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This study aims to examine the effects of physical attraction, social attraction and task attraction, which are interpersonal attraction components of service staff, on interactional justice, procedural justice and distributive justice, all of which are components of service justice.

This study was conducted after deriving measurement tools through two preliminary studies. The research sample was made by those who have visited the restaurant where the service staff provides services directly to the customers. Respondents were instructed by investigators to complete the questionnaire based on their most recent visit to the most visited restaurants in the past three months. They received a $5 gift voucher after completing the questionnaire.

Physical attraction negatively affected interactional justice, procedural justice and distributive justice. Social attraction had a negative impact on procedural justice. Task attraction had the greatest positive impact on all service justice factors.

To attract customers’ positive perceptions of service execution and outcomes, task attraction should be considered first rather than physical attraction and social attraction of service staff.

This study expanded the scope of research on interpersonal attraction by studying physical attraction, social attraction and task attraction as interpersonal attraction factors at service encounters, and on service justice by setting the interpersonal attraction as a variable affecting service justice.

With the continuous improvement of artificial intelligence (AI) technology, intelligent personal assistants (IPAs) based on AI have seen unprecedented growth. The present study investigates the effect of anthropomorphism on cognitive and emotional trust and the role of interpersonal attraction in the relationship between anthropomorphism and trust.

A structural equation modeling technique with a sample of 263 consumers was used to analyze the data and test the conceptual model.

The findings illustrate that the anthropomorphism of IPAs did not directly induce trust. Anthropomorphism led users to assign greater social attraction and task attraction to IPAs, which in turn reinforced cognitive or emotional trust in these assistants. Compared with task attraction, social attraction was more powerful in strengthening both cognitive trust and emotional trust. The present study broadens the current knowledge about interpersonal attraction and its role in AI usage by examining two types of interpersonal attraction of IPAs.

As trust plays an important role in the rapid development of human–computer interaction, it is imperative to understand how consumers perceive these intelligent agents and build or improve trust. Prior studies focused on the impact of anthropomorphism on overall trust in AI, and its underlying mechanism was underexplored. The findings can help marketers and designers better understand how to enhance users' trust in their anthropomorphic products, especially by increasing social interactive elements or promoting communication.

The existing literature dealing with attractiveness during a service encounter focuses on employee attractiveness and its consequences. This paper aims to consider the other side of the coin by focusing on customers’ attractiveness.

On the basis of two studies, this paper presents and tests a model explaining the specific role that employee social attraction plays in customer service perception and satisfaction judgment.

It suggests that the appraisal of customers’ physical attractiveness and homophily may lead to situations in which employees are socially attracted to customers, thus influencing customer service perception.

Consequently, this research provides insights into the role of attraction determinants in a service context. In addition, it demonstrates how employees’ social attraction is triggered in a service context. The findings contribute to satisfaction research by extending prior research perceptions on dyadic service encounters and examining both employee attitude and customer perceptions in service interactions.

Chatbot users’ communication experience with disembodied conversational agents was compared with instant messaging (IM) users’ communication experience with human conversational agents. The purpose of this paper is to identify what affects users’ intention to reuse and whether they perceive any difference between the two.

A conceptual model was developed based on computer-mediated communication (CMC) and interpersonal communication theories. Data were collected online from four different continents (North America, Europe, Asia and Australia). Partial least squares structural equation modeling was applied to examine the research model.

The findings mainly reveal that media richness and social presence positively influence trust and reuse intention through task attraction and social attraction; IM users reported significantly higher scores in terms of communication experience, perceived attractiveness of the conversational agent, and trust than chatbot users; users’ trust in the conversational agents is mainly determined by perceived task attraction.

Customers’ evaluation of the communication environment is positively related to their perceived competence of the conversational agent which ultimately affect their intention to reuse chatbot/IM. The findings reveal determinants of chatbot/IM adoption which have rarely been mentioned by previous work.

Practitioners should note that consumers in general still prefer to interact with human conversational agents. Practitioners should contemplate how to combine chatbot and human resources effectively to deliver the best customer service.

This study goes beyond the Computer as Social Actor paradigm and Technology Acceptance Model to understand chatbot and IM adoption. It is among one of the first studies that compare chatbot and IM use experience in the tourism and hospitality literature.

Following the hierarchy-of-effects model, this study aims to propose a two-step process framework to investigate social media post efficacy via attraction and likes.

The study analyzes 113,785 social media posts from 126 WeChat official accounts to explore how external (headline features and account type) and internal (content features and media type) features impact social media post attractions and likes, respectively.

The antecedents of post attraction differ from those of post likes. First, headline features (punctuation, length, sentiment and lexical density) and account type significantly influence social media post attraction. Second, content features (depth, tone, domain specificity, lexical density and readability) and media type affect social media post likes.

First, this study considers online user engagement as a two-step process regarding social media posts and explores different influencing factors. Second, the study constructs new variables (account type and domain specificity) in each stage of the two-step process model.

The purpose of this paper is to develop a comprehensive research model that can explain customers’ continuance intentions to adopt and use intelligent personal assistants (IPAs).

This study proposes and validates a new theoretical model that extends the parasocial relationship (PSR) theory. Partial least squares analysis is employed to test the research model and corresponding hypotheses on data collected from 304 survey samples.

Interpersonal attraction (task attraction, social attraction, and physical attraction) and security/privacy risk are important factors affecting the adoption of IPAs.

First, this is the first empirical study to examine user acceptance of IPAs. Second, to the authors’ knowledge, no research has been conducted to test the role of PSR in the context of IPAs. Third, this study verified the robustness of the proposed model by introducing new antecedents reflecting risk-related attributes, which has not been investigated in prior PSR research. But this study has limitations that future research may address. First, key findings of this research are based only on data from users in the USA. Second, individual differences among the survey respondents were not examined.

