Grouping environmental factors influencing individual decision‐making behavior in software projects: A cluster analysis. Issue 1 (23rd October 2017)

• Record Type: Journal Article
• Authors: Jia, Jingdong; Mo, Hanlin; Capretz, Luiz Fernando; Chen, Zupeng
• Is Part Of: Journal of software. Volume 30:Issue 1(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-10-23
• Subjects: cluster analysis -- decision‐making behavior -- environmental factor -- semantic similarity -- WordNet; Software engineering -- Periodicals; Computer software -- Development -- Periodicals; Software maintenance -- Periodicals; 005.1
• DOI: 10.1002/smr.1913
• Languages: English
• ISSNs: 2047-7473

Abstract

Abstract: An individual's decision‐making behavior is heavily influenced by and adapted to external environmental factors. Given that software development is a human‐centered activity, individual decision‐making behavior may affect the software project quality. Although environmental factors affecting decision‐making behavior in software projects have been identified in prior literature, there is not yet an objective and a full taxonomy of these factors. Thus, it is not trivial to manage these complex and diverse factors. To address this deficiency, we first design a semantic similarity algorithm between words by utilizing the synonymy and hypernymy relationships in WordNet. Further, we propose a method to measure semantic similarity between phrases and apply it into k‐means clustering algorithm to group these factors. Subsequently, we obtain a taxonomy of the environmental factors affecting individual decision‐making behavior in software projects, which includes 11 broad categories, each containing 2 to 5 sub‐categories. The taxonomy presented herein is obtained by an objective method, and quite comprehensive, with appropriate references provided. The taxonomy holds significant value for researchers and practitioners; it can help them to better understand the major aspects of environmental factors, also to predict and guide the behavior of individuals during decision making towards a successful completion of software projects. Abstract : Based on the synonymous and hypernym in WordNet, we design algorithms to measure semantic similarity between words, further phrases. Then, k‐means was adopted to group these environmental factors provided in prior literature. We finally obtained a relatively objective and comprehensive taxonomy of environmental factors affecting individuals decision‐making behaviors in software projects, which include the optimal 11 categories with centroids as the name of category and 38 sub‐categories.