Prediction of Knowledge Management for Success of Franchise Hospitality in a Post-Pandemic Economy

Abstract

Due to its unpredictability, the novel coronavirus (COVID-19) pandemic has changed the global business climate and commercial management practices in unprecedented ways. As a direct result of the pandemic, the hospitality and tourism sectors have shut down, and business failure rates have occurred exponentially. The franchise hospitality industry has experienced significant impact and challenged a basic understanding of knowledge management (KM) implementation in the face of the COVID-19 outbreak. A strategic KM implementation practice can not only guide a large-scale operation, but also adjust an organization’s performance and competitiveness. The purpose of this study is to examine the influential criteria of success through effective KM implementation and to predict the probability of successful KM in a post-pandemic era. The conceptual framework for KM applies an analytic hierarchical prediction model reliant upon consistent fuzzy preference relations to assist the franchise hospitality sector’s consciousness of the influential criteria. An empirical case study is used to apply pairwise comparisons used to determine the priority weights and two possible outcomes. The case study will assist franchise organizations to analyze whether or not to implement KM, interdict application, or adopt revised actions. This assistance will enhance the success possibility of KM implementation within such a crisis environment. This study uses a case setting by assessing 15 franchises hospitality experts’ opinions in Taiwan relevant to KM implementation.