A Hybrid MCDM Model for Live-Streamer Selection via the Fuzzy Delphi Method, AHP, and TOPSIS

Abstract

The development of the Internet is a key revolution of the 20th century. The Internet has led to a boom in e-commerce. Online shopping is generally the most popular shopping option for consumers. The coronavirus disease 2019 (COVID-19) pandemic has resulted in adopting various measures, such as lockdown and stay-at-home orders, in various countries. This has led to changes in people’s consumption habits. In Taiwan, consumer behavior has also rapidly shifted to online shopping after the outbreak of the COVID-19. As livestreaming breaks time and space barriers, its real-time, interactive, and authentic features are unparalleled compared to other marketing methods, thereby creating a brand-new shopping experience for consumers. Accordingly, livestream shopping, a new consumption model, has developed and become an essential part of people’s daily lives. Live-streamers, who are similar to salespersons in traditional markets, play a vital role in e-commerce livestreaming. The success of livestream shopping has highlighted the importance of live-streamers. The competition among live-streamers has become more intense because of the arrival of many newcomers. Thus, operators must make careful hiring decisions. However, no related literature in the past has investigated this important topic. Therefore, this study applied a hybrid multi-criteria decision-making (MCDM) model comprising the fuzzy Delphi method (screen the selection criteria), analytic hierarchy process (AHP) (obtain the weight of each dimension and criterion), and technique for order preference by similarity to ideal solution (TOPSIS) (rank the alternatives) to assist the managers of shopping websites in selecting live-streamers. We interviewed the managers of shopping websites and reviewed the related literature to compile the selection criteria. Following the fuzzy Delphi method, 15 important selection criteria were retained based on the 30 managers’ opinions. Further, the criteria were classified into dimensions based on the previous literature and interviews conducted on managers to establish a hierarchical framework. On the basis of this hierarchical framework, AHP and TOPSIS were applied to help a case company select live-streamers. A comparative analysis between the outcomes from AHP and AHP/TOPSIS was also conducted in this study. This study is the first empirical study on live-streamers’ selection and adds to the literature on livestreaming.