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In order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to propose a scientific and reasonable centralized traffic control (CTC) system risk assessment method.

First, system-theoretic process analysis (STPA) is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis. Then, to enhance the accuracy of weight calculation, the fuzzy analytical hierarchy process (FAHP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and entropy weight method are employed to calculate the subjective weight, relative weight and objective weight of each index. These three types of weights are combined using game theory to obtain the combined weight for each index. To reduce subjectivity and uncertainty in the assessment process, the backward cloud generator method is utilized to obtain the numerical character (NC) of the cloud model for each index. The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system. This cloud model is used to obtain the CTC system's comprehensive risk assessment. The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud. Finally, this process yields the risk assessment results for the CTC system.

The cloud model can handle the subjectivity and fuzziness in the risk assessment process well. The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.

This study provides a cloud model-based method for risk assessment of CTC systems, which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment, achieving effective risk assessment of CTC systems. It can provide a reference and theoretical basis for risk management of the CTC system.

The primary purpose of this paper is to identify the so-called core authors and their publications according to pre-defined criteria and thereby direct the users to the fastest and easiest way to get a picture of the otherwise pervasive field of bankruptcy prediction models. The authors aim to present state-of-the-art bankruptcy prediction models assembled by the field's core authors and critically examine the approaches and methods adopted.

The authors conducted a literature search in November 2022 through scientific databases Scopus, ScienceDirect and the Web of Science, focussing on a publication period from 2010 to 2022. The database search query was formulated as “Bankruptcy Prediction” and “Model or Tool”. However, the authors intentionally did not specify any model or tool to make the search non-discriminatory. The authors reviewed over 7,300 articles.

This paper has addressed the research questions: (1) What are the most important publications of the core authors in terms of the target country, size of the sample, sector of the economy and specialization in SME? (2) What are the most used methods for deriving or adjusting models appearing in the articles of the core authors? (3) To what extent do the core authors include accounting-based variables, non-financial or macroeconomic indicators, in their prediction models? Despite the advantages of new-age methods, based on the information in the articles analyzed, it can be deduced that conventional methods will continue to be beneficial, mainly due to the higher degree of ease of use and the transferability of the derived model.

The authors identify several gaps in the literature which this research does not address but could be the focus of future research.

The authors provide practitioners and academics with an extract from a wide range of studies, available in scientific databases, on bankruptcy prediction models or tools, resulting in a large number of records being reviewed. This research will interest shareholders, corporations, and financial institutions interested in models of financial distress prediction or bankruptcy prediction to help identify troubled firms in the early stages of distress.

Bankruptcy is a major concern for society in general, especially in today's economic environment. Therefore, being able to predict possible business failure at an early stage will give an organization time to address the issue and maybe avoid bankruptcy.

To the authors' knowledge, this is the first paper to identify the core authors in the bankruptcy prediction model and methods field. The primary value of the study is the current overview and analysis of the theoretical and practical development of knowledge in this field in the form of the construction of new models using classical or new-age methods. Also, the paper adds value by critically examining existing models and their modifications, including a discussion of the benefits of non-accounting variables usage.

The sharing economy has evolved as a result of the diffusion of information and communication technology and facilitates collaborative consumption and production otherwise known as value co-creation. The present research aims to explore the consumer responses to value co-creation in sharing economy such as satisfaction, brand preference and enduring buyer–platform relationships, amid consumer's CSR concerns.

Drawing on the sharing economy and value co-creation literature and rooted in the stimulus-organism-response framework, an online panel data provider was employed to recruit 393 actual sharing economy consumers from the United States. Empirical analyses are performed using structural equation modeling through Amos, version.27.

Findings confirm that value co-creation intentions contribute to consumers' satisfaction, brand preference and sustainable social relationships in the sharing economy. As expected, heightened concerns of corporate social responsibility (CSR) led to decreased consumer satisfaction with the sharing economy platform.

The study contributes to the digital sharing economy literature by emphasizing the role of CSR perceptions for building long-term relationships (buyer–platform relationships) where value co-creation is crucial.

Environmental tourism impacts are considered to be unbalanced. The implementation of environmental sustainability focuses on restoring a balance through environmentally responsible behavior. As Generation Z was found in recent studies to exhibit divergent levels of environmentally responsible behavior compared to other generations, but also to have intra-generational differences, this study aims to explore the underlying reasons and explanations behind their attitudes and behavioral attempts.

Four focus group discussions with young people belonging to Generation Z allow to probe deep into their environmental sustainability orientation.

The results of this study demonstrate that Generation Z’s environmental attitude is triggered by social pressure, social media, as well as by the COVID-19 pandemic. For their touristic behavioral intention, they concentrate predominantly on climate-friendly travel and on-site mobility, waste avoidance as well as emphasizing economic and social sustainability. By furthermore highlighting Generation Z’s responsibility ascription to the supply and the demand side, in addition to illustrating the demand for framework conditions to be created from governments and destinations, the knowledge scope on environmental sustainability is expanded.

