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Since the outbreak of the COVID-19 pandemic, most organizations have experienced a sudden and unprecedented drop in revenue and productivity. However, the pandemic did not exclusively negatively impact organizations; rather, it resulted in both negative and positive effects. To delve into the multi-level process through which organizational outcomes change from negative to positive indicators, this study focuses on organizational resilience as a theoretical concept to overcome pandemic-related turmoil.

The authors conducted a multi-level analysis based on grounded theory with a sample of 30 healthcare employees who worked in hospitals and were simultaneously enrolled in a part-time master of business administration (MBA) program at a university in the Midwest. Of the 30 participants, 21 were from a single university hospital (UH), and the remaining 9 participants were from other hospitals (non-UH).

The authors analyzed the data and incorporated three existing perspectives of organizational resilience (attribute, process and multi-level views) into an integrated model. The authors identified 25 first-order concepts and 8 second-order themes and categorized them into 4 aggregate dimensions at different unit levels: organizational field, leadership, operation and individual units.

A resilient hospital operates as a cohesive system, with entities at various levels – from individuals and teams to the broader organization – collaborating seamlessly to foster resilience. Top management team (TMT) should persistently communicate with employees to provide information about the current crisis and clear strategic directions to reduce employees' fear and prevent anomie stemming from future uncertainty. Managers should not only be concerned about employees' physical safety from infection and psychological safety from isolation but also encourage employees to elicit meaningfulness from their work. Furthermore, TMT and human resource (HR) teams should adapt human resource management (HRM) practices to allow for flexibility and optimism in employee roles.

In this study, the authors utilized a qualitative methodology with grounded theory in order to develop a comprehensive model that holds theoretical, methodological and practical significance. Theoretically, the authors' novelty lies in the synthesis of three distinct perspectives: attribute, process and multi-level. The authors merged these approaches into a unified model, identifying precursors of resilience at different levels. Methodologically, the authors focused on hospitals as target samples, which were the foremost and representative organizations severely confronting the crisis and turmoil brought by the pandemic. The authors documented organizations' experiences amidst the crisis as they unfolded in real time rather than in hindsight. This approach highlights the immediacy and significance of the authors' research in the realm of crisis management. Practically, the authors' findings illuminate that organizational resilience can be developed through a collaborative effort. It emerges from coordinated interactions across various organizational actors, from employees and middle managers to the TMT.

This paper aims to examine the impact of metaverse experiences on customers’ offline behavioral intentions: How do customers’ visits to a hospitality business’s virtual property in the metaverse affect their intentions to visit the physical property in the real world?

Based on the general learning model and social cognitive theory, this research hypothesizes the positive impact of metaverse experiences on customers’ visit intentions and explores two boundary conditions for positive impact: user–avatar resemblance and servicescape similarity. Two experimental studies were conducted.

Metaverse experience has a significant impact on customers’ visit intentions, and this impact is moderated by user–avatar resemblance and servicescape similarity.

This research addresses the call for empirical studies regarding the effects of metaverse experience on people’s behavioral intentions.

As one of the earliest empirical studies on the marketing effects of the metaverse, this research provides a basis for future metaverse studies in the hospitality field.

The purpose of this study is to introduce new tools to develop a more precise and focused bibliometric analysis on the field of digitalization in healthcare management. Furthermore, this study aims to provide an overview of the existing resources in healthcare management and education and other developing interdisciplinary fields.

This work uses bibliometric analysis to conduct a comprehensive review to map the use of the unified theory of acceptance and use of technology (UTAUT) and the unified theory of acceptance and use of technology 2 (UTAUT2) research models in healthcare academic studies. Bibliometric studies are considered an important tool to evaluate research studies and to gain a comprehensive view of the state of the art.

Although UTAUT dates to 2003, our bibliometric analysis reveals that only since 2016 has the model, together with UTAUT2 (2012), had relevant application in the literature. Nonetheless, studies have shown that UTAUT and UTAUT2 are particularly suitable for understanding the reasons that underlie the adoption and non-adoption choices of eHealth services. Further, this study highlights the lack of a multidisciplinary approach in the implementation of eHealth services. Equally significant is the fact that many studies have focused on the acceptance and the adoption of eHealth services by end users, whereas very few have focused on the level of acceptance of healthcare professionals.

To the best of the authors’ knowledge, this is the first study to conduct a bibliometric analysis of technology acceptance and adoption by using advanced tools that were conceived specifically for this purpose. In addition, the examination was not limited to a certain era and aimed to give a worldwide overview of eHealth service acceptance and adoption.