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This study aims to examine the underlying emotional process that explains how context-specific stimuli involved in virtual reality (VR) destinations translate into presence perceptions and behavioral intentions.

In total, 403 potential tourists participated in a self-administered online survey after they watched a randomly assigned VR tour. The Lavaan package in R software was used to conduct structural equation analysis and examine the proposed theoretical framework.

The results reveal that media content consisting of informativeness, aesthetics and novelty was positively related to users’ sense of presence in a VR tour. The effect of media content on presence was partially mediated by emotional arousal.

Managers and VR designers can create an emotive virtual tour that contributes to the user’s sense of presence to promote attraction to the target destination. The VR content needs to be informative, aesthetic and novel, which can excite users during the VR tour, portray virtual destinations clearly and eventually influence potential tourists’ visit intentions.

Research on the emotional mechanism to generate presence is still in its infancy. This study integrates presence theory into a conceptual framework to explore how media content influences presence and decision-making through the emotional mechanism.

This study investigates the role of environmental, social and governance (ESG) policies in enhancing the resilience of Chinese firms during the COVID-19 crisis. By analyzing data from over 3,069 publicly listed companies, the research aims to elucidate the impact of robust ESG practices on stock market performance and operational outcomes during economic disruptions.

Using a dataset comprising ESG scores and financial performance metrics of Chinese firms, we conduct an empirical analysis to assess the correlation between ESG practices and corporate resilience during the COVID-19 pandemic. The study focuses on evaluating the individual contributions of the social and governance components to overall firm performance.

The analysis reveals that firms with higher ESG scores, especially in social and governance aspects, exhibit superior stock market performance and operational outcomes during the pandemic. Companies with strong governance mechanisms demonstrate more pronounced benefits, including better long-term sales growth and return on equity (ROE). The findings highlight the critical role of ESG policies in ensuring corporate stability and competitive advantage during crises.

This article provides a comprehensive overview of the impact of corporate ESG ratings on corporate trust and offers a detailed discussion on the protective role of ESG/CSR on firm value during crises, thus providing an original literature contribution.

This study aims to understand the reasons for individuals switching from traditional banks to Internet-only banks and examine how switching intentions differ between Generation X and Generation Z. Notably, Generation Z, being digital natives, exhibits distinct characteristics compared to Generation X, who often referred to as digital immigrants. Given the technology-driven nature of Internet-only banks, a multi-group analysis between these two generations was conducted.

This study utilizes Bansal’s push–pull–mooring model as a framework to analyze switching intention. The study collected survey data from 383 Korean participants, consisting of 198 participants from Generation Z and 185 participants from Generation X.

The findings indicate that low satisfaction and discomfort are factors that push people to leave traditional banks. Specifically, Generation Z shows a significantly higher inclination to leave traditional banks due to discomfort. On the other hand, relative advantage, compatibility, observability and trialability are factors that pull people to switch to Internet-only banks. Generation X is more likely to consider adopting Internet-only banks when compatibility is high and complexity is low.

This study is the first to explore unique motivators for Generation Z, such as their discomfort with interpersonal interactions in the retail banking sector. These findings challenge earlier research emphasizing human interaction’s importance in technology adoption, offering insights into their future adoption of contactless services.

As environmental protection and sustainable development become more widely recognized, greater emphasis has been placed on the significance of green supplier selection (GSS), which can support businesses both upstream and downstream in enhancing their environmental performance while preserving their strategic competitiveness. Therefore, this paper aims to propose a new framework to study GSS.

Firstly, this paper establishes a GSS evaluation criteria system including product competitiveness, green performance, quality of service and enterprise social responsibility. Secondly, based on the spherical fuzzy sets (SFSs), the Average Induction Ordered Weighted Averaging Operator-Criteria Importance Through Inter Criteria Correlation (AIOWA-CRITIC) method is used to determine the subjective and objective weights and the combination of weights are determined by game theory. In addition, the GSS framework is constructed by the Cumulative Prospect Theory-Technique for Order Preference by Similarity to Ideal Solution (CPT-TOPSIS) method. Finally, the validity and robustness of the framework is verified through sensitivity comparative and ablation analysis.

