Clustering new product development projects from the perspective of knowledge management

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.

Graphical abstract

Keywords

multi-project management / new product development (NPD) / knowledge management / clustering / dependency structure matrix (DSM)

References

[1] Abbasi D, Ashrafi M, Ghodsypour S, (2020). A multi objective-BSC model for new product development project portfolio selection. Expert Systems with Applications, 162: 113757

[2] Abdolvand N, Albadvi A, Aghdasi M, (2015). Performance management using a value-based customer-centered model. International Journal of Production Research, 53( 18): 5472–5483

[3] Argote L, Fahrenkopf E, (2016). Knowledge transfer in organizations: The roles of members, tasks, tools, and networks. Organizational Behavior and Human Decision Processes, 136: 146–159

[4] Bai L, Zheng K, Wang Z, Liu J, (2022). Service provider portfolio selection for project management using a BP neural network. Annals of Operations Research, 308( 1-2): 41–62

[5] Bashir H, Ojiako U, Marshall A, Chipulu M, Yousif A, (2022). The analysis of information flow interdependencies within projects. Production Planning and Control, 33( 1): 20–36

[6] BiYYangQChangMYaoT (2020). DSM-based knowledge transfer modeling between projects for multi-project clustering analysis. Proceedings of the 22nd International DSM Conference (DSM 2020), MIT, Cambridge, Massachusetts, USA. 105–113

[7] Browning T R, (2016). Design structure matrix extensions and innovations: A survey and new opportunities. IEEE Transactions on Engineering Management, 63( 1): 27–52

[8] Cao H, Hall N, Wan G, Zhao W, (2024). Optimal intraproject learning. Manufacturing & Service Operations Management, 26( 2): 681–700

[9] Carrillo J E, Franza R M, (2006). Investing in product development and production capabilities: The crucial linkage between time-to-market and ramp-up time. European Journal of Operational Research, 171( 2): 536–556

[10] Chen H, Ding G, Zhang J, Li R, Jiang L, Qin S, (2022). A filtering genetic programming framework for stochastic resource constrained multi-project scheduling problem under new project insertions. Expert Systems with Applications, 198: 116911

[11] Daie P, Li S, (2016). Managing product variety through configuration of pre-assembled vanilla boxes using hierarchical clustering. International Journal of Production Research, 54( 18): 5468–5479

[12] Frank A G, Ribeiro J L D, (2014). An integrative model for knowledge transfer between new product development project teams. Knowledge Management Research and Practice, 12( 2): 215–225

[13] Gao X, Wu S, (2019). CUBOS: An internal cluster validity index for categorical data. Tehnicki Vjesnik, 26( 2): 486–494

[14] Haug A, (2023). Factors influencing knowledge sharing in new product development in high-tech manufacturing firms. International Journal of Production Research, 61( 19): 6418–6433

[15] Klessova S, Thomas C, Engell S, (2020). Structuring inter-organizational R&D projects: Towards a better understanding of the project architecture as an interplay between activity coordination and knowledge integration. International Journal of Project Management, 38( 5): 291–306

[16] Korhonen T, Laine T, Lyly-Yrjanainen J, Suomala P, (2016). Innovation for multiproject management: The case of component commonality. Project Management Journal, 47( 2): 130–143

[17] Kumar S, Toshniwal D, (2016). Analysis of hourly road accident counts using hierarchical clustering and cophenetic correlation coefficient (CPCC). Journal of Big Data, 3( 1): 13–24

[18] Lin L, Wang H, (2019). Dynamic incentive model of knowledge sharing in construction project team based on differential game. Journal of the Operational Research Society, 70( 12): 2084–2096

[19] Liu T, Shi Z, Dong H, Bai J, Yan Y, (2024). Risk evaluation for the task transfer of an aircraft maintenance program based on a multielement connection number. Frontiers of Engineering Management, 11( 1): 16–31

[20] Navaei J, Elmaraghy H, (2016). Grouping part/product variants based on networked operations sequence. Journal of Manufacturing Systems, 38: 63–76

[21] Navaei J, Elmaraghy H, (2018). Optimal operations sequence retrieval from master operations sequence for part/product families. International Journal of Production Research, 56( 1–2): 140–163

[22] Ochodek M, Staron M, Meding W, (2019). SimSAX: A measure of project similarity based on symbolic approximation method and software defect inflow. Information and Software Technology, 115: 131–147

[23] Ou Y, Guo Q, Liu J, (2022). Identifying spreading influence nodes for social networks. Frontiers of Engineering Management, 9( 4): 520–549

[24] Özkan-Seely F, Gaimon C, Kavadias S, (2015). Dynamic knowledge transfer and knowledge development for product and process design teams. Manufacturing & Service Operations Management, 17( 2): 177–190

[25] Pan M, Chandrasekaran A, Hill J, Rungtusanatham M, (2022). Multidisciplinary R&D project success in small firms: The role of multi-project status and project management experience. Production and Operations Management, 31( 7): 2806–2821

[26] Patriarca R, Simone F, Di Gravio G, (2023). Supporting weather forecasting performance management at aerodromes through anomaly detection and hierarchical clustering. Expert Systems with Applications, 213: 119210

[27] Qiao Y, Fricker J D, Labi S, (2019). Quantifying the similarity between different project types based on their pay item compositions: application to bundling. Journal of Construction Engineering and Management, 145( 9): 04019053

[28] Santoro F M, Borges M R, Rezende E A, (2006). Collaboration and knowledge sharing in network organizations. Expert Systems with Applications, 31( 4): 715–727

[29] Stock G N, Tsai J C, Jiang J, Klein G, (2021). Coping with uncertainty: Knowledge sharing in new product development projects. International Journal of Project Management, 39( 1): 59–70

[30] Vali M, Salimifard K, Gandomi A H, Chaussalet T J, (2022). Care process optimization in a cardiovascular hospital: An integration of simulation-optimization and data mining. Annals of Operations Research, 318( 1): 685–712

[31] Wu Y, (2015). Organizational structure and product choice in knowledge-intensive firms. Management Science, 61( 8): 1830–1848

[32] Xu J, He M, Jiang Y, (2022). A novel framework of knowledge transfer system for construction projects based on knowledge graph and transfer learning. Expert Systems with Applications, 199: 116964

[33] Yang Q, Yang N, Browning T R, Jiang B, Yao T, (2022). Clustering product development project organization from the perspective of social network analysis. IEEE Transactions on Engineering Management, 69( 6): 2482–2496

[34] Yang Q, Yao T, Lu T, Zhang B, (2014). An overlapping-based design structure matrix for measuring interaction strength and clustering analysis in product development project. IEEE Transactions on Engineering Management, 61( 1): 159–170

[35] Zhang L, Zhao M, Wang Q, (2016). Research on knowledge sharing and transfer in remanufacturing engineering management based on SECI model. Frontiers of Engineering Management, 3( 2): 136–143

[36] Zhang Z, Min M, (2022). Research on the NPD coordination, knowledge transfer process and innovation performance of interfirm projects in China. Asia Pacific Journal of Management, 39( 4): 1161–1186

[37] Zhou Q, Deng X, Wang G, Mahmoudi A, (2022). Linking elements to outcomes of knowledge transfer in the project environment: Current review and future direction. Frontiers of Engineering Management, 9( 2): 221–238

[38] Zou X, Yang Q, Wang Q, Jiang B, (2024). Measuring the system resilience of project portfolio network considering risk propagation. Annals of Operations Research, 340( 1): 693–721

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