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Wellness tourism is growing in importance as increasing numbers of travelers place a priority on their health and well-being by traveling. This study examined the relationships between wellness tourism destination attributes, perceived quality, perceived mental health, eudaimonic well-being, overall satisfaction and behavioral loyalty to corroborate a model explaining wellness tourism destination loyalty in Thailand.

The conceptual model of this study was examined using a survey research design. The survey questionnaire was distributed to Chinese tourists who had previously traveled to Thailand and engaged in wellness tourism activities during their trip.

The findings revealed that healthful food choices, core facilities and staff service significantly influenced perceived quality. This perceived quality was a crucial factor in determining perceived mental health, which in turn impacted eudaimonic well-being. Overall satisfaction was directly influenced by perceived quality, perceived mental health and eudaimonic well-being. Additionally, perceived quality had a direct effect on behavioral loyalty.

With the growing global interest in wellness and travel, this study offers valuable insights for tourism marketers in Thailand to enhance their wellness tourism strategies. Tourism organizations should emphasize the quality of food, facilities and staff service to attract wellness-oriented travelers.

This study highlights the interconnectedness of perceived quality, good mental health and eudaimonic well-being. High-quality experiences contribute to improved mental health and in turn enhance eudaimonic well-being.

In a reflection of individuals’ interest in maintaining a healthy lifestyle, nutraceutical restaurants, which provide health benefits, have emerged on the market. However, little is known about the underlying factors and mechanisms of the consumption of nutraceutical foods. Therefore, grounded in an extended cognitive–affective–conative model, this study examines the role of dining motivations and restaurant attributes in explaining an integrated model that focuses on customers’ loyalty formation process.

Data were collected from 893 Chinese customers who had recently dined at traditional Chinese medicine restaurants. Using partial least squares structural equation modeling, this study examined the structural relationships among dining motivations, restaurant attributes, customers’ perceived benefits, overall satisfaction, place attachment and revisit intentions.

The results of a confirmatory factor analysis revealed that two main motivations (i.e. health and traditional culture) and five restaurant attributes (i.e. food, service staff food recommendation, service staff service quality, furniture and tableware and atmosphere) are stimuli that influence customers’ perceived benefits. This study also revealed that four types of perceived benefits (functional, emotional, social and epistemic) significantly affect overall satisfaction and place attachment, which determine revisit intentions.

The findings of this study help identify not only important dining motivations and restaurant attributes but also their roles in loyalty formation with respect to traditional Chinese medicine restaurants. Thus, the results contribute to an improved understanding of how to satisfy customers’ dining motivations and efficiently manage restaurant attributes to strengthen customer loyalty.

This study is among the first to simultaneously examine the effects of customer motivation and restaurant attributes and to explain how they affect customer loyalty behaviors at traditional Chinese medicine restaurants.

This study develops a model and algorithm to solve the decentralized resource-constrained multi-project scheduling problem (DRCMPSP) and provides a suitable priority rule (PR) for coordinating global resource conflicts among multiple projects.

This study addresses the DRCMPSP, which respects the information privacy requirements of project agents; that is, there is no single manager centrally in charge of generating multi-project scheduling. Accordingly, a three-stage model was proposed for the decentralized management of multiple projects. To solve this model, a three-stage solution approach with a repeated negotiation mechanism was proposed.

The experimental results obtained using the Multi-Project Scheduling Problem LIBrary confirm that our approach outperforms existing methods, regardless of the average utilization factor (AUF). Comparative analysis revealed that delaying activities in the lower project makespan produces a lower average project delay. Furthermore, the new PR LMS performed better in problem subsets with AUF < 1 and large-scale subsets with AUF > 1.

A solution approach with a repeated-negotiation mechanism suitable for the DRCMPSP and a new PR for coordinating global resource allocation are proposed.

This study aims to explore work–life integration (WLI) as a crucial mechanism underpinning the transformation of the hospitality and tourism industry from shifts in work paradigms, including rapid technological advancements, flexible work forms, quiet quitting, increasing awareness of well-being, cultural diversity and gender disparity. It further develops the coping strategies and research agenda.

Through the bridged lens of the work–life boundary theory and conservation of resources theory, this research critically analyzes the literature on emerging work paradigms and WLI and develops a conceptual framework guiding the systematic examination of the WLI mechanisms underpinning the influence from work paradigm shifts.