The results show that Y3 is the most promising green supplier in China. This study provides a feasible guidance for GSS, which is important for the greening process of the whole supply chain.

Under spherical fuzzy sets, AIOWA and CRITIC are used to determine weights of indicators. CPT and TOPSIS are combined to construct a decision model, considering the ambiguity and uncertainty of information and the risk attitudes of decision-makers.

The study has practical implications for decision-makers in that increasing board competence and expertise through training on environmental issues will promote green policy-making.

This study included 655 firm-year observations from companies listed on the Indonesia Stock Exchange between 2017 and 2021. Panel data regression analysis is used to investigate the hypotheses. Additionally, a robustness test is conducted to validate the consistency of the primary test results.

The results demonstrate that green theme training from the board of directors, board of commissioners and independent commissioners has a positive and significant impact on the implementation of green innovation at each level of the board. This result is aligned with the robustness test performed.

This study is restricted by the fact that the only data sources used to examine the board’s green training are publication reports and other reports that disclose the board’s training activities. Therefore, future research can be done by considering other methods, such as surveys to trace green training followed by the board. Additional research may also examine green theme training in the corporate governance structure from a different theoretical angle, such as agency theory and human capital theory.

In practice, the study has implications for decision-makers in that increasing board competence and expertise through training on environmental issues will be able to promote green policy-making.

This study concentrates on Indonesia with two-board governance characteristics: the board of directors and the board of commissioners. Several scholars have examined the board of directors in light of resource dependence theory. To the best of the authors’ knowledge, no research has explained the supervisory board within the context of two-board governance. In addition, the authors have not found research that analyzes board training activities related to the environment.

The purpose of this paper is to explore how GenAI can help companies achieve a higher level of hyper-segmentation and hyper-personalization in the tourism industry, as well as show the importance of this disruptive tool for tourism marketing.

This paper used the Web of Science and Google Scholar databases to provide updated studies and expert authors to explore GenAI in the tourism industry. Analysing hyper-segmentation and hyper-personalization modalities through GenAI and their new challenges for tourists, tourism cities and companies.

Findings reveal that GenAI technology exponentially improves consumers’ segmentation and personalization of products and services, allowing tourism cities and organizations to create tailored content in real-time. That is why the concept of hyper-segmentation is substantially focused on the customer (understood as a segment of one) and his or her preferences, needs, personal motivations and purchase antecedents, and it encourages companies to design tailored products and services with a high level of individual scalability and performance called hyper-personalization, never before seen in the tourism industry. Indeed, contextualizing the experience through GenAI is an important way to enhance personalization.

This paper also contributes to enhancing and bootstrapping the literature on GenAI in the tourism industry because it is a new field of study, and its functional operability is in an incubation stage. Moreover, this viewpoint can facilitate researchers and companies to successfully integrate GenAI into different tourism and travel activities without expecting utopian results. Recently, there have been no studies that tackle hyper-segmentation and hyper-personalization methodologies through GenAI in the tourism industry.

In this study, the authors develop a path model and investigate the effect of pandemic-oriented customer mistreatment on service sabotage through the lens of self-presentation theory. Moreover, the authors question the role of service climate as a moderator of the relationship between service sabotage and service performance.

Data were collected via a survey of 165 F&B frontline employees in restaurants in Iran. The hypotheses are examined using confirmatory factor analysis, structural equation modeling and ordinary least squares regression.

The findings reveal that POCM has a substantial and positive effect on service sabotage, and service climate mitigates the effect of service sabotage on service performance.

The study introduces and conceptually defines the term POCM. Furthermore, the authors apply the self-presentation theory as the overarching theory to explain underlying conditions in customer mistreatment and service sabotage. Moreover, although prior literature has described the saboteur–customer relationship as a one-line interaction, this study contributes to employee sabotage as a multi-linear transaction.

