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Drawing upon curiosity drive theory, we examine the effects of epistemic curiosity (EC) on employees' innovative work behavior. Additionally, we explore the potential mediating role of work engagement (WE) and the moderating effects of leader-member exchange (LMX).

The data were collected from 406 employees employed in public service organizations within the United Arab Emirates. Structural equation modeling was employed as the analytical approach to test the hypotheses.

The findings of this study indicate that EC is positively related to innovative work behavior. Further, WE mediates the relationship between EC and creative work behavior. Moreover, LMX moderates the indirect effect of WE on the link between EC (interest and deprivation types) and innovative work behavior. The mediating association is stronger when the leader and member’s exchange is high.

This study will assist practitioners of service organizations in focusing their attention on EC to enhance employees' innovative work behavior and achieve optimal performance. Our research extends work on interest and innovative work behavior in an emerging economic context.

Our study suggests that policymakers should embrace the philosophy of curiosity to nurture innovative behavior in the workplace.

This study, a theoretical article, aims to introduce new institutionalism as a framework through which business and management researchers can explore the significance of artificial intelligence (AI) in organizations. Although the new institutional theory is a fully established research program, the neo-institutional literature on AI is almost non-existent. There is, therefore, a need to develop a deeper understanding of AI as both the product of institutional forces and as an institutional force in its own right.

The authors follow the top-down approach. Accordingly, the authors first briefly describe the new institutionalism, trace its historical development and introduce its fundamental concepts: institutional legitimacy, environment and isomorphism. Then, the authors use those as the basis for the queries to perform a scoping review on the institutional role of AI in organizations.

The findings reveal that a comprehensive theory on AI is largely absent from business and management literature. The new institutionalism is only one of many possible theoretical perspectives (both contextually novel and insightful) from which researchers can study AI in organizational settings.

The authors use the insights from new institutionalism to illustrate how a particular social theory can fit into the larger theoretical framework for AI in organizations. The authors also formulate four broad research questions to guide researchers interested in studying the institutional significance of AI. Finally, the authors include a section providing concrete examples of how to study AI-related institutional dynamics in business and management.

This study aims to examine the effect of Industry 4.0 technology on resilience in established cross-border supply chain(s) (SC).

A literature review provides insight into the resilience capabilities of cross-border SC. The research uses a case study of operational international SC: the producers, importers, logistics companies and UK Government (UKG) departments. Semi-structured interviews determine the resilience capabilities and approaches of participants within cross-border SC and how implementing an Industry 4.0 Internet of Things (IoT) and capitals Distributed Ledger (blockchain) based technology platform changes SC resilience capabilities and approaches.

A blockchain-based platform introduces common assured data, reducing data duplication. When combined with IoT technology, the platform improves end-to-end SC visibility and information sharing. Industry 4.0 technology builds collaboration, trust, improved agility, adaptability and integration. It enables common resilience capabilities and approaches that reduce the de-coupling between government agencies and participants of cross-border SC.

The case study presents challenges specific to UKG’s customs border operations; research needs to be repeated in different contexts to confirm findings are generalisable.

Operational SC and UKG customs and excise departments must align their resilience strategies to gain full advantage of Industry 4.0 technologies.

Case study research shows how Industry 4.0 technology reduces the de-coupling between the SC and UKG, enhancing common resilience capabilities within established cross-border operations. Improved information sharing and SC visibility provided by IoT and blockchain technologies support the development of resilience in established cross-border SC and enhance interactions with UKG at the customs border.

Researchers have tried analysing how the organizations’ practices of doing good can help improve their employees’ satisfaction over the past couple of decades. Employee satisfaction has a complicated relationship with a company’s corporate social responsibility (CSR) activities. Subsequently, the purpose of this paper is to conduct a bibliometric analysis and a literature review to trace the links between CSR and employee satisfaction, summarize and analyse the advances in this field, the knowledge gaps, publishing trends and further directions for future research.

The authors conducted a bibliometric analysis followed by a literature review of papers indexed in the Scopus database and published between 2000 and 2022. A total of 233 papers were identified, while 152 of them met the inclusion criteria for the analysis.

