Emergent Strategy and Innovation in Entrepreneurship: A Complex Adaptive Systems Perspective

Abstract

Entrepreneurship research increasingly recognises that opportunities, strategies and innovations develop in settings where technologies, institutions and stakeholder relationships change together. Yet the relevant literatures often locate explanation at different levels: opportunity research privileges entrepreneurial judgement, ecosystem research emphasises interdependence, and strategic entrepreneurship concentrates on the mobilisation of resources. This conceptual paper connects these levels through a complex adaptive systems perspective. It asks how entrepreneurs translate distributed environmental change into coordinated action and innovation without assuming either complete foresight or purely spontaneous adaptation. The framework was developed through a theory-integration approach that compares the causal roles assigned to variation, interaction, feedback and selection across complexity, opportunity and strategic entrepreneurship research. It distinguishes five constructs: environmental complexity and disequilibrium, opportunity emergence, adaptive entrepreneurial capability, adaptive self-organisation, and innovation outcomes. Three propositions specify the mechanism. Environmental disequilibrium makes opportunities more likely to emerge when change creates interpretable gaps in existing arrangements; adaptive entrepreneurial capability strengthens the conversion of those possibilities into self-organised action; and emergent strategy carries the effect of such action into innovation while performance feedback reshapes later interpretation and capability. The contribution is a process model that joins individual judgement to collective reconfiguration and treats innovation as both an outcome and a source of subsequent adaptation. The framework also identifies boundary conditions—resource slack, network accessibility and feedback quality—that can interrupt the proposed sequence. The paper concludes with an empirical agenda using longitudinal, multilevel and process-sensitive designs.