Innovating Restaurant Inventory Management Application Enhancing Quality And Efficiency Through Extreme Pro-gramming Approach
Keywords:
Inventory Management, Extreme Programming, RestaurantAbstract
This research investigates the complex challenges in inventory management within the restaurant industry, including the risk of inventory calculation errors, stock shortages, and material wastage. The Extreme Programming (XP) method is utilized to develop an inventory management application to address these issues. Through user requirement analysis, XP-based application development, and user evaluation stages, this study successfully designs and implements an efficient and adaptive application. User evaluation results indicate positive feedback, with 85% of users expressing satisfaction with the application, affirming that it provides optimal value by enhancing operational efficiency and improving restaurant customer experience. This research contributes to implementing the adaptive and responsive XP method to address changes in inventory management, proving its effectiveness in dealing with the complexities of the dynamic restaurant industry.
Downloads
References
Abdul Aziz, N., Othman, N. A., & Abdul Murad, S. M. Bin. (2023). The effects of social support and social media influencers’ credibility on emotional brand attachment: The mediating roles of trust in multichannel. Social Sciences and Humanities Open, 8(1). https://doi.org/10.1016/j.ssaho.2023.100727
Al-Saqqa, S., Sawalha, S., & Abdelnabi, H. (2020). Agile software development: Methodologies and trends. International Journal of Interactive Mobile Technologies, 14(11). https://doi.org/10.3991/ijim.v14i11.13269
Bansal, N., Singh, D., & Kumar, M. (2023). Computation of energy across the type-C piano key weir using gene expression programming and extreme gradient boosting (XGBoost) algorithm. Energy Reports, 9, 310–321. https://doi.org/10.1016/j.egyr.2023.04.003
Chen, A., & Peng, N. (2023). Antecedents to Consumers’ Green Hotel Stay Purchase Behavior during the COVID-19 Pandemic: The influence of green consumption value, emotional ambivalence, and consumers’ perceptions. Tourism Management Perspectives, 47. https://doi.org/10.1016/j.tmp.2023.101107
Chen, J., Yu, T., Yin, L., Tang, J., & Wang, H. (2020). A unified time scale intelligent control algorithm for microgrid based on extreme dynamic programming. CSEE Journal of Power and Energy Systems, 6(3), 583–590. https://doi.org/10.17775/CSEEJPES.2019.00100
Debasa, F., Gelashvili, V., Martínez-Navalón, J. G., & Saura, J. R. (2023). Do stress and anxiety influence users’ intention to make restaurant reservations through mobile apps? European Research on Management and Business Economics, 29(1). https://doi.org/10.1016/j.iedeen.2022.100205
Dingsoeyr, T., Falessi, D., & Power, K. (2019). Agile Development at Scale: The Next Frontier. In IEEE Software (Vol. 36, Issue 2, pp. 30–38). IEEE Computer Society. https://doi.org/10.1109/MS.2018.2884884
Dingsøyr, T., Nerur, S., Balijepally, V., & Moe, N. B. (2012). A decade of agile methodologies: Towards explaining agile software development. In Journal of Systems and Software (Vol. 85, Issue 6). https://doi.org/10.1016/j.jss.2012.02.033
El-Said, O., & Al Hajri, S. (2022). Are customers happy with robot service? Investigating satisfaction with robot service restaurants during the COVID-19 pandemic. Heliyon, 8(3). https://doi.org/10.1016/j.heliyon.2022.e08986
Ferreira, D., Vale, M., Miguel Carmo, R., Encalada-Abarca, L., & Marcolin, C. (2021). The three levels of the urban digital divide: Bridging issues of coverage, usage and its outcomes in VGI platforms. Geoforum, 124, 195–206. https://doi.org/10.1016/j.geoforum.2021.05.002