The subsequent analysis sheds light on the overlaps and connections between the two phenomena in human resource management (HRM). The authors outline potential avenues for future research and practical insight into how to leverage CSR activities for increasing work satisfaction.

By detailing the different ways CSR and employee satisfaction impact one another, analysing their relations and other supporting constructs, the authors contribute to the academic discourse by synthesizing prevailing literature and introducing practical guides for human resource (HR) professionals, managers and executives to manage turbulent surroundings more effectively, considering the major disruptions post-COVID-19 and the adoption of advanced technologies.

This study aims to focus on assessing the psychometric properties necessary to validate the internal structure of the TOURQUAL scale.

A quantitative research study was conducted in collaboration with the Brazilian Network of Tourism Observatories, comprising 927 respondents surveyed between October 2021 and May 2022. The data analysis involved the application of descriptive statistics and exploratory factor analysis, in alignment with the principles outlined in the Standards for Educational and Psychological Testing 2014 to validate the scale.

The findings of this study validate the TOURQUAL scale as a robust tool for assessing the perceived quality of tourist services, with results demonstrating one-dimensionality and replicability.

To the best of the authors’ knowledge, this study is the first to assess the psychometric properties for validating the internal structure of the TOURQUAL scale.

Circular supply chain management (CSCM) is considered a promising solution to attain sustainability in the current industrial system. Despite the exigency of this approach, its application in the food industry is a challenge because of the nature of the industry and CSCM being a novel approach. The purpose of this study is to develop an industry-based systematic analysis of CSCM by examining the challenges for its application, exploring the effects of recognised challenges on various food supply chain (FSC) stages and investigating the business processes as drivers.

Stakeholder theory guided the need to consider stakeholders’ views in this research and key stakeholders directly from the food circular supply chain were identified and interviewed (n = 36) following qualitative methods.

Overall, the study reveals that knowledge, perception towards environmental initiatives and economic viability are the major barriers to circular supply chain transition in the UK FSC.

This research provides a holistic perspective analysing the loopholes in different stages of the supply chain and investigating the way a particular circular supply chain stage is affected by recognised challenges through stakeholder theory, which will be a contribution to designing management-level strategies. Reconceptualising this practice would be beneficial in bringing three-tier (economic, environmental and social) benefits and will be supportive to engage stakeholders in the sustainability agenda.

This study aims to use the extended model of goal-directed behavior (EMGB) to examine the interaction between wine purchasing motivations and prior knowledge and their impact on consumers’ wine purchase intentions and decisions.

The survey was conducted in large discount retail stores in South Korea, and structural equation modeling analysis reveals EMGB’s strong predictive ability to understand wine buying behavior.

Notably, the findings reveal that social life and enjoyment motivations play a significant role in shaping consumers' attitudes. In addition, positive emotions, attitudes, prior knowledge, subjective norms and negative anticipated emotions all have a positive effect on desire, while desire, prior knowledge and frequency of past behavior have a significant impact on behavioral intention. Contrary to previous studies, celebration motivation has no significant effect on attitude and perceived behavioral control has no significant effect on desire and behavioral intention.

The findings provide practical insights for marketers to conduct targeted wine marketing campaigns and increase consumers' intention to purchase wine.

This study furthers the understanding of the complex mechanisms involved in shaping the intention to purchase wine using the EMGB framework.

This study aims to examine the impact of artificial intelligence (AI) adoption on job insecurity and its subsequent effect on turnover intentions within the hotel industry. It investigated how AI-induced job insecurity affects the likelihood of employees considering leaving their current hotel jobs for other hotels or for opportunities outside the hotel sector, mediated by feelings of job stress and insecurity.

Quantitative data analysis used 259 responses from frontline hotel employees. Confirmatory factor analysis was used to explore the factor structure and assess model fit indices. Structural equation modeling was then applied to test the hypotheses.

Findings reveal that AI awareness has a positive impact on job stress and insecurity. Moreover, job insecurity is found to positively affect turnover intentions, with a notably stronger effect observed for turnover intentions toward non-hotel companies. Additionally, the influence of social capital as a moderator on the relationship between job insecurity and turnover intention varies depending on the specific dimensions of turnover intention.

