Low Eve Chee

Type of the article: Research Article

Abstract
Digital menu systems have revolutionized restaurant operations by catering to consumers’ demand for convenience and personalized dining experiences. However, the performance of the ordering system varies across restaurants, making it essential to understand how digital menu system satisfaction influences key drivers of dining experience. Cross-sectional, self-administered online survey (convenience sampling) was conducted among 448 Malaysian restaurant patrons from December 2023 to May 2025 to capture recent dining behavior. Respondents were recruited from a broad range of income groups and dining contexts across urban, suburban, and rural areas in Malaysia, encompassing experiences at low-cost casual eateries, mid-range family, chain restaurants, and upscale venues, thereby capturing socioeconomic variation. The study examines the relationship between performance expectancy, effort expectancy, visual appeal, and perceived engagement, as well as their impact on restaurant loyalty, with the moderating role of satisfaction with digital menu systems. The analysis, conducted using Partial Least Squares Path Modeling (PLS-PM) in SmartPLS 4, assessed the relationships between variables. The results show that performance expectancy (β = 0.173, p < 0.002), effort expectancy (β = 0.208, p < 0.001), visual appeal (β = 0.262, p < .001), and perceived engagement (β = 0.189, p < 0.001) positively predict restaurant loyalty, explaining R² = 57% of variance in loyalty. Nevertheless, digital menu system satisfaction moderates only the relationship between visual appeal and restaurant loyalty (interaction β = 0.089, p = 0.042). The findings demonstrate that well-designed digital menu systems enhance order accuracy, navigation, and decision-making, highlighting the importance of functionality and visual design in fostering customer loyalty.

Acknowledgment
The authors gratefully acknowledge funding from the Ministry of Higher Education Malaysia through the Fundamental Research Grant Scheme with Project Code: FRGS/1/2022/SS01/USM/02/11.