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Artificial intelligence (AI) is experiencing growth and prosperity worldwide because of its convenience and other benefits. However, AI faces challenges related to consumer resistance. Thus, drawing on the user resistance theory, this study explores factors that influence consumers’ resistance to AI and suggests ways to mitigate this negative influence.

This study tested four hypotheses across four studies by conducting lab experiments. Study 1 used a questionnaire to verify the hypothesis that AI’s “substitute” image leads to consumer resistance to AI; Study 2 focused on the role of perceived threat as an underlying driver of resistance to AI. Studies 3–4 provided process evidence by the way of a measured moderator, testing whether AI with servant communication style and literal language style is resisted less.

This study showed that AI’s “substitute” image increased users' resistance to AI. This occurs because the substitute image increases consumers’ perceived threat. The study also found that using servant communication and literal language styles in the interaction between AI and consumers can mitigate the negative effects of AI-substituted images.

This study reveals the mechanism of action between AI image and consumers’ resistance and sheds light on how to choose appropriate image and expression styles for AI products, which is important for lowering consumer resistance to AI.

The topic of employees’ taking charge behaviors has garnered increasing interest in both practical and academic fields. Leaders play a critical role in influencing followers’ taking charge behaviors, yet few studies have explored the predicting role of benevolent leadership. Drawing from proactive motivation literature, this paper aims to investigate a moderated mediation model that examines work engagement as the mediator and role-breadth self-efficacy as the moderator in the relationship between benevolent leadership and taking charge.

Matched data were collected from 297 followers and their group leaders in three subsidiaries of a large telecommunication company in China. The authors used hierarchical linear modeling to test the hypotheses.

The results revealed that benevolent leadership was positively related to followers’ work engagement and consequently their taking charge behaviors. Moreover, such moderated mediation relationship was stronger among followers who had low rather than high levels of role-breadth self-efficacy.

The primary contribution of this study is building a contingent model for the effect of benevolent leadership on follower taking charge and thereby extending the nomological networks of both benevolent leadership and taking charge literatures. Another contribution is that this research provides a new perspective to understand how leadership leads to followers’ taking charge behaviors.

This is the first study to investigate how and when benevolent leadership predicts follower taking charge.

Online platforms are providing diversified and personalized services with user information. Users should decide if they should give up parts of information for convenience, with their information being at the risk of being illegally collected, leaked, spread and misused. This study aims to explore the main factors influencing users' online information disclosure intention from the perspectives of privacy, technology acceptance and trust, and the authors extend previous research with two moderators.

Based on 48 independent empirical studies, this paper conducted a meta-analysis to synthesize existing results from collected individual studies. This meta-analysis explored the main factors influencing users' online information disclosure intention from the perspectives of privacy, technology acceptance and trust.

The meta-analysis results based on 48 independent studies revealed that perceived benefit, trust, subjective norm and perceived behavioral control have significant positive effects, while perceived privacy risk and privacy concern have significant negative effects. Moreover, cultural background and platform type moderate the relationship between antecedents and online information disclosure intention.

This paper explored the moderating effects of an individual factor and a platform factor on users' online information disclosure intention. The moderating effect of cultural differences is examined with Hofstede's dimensions, and the moderating role of the purpose of online information disclosure is examined with platform type. This study extends online information disclosure literature with a multi-perspective meta-analysis and provides guidelines for practitioners.

Effectively engaging patients is critical for the sustainable development of online health communities (OHCs). Although physicians’ general knowledge-sharing, which is free to the public, represents essential resources of OHCs that have been shown to promote patient engagement, little is known about whether such knowledge-sharing can backfire when superfluous knowledge-sharing is perceived as overwhelming and anxiety-provoking. Thus, this study aims to gain a comprehensive understanding of the role of general knowledge-sharing in OHCs by exploring the spillover effects of the depth and breadth of general knowledge-sharing on patient engagement.

The research model is established based on a knowledge-based view and the literature on knowledge-sharing in OHCs. Then the authors test the research model and associated hypotheses with objective data from a leading OHC.

Although counterintuitive, the findings revealed an inverted U-shape relationship between general knowledge-sharing (depth and breadth of knowledge-sharing) and patient engagement that is positively associated with physicians’ number of patients. Specifically, the positive effects of depth and breadth of general knowledge-sharing increase and then decrease as the quantity of general knowledge-sharing grows. In addition, physicians’ offline and online professional status negatively moderated these curvilinear relationships.

This study further enriches the literature on knowledge-sharing and the operations of OHCs from a novel perspective while also offering significant specific implications for OHCs practitioners.

This study aims to identify profiles of inclusion in the workplace to provide evidence-based guidance to build an inclusive organization.

Latent profile analysis (LPA), a person-centred classification analytical tool, was applied to determine the subtypes of inclusion with Mplus 7.4, using two-wave data collected from 368 employees in 8 Chinese companies.

Three subgroups were identified: identity inclusion group (the highest level of inclusion, 34.0%), value inclusion group (the moderate level of inclusion, 47.5%) and low inclusion group (the lowest level of inclusion, 18.5%). The findings indicate that groups with male, aged and highly educated members, as well as members from developed areas generally tend to feel more included and greater inclusion relates to more favourable outcomes and fewer detrimental consequences.

As this study was conducted only in China, the results may not be generalizable to non-Chinese contexts.

The results may help organizational leaders develop a deeper understanding of the significance and the crux of inclusion. To address the duality of workforce diversity, managers can take initiatives to create an inclusive organization. To achieve inclusion, managers should pay attention to ways of improving the perceptions of inclusion among all employees.

This is among the first studies to identify the variants in inclusion in China using LPA. It reveals the subtypes and characteristics of inclusion and can serve as a starting point to explore how to realize organizational inclusion in theory and practice.

The purpose of this paper is to model how risk governance (RG) influences risk prevention behaviors toward food safety issues, considering the perception of related risks in the Taiwanese context.

The national representative data on risk society modules from the Taiwan Social Change Survey data were used (sample size = 2,005). The procedure for the analysis consisted of investigation of the model fit indices of structural equation modeling, incorporating the mediation effect. Multiple-group analysis was used to examine the moderation effects.

Results show that the theory of reasoned action (TRA) and the advanced TRA can accurately explain personal risk perception (RP) (R²=0.40) and risk prevention (R²=0.42). Results also suggest that RG institutions can affect personal RP and risk prevention through subjective norms. In addition, moderation effects of media and gender were found.

This study is one of the first attempts to examine the RG effects on RP and risk prevention behavior of food safety issues in Taiwan. The results and findings may be helpful for RG institutions.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.