Consumer Attitude and Intention Toward AI-Based Smart Ordering and Delivery Systems in the Fast-Food Industry - Azura Abdullah Effendi; Tek Yew Lew; Wei Ning Ooi; Soak Suan P’ng; Mei Shan Poh; Puteri Balqis Binti Hamizan; Arun Singh Tomar; Daisy Mui Hung Kee (International Journal of Applied Business and International Management, 2025)
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.