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PREDICTING THE USAGE OF ONLINE FOOD DELIVERY SERVICES: A META-ANALYTIC STRUCTURAL EQUATION MODELING STUDY

  • 언어ENG
  • URLhttps://db.koreascholar.com/Article/Detail/422296
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글로벌지식마케팅경영학회 (Global Alliance of Marketing & Management Associations)
초록

With the development of information technology, online food delivery services have significantly changed people’s food consumption patterns. The outbreak of COVID-19 has further facilitated the development due to restaurant restrictions and social distancing measures. Due to the emergence of online food delivery services, scholars have paid increasing attention to this popular topic, and a large number of studies have examined which factors are related to consumers’ intention to use online food delivery services. However, previous studies showed inconsistent findings, and relationships between variables lack a comprehensive understanding. Therefore, this study aimed to develop a research model and examine the factors influencing consumers’ intention to use online food delivery services. By reviewing and analyzing 52 studies with 53 independent samples (N = 22,937), the meta-analytic structural equation modeling approach was carried out to assess the research model. The findings indicate that two attributes of online food delivery services (i.e., convenience and price-saving orientation) play different roles in the research model. Specifically, convenience significantly impacted perceived ease of use but had no direct impact on perceived usefulness. Price-saving orientation significantly influenced both perceived ease of use and perceived usefulness. Moreover, relationships between perceived ease of use, perceived usefulness, and perceived trust were significant, and these factors ultimately significantly led to the intention to use food delivery services. The findings contribute to theoretical advancement in the extant literature on food delivery services and help firms develop to provide better food delivery services for consumers’ continuous usage.

저자
  • Weisheng Chiu(Hong Kong Metropolitan University, Hong Kong)
  • Badu-Baiden Frank(Hong Kong Metropolitan University, Hong Kong)
  • Peter Kim Tan Cheung(Hong Kong Metropolitan University, Hong Kong)