristics and social identity theories. We then develop an uncertainty reduction model of relational demography, which describes a two-stage process of uncertainty emergence and reduction in a workgroup setting. The first stage depicts how structural features of the workgroup (workgroup composition) and occupation (the legitimacy of its status hierarchy) induce two forms of uncertainty: uncertainty about group norms and uncertainty about instrumental outcomes. The second part of the model illustrates employees' choice of uncertainty reduction strategies, depending on the type of uncertainty they experience, and the status of their demographic categories. Implications for theory and practice are discussed.

The purpose of this work is to analyse the relationships between the personality traits of linked users in online social networks. First the authors tried to discover relation patterns between personality dimensions in conversations. They also wanted to verify some hypotheses: whether users' personality is stable throughout different conversation threads and whether the similarity-attraction paradigm can be verified in this context. They used the five factor model of personality or Big Five, which has been widely studied in psychology.

One of the approaches to detect users' personalities is by analysing the language they use when they talk to others. Based on this assumption the authors computed users' personality from the conversations extracted from the MySpace social network. Then the authors analysed the relationships among personality traits of users to discover patterns.

The authors found that there are patterns between some personality dimensions in conversation threads, for example, agreeable people tend to communicate with extroverted people. They confirmed that the personality stability theory can be verified in social networks. Finally the authors could verify the similarity-attraction paradigm for some values of personality traits, such as extroversion, agreeableness, and openness to experience.

The results the authors found provide some clues about how people communicate within online social networks, particularly who they tend to communicate with depending on their personality. The discovered patterns can be used in a wide range of applications, such as suggesting contacts in online social networks. Although some studies have been made regarding the role of personality in social media, no similar analysis has been done to evaluate how users communicate in social media considering their personality.

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.

We offer a new perspective on group affective diversity by introducing the construct of mixed group mood, denoting co-occurring positive and negative mood states between different members of a group. Mixed group mood is characterized by four facets, namely members’ distribution between two positive and negative subgroups, subgroups’ average mood intensity, subgroups’ mood intensity heterogeneity, and individual members’ mood ambivalence. Building on information/decision-making and social categorization/similarity–attraction perspectives, we explore the performance consequences of mixed group mood along these four facets and we discuss implications and directions for future research.

This study sought to test two competing sets of hypotheses derived from two different theoretical perspectives regarding (1) the effects of leader–follower similarity and dissimilarity in psychological resilience on the follower's absenteeism in times of organizational crisis and (2) the moderating effect of relational demography (gender and age similarity) in these relationships.

Polynomial regression and response surface analysis were performed using data from 510 followers and 149 supervisors in a financial firm in Canada.

The results overall support the similarity–attraction perspective, but not the resource complementarity perspective. Dissimilarity in resilience was predictive of followers' absenteeism, and similarity in surface-level conditions (gender and age) attenuates the relational burdens triggered by resilience discrepancy.

The findings reiterate the importance of developing employees' resilience, while shedding light on the importance for managers of being aware of their potential misalignment with subordinates resilience.

The results (1) suggest that it is the actual (di)similarity with the leader, rather than leader's degree of resilience, that shapes followers' absenteeism and (2) add nuance to the resilience literature.

This study aims to propose a consensus model that considers dynamic trust and the hesitation degree of the expert's evaluation, and the model can provide personalized adjustment advice to inconsistent experts.

The trust degree between experts will be affected by the decision-making environment or the behavior of other experts. Therefore, based on the psychological “similarity-attraction paradigm”, an adjustment method for the trust degree between experts is proposed. In addition, we proposed a method to measure the hesitation degree of the expert's evaluation under the multi-granular probabilistic linguistic environment. Based on the hesitation degree of evaluation and trust degree, a method for determining the importance degree of experts is proposed. In the feedback mechanism, we presented a personalized adjustment mechanism that can provide the personalized adjustment advice for inconsistent experts. The personalized adjustment advice is accepted readily by inconsistent experts and ensures that the collective consensus degree will increase after the adjustment.

The results show that the consensus model in this paper can solve the social network group decision-making problem, in which the trust degree among experts is dynamic changing. An illustrative example demonstrates the feasibility of the proposed model in this paper. Simulation experiments have confirmed the effectiveness of the model in promoting consensus.

The authors presented a novel dynamic trust consensus model based on the expert's hesitation degree and a personalized adjustment mechanism under the multi-granular probabilistic linguistic environment. The model can solve a variety of social network group decision-making problems.