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This study aims to conduct a critical review of the research on the sharing economy to identify its key intellectual foundations and their evolution and offers thematic and methodological recommendations for future research to advance the domain.

A tri-method approach using bibliometric (co-citation) analysis, thematic content analysis and a quantitative systematic literature review was conducted on sharing economy research in hospitality and tourism journals, up to and including May 2020.

The findings from the three methods were coherent and provide a clear picture of the fact that while research on the sharing economy in hospitality and tourism has achieved significant depth, the breadth of the understanding of this area remains somewhat limited. Each of the three periods of research on the sharing economy identified in the study were marked by a focus on specific thematic areas, with largely Western-situated researchers demonstrating limited theoretical engagement and using a limited range of methods and perspectives (disciplinary, stakeholders and sectors) to examine these themes.

Recommendations for future thematic research opportunities are provided using a multi-level perspective. The present review does not include research that incorporates the impacts of COVID-19, which has significantly disrupted the hospitality and tourism industry and is the focus of current research in the field. However, the review represents the largest and most comprehensive assessment of the state of research on the sharing economy prior to COVID-19, and, as such, can serve as a valuable baseline for future reviews of sharing economy research during and after the pandemic.

In contrast with previous literature reviews, the present review is comprehensive in its scope, methodology and temporal coverage of sharing economy research. It also examines the evolution of research on the topic, enabling a more nuanced identification of gaps and future thematic and methodological research opportunities.

The aim of this study is to understand the knowledge-sharing structure and co-production of trip-related knowledge through online travel forums.

The travel forum threads were collected from TripAdvisor’s Sydney travel forum for the period from 2010 to 2014, which contains 115,847 threads from 8,346 conversations. The data analytical technique was based on a novel methodological approach – visual analytics, including semantic pattern generation and network analysis.

Findings indicate that the knowledge structure is created by community residents who camouflage as local experts and serve as ambassadors of a destination. The knowledge structure presents collective intelligence co-produced by community residents and tourists. Further findings reveal how these community residents associate with each other and form a knowledge repertoire with information covering various travel domain areas.

The study offers valuable insights to help destination-management organizations and tour operators identify existing and emerging tourism issues to achieve a competitive destination advantage.

This study highlights the process of social media mediated travel knowledge co-production. It also discovers how community residents engage in reaching out to tourists by camouflaging as ordinary users.

Taking a global perspective, this paper aims to examine the impact of COVID-19 on Airbnb booking activities through three critical perspectives – the initial Wuhan lockdown, local COVID-19 cases and local lockdowns.

Using Airbnb reviews and cancellations as proxies for Airbnb bookings on a global scale, econometrics was used to examine the impacts of the initial Wuhan lockdown, local COVID-19 cases and local lockdowns on Airbnb bookings.

The authors find that local lockdowns result in a 57.8% fall in global booking activities. Every doubling of newly infected cases is associated with a 4.16% fall in bookings. The sensitivity of bookings to COVID-19 decreases with geographic distance to Wuhan and increases with government stringency of lockdown policies and human mobility within a market.

The empirical evidence from this research can provide governments with insights into more accurate assessment of the financial loss of Airbnb hosts so that proper support can be offered based on the financial needs because of due to sudden lockdown.

This research contributes to new knowledge on peer-to-peer accommodation during a time of crisis and provides much needed global evidence to understand the impacts of COVID-19 on the accommodation industry.

This study aims to identify the key determinants of Airbnb rating scores.

This study is based on a sample of 127,257 listings across 43 cities. A total of 24 explanatory variables were identified, and they were further grouped into host verification information, communication, policy of renting, space, information about environment, price and experience of hosting. Both Tobit and ordered logit models were used to perform the analysis.

The results indicate that good communication, large space and provision of information about the listings’ environment have a positive effect on users’ satisfaction, whereas experience of hosting negatively influences users’ satisfaction.

This study contributes to the peer-to-peer accommodation literature by affording a more complete understanding about guest satisfaction and its determinants.

The study aims to provide a critical review of the origin, development and process of sentiment analysis (SA) and a demonstration for hospitality researchers and students on how to perform SA using a sample study.

A critical review and sample case demonstration approach was applied. The sample study used Leximancer to perform SA using TripAdvisor review data.

A critical evaluation of the most popular SA tools was provided, highlighting their advantages and disadvantages. A step-by-step demonstration with data provided makes it possible for readers to learn this technique at own pace.

By providing a critical review of SA supported with a demonstration case study, this study makes a timely contribution for broader awareness and understanding, as well as the application of SA in hospitality.

The purpose of this study is to explore the impact of mobile learning platforms on users' study efficiency and develop cognitive indicators to evaluate users' study efficiency on mobile learning platforms.

Layout style was the only independent factor that was investigated. A between-group experimental design was employed. Eye movement data were recorded during the experiment, following which participants were asked to complete an after-scenario questionnaire. This study evaluated the usability of the proposed new design using both subjective and objective data. The computer system usability questionnaire V3 (CSUQ) was used to measure subjective data. For the eye-tracking measure, gaze entropy, the proportion of fixation count and duration of each AOI were calculated. Gaze entropy reflects the complexity of information organization. Fixation counts and AOI duration represent the difficulty of information processing and attention distribution, respectively during the task.

