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The aim of this paper is to review and categorise the body of existing research in order to better understand the state of food tourism. The primary objective of this study is to identify emerging themes in the area of food tourism and to highlight the relationships among them.

This research consists of a systematic literature review of academic articles from the Scopus and Web of Science databases.

Ten themes of Food Tourism emerged from the analysis, i.e. Food Tourism and Local Food, Food Tourism and Sustainability, Food Tourism and Economy, Food Tourism and Food waste management, Food Tourism and Culture, Food Tourism and Environment, Food Tourism and Information Technology, Food Tourism and COVID-19, Food Tourism and Post pandemic consumer trust and Food Tourism and Tourism and Hospitality sector.

This study elaborates on the theoretical pieces of evidence on the connection between food and tourism. Not only limited to food tourism, but this paper also contributes to the literature in the area of economy, sustainability, post-COVID-19, food waste management, environment and technological innovations in food tourism.

This study contributes to a deeper understanding of the topic at hand. The study begins by systematically examining the topic to offer a thorough and in-depth analysis of food tourism. There is not a single study which has covered these many themes of food tourism, which makes it an important contribution to the literature.

This paper examines the ways in which Chinese university middle managers evaluate subordinate performance in response to the Chinese Double First-Class University Plan, a national project that ranks the performance of universities. In exploring compromise arrangements, the hybridised valuing activity of middle managers is found to be shaped by emergent and extant macro-foundations.

The qualitative data from 49 semi-structured interviews at five Chinese public universities were conducted. Drawing on macro-foundational studies and the sociology of worth (SW) theory, the analysis helps to identify socially shared patterns of actions and outcomes.

The findings elucidate the interplay between diverse economic, social, political and institutional values and the compromise-making by middle managers. The authors find that contextual factors restrict Chinese academic middle managers' autonomy, preventing workable compromise. Through the selective adoption of international and local management practices, compromise has evolved into a private differential treaty at the operational level.

A nuanced explanation reveals how the macro-foundations of Chinese society influence middle managers who engage with accounting when facilitating compromise. This study helps outsiders better understand the complex convergence and divergence of performance evaluative practices in Chinese universities against the backdrop of global market-based forces and the moral dimensions of organisational life. The findings have wider implications for the Chinese government in navigating institutional steps and developing supportive policies to enable middle managers to advance productive but also sustainable compromise.

The purpose of this study is to explore the potential contribution of the metaverse to improve training and development as a function of human resource development (HRD) perspective. The authors explore the benefits and challenges of the metaverse and introduce cases of companies using the metaverse in training.

A narrative literature review was conducted to collect information on the metaverse in training. The authors reviewed peer- and non-peer-reviewed articles, book chapters, white papers, corporate websites and blogs and business magazines.

A total of 75 articles were reviewed, including 14 cases, which were summarized to demonstrate how companies are applying metaverse technology in training contexts. For a more in-depth review, three cases were selected and summarized in terms of context, process and outcomes.

The metaverse is an emergent topic in HRD. It has the potential to revolutionize the functions of training and development through the combination of advanced technologies, including virtual reality, augmented reality and mixed reality. This article is the foundational attempt to provide a comprehensive summary of existing literature and case studies that highlight the potential of the metaverse in training within the context of HRD.

The issue of energy efficiency is becoming increasingly prevalent globally due to factors such as the expansion of the population, economic growth and excessive consumption that is not sustainable in the long run. Additionally, healthcare facilities and hospitals are facing challenges as their operational costs continue to rise. The research aim is to develop strategic frameworks for managing green hospitals, towards energy efficiency and corporate governance in hospitals and healthcare facilities.

This research employs a qualitative case study approach, with a sample of ten hospitals examined through interviews with senior management, executives and healthcare facilities managers. Relevant data was also collected from literature and analysed through critical appraisal and content analysis. The research methodology is based on the use of grounded theory research methodologies to build theories from case studies.