The analysis reveals the underpinning mechanisms in managing WLI, highlighting the importance of systematic and customized work–life management strategies in adapting to evolving work paradigms. An integrated conceptual framework is developed to guide future research and practical applications.

This study underscores the critical need for strategic WLI management, emphasizing its importance for sustainable industry development. It also proposes actionable work–life management strategies for stakeholders, aiming for positive outcomes at personal, organizational and industrial levels amid the paradigm shifts.

The comprehensive conceptual framework uniquely bridged two theories that afford a novel, interconnected and in-depth approach to analyzing how work paradigm shifts reshape the industry. It further broadens the research agenda on WLI, with promising research directions proposed for advancing the understanding of the ever-evolving hospitality and tourism work landscapes.

This study aims to assess the factors influencing the effective implementation of extended producer responsibility (EPR) practices within the context of sustainable accounting goals and circular economy principles. It seeks to provide insights into the significance of EPR policies for manufacturing industries striving to enhance their environmental, social and governance performance while ensuring sustainable accounting of their business operations.

The methodology proposed in this article is based on the decision-making trial and evaluation laboratory (DEMATEL) technique. This approach formulates a structural framework for evaluating influential elements among critical recognized factors. By using DEMATEL, the study examines the interconnectedness between assessed factors through a cause-and-effect diagram, facilitating the integration of EPR into sustainable accounting practices.

The research findings reveal that the most impactful contributors to sustainable accounting practices of EPR within the framework of sustainable development goals and circular economy are producers, consumers, eco-design, public awareness and the support of local authorities. These findings underscore the importance of considering these factors in implementing EPR and advancing sustainable accounting practices.

This paper contributes to the literature by proposing a DEMATEL-based model for evaluating the factors affecting the implementation of EPR within the context of sustainable accounting goals and circular economy principles.

Sustainability is of growing significance in the contemporary business landscape as organizations strive to minimize their environmental impact and optimize supply chain (SC) operations. Gaining insights into the influence of Triple A SC practices on sustainable performance can offer valuable perspectives for practitioners and policymakers. This study aims to comprehensively review existing academic literature on Triple A supply chain management (SCM) and sustainability, examining its impact on sustainable performance while identifying key influencing factors.

This review follows the six steps and 14 decisions of conducting a systematic literature review to comprehensively review 57 papers published between 2004 and 2023.

Based on the content analysis of the selected papers, this study summarizes the antecedents, practices and outcomes of Triple A SCM, with a particular focus on its implications for sustainability. This paper builds a conceptual framework from the descriptive and thematic findings to enrich the relevant aspects of Triple A SCM.

This study establishes a connection between Triple A SCM and sustainable performance by examining its impact on economic, social and environmental aspects. This review identifies research gaps and acknowledges the lack of specificity in implementing Triple A SCM across diverse industries, regions and competitive markets with varying external environments. It emphasizes the necessity to customize approaches based on contextual factors and provides valuable recommendations for future research to advance the concept of Triple A SCM.

This research aims to extract Industry 4.0 technological building blocks (TBBs) capable of value generation in collaborative consumption (CC) and the sharing economy (SE). Furthermore, by employing a mixed methodology, this research strives to analyse the relationship amongst TBBs and classify them based on their impact on CC.

Due to the importance of technology for the survival of collaborative consumption in the future, this study suggests a classification of the auxiliary and fundamental Industry 4.0 technologies and their current upgrades, such as the metaverse or non-fungible tokens (NFT). First, by applying a systematic literature review and thematic analysis (SLR-TA), the authors extracted the TBBs that impact on collaborative consumption and SE. Then, using the Bayesian best-worst method (BBWM), TBBs are weighted and classified using experts’ opinions. Eventually, a score function is proposed to measure organisations’ readiness level to adopt Industry 4.0 technologies.

The findings illustrated that virtual reality (VR) plays a vital role in CC and SE. Of the 11 TBBs identified in the CC and SE, VR was selected as the most determinant TBB and metaverse was recognised as the least important. Furthermore, digital twins, big data and VR were labelled as “fundamental”, and metaverse, augmented reality (AR), and additive manufacturing were stamped as “discretional”. Moreover, cyber-physical systems (CPSs) and artificial intelligence (AI) were classified as “auxiliary” technologies.

With an in-depth investigation, this research identifies TBBs of Industry 4.0 with the capability of value generation in CC and SE. To the authors’ knowledge, this is the first research that identifies and examines the TBBs of Industry 4.0 in the CC and SE sectors and examines them. Furthermore, a novel mixed method has identified, weighted and classified pertinent technologies. The score function that measures the readiness level of each company to adopt TBBs in CC and SE is a unique contribution.

