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This paper aims to uncover the insights derived from past experimental studies in promoting sustainable tourism. It also advocates for leveraging future experimental designs to position tourism as a catalyst for positive change toward sustainable development goals.

A review of previous literature examines the contributions of experimental design in both tourist studies and employee studies within the tourism fields.

Previous experimental studies have explored effective methods shaping tourists’ sustainable behaviors and management strategies contributing to employees’ decent work. The importance of integrating digital technology in these interventions is highlighted. A future research agenda encompassing three dimensions – technological progress, theory development and practical implications and research design – is proposed to leverage experimental studies for fostering sustainable development within the tourism industry.

This study, through a comprehensive review, highlights the significant impacts of previous experimental studies on encouraging responsible consumption among tourists and championing improved working conditions for employees. It underscores the necessity for enhanced experimental design, which should integrate theoretical frameworks and prioritize technological innovations to address real-world challenges. These improvements are crucial for advancing the tourism industry toward greater sustainability.

This study aims to explore the key attributes of robot chef restaurants and their influencing factors from the perspective of customers and analyzes how these key attributes affect customer perceived value.

A mixed-methods research design was used in this study. Using 473 online reviews and ratings (Study 1), the research summarized customers’ evaluations on three types of attributes (environment, service and food) and identified the key attributes along with their influencing factors. Subsequently, through field questionnaires (Study 2) involving 269 actual customers, structural equation modeling was used to analyze how the identified key attributes and their influencing factors impact customer perceived value.

This study reveals that customers in robot chef restaurants prioritize food attributes, particularly valuing food authenticity alongside food quality. In contrast to traditional restaurants, customers’ evaluations of food attributes in robot chef restaurants are significantly influenced by the competence of robot chefs. Notably, customers’ negative attitudes toward robots diminish the positive effects on both food quality and food authenticity.

To enhance customer perceived value, robot chef restaurants should concentrate on food attributes. They can achieve this by fostering a high-quality, authentic food experience through the elevation of robot chefs’ competence and by providing customer education.

This study expands research on the customer experience in robotic restaurants by proposing an integrated model determining factors that affect the perceived customer value.

Customer misbehavior has a negative impact on frontline employees. However, the underlying mechanisms from customer misbehavior to employees’ negative outcomes need to be further unfolded and examined. This study aims to propose that employees’ affective rumination and problem-solving pondering could be the explanatory processes of customer misbehavior influencing employee attitudes in which coworker support could be a moderator.

A mixed-method approach was designed to test this study’s predictions. Study 1 conducted a scenario-based experiment among 215 full-time hospitality employees, and Study 2 used a two-wave, longitudinal survey of 305 participants.

The results demonstrate the impact of customer misbehavior on work–family conflict and withdrawal behaviors. The mediating role of affective rumination is supported and coworker support moderates the processes.

Customer misbehavior leads to negative outcomes among frontline employees both at work and family domains. Hotel managers should help frontline employees to cope with customer misbehavior by avoiding negative affective spillover and providing support properly.

The studies have unfolded the processes of affective rumination and problem-solving pondering through which customer misbehavior influences work–family conflict and withdrawal behaviors among frontline employees. The surprising findings that coworker support magnified the negative effects have also been discussed.

The purpose of this study is to investigate the behavior of a silicon solar cell when subjected to a magnetic field. Specifically, the study aims to understand how the presence of the magnetic field influences the distribution of excess minority carriers within the base region of the solar cell. By solving the one-dimensional continuity equation under these conditions, the study seeks to elucidate the transient dynamics of carrier generation, recombination and transport processes. This research contributes to the broader understanding of how external magnetic fields can impact the performance and efficiency of silicon solar cells, potentially informing future optimizations or applications in photovoltaic technology.

The solar cell is assumed to be uniformly illuminated, which simplifies the analysis of carrier generation to a function of depth (x). The emitter and space charge region contributions are considered while neglecting the diffusion region. The injection level remains constant throughout the analysis, focusing specifically on the base thickness region, H = 200 µm.

