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All Journal International Journal of Tourism and Hospitality in Asia Pasific
Jannah, Nur Aini Raudhatul
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Humanities

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Utilizing Artificial Intelligence (AI) in Customer’s Purchase Intentions on GrabFood Ravi, Thevisri; Yusof, Rosmelisa; Koay, Loke Kean; Teoh, Yee Teng; Thin, Mun Yee; Donold, Tiffany Audrey Anak; Jannah, Nur Aini Raudhatul; Mittal, Prachi; Srivastava, Rishabh; Kee, Daisy Mui Hung
International Journal of Tourism and Hospitality in Asia Pasific Vol 7, No 2 (2024): June 2024
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/ijthap.v7i2.3212

Abstract

Generally, food delivery is a courier service that transfers consumer needs from stores or restaurants to the customer’s doorstep. With the advent of artificial intelligence, people now could order meals and other goods from the convenience of their homes. As such, Grab Holdings, which was founded in 2012 as a taxi-hailing service, is now well-known for providing consumer services including rides (Grab Transport), food deliveries (GrabFood), and package deliveries (Grab Express). The primary purpose of this research is to study on how the artificial intelligence that was utilized in customer’s purchase intentions on Grab Food.  The independent variables used to measure this study are instant delivery of foods, estimation of delivery time, customized recommendation on food, interactivity, cashless payment method used and consumer behavior corresponding to the dependent variable of consumer’s intention to use GrabFood. To support the findings of the research, an online survey has been carried out to gather the data needed. This survey was targeted on 100 Malaysian, Indonesian and Indian respondents, from all age groups, ethnicity, and gender. Following, the data gathered were verified using the SPSS software. Based on the study, the result shows that there is a significant correlation between the independent and dependent variables. In addition, instant delivery of foods and customized recommendations on food has a major influence on consumers’ purchase intention on GrabFood Delivery.
Utilizing Artificial Intelligence (AI) in Customer’s Purchase Intentions on Online Food Delivery Service Ravi, Thevisri; Yusof, Rosmelisa; Koay, Loke Kean; Teoh, Yee Teng; Thin, Mun Yee; Donold, Tiffany Audrey Anak; Jannah, Nur Aini Raudhatul; Mittal, Prachi; Srivastava, Rishabh; Kee, Daisy Mui Hung
International Journal of Tourism and Hospitality in Asia Pasific Vol 7, No 2 (2024): June 2024
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/ijthap.v7i2.3212

Abstract

Generally, food delivery services like GrabFood act as couriers, transporting consumer needs from restaurants or stores directly to their doorsteps. The rise of Artificial Intelligence (AI) has further revolutionized this convenience, allowing people to order meals and other goods from the comfort of their homes. This research investigates how AI is utilized to influence customer purchase intentions on GrabFood. The study examines the impact of six independent variables: instant food delivery, estimated delivery time, customized food recommendations, interactivity, cashless payment methods, and consumer behavior. These variables are analyzed in relation to the dependent variable – the customer's intention to use GrabFood. To gather data, an online survey was conducted with 100 respondents. The collected data was then verified using SPSS software. The findings revealed that delivery speed is a key driver, with both instant delivery and estimated delivery time showing a significant positive correlation (? = 0.457) with purchase intention. However, other features like personalized recommendations (? = 0.174), cashless payment methods (? = 0.119), and user interaction (? = -0.188) did not significantly impact user decisions. These findings require further exploration to understand user preferences for these features.
Co-Authors Donold, Tiffany Audrey Anak Kee, Daisy Mui Hung Koay, Loke Kean Mittal, Prachi Ravi, Thevisri Srivastava, Rishabh Teoh, Yee Teng Thin, Mun Yee Yusof, Rosmelisa