Framework for empirical examination and modeling structural dependencies among inhibitors that impact SPI implementation initiatives in software SMEs

Abstract

AbstractContextSince last more than one‐decade software process improvement, widely known as SPI has received the attention of the software engineering community.ObjectiveThe objective of the paper is to empirically examine and develop a framework to model structural dependences among inhibitors that impact SPI initiatives in software SMEs.MethodsAuthors used mixed method approach (empirical analysis and interpretive structural modeling, ISM) to evaluate, model, and analyze the association between SPI inhibitors in software SMEs.ResultsThe results from empirical analysis and ISM show that lack of management commitment, lack of resources, and lack of communication and information sharing are the key SPI inhibitors. The association of various inhibitors with SPI implementation is found statistically significant with effect size (0.42 < Ø < 0.75, P < 0.05). Also, Spearman's coefficient of correlation for rankings of SPI inhibitors is found to be moderate to high, ie, 0.601 (P = 0.01 < 0.05) for SLR and interviews; 0.794 (P = 0.00) for SLR and empirical analysis; and 0.711 (P = 0.002 < 0.01) for interviews and empirical analysis.ConclusionsAnalysis of SPI inhibitors through the proposed triangulation approach and development of software process improvement inhibitors model highlights the importance of structural dependencies among the inhibitors.