ABSTRACT
This paper investigates to what extent non-R&D activities individually and jointly drive innovation processes in small- and medium-sized enterprises (SMEs). We argue that non-R&D-performing and R&D-performing SMEs (non-R&D vs R&D performers) differ with respect to the separate and combined effects of non-R&D activities on technological innovations (product vs process). Drawing on a sample of 1392 Chinese manufacturing SMEs, our empirical results paint a complex and comprehensive picture of innovation processes in SMEs based on a set of non-R&D activities. We find that non-R&D performers rely primarily on embodied knowledge to develop innovations, and that R&D performers can access external networking in which customers and scientific sources drive product innovation and suppliers affect process innovation. We also find that the existence of substitutability between internal and external innovation sourcing strategies composed of non-R&D activities is limited to product innovation for non-R&D performers and process innovation for R&D performers.
Acknowledgments
The author is grateful to the editors, the anonymous reviewers, and Dr. Hamdy Abdelaty for their useful comments on earlier versions of this paper.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 This study builds upon, and has been influenced by, the work of Barge-Gil, Jesus Nieto, and Santamaría (Citation2011), and thus we strongly recommend their paper to our readers.
2 We take a firm-level view of complementarity/substitutability.
3 We thank a reviewer for the concept of ‘group AC’. A network-level analysis is beyond the scope of this study which focuses on complementarity/substitutability at the firm level.
4 According to the ES, we define an innovative firm as a firm that introduced at least one type of innovation. Non-R&D activities can be observed for innovative firms only.
5 For R&D performers, internal R&D is one of internal knowledge sources.
6 The selection of exclusive restriction is primarily driven by our sample in which the selected variable has no significant impact on innovation outputs.
7 The results of the selection equation are available upon request.
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Hailun Zhang
Hailun Zhang is a PhD candidate at School of Business and Economics, Freie Universität Berlin. Her research interests include SME innovation and non-R&D innovation.