Replication package - Prioritizing Feature Requests from App Reviews in Agile Mobile Software Development: A Mixed-Methods Empirical Study of Practitioners' Perspectives

Agile mobile software development increasingly relies on user feedback from app store reviews to inform requirements and feature request prioritization. While prior research has explored requirement elicitation and classification from user reviews, limited empirical evidence exists on how practitioners prioritize feature requests derived from such feedback in real-world agile mobile development contexts. This paper presents a mixed-methods empirical study combining a large-scale survey of 169 practitioners and semi-structured interviews with 12 practitioners to examine current practices, decision criteria, and challenges in prioritizing feature requests from app reviews. The study investigates (i) the factors influencing prioritization decisions, (ii) commonly used prioritization strategies, and (iii) how different types of feature requests are handled in practice. The results indicate that business value, implementation cost, and technical risk are the most influential prioritization factors, while contextual elements such as app store platform, organizational context, and regulatory constraints further shape decision-making. Ranking-based and classification-based components are frequently used in combination, and enhancement-related feature requests are typically addressed before other types. Although practitioners report interest in automation and machine learning support, concerns related to data quality, contextual interpretation, and trust limit their current adoption. These findings provide empirical insights into how app review feedback is translated into prioritization decisions and offer guidance for designing context-aware prioritization strategies in agile mobile software development.