The research developed three integrated conceptual strategic frameworks for managing hospitals and healthcare facilities towards energy efficiency, green hospital initiatives and corporate governance. The research also outlined the concepts of green hospitals and energy efficiency management systems and best practices based on the conclusions drawn from the investigated case studies.

The study is limited to the initiatives and experiences of the healthcare facilities studied in the Middle East and North Africa (MENA) region.

The research findings, conclusions, recommendations and proposed frameworks and concepts contribute significantly to the existing body of knowledge. This research also provides recommendations for hospital managers and policymakers on how to effectively implement and manage energy efficiency initiatives in healthcare facilities.

This paper aims to establish the determinants of production in the Spanish Designation of Origin (DO) area for Cava wine and forecasts sales to establish vineyard area variations that maintain market equilibrium.

By applying a vector autoregressive (VAR) model, the authors forecast demand and the consequent requirements for base wine production.

The results show that Cava sales determine the base wine supply. After forecasting demand and the consequent requirements for base wine, the authors’ results show that, to avoid oversupply, the vineyard area for Cava wine should not be increased.

The paper develops a simple and effective method for DOs affected by the current European wine plantation regulations to forecast from a supply and demand perspective and their surface needs in response to market changes.

This study contributes to the literature because, to the best of the authors’ knowledge, no other study has investigated the determinants of Cava supply and demand or defines a model to assess the effects of changes in growing areas. The model is applicable to other European protected designations of origin wines and would help policymakers to accurately establish vine planting authorizations.

Compared with traditional methods relying on manual teaching or system modeling, data-driven learning methods, such as deep reinforcement learning and imitation learning, show more promising potential to cope with the challenges brought by increasingly complex tasks and environments, which have become the hot research topic in the field of robot skill learning. However, the contradiction between the difficulty of collecting robot–environment interaction data and the low data efficiency causes all these methods to face a serious data dilemma, which has become one of the key issues restricting their development. Therefore, this paper aims to comprehensively sort out and analyze the cause and solutions for the data dilemma in robot skill learning.

First, this review analyzes the causes of the data dilemma based on the classification and comparison of data-driven methods for robot skill learning; Then, the existing methods used to solve the data dilemma are introduced in detail. Finally, this review discusses the remaining open challenges and promising research topics for solving the data dilemma in the future.

This review shows that simulation–reality combination, state representation learning and knowledge sharing are crucial for overcoming the data dilemma of robot skill learning.

To the best of the authors’ knowledge, there are no surveys that systematically and comprehensively sort out and analyze the data dilemma in robot skill learning in the existing literature. It is hoped that this review can be helpful to better address the data dilemma in robot skill learning in the future.

The purpose of this paper is to explore the moderating role of Lean Six Sigma (LSS) practices in explaining the relationship between quality management practices (QMPs) and quality performance.

Partial least square-based structural equation modeling (PLS-SEM) was used to empirically examine the moderating effect of LSS practices on QMPs and quality performance in Malaysian medical device manufacturing companies.

Findings revealed that both QMPs and LSS practices have a significant and positive effect on quality performance. Furthermore, LSS practices served as a substitute for moderating the positive relationship between QMPs and quality performance in such a way that the relationship becomes weaker as LSS practices increase.

LSS is acknowledged as the most well-known hybrid methodology; however, due to its relative newness, it has not been studied in great detail. Unlike previous studies, this paper argued that Lean and Six Sigma practices are distinct from its predecessor TQM practices; moreover, both Lean and Six Sigma practices do not need to substitute QM/TQM practices instead of complimenting the QMPs. In addition, this study adds to the growing body of QM literature by empirically examine the effect of LSS practices in moderating the relationship between QMPs and quality performance.

On the basis of the hierarchical organizational structure, this study investigated how empowering leadership influences hotel employees' proactive work behavior through multiple cross-level mediation processes. This study also investigated whether psychological empowerment, positive psychological capital, job characteristics and job embeddedness can activate the linkage of the aforementioned trickle-down effects.

