期望理论
维数(图论)
透视图(图形)
营销
预期寿命
习惯
业务
心理学
计算机科学
社会心理学
社会学
数学
纯数学
人工智能
人口学
人口
作者
Pei‐Hsuan Tsai,Wei‐Hung Hsiao,Chih‐Jou Chen
摘要
Abstract The emergence of the COVID‐19 pandemic dramatically lowered the foodservice industry's income overnight. Conversely, the practical measure of remaining at home to deal with the pandemic's impact has boosted the online food delivery business. In this study, a consumer perspective was adopted and an adapted version of the extended unified theory of acceptance and use of technology (UTAUT2) was used alongside multi‐attribute decision‐making methods (DEMATEL, DANP and modified VIKOR) to construct a model for evaluating and selecting a food delivery platform (FDP). The results of the INRM (influential network relation map) revealed that the first dimension to be improved upon and adjusted should be security, followed by effort expectancy, performance expectancy, social influence, facilitating conditions, hedonic motivation and habit. The DANP influential weights suggested that habits were the most important dimension, followed by hedonic motivation, while performance expectancy was the least important. According to the results of the gap analysis, the first dimension that required improvement was performance expectancy, followed by effort expectancy, facilitating conditions, security, social influence, habits and hedonic motivation. It is expected that the findings of this study can serve as a reference for consumers selecting FDPs to better satisfy their dining needs. The novel model is discussed in terms of theoretical, practical and managerial implications.
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