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Although significant research has examined the concept of transformational leadership, few studies have explored the indirect impact of transformational leadership on individual and organizational outcomes within the context of crisis. Accordingly, this study aims to advance our understanding of the indirect impact of transformational leadership on school performance and principals' work alienation within the context of the COVID-19 pandemic. In doing so, this study contributes to this developing stream of literature by hypothesizing the indirect effect of two relational resources, namely employee trust and relational coordination, which mediate the relationship between transformational leadership, school performance and principals' work alienation.

This study draws on a unique sample of 634 principals from Irish primary schools navigating the COVID-19 crisis. Structural equation modeling (SEM) was performed using Mplus 8.3 to test the hypothesized model.

Mixed findings emerged concerning the mediating process of relational resources and their impact on transformational leadership, school performance and principals' work-alienation. In particular, support is found for the critical role of principals whose transformational leadership style can help increase school performance. However, evidence suggests that employee trust does not mediate the relationship between transformational leadership and principals' work alienation.

This study provides several practical insights for education professionals, policymakers and HRM practitioners across each phase of the crisis management cycle. Firstly, regarding the pre-crisis stage, educational institutions should invest in targeted leadership development programs that prioritize relationship-building and effective communication among stakeholders. Second, during crises, the study emphasizes the role of relational resources in mediating the impact of leadership on school performance. Moreover, the study illustrates the importance of proactively cultivating strong connections with stakeholders, fostering timely, problem-solving-based communication. Finally, in the post-crisis phase, collaboration with government stakeholders is recommended to inform recovery policies.

This study makes several contributions to the literature on leadership and crisis management. First, this study adds new insights suggesting how principals as leaders influence school performance during crisis. Second, by adopting a relational perspective, this study suggests two types of relational resources (i.e. employee trust and relational coordination), as the mediators between transformational leadership, school performance and principals' work alienation. Third, this study moves the existing research on leadership during crisis forward by focusing on the functional effectiveness of leadership while focusing on the principals' work alienation during the pandemic.

This study aims to think critically about collaborative working through the practical application of an ethics of care approach. The authors address the following research questions: How can the authors embed an ethics of care into academic collaboration? What are the benefits and challenges of this kind of collaborative approach? The contextual focus also incorporates a collective sense making of academic identities over the course of the COVID-19 pandemic.

The authors focus on the activities of the “Consumer Research with Impact for Society” collective at and around the 2021 Academy of Marketing conference. The authors draw on the insights and labour of the group in terms of individual and collaborative reflexivity, workshops and the development of a collaborative poem.

First, the authors present the “web of words” as the adopted approach to collaborative writing. Second, the authors consider the broader takeaways that have emerged from the collaboration in relation to blurring of boundaries, care in collaboration and transformations.

The overarching contribution of the paper is to introduce an Ethics of Collective Academic Care. The authors discuss three further contributions that emerged as central in its operationalisation: arts-based research, tensions and conflicts and structural issues. The application of the “web of words” approach also offers a template for an alternative means of engaging with, and representing, those involved in the research.

The purpose of this study is to reveal the research trends in guest experiences of service robots in the hospitality industry.

In this study, a review was carried out on the Web of Science (WoS) database with the assistance of bibliometric analysis techniques. Cluster analysis was also employed for this to group important data to determine the relationships and to visualize the areas in which the studies are concentrated. The thematic content analysis method was used to reveal on which customer experiences and on which methods the focuses were.

On the subject of experiences of service robots, the greatest number of publications was in 2021. In terms of country, China has come to the fore in the distribution of publications. As a result of thematic content analysis, it was determined that the leading factor was the main dimension of emotional experience. In terms of sub-dimensions, social interactions attracted more attention. Most of the studies discussed were not based on any theory. Apart from these, the Technology Acceptance Model (TAM), the Service Quality Model (SERVQUAL) and Perceived Value Theory (PVT) were featured more prominently among other studies.

In this study, only the WoS database was reviewed. In future studies, it would be possible to make contextual comparisons by scanning other databases. In addition to quantitative research designs, social dimensions may be examined in depth following qualitative research methods. Thus, various comparisons can be made on the subject with mixed-method research designs. Experimental research designs can also be applied to where customers have experienced human-robot interactions (HRIs).

In the hospitality industry, it is critical to uncover every dimension of guests' robot acceptance. This study, which presents the current situation on this basis, guides future projections for the development of guest experiences regarding service robots in the hospitality industry.

This study investigates how artificial intelligence (AI) chatbots persuade customers to accept their recommendations in the online shopping context.

Drawing on the elaboration likelihood model, this study establishes a research model to reveal the antecedents and internal mechanisms of customers' adoption of AI chatbot recommendations. The authors tested the model with survey data from 530 AI chatbot users.

The results show that in the AI chatbot recommendation adoption process, central and peripheral cues significantly affected a customer's intention to adopt an AI chatbot's recommendation, and a customer's cognitive and emotional trust in the AI chatbot mediated the relationships. Moreover, a customer's mind perception of the AI chatbot, including perceived agency and perceived experience, moderated the central and peripheral paths, respectively.

This study has theoretical and practical implications for AI chatbot designers and provides management insights for practitioners to enhance a customer's intention to adopt an AI chatbot's recommendation.

1. The study investigates customers' adoption of AI chatbots' recommendation.

2. The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

3. The central and peripheral cues are generalized according to cooperative principle theory.

4. Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

5. Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

6. Customers' mind perception positively moderates the central and peripheral paths.

The study investigates customers' adoption of AI chatbots' recommendation.

The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

The central and peripheral cues are generalized according to cooperative principle theory.

Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

Customers' mind perception positively moderates the central and peripheral paths.