# A Hybrid MCDM Model for Live-Streamer Selection via the Fuzzy Delphi Method, AHP, and TOPSIS
## 1 Introduction
As a result, the geometric mean is adopted in the fuzzy Delphi method for representing the opinions of experts and screening the selection criteria for live-streamers. Many studies have combined the fuzzy Delphi method with AHP to improve the research results. Most studies first identified important elements using the fuzzy Delphi method and then determined their importance using AHP [33]. TOPSIS serves as another appropriate option because it is suitable for multiple criteria, and it is simple and easy to understand [34]. Notably, TOPSIS is one of the most commonly applied methods to solve multi-attribute decision-making (MADM) problems. It is easy to understand and apply [35]. In the mathematical approach of MCDM, TOPSIS is most widely used [36]. AHP and TOPSIS are helpful and practical methods, respectively, for determining the relative importance of the elements and ranking the alternatives [37]. Additionally, the results obtained from AHP and TOPSIS are objective and accurate [38]. Thus, integrating them can produce more favorable results than using only TOPSIS [39]. It is worth noting that [PERSON] et al. [40] integrated them to select bloggers for hotels with no rank reversal occurrence in their study. Therefore, this study applied a hybrid MCDM model comprising the fuzzy Delphi method, AHP, and TOPSIS to assist the managers of shopping websites in selecting their live-streamers. Although livestream shopping is currently experiencing unprecedented growth, research on livestreaming businesses has only emerged recently [13]. For instance, [PERSON] [13] developed an integrated model to explore the elements influencing livestream shopping intention. [PERSON] [9] investigated the legal issues of Facebook live shopping. [PERSON] et al. [14] investigated the influence of e-commerce livestreaming on customer repurchase intentions using empirical research approaches. [PERSON] et al. [10] investigated the influential elements of audiences' trust and loyalty intention toward online streaming broadcasters based on the elaboration likelihood model (ELM). [PERSON] et al. [11] bettered the content quality and competitiveness of live platforms to improve the effect of livestream marketing. [PERSON] and [PERSON] [15] used the stimulus-organism-response (SOR) model to explore how relational bonds improve customer engagement. Finally, [PERSON] et al. [12] explored how livestream shopping affects consumer purchase intention. However, we found that no related literature in the past has investigated our specific topic. To conduct this study, the managers of shopping websites were interviewed, and related studies were reviewed to compile a set of selection criteria. We used the fuzzy Delphi method to screen the selection criteria and then constructed a hierarchical framework. Next, the weights of each dimension and each selection criterion were determined and integrated using AHP. Lastly, to address the excessive pairwise comparison matrices and reduce difficulty filling out the questionnaire among the decision-makers, the integrated weights of the selection criteria compiled using AHP were incorporated into TOPSIS. This assists in selecting the best live-streamer, thereby increasing the efficiency of decision-making. The study's objectives are as follows:  
1. Interview the managers of shopping websites and review related literature to compile the selection criteria. Then, screen the selection criteria for live-streamers based on the fuzzy Delphi method, classify them, and establish a hierarchical framework based on past literature and interviews with the managers. The hierarchical framework can be used to help the managers of shopping websites select live-streamers. 2. Assist the managers in a case shopping website to select the best live-streamer by incorporating the hierarchical framework in combination with AHP and TOPSIS. The consecutive sections of this study are described as follows. The next section presents the conceptual framework, followed by the research methods.