Comparative analysis of requirements prioritization methods for personalized nutrition web applications

This study investigates the application of five requirements prioritization methods – MoSCoW, Kano Model, Weighted Scoring, RICE, and Cost of Delay (CoD) – in the development of a web application for personalized nutrition. The research addresses the challenge of managing limited resources (time, financial, and human) while maximizing user value and ensuring safety in a high-stakes domain. Through a comparative analysis, the strengths and weaknesses of each method are evaluated, revealing that a hybrid approach, tailored to different development phases, is most effective. Core functionalities such as allergen management and diet personalization consistently ranked as high priority across all methods. The study proposes a dynamic framework that integrates MoSCoW and Weighted Scoring for MVP definition, and RICE and Kano for scaling, emphasizing the importance of balancing safety, user satisfaction, and implementation complexity. The findings offer practical recommendations for developers and product managers in health-tech and other regulated domains.