This study contributes to enhancing both theoretical frameworks and empirical insights into turnover dynamics within the hotel sector. However, future research should take into account employees’ positions, roles, organizations and career levels by examining these factors in relation to technology awareness, job stress, job insecurity and turnover intention.

This study initially focuses on the phenomenon of dynamic turnover issues within the hospitality sector, offering empirical and practical perspectives on effectively integrating new technologies and managing human resources amidst the automation and AI era.

本研究探讨了人工智能（AI）应用对酒店业工作不安全感的影响, 以及其对员工流失意向的后续影响。研究调查了AI引发的工作不安全感如何通过工作压力和不安全感的感受影响员工考虑离开当前酒店工作、转投其他酒店或者寻求酒店行业外的机会。

本研究采用了259名一线酒店员工的定量数据分析。采用验证性因子分析（CFA）探索因子结构并评估模型拟合指标。随后, 应用结构方程模型（SEM）来检验假设。

研究结果显示, AI意识对工作压力和不安全感有积极影响。此外, 工作不安全感被发现对员工流失意向产生正向影响, 尤其是对转投非酒店公司的流失意向影响更为显著。此外, 社会资本作为调节变量对工作不安全感与流失意向之间的关系的影响取决于流失意向的具体维度。

本研究有助于加强酒店业人才流失动态的理论框架和实证见解。然而, 未来研究应考虑员工的职位、角色、组织和职业水平, 通过研究这些因素与技术意识、工作压力、工作不安全感和流失意向之间的关系。

本研究首次聚焦于酒店业中动态人才流失问题的现象, 提供了在自动化和人工智能时代有效整合新技术并管理人力资源的实证和实践观点。

This paper aims to examine the impact of the COVID-19 pandemic on the private label food products, specifically assessing the stability and changes in factors influencing purchasing decisions, and comparing pre-pandemic and post-pandemic datasets.

The study employs the Extra Tree Classifier method, a robust quantitative approach, to analyse data collected from questionnaires distributed among two distinct consumer samples. This methodological choice is explicitly adopted to provide a clear classification of factors influencing consumer preferences for private label products, surpassing conventional qualitative methods.

Despite the profound disruptions caused by the COVID-19 pandemic, this research underscores the persistent hierarchy of factors shaping consumer choices in the private label food market, showing an overall stability in consumer behaviour. At the same time, the analysis of individual variables highlights the positive increase in those related to product quality, health, taste, and communication.

The use of online surveys for data collection may introduce a self-selection bias, and the non-probabilistic sampling method could limit the generalizability of the results.

Practical implications suggest that managers in the private label industry should prioritize enhancing quality control, ensuring effective communication, and dynamically adapting strategies to meet evolving consumer preferences, with a particular emphasis on quality and health attributes.

This study contributes to the existing body of literature by providing insights into the profound transformations induced by the COVID-19 pandemic on consumer behaviour, specifically in relation to their preferences for private label food products.

To extend research into sport consumer behaviors related to online sports betting, this study is designed to identify and examine the relationship between online sports betting motivations and online sports betting intentions. By applying a push-pull framework from online sport consumption and gambling studies, nine motivations to engage in online sports betting were identified. These motivations were hypothesized to motivate online sports betting intentions.

A quota sampling technique based on the sports bettor demographics available in the American Gaming Association (AGA, 2019) and the Pew Research Center (2022) obtained a total of 550 completed surveys that met the inclusion and exclusion criteria. For data analyses, confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used to examine the measurement model and the hypothesized model, respectively.

The results revealed that four motivations (i.e. monetary gain, excitement, convenience and negative technology-readiness) were related to online sports betting intention, while five motivations (i.e. sport fandom, positive technology-readiness, impulsivity, socialization and promotion) were not.

The results provide foundational theoretical knowledge of what motivates sports fans to participate in online sports betting. Furthermore, the findings assist practitioners in their allocation of resources by enhancing their understanding of online sports betting motivations.