The findings of this study reveal significant insights into the behavior of a silicon solar cell under the influence of a magnetic field. Key findings include Impact on carrier distribution: the magnetic field affects the distribution of excess minority carriers within the base region of the solar cell. This distribution is crucial for understanding the efficiency of carrier collection and overall cell performance. Transient dynamics: the transient behavior of carrier generation, recombination and transport processes in the base region is influenced by the magnetic field. This understanding helps in predicting the response time and effectiveness of the solar cell under varying magnetic field strengths. Optimization potential: insights gained from this study suggest potential strategies for optimizing the design and operation of silicon solar cells to enhance their performance in environments where magnetic fields are present. Theoretical framework: the study provides a theoretical framework based on the one-dimensional continuity equation, offering a systematic approach to analyzing and predicting the behavior of solar cells under magnetic field conditions. These findings contribute to advancing the understanding of how external factors such as magnetic fields can impact the operation and efficiency of silicon solar cells, thereby guiding future research and development efforts in photovoltaic technology.

The originality and value of this study lie in its contribution to advancing the understanding of how magnetic fields influence silicon solar cell performance, providing both theoretical insights and potential practical applications in diverse technological contexts.

This study is of great significance in revealing the interactive and coordinated relationship between tourism development and the ecological environment, improving the level of environmental governance in the process of tourism economic development and realising the dual-carbon goal and sustainable development of the tourism industry.

This paper performs slack-based measure (SBM)-data envelopment analysis (DEA) analysis, benchmark regression and threshold effect measurement on a sample of 277 cities in China from 2011 to 2019, to estimate the impact of the digital economy on tourism eco-efficiency and to identify the moderating role of environmental regulation.

China’s tourism eco-efficiency shows a spatio-temporal characteristic of steady growth amid fluctuations. The digital economy has a positive facilitating effect on tourism eco-efficiency, which is non-linear with a single threshold effect (0.631), and when the level of the digital economy exceeds the threshold value, its facilitating effect increases from 0.696 to 0.927. Environmental regulation does not play the role of “the icing on the cake” during the digital economy’s impact on tourism eco-efficiency.

This study for the first time includes the digital economy, eco-efficiency and environmental regulation in the research perspective, and analysed the mechanism of action between the three, expanding the depth of research on the digital economy and environmental regulation in the field of tourism. Meanwhile, based on the development needs of policy specialisation and industrial refinement, this study has strong practical significance when conducted at the city level.

This study aims to unravel the complex coopetitive interactions in supply chains. It delves into the paradoxical relationship between cooperative and competitive interactions among supply chain entities, offering a comprehensive exploration of coopetition’s manifestations and management across various supply chain types.

The study uses a three-phase methodology, beginning with a scoping review to establish a theoretical framework, followed by a systematic literature review yielding 130 papers and concluding with correspondence analysis using similarity indexes. This approach facilitates a deep dive into the diverse aspects of coopetition, including its drivers, practices, outcomes and associated risks.

The research identifies three distinct types of coopetition in supply chains: technology-based, socially based and channel-based. These models are underscored by specific drivers and outcomes, with technology-based coopetition focusing on market competitiveness and operational capacity, socially based on trust and power dynamics and channel based on product characteristics. The study introduces five propositions for further investigation and provides a comprehensive typology of coopetition within supply chains.

The study’s findings are limited by the scope of the existing literature and the chosen academic databases. Future research should empirically validate the proposed coopetition configurations and propositions, exploring their applicability in other, less studied supply chains.

The study offers practitioners a valuable typology and framework to understand and manage coopetition in their respective supply chains. This typology serves as a decision-making tool for identifying suitable coopetition strategies and maximizing their benefits while mitigating associated risks.

This study stands out for its unique approach to categorizing coopetition in supply chains, offering a novel typology that goes beyond the manufacturer’s perspective. It fills a significant gap in the literature by providing a broad view of coopetition, considering various supply chain types and their respective coopetitive dynamics.

We aim to examine two issues. First, we intend to identify the best performing expected return proxies. Second, we investigate whether the expected return proxies for individual stocks can track the corresponding realized returns during extremely good or extremely bad times of the economic environment related to business conditions, stock market valuation and broad market performance.

We construct four sets of expected return proxies, including: (1) characteristic-based proxies; (2) standard risk-factor-based proxies; (3) risk-factor-based proxies that allow betas to vary with firm characteristics and (4) macroeconomic-variable-based proxies. First, we estimate expected returns for individual stocks using newly developed methods and evaluate the performance of these expected return proxies based on the minimum variance criterion of Lee et al. (2020). Second, we regress expected return proxies and realized returns on indicator variables that capture the extreme phases of the economic environment. Then we compare the estimated coefficients from these two sets of regressions and see if they are similar in magnitude via formal hypothesis testing.