This study draws data from 826 international tourist hotel employees at different times with hierarchical linear modeling (HLM) analyses.

Multiple cross-level mediation analyses indicate that (1) psychological empowerment mediates the cross-level influences of empowering leadership on job characteristics and positive psychological capital; (2) positive psychological capital mediates the cross-level influences of empowering leadership on job embeddedness and proactive work behavior; and (3) job embeddedness mediates the cross-level influences of psychological empowerment and job characteristics on proactive work behavior.

In the post-pandemic era, the valuable trickle-down effects of empowering leadership could spill over into employees' positive beliefs of psychological empowerment, which ultimately benefit working responsibility and organizational operations.

The results support and suggest that maximizing the benefits of empowering leadership could eventually foster proactivity and performance in the workplace under hospitality and tourism settings.

To measure the dynamic features of compassion as an emotional and behavioral construct, the present research used a univariate latent growth modeling (LGM) approach within the structural equation modeling (SEM) framework. The aim was to trace the dynamic development of compassion longitudinally in accounting and business students during a three-credit English course at university.

The suggested method ensures the measurement invariance over time, deals with the first order latent variable, traces its growth and takes into account the measurement errors. This longitudinal analytical method was used to explore the initial state and the growth of compassion in four points of time during a language course. The data were collected from 60 adult accounting and business students in four time phases using Sprecher and Fehr's Compassionate Love Scale and were analyzed in Mplus 8.4 with univariate LGM.

The model fit was accepted and the invariance of the latent factor was confirmed over time. The negative covariance between intercept and slope (second-order latent variables) suggested that lower initial scores in L2 learners' compassion show a faster increase in compassion over time as the mean of slope is larger than that of the intercept. L2 learners who started off at a higher level of compassion showed a slower change in compassion over time. This can be at least partly explained by the teacher's motivating role or learners' compassion but needs to be further explored in complementary qualitative phases for deeper insights.

In the present research, awareness was raised of the developmental nature of compassion as an emotional and behavioral construct essential to the accounting and business profession. The great strength of this research lies in the dynamic approach to the compassion construct and the LGM used to capture the temporal growth of compassion and how it evolved through the L2 course.

The purpose of this study is to test the impact of time and price sensitivity on consumer satisfaction and purchase intention on online-to-offline (O2O) takeout platforms and explore the moderating effect of purchase preference on time sensitivity and satisfaction, as well as price sensitivity and satisfaction, in order to guide market pricing.

A structural equation model (SEM) of customer purchase intention was constructed, and the relationships between the variables (time sensitivity, price sensitivity, satisfaction and purchase intention) were examined. The completed questionnaires of 349 respondents were collected from the Questionnaire Star platform in China. The research model and hypotheses were then tested. Analytic hierarchy procedure was used to determine the moderating effect of purchase preference. Finally, the study proposes a pricing strategy for customer-active selective services.

Satisfaction positively influences purchase intention, and price sensitivity significantly increases satisfaction and further increases purchase intention; however, time sensitivity negatively affects satisfaction. Specifically, purchase preference has strongly moderated the relationship between time, price sensitivity and satisfaction. In addition, the findings show that when purchase preference is high, the effect of price sensitivity on satisfaction is stronger, suggesting the importance of purchase preference in strengthening purchase intentions. The research work recommends a pricing strategy involving value-added pricing primarily for time-sensitive customers, which can help build a high-end brand image and reduce price competition. Reduced pricing is mainly for price-sensitive customers, which is conducive to stimulating consumption within a specific time. This pricing strategy is important for adjusting market sensitivity and flexibility.

This research provides new ideas for related disciplines and guidance for the differentiated pricing and promotion of takeout platforms, as well as a theoretical basis for the diversified development of takeout platforms, improvement of personalized service quality and enhancement of customer stickiness. This study fills gaps in the existing literature on the moderating effect of purchase preference on time sensitivity and satisfaction and price sensitivity and satisfaction.