When the World Health Organization (WHO) analyzed the culprits of global warming, it was found that in developed countries with relatively few high-polluting heavy industries, the medical sector is one of the sources of high-density carbon emissions. Therefore, the medical industry has a noticeable impact on the environment. Amid the current COVID-19 epidemic, this study adopts the theory of planned behavior (TPB), widely used in decision-making science. We selected a regional teaching hospital with 339 employees in Taiwan to obtain valid questionnaire data. We explore the comparative analysis of different intra-organizational stakeholders’ “attitudes,” “subjective norms,” and “perceived behavioral control” on the hospital’s behavioral intention to promote green healthcare. The results show that the TPB model has reliable explanatory power. All three factors have a positive and significant effect on promoting green hospital behavior. Among them, perceived behavioral control was the most notable. A comparative analysis of the differences among stakeholders in the research model shows that “medical administrators” and “nursing staff” have a higher proportion of significant influence effects in various hypotheses, highlighting the critical roles of these two groups in promoting green hospitals. This research policy suggests that the cross-departmental staff in the hospital put forward green innovation ideas, strengthen internal environmental education and management, establish a good incentive system for front-line nursing staff, and implement the sustainable development strategy of the hospital.

The evolution of the internet has increased the development of virtual communities. This has created an enabling environment for hospitality industry owners to interact, share and exchange information and ideas virtually. The COVID-19 pandemic has been a further catalyst in the dramatic expansion of virtual communities. This study aims to fill the gap by investigating the adoption of professional knowledge by the hospitality industry during the COVID-19 pandemic. Employing a sample of 285 members, this study found that self- and socially regulated learning affects knowledge adoption outcomes. In addition, technological innovation and benefits affect self- and socially regulated learning. These findings allow us to provide theoretical and practical implications.

Virtual reality technology in recent year has been a hot topic in tourism and hospitality field, both for research and practical purposes. Virtual technology has some limitation, such as costs and time, which can be addressed by a different form of virtual technology, which is video games. The purpose of this study is to analyze the effects of mental imagery, sense of presence and addition of storytelling towards tourism experience by using video games as a medium. Previous studies have analyzed effects of mental imagery and presence towards the tourism experience, but there is lack of research in using storytelling or narratives to add to the tourism experience. Storytelling has been studied in marketing field, and has been found to be a great marketing tool, because people love to hear stories. Video games can be a better tool for delivering storytelling, while providing solid mental imagery and a sense of presence to the location. The methodology proposed for this study is a quantitative approach, using survey questionnaire as a tool. Two sampling method is proposed. The first is to use players of location-based games as the population, and randomly take the sample. The second method is to uses tourists or potential tourists of a destination, have the respondents try out the game, and answer the questionnaire. The proposed research could provide the importance of storytelling to be added for virtual reality and video games usage in tourism and hospitality field.

This review paper aims at providing a systematic analysis of articles published in various journals and related to the uses and business applications of big data. The goal is to provide a holistic picture of the place of big data in the tourism industry. The reviewed articles have been selected for the period 2013-2020 and have been classified into 8 broad categories namely business strategy and firm performance; banking and finance; healthcare; hospitality; networks and telecommunications; urbanism and infrastructures; law and legal regulations; and government. While the categories are reflective of components of tourism industries and infrastructures, the meta-analysis is organized around 3 broad themes: preferred research contexts, conceptual developments, and methods used to research big data business applications. Main findings revealed that firm performance and healthcare remain popular contexts of research in the big data realm, but also demonstrated a prominence of qualitative methods over mixed and quantitative methods for the period 2013-2020. Scholars have also investigated topics involving the notions of competitive advantage, supply chain management, smart cities, but also ethics and privacy issues as related to the use of big data.

BACKGROUND Taiwan is grappling with the profound implications of a rapidly aging demographic, a trend contributing to an increased burden of critical illnesses. These diseases are now emerging as predominant contributors to mortality rates in the country. This demographic shift poses complex healthcare challenges and necessitates a reevaluation of resource allocation and care strategies to accommodate the escalating needs of this vulnerable segment of the population. OBJECTIVE In the wake of the COVID-19 pandemic, healthcare environments have encountered unprecedented risks, exacerbating the vulnerabilities of middle-aged and elderly individuals, especially those with pre-existing critical illnesses. This heightened risk landscape accentuates the critical need to closely analyze the factors influencing healthcare-seeking behavior in this demographic. Understanding their intentions and decision-making processes in seeking medical attention is now more crucial than ever to ensure that their healthcare needs are met effectively and safely during such a global health crisis. METHODS This study applied the Theory of Planned Behavior and examined critical illness patients' “behavioral intention” during COVID-19. Constructs such as “attitude,” “subjective norm,” “perceived behavioral control,” “perceived risk,” and “trust” were considered. Data from 526 valid questionnaires were analyzed using smart partial least squares structural equation modeling. RESULTS All 17 hypotheses within the research framework, including five major constructs and 12 sub-constructs, were supported. Trust emerged as the most significant construct, followed by attitude, perceived risk, perceived behavioral control, and subjective norm. The sub-constructs mediated the relationship between the major constructs and behavioral intention. Notably, there were significant differences in the healthcare behavioral intention model among the three common critical illnesses (hypertension, diabetes mellitus, and hyperlipidemia). CONCLUSIONS The expanded Theory of Planned Behavior offers a comprehensive framework for understanding the complex factors that influence the healthcare-seeking behaviors of middle-aged and elderly populations, particularly those with critical illnesses, in the context of the COVID-19 pandemic. This theoretical model illuminates how attitudes, subjective norms, perceived behavioral control, perceived risk, and trust interact to shape the intentions and decisions of these individuals when accessing healthcare services during a time of heightened vulnerability and public health challenges. CLINICALTRIAL NONE