In particular, this study enriches environmentally responsible behavior research by incorporating the perspective of Generation Z, while it deepens Generation Z’s behavioral understanding. Furthermore, the results of this study allow to derive implications for tourism policymakers.

环境旅游影响被认为是不平衡的。环境可持续性的实施侧重于通过对环境负责的行为来恢复平衡。由于最近的研究发现Z一代与其他几代人相比表现出不同的环境责任行为水平, 且存在代际差异, 本研究探讨了他们的态度和行为尝试背后的潜在原因和解释。

采用四个焦点小组与Z世代年轻人讨论, 深入探究他们的环境可持续性导向。

这项研究的结果表明, Z世代的环境态度是由社会压力、社交媒体以及COVID-19大流行引发的。对于他们的旅游行为意向, 他们主要关注气候友好型旅行和现场移动性, 避免浪费以及强调经济和社会的可持续性。通过进一步强调Z世代对供给侧和需求侧的责任归因, 并阐释政府和目的地对框架条件的需求, 扩大了环境可持续性的知识范围。

特别地, 本研究通过纳入Z世代的视角, 丰富了环境责任行为研究, 加深了Z世代的行为理解。此外, 本研究的结果可以为旅游政策制定者提供启示。

Los impactos medioambientales del turismo se consideran desequilibrados. La implementación de la sostenibilidad medioambiental se centra en restablecer el equilibrio mediante un comportamiento responsable con el medio ambiente. Estudios recientes señalan que la Generación Z muestra niveles divergentes de comportamiento responsable con el medio ambiente en comparación con otras generaciones, pero también presenta diferencias intra-generacionales. Este estudio explora las razones y explicaciones subyacentes a sus actitudes e intenciones de comportamiento.

Cuatro grupos de discusión con jóvenes de la Generación Z permiten profundizar en su orientación hacia la sostenibilidad medioambiental.

Los resultados de este estudio evidencian que la actitud medioambiental de la Generación Z está provocada por la presión social, medios sociales, así como por la pandemia del COVID-19. En cuanto a su intención de comportamiento turístico, se concentran predominantemente en los viajes respetuosos con el clima y la movilidad in situ, evitar residuos, así como en hacer hincapié en la sostenibilidad económica y social. Al destacar la responsabilidad que la Generación Z atribuye a la oferta y la demanda, además de inculcar la demanda para la creación de condiciones marco por parte de gobiernos y destinos, se amplía el alcance del conocimiento sobre la sostenibilidad medioambiental.

En particular, este estudio enriquece la investigación sobre el comportamiento responsable con el medio ambiente al incorporar la perspectiva de la Generación Z y profundizar en la comprensión del comportamiento de esta generación. Asimismo, los resultados de este estudio permiten desarrollar implicaciones para los responsables de las políticas turísticas.

The purpose of this study is to analyze state-of-the-art knowledge of artificial intelligence (AI) research in hospitality.

This study adopts the theory-context-methods framework to systematically review 100 AI-related articles recently published (i.e. from 2021 to April 2023) in three top-tier hospitality journals, namely, the International Journal of Contemporary Hospitality Management, International Journal of Hospitality Management and Journal of Hospitality Marketing and Management.

Findings suggest that studies of AI applications in hospitality are mostly theory-driven, whereas most AI methods research adopts a data-driven approach. State-of-the-art AI applications research exhibits the most interest in service robots. In AI methods research, little attention was paid to the amid-service/experience.

This study reveals inadequacies in theory, context and methods in contemporary AI research. More research from hospitality suppliers’ perspectives and research on generative AI applications are advocated in response to the unveiled research gaps and recent AI developments.

This study classifies the most recent AI research in hospitality into two main streams – AI applications research and AI methods research – and discusses the gaps in each research stream and latest AI developments. The paper then suggests future research directions to guide researchers in advancing AI research in hospitality.

Building upon the cognition-affect-behavior (CAB) model and script theory, this research aims to enrich the existing literature on historic town tourism consumption by offering empirical evidence of how the cognitive and affective images of historic towns contributes to tourists' memorable tourism experiences (MTE) and revisit intention, while identifying the cognitive image dimensions that are relevant for evaluating historic towns.

An on-site survey was conducted with 486 local tourists who visited the historic towns in Chengdu. partial least squares-structural equation modeling (PLS-SEM) was utilized to assess both the measurement and structural models.

(1) Cognitive image emerged as a significant predictor of affective image; (2) Both cognitive image and affective image had a positive influence on MTE, in which cognitive image played a more dominant role in shaping MTE; (3) MTE was found to strongly predict revisit intention among tourists; (4) MTE and affective image mediated the relationship between cognitive image and revisit intention.