The results indicated that interface layout presents significant effects on user's learning efficiency, usability and cognitive load. Sequential layout improved efficiency and satisfaction among participants and reduced information complexity. The results provided useful insights for designers whose goal is to improve user's learning efficiency under mobile learning scheme.

This study investigated the effects of interface layout on usability, user performance and cognitive load using subjective ratings and eye-tracking technology. Gaze entropy was used to measure the complexity of information organized by the interface design. Fixation count and duration proportion were used to identify the difficulty of information processing and distinguish users' distribution of cognitive resources. The results indicated that a vertical layout panel design was more efficient than a horizontal layout panel design. The design implications of the eye tracking indicators and research results were then summarized. This study is expected to encourage designers to optimize their design proposals using eye tracking testing.

Project-based organizations (PBOs) face challenges to enhance employee work engagement because of dynamic and constant role configuration. Accordingly, this study aims to explore how ethical leadership enhances employee work engagement from a sensemaking perspective.

This study used a questionnaire-based quantitative research design to collect data from 194 full-time employees in PBOs. The data were analyzed via partial least squares-structural equation modeling (PLS-SEM) technique to test hypotheses.

The findings show a positive relationship between ethical leadership and work engagement. Additionally, the relationship between ethical leadership and work engagement is mediated by two sensemaking mechanisms, i.e. goal commitment and prosocial.

This study deepens the understanding of how ethical leadership enhances work engagement in PBOs by providing two sensemaking mechanisms. By exploring the sensemaking process through which ethical leaders help employees construct identity, the findings contribute to the current literature on how ethical leadership enhances work engagement in PBOs.

By using an integrated theoretical analysis model and a practice analysis model, this study constructed an evaluation indicator system for public participation in post-disaster housing reconstruction.

This study investigated and summarised the public participation of earthquake victims in house building in Dujiangyan. A total of 16 analysis elements were proposed, including the subject and object for evaluation. A mixed qualitative and quantitative evaluation model was established.

The implementation results indicated that this evaluation index system was objective oriented and had public policy attributes. The index can effectively reflect the diverse needs of disaster victims, address multiple social aspects and evaluate and rate public participation.

This paper proposed a mixed research method that integrates analysis processes, such as theories and practical investigation, which are the pillars of public participation evaluation. The evaluation indicators had quantitative characteristics.

With the growing awareness about the environment and climate, sustainability has gained increased attention of investors. Many investors now factor in the long-term sustainability of successful and responsible companies when making their investment choices. The purpose of this paper is to investigate whether or not the sustainability performance of a company affects the informativeness of its earnings by exploring the mediating effect of sustainability performance on the association between stock returns and earnings changes.

Using a sample of firms for the period 2009–2016 with available sustainability data from TruValue Labs' database, the authors investigate how the sustainability performance of a firm mediates the relationship between stock returns and earnings (changes). The authors use ordinary least squares (OLS) regressions to test their hypotheses.

Consistent with the voluntary disclosure and environmental, social and governance (ESG) performance literature, the authors find that higher sustainability performance improves the stock price informativeness of earnings. The authors find evidence in support of increased earnings response coefficient with increased sustainability performance.

This study adds to the literature supporting the notion of sustainability investing indicating that sustainability performance of a firm affects the stock price informativeness and predictability of earnings (changes) of the firm.

This study has value for, both, investors and managers regarding the importance of sustainability performance of the firm. Sustainability performance of the firm sends signals to market participants, increasing the informational content of the reported earnings as well as predictability of future earnings.

As online learning is the embryonic form of education in the metaverse, it is extremely important to explore the behavioral preferences of users. The aim is to explore the impact of interactive features on continuous use in online learning and to further explore what kind of interaction mode should be constructed for different types of students to obtain the best educational experience.

The study developed an empirical model and used a real-world dataset to test hypotheses. Specifically, the interaction in online learning is analyzed from different dimensions, including the interaction intensity of multiple subjects, the immersion of interactive technology, the timeliness of interactive feedback, and the fun in interaction.

The authors found that the intensity of interaction, immersion, timeliness of feedback and fun in the interaction all had significant positive effects on continuous use. Among them, the most important is the interaction between teachers and students. With the growth of user grades, the role of parents in the interaction is getting smaller and smaller, and the fun in the interaction is gradually becoming unnecessary. For high school students, gamified interactions can even have a negative impact. In addition, from the perspective of gender, males prefer immersive interaction, while females pay more attention to themselves and have negative feedback on fees.

The authors deepened the interaction and summarized the impact of different interactive features on continuous use in online learning platforms. The authors focused on the impact of the immersive experience brought by the application of interactive technology, which can confirm the user behavior preferences of online learning in the context of the metaverse. The research also provides a reference for online learning institutions to set up course interaction modes and targeted marketing programs.