Fojtik, R. (2011). Extreme programming in development of specific software. Procedia Computer Science, 3, 1464–1468. https://doi.org/10.1016/j.procs.2011.01.032
Hakim, M. P., Zanetta, L. D. A., & da Cunha, D. T. (2021). Should I stay, or should I go? Consumers’ perceived risk and intention to visit restaurants during the COVID-19 pandemic in Brazil. Food Research International, 141. https://doi.org/10.1016/j.foodres.2021.110152
Ho, B., Mayberry, T., Nguyen, K. L., Dhulipala, M., & Pallipuram, V. K. (2024). ChatReview: A ChatGPT-enabled natural language processing framework to study domain-specific user reviews. Machine Learning with Applications, 15, 100522. https://doi.org/10.1016/j.mlwa.2023.100522
Omar, M. S., Ariffin, H. F., & Ahmad, R. (2016). Service Quality, Customers’ Satisfaction and the Moderating Effects of Gender: A Study of Arabic Restaurants. Procedia - Social and Behavioral Sciences, 224, 384–392. https://doi.org/10.1016/j.sbspro.2016.05.393
Pilar Opazo, M. (2012). Discourse as driver of innovation in contemporary haute cuisine: The case of elBulli restaurant. International Journal of Gastronomy and Food Science, 1(2), 82–89. https://doi.org/10.1016/j.ijgfs.2013.06.001
Pleerux, N., & Nardkulpat, A. (2023). Sentiment analysis of restaurant customer satisfaction during COVID-19 pandemic in Pattaya, Thailand. Heliyon, 9(11). https://doi.org/10.1016/j.heliyon.2023.e22193
Santiago, J., Borges-Tiago, M. T., & Tiago, F. (2024). Embracing RAISA in restaurants: Exploring customer attitudes toward robot adoption. Technological Forecasting and Social Change, 199. https://doi.org/10.1016/j.techfore.2023.123047
Santos, R., Cunha, F., Rique, T., Perkusich, M., Almeida, H., Perkusich, A., & Icaro Costa, ´. (n.d.). A Comparative Analysis of Agile Teamwork Quality Instruments in Agile Software Development: A Qualitative Approach. https://doi.org/10.18293/DMSVIVA2023-217
Serrador, P., & Pinto, J. K. (2015). Does Agile work? - A quantitative analysis of agile project success. International Journal of Project Management, 33(5). https://doi.org/10.1016/j.ijproman.2015.01.006
Shrivastava, S. V., & Rathod, U. (2014). Risks in Distributed Agile Development: A Review. Procedia - Social and Behavioral Sciences, 133, 417–424. https://doi.org/10.1016/j.sbspro.2014.04.208
Staley, L., & Jucker, A. H. (2021). “The uh deconstructed pumpkin pie”: The use of uh and um in Los Angeles restaurant server talk. Journal of Pragmatics, 172, 21–34. https://doi.org/10.1016/j.pragma.2020.11.004
Suginouchi, S., & Mizuyama, H. (2022). Scheduling Auction based restaurant reservation method for achieving social distancing. Procedia CIRP, 112, 39–44. https://doi.org/10.1016/j.procir.2022.09.021
Suginouchi, S., Nii, Y., & Mizuyama, H. (2023). Dynamic restaurant reservation method using Scheduling Dutch Auction for addressing social distancing. Procedia CIRP, 118, 26–31. https://doi.org/10.1016/j.procir.2023.06.006
Sularto, L., Wardoyo, & Yunitasari, T. (2015). User Requirements Analysis for Restaurant POS and Accounting Application Using Quality Function Deployment. Procedia - Social and Behavioral Sciences, 169, 266–280. https://doi.org/10.1016/j.sbspro.2015.01.310
Wang, J. F., Lin, Y. C., Kuo, C. F., & Weng, S. J. (2017). Cherry-picking restaurant reservation customers. Asia Pacific Management Review, 22(3), 113–121. https://doi.org/10.1016/j.apmrv.2016.12.001
Wood, S., Michaelides, G., & Thomson, C. (2013). Successful extreme programming: Fidelity to the methodology or good teamworking? Information and Software Technology, 55(4), 660–672. https://doi.org/10.1016/j.infsof.2012.10.002