In this study, the authors identify new perspectives on the dark side of hospitality services in crises, such as the COVID-19 pandemic. The authors argue that pandemic-induced changes are essential not simply because they change customers’ moods and lower their patience threshold, but they further provoke ostentatious behaviors in saboteur–customer relations. These findings shed new light on the literature and provide managerial implications for enhancing hospitality performance.

Prior research has proposed a number of scales measuring the customer experience (CX), which tend to conceptualize and operationalize CX differently, raising potential confusion among researchers (e.g. regarding which scale to use). Addressing this issue, this article conducts a systematic review to inventorize key CX scales and assess their theoretical rigor, with a focus on the identification of potential scale-related drawbacks or risks.

Drawing on the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) approach, 104 CX scale development studies published between 1996 and 2024 are identified and analyzed in terms of their respective CX conceptualization, dimensionality, itemization, and adopted theoretical perspective to evaluate their theoretical rigor.

The findings reveal the existence of five main risks associated with the adoption of specific CX or related scales, including (1) defining experience with explicit reference to other extant constructs, (2) failure to accurately and comprehensively capture the experience, (3) experience-based tautology and theoretical indeterminacy, (4) experience-based composite constructs, and (5) lacking robustness of experience-based conceptual models. Based on these observations, recommendations are offered for scholars to improve the rigor of their adopted, refined, or proposed CX or related scales.

This article assesses the benefits and potential risks inherent in the adoption of particular CX scales, equipping researchers with a CX roadmap.

With the trend of adopting and studying artificial intelligence (AI) service robots at restaurants, the authors’ understanding of how customers perceive robots differently across restaurant segments remains limited. Therefore, building upon expectancy theory, this study aims to propose a trust-based mechanism to explain customers’ support for AI-based service robots.

For cross-segment validation, data were collected from online survey participants under the scenarios of experiencing AI service robots in luxury (n = 428), fine-dining (n = 420), casual (n = 409) and quick-service (n = 410) restaurant scenarios.

In all four segments, trust in technology increased willingness to accept AI service robots, which was then positively related to customers’ support for AI-based service robots. Meanwhile, customers’ AI performance expectancy mediated the relationship between trust in technology and willingness to accept AI service robots. On the other hand, at luxury, fine-dining and casual restaurants, males perceived a stronger positive relationship between trust in technology and AI performance expectancy. No generational differences were found in the four restaurant segments between trust in technology and AI performance expectancy.

To the best of the authors’ knowledge, this study is one of the first attempts in hospitality research to examine cross-segment validation of customers’ responses to AI-based service robots in the luxury, fine-dining, casual and quick-service restaurant segments.

This systematic literature review (SLR) aims to critically analyze the current academic research on the adoption of artificial intelligence (AI) in supply chain management (SCM) and develop a theoretical framework and future research agenda.

Through a comprehensive review of 68 relevant papers, this study synthesizes the findings to identify key themes based on extended technology-organization-environment (TOE) theory.

This study analyzes AI integration in SCM based on the TOE framework, identifying drivers (technological, organizational, environmental and human), barriers (technical, organizational, economic and human) and outcomes (operational, environmental, social and economic) of AI adoption. It emphasizes AI's potential in improving SCM practices like resilience, process improvement and sustainable operations, contributing to better decision-making, efficiency and sustainable practices. The study also provided a novel framework that offers insights for strategic AI integration in SCM, aiding policymakers and managers in understanding and leveraging AI's multifaceted impact.

The originality of the study lies in the development of a theoretical framework that not only elucidates the drivers and barriers of AI in SCM but also maps the operational, financial, environmental and social outcomes of AI-enabled practices. This framework serves as a novel tool for policymakers and managers, offering specific, actionable insights for the strategic integration of AI in supply chains (SCs). Furthermore, the study's value is underscored by its potential to guide policy formulation and managerial decision-making, with a focus on optimizing SC efficiency, sustainability and resilience through AI adoption.