Exploring the Practices and Factors Influencing Requirements Change Management in Agile Global Software Development: A Systematic Literature Review

Requirements change management (RCM) in agile global software development (AGSD) represents a challenging and underexplored issue. Despite an increasing number of researchers showing interest in this area, most current studies remain confusing. On the one hand, studies aim to identify 'practical' (i.e., actionable) agile practices with contextual influencing factors. However, this confusion has generated conceptually vague results, making it difficult for both researchers and practitioners to derive clear insights and actionable strategies from the findings. These limitations represent a barrier to both the theoretical accumulation of RCM knowledge and providing practitioners with useful guidance on the topic. This study attempts to fill this gap by employing a systematic literature review (SLR) for the 2016-2026 timeframe. The literature review followed Kitchenham and Charters' guidelines and used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 reporting guidelines. In total, 55 primary studies were identified, coded, and examined using a formally defined coding system that clearly distinguished practices from influencing factors. Based on these analyses, the SLR identified 23 agile RCM practices and grouped them into five practice families: communication, requirements management, management, development/software engineering, and agile practices. Additionally, the analysis also identified eight contextual factors that influence RCM success. An explanatory conceptual model was developed to describe how practices can generate successful RCM processes by identifying six mechanisms: information alignment, requirement clarification, shared understanding formation, decision structuring, adaptive coordination, and technical validation, which can lead to process- and project-level outcomes. Therefore, the results of the SLR present a structured knowledge base that provides evidence for understanding RCM in AGSD and develops a foundation for future empirical verification.

Text 127232.pdf - Published Version Available under License Creative Commons Attribution. Download (6MB) Official URL or Download Paper: https://ieeexplore.ieee.org/document/11579315/

Actions (login required)

View Item