Diving into the uncertainties of open innovation: A systematic review of risks to uncover pertinent typologies and unexplored horizons. (January 2023)

• Record Type: Journal Article
• Authors: Madanaguli, Arun; Dhir, Amandeep; Talwar, Shalini; Clauss, Thomas; Kraus, Sascha; Kaur, Puneet
• Is Part Of: Technovation. Volume 119(2023)
• Publication Date: 2023-01
• Subjects: Open innovation -- Systematic literature review -- Risks -- Value co-creation -- Uncertainties; Technological innovations -- Periodicals; Industrial management -- Periodicals; Innovations -- Périodiques; Gestion d'entreprise -- Périodiques; Electronic journals; 658.57
• DOI: 10.1016/j.technovation.2022.102582
• Languages: English
• ISSNs: 0166-4972

Abstract

Abstract: The open innovation paradigm has created substantial new opportunities for firms in various sectors. However, scholars have long expressed concern that open innovation also entails a dark side, which can result in value co-destruction. This concern highlights the importance of devoting attention to the perils of pursuing open innovation. Existing scholarship has given due credence to these perils by examining various associated risks and uncertainties. We observe that the extant literature is siloed and unorganized, which impedes future research. Positing that an endeavor to organize existing studies may enhance the pace of research in the area, we attempt to address this gap by reviewing the relevant literature. We thus utilize the systematic literature review approach to identify, synthesize, and critically analyze 80 related research articles. Based on this analysis, we present the bibliometric profile of the extant research and a typology of five risks in open innovation: data-related risks, people-related risks, firm-level risks, outcome risks, and other risks. In addition, we discuss a specific risk management approach for each of the identified risks. Beyond providing a lucid narrative of the extant literature, we also identify unexplored avenues and offer an overarching framework to conceptualize future research potential in the area. From a practical perspective, managers can utilize this framework as a risk assessment tool when engaging in open innovation. In sum, this review—one of the first of its kind—offers a valuable consolidation of the state of the art of open innovation risk research, which can meaningfully advance theory and practice in the area. Highlights: This review categorizes risks in open innovation into five major risk segments. Research profile of literature suggests an increasing trend of work on risk in open innovation. Prominent risks and corresponding risk management steps are summarized. Risks are mapped to various steps in the innovation process. A learning-based risk assessment framework for open innovation is advanced.