Kawamura, Tomoyuki

写真a

Affiliation

Graduate School of System Design and Management ( Hiyoshi )

Position

Project Professor (Non-tenured)
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Papers 【 Display / hide 】

  • Factors Affecting Cross-Functional Collaboration in New Business Development in Japanese Enterprises

    Ozawa C., Kawamura T., Noguchi H., Toma T.

    IEEE International Conference on Industrial Engineering and Engineering Management    1165 - 1169 2025

    ISSN  21573611

    　View Summary

    To maintain sustainable competitive advantage, firms must continuously innovate by developing new business ventures. Cross-functional collaboration is a critical driver of success in this process. This study contributes to the advancement of corporate entrepreneurship literature by identifying key factors that facilitate cross-functional collaboration during the concept development stage. A web-based survey collected 411 valid responses from employees involved in new business development in Japanese companies. Factor analysis and multiple regression analysis revealed two significant determinants of cross-functional collaboration: i) individual curiosity and proactive engagement in new business development, and ii) managerial understanding and support for such initiatives. These findings suggest that enhancing individual motivation and securing management commitment are essential to promote effective collaboration across job functions. By addressing these elements, organisations can accelerate the creation of new business opportunities and strengthen their innovation capabilities.

  • Factors of Organizational Culture Affecting the Promotion of Digital Transformation - A Comparison Based on Company Size

    Kawamura T., Noguchi H., Washitani Y., Toma T.

    IEEE International Conference on Industrial Engineering and Engineering Management    893 - 897 2024

    ISSN  21573611

    　View Summary

    It is said that many companies have not achieved sufficient results from digital transformation (DX); therefore, companies must gain the ability to efficiently promote DX. The purpose of this study was to propose improvements to promote efficient DX by clarifying the differences in the factors of organizational culture that influence the promotion of DX based on differences in company size. By applying multigroup structural equation modeling using the results of previous research, the differences in factors between small and medium-sized enterprises (SMEs) and large enterprises (LEs) were identified. Based on these results, it was proposed that SMEs should focus on improving the characteristics of members of DX promotion organizations, and that LEs should focus on improving the management and capabilities of DX promotion organizations. It is expected that companies will efficiently promote DX by considering these results.

  • Outcome prediction of software projects for information technology vendors

    Kawamura T., Toma T., Takano K.

    IEEE International Conference on Industrial Engineering and Engineering Management (IEEE International Conference on Industrial Engineering and Engineering Management)  2017-December   1733 - 1737 2018.02

    ISSN  9781538609484

    　View Summary

    © 2017 IEEE. Several studies indicate that roughly 70% of the projects based on the software development have resulted in failure, thereby researchers and practitioners have been tried to develop solutions that will improve project success rates. It is insisted that to raise success rates, support should be provided by the organization to which the projects belong. With the aid of predictions that incorporate project outcomes for various information technology (IT) vendors, this study aims at identifying projects that should be preferentially supported by an organization. The data of 332 projects of various Japanese IT vendors were collected using an Internet survey, and a success/failure prediction algorithm is created by employing the Bayes classifier technique on the collected data. A resultant algorithm with 77.3% prediction capability was obtained. It is expected that the success/failure prediction procedure, including the prediction algorithm, help significantly to specify projects that an organization needs to participate in as priority.

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Papers, etc., Registered in KOARA 【 Display / hide 】

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Research Projects of Competitive Funds, etc. 【 Display / hide 】

  • Research on project manager competencies for digital transformation

    2024.04
    -
    2027.03

    基盤研究(C), Principal investigator

  • Research on organizational culture that affect promotion of Digital Transformation

    2020.04
    -
    2023.03

    MEXT,JSPS, Grant-in-Aid for Scientific Research, Grant-in-Aid for Early-Career Scientists , Principal investigator

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Courses Taught 【 Display / hide 】

  • PROJECT MANAGEMENT

    2026

  • DECISION MAKING AND RISK MANAGEMENT UNDER UNCERTAINTY

    2026

  • PROJECT MANAGEMENT

    2025

  • DECISION MAKING AND RISK MANAGEMENT UNDER UNCERTAINTY

    2025

  • PROJECT MANAGEMENT

    2024

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