A contingency fit model of critical success factors for software development projects A comparison of agile and traditional plan-based methodologies

Purpose - While the choices available for project management methodologies have increased significantly, questions remain on whether project managers fully consider their alternatives. When project categorization systems and criteria are not logically matched with project objectives, characteristics and environment, this may provide the key reason for why many software projects are reported to fail to deliver on time, budget or do not give value to the client. The purpose of this paper is to identify and categorize critical success factors (CSFs) and develop a contingency fit model contrasting perspectives of traditional plan-based and agile methodologies. Design/methodology/approach - By systematically reviewing the previous literature, a total of 37 CSFs for software development projects are identified from 148 articles, and then categorized into three major CSFs: organizational, team and customer factors. A contingency fit model augments this by highlighting the necessity to match project characteristics and project management methodology to these CSFs. Findings - Within the three major categories of CSFs, individual factors are ranked based on how frequently they have been cited in previous studies, overall as well as across the two main project management methodologies (traditional, agile). Differences in these rankings as well as mixed empirical support suggest that previous research may not have adequately theorized when particular CSFs will affect project success and lend support for the hypothesized contingency model between CSFs, project characteristics and project success criteria. Research limitations/implications - This research is conceptual and meta-analytic in its focus. A crucial task for future research should be to test the contingency fit model developed using empirical data. There is no broad consensus among researchers and practitioners in categorizing CSFs for software development projects. However, through an extensive search and analysis of the literature on CSFs for software development projects, the research provides greater clarity on the categories of CSFs and how their direct, indirect and moderated effects on project success can be modelled. Practical implications - This study proposes a contingency fit model and contributes towards developing a theory for assessing the role of CSFs for project success. While future empirical testing of this conceptual model is essential, it provides an initial step for guiding quantitative data collection, specifies detailed empirical analysis for comparative studies, and is likely to improve clarity in debate. Since previous studies have not rigorously assessed the impact of fit between project characteristics, project environment and project management methodology on project success, additional empirically robust studies will help to clarify contradictory findings that have limited theory development for CSFs of software development projects to date. Originality/value - Previous research for software development projects has frequently not fully incorporated contingency as moderation or contingency as fit (traditional vs agile). This research sets out to develop fully a contingency fit perspective on software development project success, through contrasting traditional plan-driven and agile methodologies. To do this, the paper systematically identifies and ranks 37 CSFs for software projects from 148 journal publications and holistically categorizes them as organizational, team, customer and project factors.