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Clustering new product development projects from the perspective of knowledge management

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Abstract

Knowledge transfer among New Product Development (NPD) projects is beneficial for reducing project duration and promoting technological innovation. To support effective knowledge transfer, we propose a clustering method for NPD projects based on similarity, integrating both structural and attribute similarities. First, to measure project structural similarity, we analyze both direct and indirect knowledge transfer relationships among project activities using the dependency structure matrix (DSM). Second, we measure project attribute similarity by calculating knowledge increments derived from sequential and iterative development processes. Finally, we apply a hierarchical clustering method to group similar projects, forming different programs. An industrial example is provided to demonstrate the proposed model. The results show that clustering projects into programs can enhance multi-project management by reducing coordination time for knowledge transfer within each program. Additionally, this approach provides some new insights, including quantifying project similarity based on knowledge transfer and understanding the influence of structural and attribute similarities on multi-project management.

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Authors and Affiliations

  1. School of Economics and Management, University of Science and Technology Beijing, Beijing, 100083, China

    Pingye Tian & Qing Yang

  2. Shougang Institute of Talent Development (Party School), Beijing, 100144, China

    Yingxin Bi

Authors
  1. Pingye Tian
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  2. Qing Yang
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  3. Yingxin Bi
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Corresponding author

Correspondence to Qing Yang.

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Competing Interests The authors declare that they have no competing interests.

Additional information

This research was supported by the National Natural Science Foundation of China (Grant Nos. W2441021 and 72271022).

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Cite this article

Tian, P., Yang, Q. & Bi, Y. Clustering new product development projects from the perspective of knowledge management. Front. Eng. Manag. (2025). https://doi.org/10.1007/s42524-025-4133-z

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  • DOI: https://doi.org/10.1007/s42524-025-4133-z

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