This research highlights the value of incorporating cognitive and affective constructs in predicting MTE, and the proposed integrated framework of the CAB model and script theory exhibits superior predictive power in understanding tourists' revisit intention.

This research provides empirical insights about how historic towns improve their marketing strategies as short day-trip destinations.

This research provides a novel insight on the applicability of an integrated model combining the CAB model and script theory in explaining the revisit behavior of local tourists within the context of historic towns.

The aim was not to perform a systematic review but firstly to search in PubMed, Science Direct, Scopus and Web of Science databases on the papers published in the last five years using tools for reviewing the statement of preferred information item for systematic reviews without focusing on a randomized analysis and secondly to perform a bibliometric analysis on the properties of films and coatings added of tocopherol for food packaging.

On January 24, 2022, information was sought on the properties of films and coatings added of tocopherol for use as food packaging published in PubMed, Science Direct, Scopus and Web of Science databases. Further analysis was performed using bibliometric indicators with the VOSviewer tool.

The searches returned 33 studies concerning the properties of films and coatings added of tocopherol for food packaging, which were analyzed together for a better understanding of the results. Data analysis using the VOSviewer tool allowed a better visualization and exploration of these words and the development of maps that showed the main links between the publications.

In the area of food science and technology, the development of polymers capable of promoting the extension of the shelf life of food products is sought, so the knowledge of the properties is vital for this research area since combining a biodegradable polymeric material with a natural antioxidant active is of great interest for modern society since they associate environmental preservation with food preservation.

This study aims to analyze review research in hospitality, identifying the structure and most recent developments in current hospitality review studies while providing exploratory insights for future research in this research area.

Using bibliometric analysis, content analysis and a quantitative systematic literature review, this study provides a comprehensive review and critical analysis of 128 review studies published in leading hospitality journals (International Journal of Contemporary Hospitality Management, International Journal of Hospitality Management and Journal of Hospitality Marketing and Management).

This paper presents a comprehensive and in-depth discussion based on the title, journal source, author contribution, year of publication, sample size, selected period, database selection, methodology, data collection methods, themes, regional selection, keywords, abstracts and results of the hospitality review studies analyzed. The findings provide new insights to advance the theoretical and practical implications of review studies in hospitality.

This research provides critical insights for both hospitality review studies and academic and industry hospitality personnel.

As a pioneering study in research on review studies, the results of this paper focus not only on a systematic overview and assessment of recent hospitality review works but also on the future agenda of hospitality and review studies.

Plastic pollution is a major issue that plagues modern society. Scholars are interested in comprehending consumers’ behavioural actions to address plastic pollution. This study aims to delve into the determinants of consumers’ engagement with social media as a medium to address plastic pollution.

A conceptual model is developed that extends the behavioural reasoning theory (BRT). Using a quantitative approach, 476 responses underwent structural equation modelling analysis.

Results indicate that “reasons for” positively correlate with attitude and intention towards socially responsible engagement. Contrarily, “Reasons against” demonstrated a positive association with socially responsible engagement intention. Attitudes favouring socially responsible engagement correlate positively with the underlying intention. The moderation analysis underscores the positive relation of social return on social media with consumers’ attitude and their “reasons for” leaning towards socially responsible engagement intention. Notably, a positive connection was established between socially responsible engagement intention and the trifecta of consumption, contribution and content creation behaviours.

By enhancing the BRT, this research sheds light on novel perspectives regarding consumers’ engagement on social media platforms. Distinctively, it is among the handful of studies probing the influence of behavioural intention across diverse behavioural outcomes. The insights gained from this study, grounded in empirical evidence from an emerging market, are poised to guide policymakers, governmental agencies and industry practitioners in formulating effective strategies to combat plastic pollution. Additionally, the study can assist in achieving the UN sustainable development goals (SDGs), specifically SGD 12, SGD 13, SDG 14 and SGD 17.

This study aims to examine authentic leadership behavior (ALB) and empowering leadership behavior (ELB) as predictors of innovative work behavior (IWB) while assessing the mediating role of work-family enrichment (WFE).

Through the explanatory research design, data was retrieved from 303 respondents from 16 small-sized hotels in Ghana and analyzed quantitatively using descriptive and inferential statistics (hierarchical component analysis within PLS-SEM).

The study’s findings revealed that both ALB and ELB positively and significantly relate to IWB. Additionally, our study found that WFE partially mediated the nexus between ALB and IWB as well as ELB and IWB.

The findings of our study imply that in the pursuit of excellence, ALB and ELB in the hospitality industry are crucial, as they not only nurture employee potential but also help employees to thrive both at home and at the workplace.

The hospitality literature lacks a comprehensive understanding of the underlying mechanism by which ALB and ELB influence IWB. To the best of the authors' knowledge, our study is the first empirical study conducted on ALB, ELB, WFE, and IWB in the hospitality industry.