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Selection of collaborative partners for ambidextrous technological innovation: an approach based on community detection

Chunhua Ju & Qianwen Cao

International Journal of Technology Management2025https://doi.org/10.1504/ijtm.2025.145462article
AJG 2ABDC B
Weight
0.41

Abstract

The selection of an appropriate partner plays a crucial role in overcoming technological barriers via technological innovation. This study aims to propose a methodology for the selection of technological innovation partners, focusing on recommending different potential partners based on ambidextrous technological innovation. This article presents a comprehensive framework for partner selection in collaborative innovation. The construction of collaboration networks relies on the existing collaborative relationships. The Louvain algorithm is employed to partition networks into distinct communities, while the number of times of co-citation is utilised for selecting the appropriate community. The community members are divided into two parts of partners for radical innovation and partners for incremental innovation based on their technical distance from the enterprise requiring partners. The partner selection methods proposed in this study demonstrate remarkable efficacy in expanding the range of partner selection options, improving selection efficiency and enhancing pertinence.

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https://doi.org/https://doi.org/10.1504/ijtm.2025.145462

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@article{chunhua2025,
  title        = {{Selection of collaborative partners for ambidextrous technological innovation: an approach based on community detection}},
  author       = {Chunhua Ju & Qianwen Cao},
  journal      = {International Journal of Technology Management},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijtm.2025.145462},
}

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Selection of collaborative partners for ambidextrous technological innovation: an approach based on community detection

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Evidence weight

0.41

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.25 × 0.4 = 0.10
M · momentum0.55 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.