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Exploring networks of proximity for partner selection, firms' collaboration and knowledge exchange. The case of clean‐tech industry
Author(s) -
Marra Alessandro,
Carlei Vittorio,
Baldassari Cristiano
Publication year - 2020
Publication title -
business strategy and the environment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.123
H-Index - 105
eISSN - 1099-0836
pISSN - 0964-4733
DOI - 10.1002/bse.2415
Subject(s) - business , knowledge management , knowledge sharing , field (mathematics) , selection (genetic algorithm) , high tech , marketing , industrial organization , computer science , mathematics , artificial intelligence , political science , pure mathematics , law
Nowadays scholars widely recognize that know‐how, capabilities and knowledge needed to generate innovations often reside outside the firm, start‐ups are a valuable source, and collaborative networks are a fundamental strategy for innovation. This is true especially for the clean‐tech sector, which is characterized by the continuous search for innovative solutions and technological advancements. The purpose of the paper is to provide a methodological support for the screening of potential partners based on network analysis and, then, help firms to select them for collaboration and knowledge exchange. The methodology can be easily adopted by managers and executives to identify firms to monitor with greater attention for future investments. The analysis is on a dataset of 4,782 clean‐tech companies operating worldwide. Results highlight that energy companies looking for external sources could investigate their network of business proximity if they intend to specialize in a defined field and/or collaborate with similar partners, while they could explore their network of strategic proximity if they intend to diversify their businesses, that is cooperating and exchanging knowledge with firms with distant but complementary capabilities and resources.