Improving Operational Efficiency and Customer Service through a Web-Based Restaurant Management Information System
DOI:
https://doi.org/10.70356/josapen.v4i1.89Keywords:
Restaurant Management Information System, Operational Efficiency, Customer Service QualityAbstract
The restaurant industry faces increasing pressure to improve operational efficiency and deliver high quality customer service in a competitive and fast paced environment. This study aims to design and implement a web-based Restaurant Management Information System (RMIS) to address common operational challenges, including order processing delays, inventory inaccuracies, and fragmented service workflows. The system was developed using an Agile approach to ensure flexibility and alignment with user requirements. Data were collected through observation, interviews, and literature review, while system evaluation was conducted through functional testing and user feedback. The results indicate that the RMIS significantly improves order processing efficiency, enhances coordination between staff, and increases customer satisfaction through faster service and real time order tracking. These findings demonstrate that a web based RMIS is an effective solution for supporting efficient restaurant operations and improving overall service quality.
Downloads
References
K. C. Laudon and J. P. Laudon, Management Information Systems: Managing the Digital Firm, 16th ed. Harlow, U.K.: Pearson Education, 2020.
Y. K. Dwivedi et al., “International Journal of Information Management Metaverse beyond the hype : Multidisciplinary perspectives on emerging challenges , opportunities , and agenda for research , practice and policy,” Int. J. Inf. Manage., vol. 66, no. July, p. 102542, 2022, doi: https://doi.org/10.1016/j.ijinfomgt.2022.102542.
M. E. Porter and J. E. Heppelmann, “How smart, connected products are transforming companies,” Harvard Business Review, vol. 93, no. 10, pp. 96–114, 2015.
J. Kandampully, T. Zhang, and A. Bilgihan, “Customer loyalty: A review and future directions with a special focus on the hospitality industry,” International Journal of Contemporary Hospitality Management, vol. 27, no. 3, pp. 379–414, 2018.
DOI: https://doi.org/10.1108/IJCHM-03-2014-0151
H. Khanh, L. Chau, T. Thuy, A. Ngo, and C. T. Bui, “Computers in Human Behavior Reports Human-AI interaction in E-Commerce : The impact of AI-powered customer service on user experience and decision-making,” Comput. Hum. Behav. Reports, vol. 19, no. April, p. 100725, 2025, doi: https://doi.org/10.1016/j.chbr.2025.100725.
E. M. Rogers, Diffusion of Innovations, 5th ed. New York, NY, USA: Free Press, 2003.
V. Venkatesh, J. Y. Thong, and X. Xu, “Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology,” MIS Quarterly, vol. 36, no. 1, pp. 157–178, 2012.
DOI: https://doi.org/10.2307/41410412
F. Heron et al., “Science of Computer Programming Contextual abstraction in a type system for component-based high performance computing platforms,” Sci. Comput. Program., vol. 132, pp. 96–128, 2016, doi: https://doi.org/10.1016/j.scico.2016.07.005.
B. Nguyen, L. Simkin, and A. I. Canhoto, “The dark side of digital personalization: An agenda for research and practice. Journal of Business Research,“ 116, 209-221, 2020.
Y. Fei, J. Liou, and P. Jui, “Evaluating the dual impact of AI and RPA on sustainability and brand equity : A case study of digital transformation in Taiwan ’ s service sector,” Cleaner Engineering and Technology, vol. 29, no. October, 2025. doi: https://doi.org/10.1016/j.clet.2025.101106.
F. Marchesani and F. Ceci, “Technovation A quadruple helix view on smart city : Exploring the effect of internal and external open innovation on public services digitalization,” Technovation, vol. 139, no. September 2024, p. 103141, 2025, doi: https://doi.org/10.1016/j.technovation.2024.103141.
L. Gonz, “Agile change approach for collaborative software development contexts : A systematic literature review,” Array, vol. 28, no. November, 2025, doi: https://doi.org/10.1016/j.array.2025.100595.
J. Kaur, O. Singh, A. Anand, and M. Agarwal, “A goal programming approach for agile-based software development resource allocation,” Decis. Anal. J., vol. 6, no. November 2022, p. 100146, 2023, doi: https://doi.org/10.1016/j.dajour.2022.100146.
D. Pakkala and K. Jukka, “Journal of Industrial Information Integration Improving efficiency and quality of operational industrial production assets information management in customer – vendor interaction,” Journal of Industrial Information Integration, vol. 41, no. June, 2024, doi: https://doi.org/10.1016/j.jii.2024.100644.
C. Sassanelli and D. A. D. J. Pacheco, “Technological Forecasting & Social Change The impact of the internet of things on the perceived quality and customer involvement of smart product-service systems,” Technol. Forecast. Soc. Chang., vol. 198, no. November 2022, p. 122939, 2024, doi: https://doi.org/10.1016/j.techfore.2023.122939.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Yeti Friyani
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
