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Management of Software Engineering Innovation in Japan pp 49–88Cite as

Statistical Analysis Results and Practical Implications of the SEE Surveys

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Abstract

The objective of the research is to better understand the mechanisms of how software engineering capabilities relate to firms’ business performance and business environment for the Japanese software industry. Based on the Software Engineering Excellence (SEE) survey results shown in Chap. 2, statistical analysis results are demonstrated using cross-section analysis, path analysis, stratified analysis, panel analysis, and longitudinal analysis. Focusing on management of software engineering innovation, we empirically verified the common order effects originating with human resource development and proceeding along the paths of service innovation, product innovation, and process innovation. Based on the panel analysis, we demonstrated several series correlations among the software engineering capabilities. The longitudinal analysis suggested positive relationships among software engineering capabilities and business performance in the long-term. However, the relationships between the software engineering capabilities and business performance vary significantly depending on the origin of a vendor: manufacturer or user spin-off or independent. Based on the analysis results, the several implications for managing innovation in software engineering in Japan, such as economies of scale and organizational inertia, are discussed in this chapter.

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Authors and Affiliations

  1. Ritsumeikan University Graduate School of Technology Management, Ibaraki, Osaka, Japan

    Yasuo Kadono

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  1. Yasuo Kadono
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Correspondence to Yasuo Kadono .

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Kadono, Y. (2015). Statistical Analysis Results and Practical Implications of the SEE Surveys. In: Management of Software Engineering Innovation in Japan. Springer, Tokyo. https://doi.org/10.1007/978-4-431-55612-1_3

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