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

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