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All Journal International Journal of Applied Business and International Management International Journal of Tourism and Hospitality in Asia Pasific Journal of the Community Development in Asia International Journal of Accounting & Finance in Asia Pasific
Lew, Tek Yew
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Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Social Sciences

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Consumer Attitude and Intention Toward AI-Based Smart Ordering and Delivery Systems in the Fast-Food Industry Effendi, Azura Abdullah; Lew, Tek Yew; Ooi, Wei Ning; P’ng, Soak Suan; Poh, Mei Shan; Binti Hamizan, Puteri Balqis; Tomar, Arun Singh; Kee, Daisy Mui Hung
International Journal of Applied Business and International Management Vol 10, No 3 (2025): December 2025
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/ijabim.v10i3.4325

Abstract

The increasing use of artificial intelligence (AI) in fast-food ordering and delivery systems has transformed service processes, yet consumer adoption remains uneven. This study examines the factors influencing consumer attitude and behavioral intention toward AI-based smart ordering and delivery systems in the fast-food industry, using McDonald’s AI-based Smart Ordering and Delivery System in Malaysia as the empirical context. Using a quantitative approach, data were collected from 150 consumers in Malaysia and analyzed using multiple regression analysis. The results show that social influence has a significant positive effect on consumer attitude (? = 0.313, p 0.001), while ease of use, enjoyment, perceived convenience, and trust do not significantly affect attitude. For behavioral intention, perceived convenience (? = 0.218, p 0.01), social influence (? = 0.291, p 0.001), and trust (? = 0.248, p 0.01) are significant predictors, whereas consumer attitude is not (? = 0.066, p 0.05). The models explain 29.8% of the variance in consumer attitude and 44.5% of the variance in behavioral intention. These findings suggest that adoption of AI-based ordering systems in fast-food contexts is driven more by social endorsement and functional considerations than by attitudinal evaluation.
Co-Authors Akbal Khan, Afra Binti Ali, Anees Jane Ali, Shahira Binti Akhter Ang, Hui Hui Ang, Jia Wei Azhar, Nurul Hanisah Binti Azmi, Nurul Atikah Binti Binti Hamizan, Puteri Balqis Bong, Allychia Ling Li Chauhan, Shalini Dat Leow, Leon Rong Effendi, Azura Abdullah Elangoh, Sarveena A/P Gupta, Shikhar Indrastata, Daiva Fifqi Ismail, Aimi Aleeya Binti Kee, Daisy Mui Hung Lee, Zi Ying Li, Jiayi Liem, Gai Sin Lim, Hui Ling Ling, Lim Hui Mathur, Garima Maulana, Erika Mohammad Hazaini, Ainun Adibah Binti Mohan, Nitin Mohd Fuad, Ahmad Azeedi Reza Bin Muthupalaniappan, Selva Ganesh A/L Nazira, Aina Oh, Zi Jian Ooi, Wei Ning Pandey, Shivangi Paul, Gadi Dung Poh, Mei Shan P’ng, Soak Suan Rozaidi, Nurul Irdina Binti Shao, Xue Wen Sharma, Gaurav Shen, Ze Bin Shoo, Yee Wen Suimi, Nursyahidah Binti Ahmad Suthesh, Sashmitha Nair Tan, Lay Hong Tan, Wan Ling Tan, Wei Chi Tan, Wei Len Tan, Yee Ling Tan, Yee Ros Teik, Saw Wei Teoh, Kok Ban Tomar, Arun Singh Yuan Li Zhafira, Adzra