This study aims to provide a comprehensive analysis of two-sided matching (TSM) research, an interdisciplinary field that integrates both theoretical and practical perspectives. By examining 756 research articles from the Web of Science database, this paper seeks to identify key trends, collaboration patterns and emerging research topics within the TSM domain.

The research utilizes bibliometric analysis combined with a structural topic model to analyze TSM-related articles published between January 1, 2000, and September 30, 2022. The study identifies leading subfields, journals, countries/regions and institutions based on publication volume, total citations and average citations per article. Interaction and collaboration patterns among these entities are examined through co-occurrence and coupling networks. Additionally, five major research topics are identified and explored using topic modeling and co-word networks. This hybrid knowledge mining approach better reveals the inherent structural changes in topic clusters. Topic distribution and network analysis are beneficial in capturing the attention allocation of different entities to knowledge.

The analysis reveals five prominent research topics in TSM: communication resource allocation, stable matching research, computing task assignment, TSM decision-making and market matching mechanism design. These topics represent the main directions of TSM research. The study also uncovers a shift in research focus from theoretical aspects to practical applications. Furthermore, the distribution of knowledge and interaction patterns among key entities align with the identified research trends.

This study offers a novel and detailed overview of TSM research highlighting significant trends and collaboration patterns within the field. By integrating bibliometric methods with structural topic modeling the study provides unique insights into the evolution of TSM research making it a valuable resource for both academic and professional communities.

The study aims to analyze the synergy of artificial intelligence (AI), with scientometrics, webometrics and bibliometrics to unlock and to emphasize the potential of the applications and benefits of AI algorithms in these fields.

By conducting a systematic literature review, our aim is to explore the potential of AI in revolutionizing the methods used to measure and analyze scholarly communication, identify emerging research trends and evaluate the impact of scientific publications. To achieve this, we implemented a comprehensive search strategy across reputable databases such as ProQuest, IEEE Explore, EBSCO, Web of Science and Scopus. Our search encompassed articles published from January 1, 2000, to September 2022, resulting in a thorough review of 61 relevant articles.

(1) Regarding scientometrics, the application of AI yields various distinct advantages, such as conducting analyses of publications, citations, research impact prediction, collaboration, research trend analysis and knowledge mapping, in a more objective and reliable framework. (2) In terms of webometrics, AI algorithms are able to enhance web crawling and data collection, web link analysis, web content analysis, social media analysis, web impact analysis and recommender systems. (3) Moreover, automation of data collection, analysis of citations, disambiguation of authors, analysis of co-authorship networks, assessment of research impact, text mining and recommender systems are considered as the potential of AI integration in the field of bibliometrics.

This study covers the particularly new benefits and potential of AI-enhanced scientometrics, webometrics and bibliometrics to highlight the significant prospects of the synergy of this integration through AI.

There is a dearth of knowledge regarding how user dependency offers valuable resources to develop the intellectual capital of social streaming apps (SSAs) companies. This study aims to integrate major conceptual components of the UandD model, identify contextualized goal-oriented SSA dependency and empirically evaluate their interrelated user-dependency relationships in the SSA context.

A mixed-methods approach was utilized in this study. First, user gratifications were elicited through a qualitative approach, considering the exploratory stage of the SSA phenomenon. Second, statistical methods were applied to investigate and extract the sub-dimensions of SSA dependency. At last, a research model was developed grounded on the UandD model and empirically validated using the quantitative approach.

The results validated the gratification-dependency-attitude-behavior relationships hypothesized by the UandD framework in SSA. The role of user-SSA dependency in enhancing intellectual capital in the social media industry has been highlighted in this study.

This research not only provides an opportunity for the UandD model to realize its theoretical potential as envisioned by scholars but also contributes to the scholarship on social streaming apps and media dependency theory by conceptualizing goal-oriented dependency in SSAs.

The research results will guide digital media practitioners to a more nuanced understanding of the relationships between their users and modern digital media apps and thus empower the practitioners to better manage their intellectual capital based on the facilitation of their users’ dependency.

This work is one of the pioneers in contextualizing the UandD model in the SSA field, refining and measuring the SSA dependency and its distinct subdimensions and employing mixed-methods to offer a comprehensive understanding of how user dependency boosts intellectual capital in the SSA industry.