We find that characteristic-based proxies and risk-factor-based proxies that allow betas to vary with firm characteristics are the two best performing proxies. Therefore, it is important to allow betas to vary with firm characteristics in constructing expected return proxies. We also find that model-based expected return proxies do a reasonably good job capturing actual returns during extremely bad and extremely good phases of business cycles measured by leading economic indicators, consumer confidence and business confidence. However, there is a large gap between the adjustment of model-based expected returns and realized returns during extreme episodes of stock market valuation or broad market performance.

We examine four types of expected return proxies and use the newly developed methodology as in Lee et al. (2020) to see which one is the best. In addition, we document whether model-based expected returns from individual stocks adjust partially or fully to keep pace with actual returns in response to changing economic conditions. No prior studies have examined these two issues.

This study examines the psychological factors that directly influence individuals’ intentions to book or arrange reservations through resort hotel websites within the context of the Unified Theory of Acceptance and Use of Technology (UTAUT). Specifically, this study focused on identifying and understanding the key drivers of online purchase intentions, including performance expectancy, effort expectancy, social influence and facilitating conditions within the UTAUT model.

This study used the UTAUT as a theoretical framework. A quantitative research approach was adopted and data were collected through surveys using a five-point Likert scale. The sample consisted of 270 participants, selected through purposive sampling. Data analysis was performed using Smart PLS software.

The results indicate that performance and effort expectancy significantly influence online purchase intentions. However, social influence did not significantly affect online purchase intention. By contrast, facilitating conditions significantly and positively influence online purchase intention.

These findings have practical implications for hotel managers and marketers. Emphasizing performance, effort expectations and facilitating conditions can improve customer perceptions of website usefulness and directly increase their intention to book. The limited impact of social influence suggests the need to focus less on social recommendations or endorsements in online marketing efforts and prioritize individual factors and objective information.

This study contributes to the field of technology and tourism by examining the psychological factors that directly influence users’ intention to purchase from resort hotel websites. This extends the understanding of online purchase intentions in the context of resort tourism and highlights the importance of facilitating conditions. This study also partially confirms the applicability of the UTAUT model in this domain and provides insights for future research on online purchase intentions in resort tourism.

Social media usage has been documented to affect the psychological well-being of its users. This study aims to examine how social media overload influences cognitive fatigue among individuals in Malaysia.

This study employed a comprehensive research framework based on the stressor-strain-outcome (SSO) model to examine how perceived overload affects social media cognitive fatigue through emotional exhaustion and anxiety. Survey data were gathered from 451 social media users in Malaysia, and data analysis was performed using PLS-SEM.

The findings revealed that information overload, communication overload and interruption overload are antecedents of emotional exhaustion. Communication overload, interruption overload and cognitive overload were identified as antecedents of anxiety, while emotional exhaustion and anxiety were confirmed as predictors of social media cognitive fatigue. However, pathway analysis indicated no relationship between emotional exhaustion and anxiety.

Our study contributes to the literature on media technology and media psychology by examining the psychological mechanisms (emotional exhaustion and anxiety). The findings offer implications for service providers, practitioners and social media users, as they facilitate measures and strategies to mitigate the adverse effects of social media while elevating psychological well-being.

Using employee voice to advocate for customers' requirements, improves hospitality service. Organizations must understand what motivates or deters employee customer-oriented voice behaviour (COVB) to achieve its goals and enhance performance. This research investigates the predictors and outcomes of COVB of front-line employees (FLEs) in the hotel industry.

The study used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to steer the article search, screening, and inclusion. The research identified the extant studies conducted in both, high/low power distance countries that met the search criteria using the databases of SCOPUS, Web of Science, EBSCOHost and through snowballing of references.

The content analysis of 55 selected studies identified four themes that explain FLEs’ COVB in the hospitality industry. These four themes include customer-related, employee-related, organizational and leadership factors. Moreover, it was found that theoretical frameworks of the most of published studies are dominated by social exchange and conservation resource theories.

This study suggests hospitality firms to develop management strategies to foster FLEs COVB especially long-term personality trainings for FLEs is suggested for innovative and novel ideas.

This is the first study, as per our knowledge, on the hospitality industry that has been conducted to analyse and synthesize the literature related to FLEs’ COVB.