Selective search and new-to-market process innovation

Author:

Aliasghar OmidORCID,Kanani Moghadam VenusORCID

Abstract

PurposeSearching for knowledge from outside firms' boundaries has been proved to be a critical strategy to develop innovation. However, the existing body of research has mainly focused on the high-tech sector in developed countries, largely neglecting the considerable role of low- and medium-technology sectors (LMT) in emerging contexts. The authors discuss the fact that knowledge search patterns and the role of internal R&D intensity differ for firms operating in LMT sectors.Design/methodology/approachA sample of 1,365 firms operating in LMT sectors in Iran was used to test the proposed conceptual model, using logistic regression analysis.FindingsThe findings show that a firm will learn from its collaboration with value chain partners only if it has a strong in-house R&D capacity. In addition, while a high level of internal research development capacity increases the impact of knowledge acquired from value chain partners, the authors did not find evidence for complementarity between the investment in internal technology development and knowledge acquired from university and science-based partners.Originality/valueUnlike previous studies in open innovation that have mainly investigated the role of knowledge search on product innovation in developed countries, this study contributes to the literature by connecting the concepts of R&D intensity and selective search, discussing that businesses operating in challenging contexts follow different knowledge search strategies to develop process-related innovation activities.

Publisher

Emerald

Subject

Industrial and Manufacturing Engineering,Strategy and Management,Computer Science Applications,Control and Systems Engineering,Software

Reference88 articles.

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