This study employs advanced text-mining techniques to offer an in-depth and comprehensive overview of the extensive body of research on Airbnb. By analyzing 1021 articles published in 416 journals spanning the period from 2015 to 2022, this study aims at revealing Airbnb research topics and trends. The results show that the primary focus of academic inquiry regarding Airbnb revolves around two domains: the company's operational practices and its impacts on various domains.
View Article and Find Full Text PDFIntroduction: Online reviews have become an important source of information for investigating customers' consumption experiences in academic studies. In the context of sharing economy-based accommodation, various studies have been conducted to investigate the user experience of Airbnb by analyzing online reviews; however, most previous Airbnb studies had focused on analyzing the user experience of Airbnb at a holistic level without distinguishing the accommodation attributes of Airbnb. Therefore, this article aimed to investigate how the preferences revealed by Airbnb users in online reviews vary across Airbnb listings with different levels of sharing and price ranges.
View Article and Find Full Text PDFDrawing on the conservation of resources (COR) theory and congruence theory, this study aims to investigate the influence of psychological capital (PsyCap) and person-job fit (PJ fit) on work-family conflict (WFC), family-work conflict (FWC) and job performance (JP), especially the moderating effect of marital status on hypothesized relationships between two directions of conflicts in the work-family interface and JP. Utilizing a two-stage design, this study surveyed 312 flight attendants employed by two international airline companies in Malaysia and used the structural equation modeling technique to test the hypothesized relationships. Findings showed that PsyCap could significantly alleviate two directions of WFC simultaneously and promote employees' JP.
View Article and Find Full Text PDFThis study aims to examine key attributes affecting Airbnb users' satisfaction and dissatisfaction through the analysis of online reviews. A corpus that comprises 59,766 Airbnb reviews form 27,980 listings located in 12 different cities is analyzed by using both Latent Dirichlet Allocation (LDA) and supervised LDA (sLDA) approach. Unlike previous LDA based Airbnb studies, this study examines positive and negative Airbnb reviews separately, and results reveal the heterogeneity of satisfaction and dissatisfaction attributes in Airbnb accommodation.
View Article and Find Full Text PDFBackground: The hospitality industry is deemed a great generator of global GDP and employment. However, high rates of voluntary turnover have gradually undermined global service organizations and brought huge losses to them. Nowadays, the hotel sector continues to be plagued by high turnover rates.
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