Abstract

Purpose– The purpose of this paper is to provide a review of the innovation literature, with special focus on studies applying a complexity perspective. As a contribution in its own right to the innovation literature, the review clarifies the concept of complexity, explores possible points of relevance and the “added value” gained from complexity theory (CT) to the study of innovation, and identifies some of the applications of the theory.Design/methodology/approach– A literature search was conducted which yielded 20 relevant articles. These articles were analyzed by focusing on the key concepts of complexity and studying their applications in the context of innovation research.Findings– Based on the approach adopted, the literature was divided into three categories, namely research focusing on microdynamics, macrodynamics, and leadership and management. The key complexity concepts identified in the innovation literature were “edge of chaos”, “phase shift”, “emergence and self-organization”, “(co)evolution”, and “complexity regulation”. The articles reviewed differed in terms of their perspectives on complexity and, accordingly, their operationalization of the complexity concepts. Key areas of development suggested by the authors include forging a stronger link with existing innovation theory and giving greater weight to empirical evidence.Research limitations/implications– While a systematic review strategy was adopted to identify all relevant research on “open innovation” and complexity, a selective snowball strategy was deemed the only feasible approach to cover research conducted on “innovation” and complexity.Practical implications– Practitioners can learn to put CT-based research in context and also learn to recognize the value of CT for innovation management. The authors distilled three important lessons for practice from the research done: embracing complexity, embracing ambidexterity, and embracing failure.Originality/value– To the best of the authors’ knowledge no review has as yet been undertaken to encapsulate the current state of applications of CT to innovation research.

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