An Integrated Approach with CLFPR-Based ANP and Fuzzy TOPSIS for Evaluating Business Performance of Rural Homestays: Study from China

Abstract

Given the high importance of the performance of rural homestays to the local economy, this study aims to fill the gap in homestay performance research and make rural homestays more competitive and sustainable after the coronavirus disease epidemic (COVID-19). Integrating a consistent linguistic fuzzy preference relations-based analytic network process (CLFPR-based ANP) and a fuzzy technique for order performance by similarity to ideal solution (TOPSIS), this study constructs a comprehensive evaluation model of the performance of rural homestays and empirically analyzes homestay performance in Zhejiang. The results show the following: (1) Among the criteria’s weights by CLFPR-based ANP, homestay operation and management, service quality, and homestay geist and community co-prosperity should be given much more attention; the importance of factors regarding the environment and building of rural homestays is gradually weakening. (2) In light of ranking alternatives based on performance evaluation by fuzzy TOPSIS, the homestay with the optimal performance has been found, which practitioners can use as a benchmark. Therefore, the priorities of these criteria further deepen the understanding of the performance of rural homestays and underline the development direction for practitioners. Simultaneously, in terms of feasibility and reliability, the integrated approach comprises a beneficial attempt and becomes an effective evaluation tool for practitioners to improve effectiveness.