Determinants of the guest-perceived performance of peer-to-peer shared accommodation

Abstract

Along with the development of information technology and the innovation of business model, the sharing economy has experienced tremendous growth in a short span of time, particularly in the P2P shared accommodation sector. Although a plethora number of articles introduced the phenomenon of short-rental platforms, limited attention has been given to the mechanism of the platform and how it affects the performance. This study looks to fill this void by exploring drivers or inhibitors of the performance, particularly the guest-perceived performance of P2P shared accommodation in China. The research objectives are as follows: 1. To develop reliable and valid scales of the key attributes and the guest-perceived performance of the P2P shared accommodation; 2. To empirically test the relationships between the guest-perceived performance of P2P shared accommodation and its determinants; and 3. To examine the traveling party's moderating effect on the relationships between the key attributes and the guest-perceived performance. Few studies have investigated the performance of P2P shared accommodation in any systematic way. In particular, much uncertainty exists about the relationship between antecedents and the guest-perceived performance. Even among industry, the characteristics and importance of the guest-perceived performance of P2P shared accommodation are yet to be fully harnessed. This will be the first study investigating how guest-perceived performance is driven or inhibited by the antecedents and to understand what link there is between them. Structural equation modeling (SEM) is used to test and estimate the causal relationships among the constructs. Five participation attributes are deemed critical antecedents to the performance, including Host Attribute, Guest Attribute, Accommodation Attribute, Interaction Attribute, and Platform Attribute. This research considers the traveling party as a moderating variable. Besides, accommodation type, accommodation size, host type, and host rental policies are incorporated as control variables. A rigorous and comprehensive process of scale development will be followed for this study. Questionnaires will be developed, pre-tested, and pilot-tested on the targeted samples. The main survey will be conducted, based on convenience sampling, among tourists who have ever used the short-rental platforms and show an interest in digital technology. The proposed structural model will be tested using a statistic software package AMOS 26.0 in the wake of exploratory factor analysis and confirmatory factor analysis.