QR CODE MENU DESIGN AND CUSTOMER SATISFACTION IN MALAYSIAN CASUAL DINING RESTAURANTS
DOI:
https://doi.org/10.55197/qjssh.v7si5.1757Keywords:
QR code menu, digital presentation, strategic item placement, visual digital prompts, customer satisfaction, casual dining restaurantAbstract
QR code menus are now standard in Malaysian casual dining, yet little is known about which mobile interface features are associated with diner satisfaction. Drawing on the Technology Acceptance Model and Menu Engineering principles, this study examines whether digital presentation, strategic item placement and visual digital prompts predict customer satisfaction in independent casual dining restaurants. A cross-sectional online survey was administered to casual dining patrons in Penang, recruited by purposive screening followed by snowball referral and required to have used a QR code menu within the preceding six months; 248 usable responses were retained. Constructs were measured on six-point Likert scales (α = .843 to .867) and analysed by multiple linear regression. The three predictors jointly explained 85.0% of the variance in customer satisfaction, R² = .850, adjusted R² = .849, F(3, 244) = 462.428, p < .001, and each was a significant positive predictor: visual digital prompts, β = .474; strategic item placement, β = .310; digital presentation, β = .178. However, the attributes proved not to be empirically separable: no construct met the Fornell-Larcker criterion, the collinearity condition index reached 37.144, and 92.5% of explained variance was shared rather than unique. Relative weights analysis accordingly returned near-equal contributions of 31.5%, 32.5% and 35.9%. The substantive finding is that QR menu interface design considered as a whole is strongly associated with customer satisfaction, while the ordering of the standardised coefficients should not be read as a hierarchy of design criteria.
References
[1] Baiomy, A.E., Jones, E., Goode, M.M. (2019): The influence of menu design, menu item descriptions and menu variety on customer satisfaction: A case study of Egypt. – Tourism and Hospitality Research 19(2): 213-224.
[2] Bakar, A.Z.A., Phebe, J. (2025): Consumer perception and satisfaction of Quick Response (QR) code in casual dining restaurants in Malaysia. – Quantum Journal of Social Sciences and Humanities 6(SI1): 148-163.
[3] Bank Negara Malaysia (2024): Financial stability review – Second half 2023. – Bank Negara Malaysia, Kuala Lumpur 100p.
[4] Bitner, M.J. (1992): Servicescapes: The impact of physical surroundings on customers and employees. – Journal of Marketing 56(2): 57-71.
[5] Brewer, P., Sebby, A.G. (2021): The effect of online restaurant menus on consumers’ purchase intentions during the COVID-19 pandemic. – International Journal of Hospitality Management 94: 10p.
[6] Chen, H.-S., Liang, C.-H., Liao, S.-Y., Kuo, H.-Y. (2020): Consumer attitudes and purchase intentions toward food delivery platform services. – Sustainability 12(23): 15p.
[7] Cronbach, L.J. (1951): Coefficient alpha and the internal structure of tests. – Psychometrika 16(3): 297-334.
[8] Davis, F.D. (1989): Perceived usefulness, perceived ease of use, and user acceptance of information technology. – MIS Quarterly 13(3): 319-340.
[9] Department of Statistics Malaysia (2024): Economic Census 2023: Food and beverage services sector. – Department of Statistics Malaysia, Putrajaya 120p.
[10] Faul, F., Erdfelder, E., Buchner, A., Lang, A.-G. (2009): Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. – Behavior Research Methods 41(4): 1149-1160.
[11] Fornell, C., Larcker, D.F. (1981): Evaluating structural equation models with unobservable variables and measurement error. – Journal of Marketing Research 18(1): 39-50.
[12] Ghazali, N.I., Othman, R., Ngali, N., Rahmat, N., Zainal Abidin, M. (2025): Digital menus and customer revisit intentions: Insights from Klang Valley restaurants using an extended TAM framework. – Information Management and Business Review 17(1(I)S): 122-134.
[13] Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E. (2010): Multivariate data analysis. – Pearson Prentice Hall 816p.
[14] Johnson, J.W., LeBreton, J.M. (2004): History and use of relative importance indices in organizational research. – Organizational Research Methods 7(3): 238-257.
[15] Kasavana, M.L., Smith, D.I. (1982): Menu engineering: A practical guide to menu analysis. – Hospitality Publishers 120p.
[16] Kimes, S.E. (2021): The future of restaurant technology. – Cornell Hospitality Report 21(1): 1-17.
[17] Kock, N. (2015): Common method bias in PLS-SEM: A full collinearity assessment approach. – International Journal of e-Collaboration 11(4): 1-10.
[18] Mohd Yusoff, Y. (2019): Actual practices of environmental performance in Malaysia’s hotel industry. – Sains Humanika 11(2-2): 73-80.
[19] Oktavia, T., Prabowo, H., Meyliana, Supangkat, S.H. (2023): QR code menu transformation: Usability testing approach for the food and beverage industry. – Journal of Theoretical and Applied Information Technology 101(10): 3912-3925.
[20] Pallant, J. (2020): SPSS survival manual. – Routledge 378p.
[21] Parasuraman, A., Zeithaml, V.A., Berry, L.L. (1988): SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. – Journal of Retailing 64(1): 12-40.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 ARNIEYANTIE ABDUL HADI, NUR NADIA MAISARAH MOHD FISOL, ELISYA ARDINI AHMAD FAUZI, NUR AISYAH YUSRA AZMI, MAS AFFANDY MASHURI, AHMAD REDHUAN ABU BAKAR, CHE KU NAJWA HUSNA CHE KU ARIS, STEPHENIE YOKE WEI WONG
This work is licensed under a Creative Commons Attribution 4.0 International License.
