Browsing by Author "Han, Meini"

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    Face recognition of profile images on accommodation platforms
    Liu, Xianwei; Li, Chunhong; Nicolau, Juan Luis; Han, Meini (Routledge, 2022-08-13)
    Visual information plays a critical role on peer-to-peer (P2P) accommodation platforms. Recent studies have found that attractive hosts possess advantages in alluring potential guests and charging high prices, highlighting the beauty premium effect from the perspective of hosts. Are attractive guests more likely to receive better service from their hosts, thus producing a beauty premium effect from the perspective of guests? To answer this undocumented research question, we collect data from Airbnb accommodations listed in Los Angeles, New York City, and Orlando in the US. By virtue of deep learning techniques, face recognition, and text-mining, our empirical results reveal a beauty premium effect from the perspective of guests that attractive guests are more satisfied with their accommodations and receive more interactions from hosts. These findings illustrate the application of face recognition in the context of P2P accommodation platforms and provide direct implications for the operation of accommodation platforms.
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    Online engagement and persistent reactions to social causes: The black-owned business attribute
    Liu, Xianwei; Han, Meini; Nicolau, Juan Luis; Li, Chunhong (Elsevier, 2022-02-01)
    The persistence of COVID-19 exerts an unprecedented impact on the tourism and hospitality industry and the Black-owned businesses had been hit disproportionately harder than any other racial group. Many platforms (e.g., Airbnb and Yelp) have run a series of campaigns to support Black-owned businesses. Determining whether these campaigns are effective in attracting supports from consumers or just merely promotional is key. Based on the theoretical framework of Hennig-Thurau et al. (2004) and Aldous et al. (2019) and data collected from Yelp, this study reveals that higher levels of engagement produce persistent reactions. Specifically, the rating support lasts for one month and then vanishes; the review support increases for three months and then gets reversed; and the verbal support lasts for three months but does not get reversed. The findings of this study contribute to theories of online engagement and provide direct implications for platforms involving social campaigns in business practice.
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    The value of rating diversity within multidimensional rating system: Evidence from hotel booking platform
    Liu, Xianwei; Li, Chunhong; Nicolau, Juan Luis; Han, Meini (Elsevier, 2023-04-01)
    An increasing number of hotel booking platforms and review websites deploy multidimensional rating systems to encourage users to provide additional evaluations of a product/service besides the overall rating. However, providing the itemized ratings of a product/service requires extra effort which makes users tend to post identical ratings (default setting). According to the information transfer theory, we postulate that rating diversity enhances review usefulness within the multidimensional rating system and; based on the loss aversion phenomenon, we also posit that the positive effect of rating diversity on review usefulness should be greater among negative reviews. Using a sample of 1,720,429 hotel reviews, this study reveals that while rating diversity enhances review usefulness, its effect varies across the valence of each review; specifically, the positive effect of rating diversity mainly functions among negative reviews. These findings yield direct implications for hotel booking platforms or review websites that deploy multidimensional rating systems.