To increase the adoption of IPAs, manufacturers should focus on developing “human-like” and “professional” assistants, in consideration of the important role of PSR and task attraction. R&D should continuously strive to realize artificial intelligence technology advances so that IPAs can better recognize the user’s voice and speak naturally like a person. Collaboration with third-party companies or individual developers is essential in this field, as manufacturers are unable to independently develop applications that support the specific tasks of various industries. It is also necessary to enhance IPA device design and its user interface to enhance physical attraction.

This study is the first empirical attempt to examine user acceptance of IPAs, as most of the prior literature has concerned analysis of usage patterns or technical features.

As computer‐mediated communication has diffused, successive technological variations raise new questions about interpersonal impressions and several standardized instruments have been advanced in literature to asses various aspect of interpersonal attraction phenomena. The purpose of this paper is to examine the claims for reliability and validity of the attraction scales by using confirmatory factor analysis (CFA) in the light of research since 1974 which has employed the scales, and then improve the measures if needed.

Random sampling procedure was carried out in two kulliyahs (Faculty) at International Islamic university Malaysia (IIUM), in which 340 students were selected from a population of 2,000 undergraduate students. A total of 26 items were tested from an instrument that has been used in previous studies; each item is expected to measure one of the three orientations' dimensions.

The analysis result confirms that the orientation of students towards interpersonal communication in online social network sites (SNS) is a multi‐dimensional construct consisting of social attraction, physical attraction and task attraction. In addition, since substantial numbers of research studies have been reported to have employed one or more of these measures, this research was examined to evaluate their reliability and validity.

Since the reliabilities found in literatures have been highly varied, it was determined that improved measures should be used in the future. Thus, a revised and improved version of these measures, using CFA, are reported and recommended in this paper for future research.

The paper has produced a second‐generation measure with substantially improved internal reliability and validity. The paper's most important and obvious conclusion is that interpersonal attraction does appear to be a multidimensional construct.

Investigating diversity presents researchers with a paradox because extremely inconsistent and conflicting findings about the effects of diversity have emerged in this field of study. It has been argued that the theoretical frameworks used have contributed to the paradox. Different and contradictory effects concerning the influence of group diversity can be predicted using these frameworks. The purpose of this paper is to examine the application of the main theoretical frameworks in the context of researching diversity.

The focus of this paper is a critical examination of three theoretical frameworks in the field of diversity research – similarity‐attraction theory, social categorization theory and the information/decision‐making approach. These are commonly applied in researching diversity. The basic elements of each theory, its applications in diversity research and its strengths and limitations are considered.

The discussion suggests that the paradox in diversity research emerges from a research tradition that views the three frameworks as being best applied separately because each framework predicts different and even contradictory outcomes. These differences are a consequence of distinctive theoretical operations. In addition, the strengths and limitations associated with each theoretical framework suggest that they might be integrated and subsequently applied in specific settings according to their respective strengths and limitations.

In order to produce more consistent results in research on diversity, it is suggested that future researchers should not rely solely on a single theoretical framework to predict the effects of diversity. In particular, different theoretical frameworks may work well with certain types of diversity as well as certain levels of analysis.

The paper provides a framework for dissecting the diversity paradox and a foundation for designing fresh approaches that might produce findings that are more consistent.

This study investigates the determinants of effective human and artificial intelligence (AI) relationship-building strategies for brands. It explores the antecedents and consequences of consumers' interactant satisfaction with communication and identifies ways to enhance consumer purchase intention via AI chatbot promotion.

Microsoft Xiaoice served as the focal AI chatbot, and 331 valid samples were obtained. A two-stage structural equation modeling-artificial neural network approach was adopted to verify the proposed theoretical model.

Regarding the IQ (intelligence quotient) and EQ (emotional quotient) of AI chatbots, the multi-dimensional social support model helps explain consumers' interactant satisfaction with communication, which facilitates affective attachment and purchase intention. The results also show that chatbots should emphasize emotional and esteem social support more than informational support.

Brands should focus more on AI chatbots' emotional and empathetic responses than functional aspects when designing dialogue content for human–AI interactions. Well-designed AI chatbots can help marketers develop effective brand promotion strategies.

This research enriches the human–AI interaction literature by adopting a multi-dimensional social support theoretical lens that can enhance the interactant satisfaction with communication, affective attachment and purchase intention of AI chatbot users.

Research indicates that inconsistent gender norm presentations are met with backlash, which is particularly damaging to women. With social media use in selection rising, it is important to understand if this remains consistent for job applicants on social media.

In two experiments, this study investigates hiring managers' reactions to job applicant (in)consistent gender norm-based communication on Facebook (n = 197) and YouTube (n = 203). Participants located in the United States were asked to review social media materials, reported perceptions of task and social attraction, and make hiring recommendations.

Inconsistent with work on backlash in face-to-face settings, results demonstrated that masculine communication styles on social media may be detrimental to job seekers, and this was more pronounced for male job seekers. Feminine presentation styles had more favorable results.

The findings challenge the long-held understanding that men have more leeway to behave in agentic ways in job seeking contexts. While this may remain true in face-to-face settings, these findings suggest that social media, lacking media richness, may be a context in which males experience backlash for agentic behavior.

The research offers a novel perspective investigating traditional gender expectations in the digital realm, paving the way for a more comprehensive understanding of gender in employment contexts. This study contributes to the growing body of research on online behavior and expands understanding of how hiring managers react to gender norms in the era of social media.