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Types of R&D Collaborations and Process Innovation: The Benefit of Collaborating Upstream in the Knowledge Chain
Author(s) -
Un C. Annique,
Asakawa Kazuhiro
Publication year - 2015
Publication title -
journal of product innovation management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.646
H-Index - 144
eISSN - 1540-5885
pISSN - 0737-6782
DOI - 10.1111/jpim.12229
Subject(s) - competitor analysis , upstream (networking) , business , downstream (manufacturing) , position (finance) , process (computing) , product (mathematics) , ranking (information retrieval) , knowledge management , marketing , industrial organization , computer science , telecommunications , mathematics , operating system , geometry , finance , machine learning
This paper explains how research and development ( R&D ) collaborations impact process innovation; given the differences in innovation mechanisms, prior insights from studies of product innovation do not necessarily apply to process innovation. Extending the knowledge‐based view of the firm, this paper classifies four types of R&D collaborations—with universities, suppliers, competitors, and customers—in terms of two knowledge dimensions: position in the knowledge chain and contextual knowledge distance. Position in the knowledge chain is the position of the R&D collaboration partner in the knowledge chain of the industry—the input–output sequence of activities that result in the transformation of raw materials into products that are used by end customers. Based on this knowledge chain, this paper considers universities and suppliers as upstream R&D collaborators, and competitors and customers as downstream R&D collaborators. Contextual knowledge distance is the difference in industry‐related contexts of operation of the R&D collaboration partners and the firm. Based on this, this paper views R&D collaborators that are suppliers and competitors as having low contextual knowledge distance to the firm, and R&D collaborators that are customers and universities as having high contextual knowledge distance to the firm. Using this classification, this paper proposes a ranking of R&D collaborations in terms of their impact on process innovation: R&D collaborations with suppliers have the highest impact, followed by R&D collaborations with universities, then R&D collaborations with competitors, and finally R&D collaborations with customers. These arguments are tested on a four‐year panel of 781 manufacturing firms. The results of the analyses indicate that R&D collaborations with suppliers and universities appear to have a positive impact on process innovation, R&D collaborations with customers appear to have no impact, and R&D collaborations with competitors appear to have a negative impact. As a consequence, the main driver of the impact of R&D collaborations on process innovation appears to be position in the knowledge chain rather than contextual knowledge distance. These novel ideas and findings contribute to the literature on process innovation. Even though process innovation tends to be internal and tacit to the firm, it can still benefit from external R&D collaborations; this paper is the first to analyze this relationship and provide a theoretical framework for understanding why this would be the case. This study also has important managerial implications. It suggests that managers need to be careful in choosing the partners for their firms' R&D collaborations. Engaging in R&D collaborations with universities and suppliers appears to be helpful for process innovation, whereas conducting R&D collaborations with competitors may potentially harm process innovation.