DETERMINANTS OF EXAMINING BEHAVIORAL ASPECTS OF USING EMERGING TECHNOLOGY IN ONLINE FOOD DELIVERY APPS. AN EXTENDED TECHNOLOGY ACCEPTANCE MODEL APPROACH
DOI:
https://doi.org/10.48165/iitmjbs.2024.SI.3Keywords:
Technology Acceptance Model, perceived enjoyment, emerging technologies, online food delivery, structural equation modelingAbstract
Purpose – The study aims to examine factors that influence customers’ intention to use emerging technology (such as chatbots, AI-based recommendations, robotics delivery, Augmented Reality/Virtual Reality) in online food delivery applications. The factors examined in this study are based on the existing theory of Technology Acceptance Model (TAM), namely perceived usefulness, perceived ease of use, attitude towards intention to use the applications, and this research expanded with an additional dimension: perceived enjoyment, which leads to the intention to use online food delivery services. Design/methodology/approach – The study employed a quantitative method, and 201 respondents participated in this study. The questionnaires were distributed using a convenience sampling technique, and the data was analyzed using the partial least square approach. The study focused on measurement properties via Confirmatory Factor Analysis (CFA) and SEM using Smart PLS 4.0. Descriptive analysis and hypothesis testing provided insights into factors influencing OFD app adoption among consumers, ensuring methodological rigor and credibility. Findings – The results show that four (4) constructs, i.e. Perceived usefulness, Perceived ease of use, Perceived Enjoyment, and Attitude towards Behavioral intention. The study indicates that user experience factors, such as enjoyment and ease of use, play a crucial role in determining the behavioral intention to use technology-based online food delivery applications in Delhi. Practical implications – The output of this study has several practical contributions, such as enhancing the existing knowledge and skillset of the shared-economy industry. OFD industry practitioners can use these results to better understand how to improve the behavioral
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