Identification of Applicable YouTubers for Hotels: A Case Study of Integrated Hybrid MCDM Model

Abstract

The coronavirus disease 2019 (COVID-19) pandemic has caused a serious business recession in various walks of life, particularly in the full-service hotel industry. YouTube has one billion active users and is undoubtedly a social media platform that companies use to build relationships with customers and create value for brands. Marketers should be aware of YouTubers’ significant influence on complex decision-making processes. Given the above reasons, identifying a YouTuber attracts the concerns of various industries; thus, this important issue is focused on and offered the study’s rationality. This study proposes an integrated hybrid MCDM model to organize the four key techniques of FDM, DEMATEL, ANP, and TOPSIS to identify YouTubers for hotels. Consequently, 12 key criteria and four core dimensions were identified to improve the decision of optimal YouTubers for promoting sustainable development and increasing the efficiency of decision-making. From the limited literature review, the proposed hybrid model was not observed regarding YouTuber identification of hotels; thus, this study provides a superior application contribution to address this important and interesting topic for academicians and practitioners.