A complex adaptive systems approach to efficiency and innovation

Abstract

Purpose

The primary objective of this paper is to discuss whether complexity science can help overcome management's dilemma of how to balance efficiency and innovation.

Design/methodology/approach

Complexity science provides an interdisciplinary theoretical approach for studying complex adaptive systems (CAS), which exhibit adequate combinations of both emergent efficiency and emergent innovation. Based on prominent models from complexity science, a generic framework of CAS is proposed that shows the design levers of such systems. This framework then serves to assess recent literature on applications of complexity science to firms. Applications cover a broad range of objectives and four organizational levels: the individual resource, the organizational sub‐unit (SU), the organizational, and the network levels. The generic framework is used to classify the applications' objectives in terms of efficiency and innovation, and to identify the design levers they use.

Findings

CAS offer a valuable theoretical perspective on efficiency and innovation. However, the proposed framework shows that these systems are not utilized to their full potential when applied to firms. Typical applications address either emergent efficiency or emergent innovation and thus fail to balance both.

Research limitations/implications

The paper does not provide an exhaustive literature review on management applications of CAS, but selects exemplary literature.

Originality/value

The paper gives a comprehensive overview of the CAS' perspective in management science. For further research, the proposed generic framework of CAS may serve to analyze, evaluate and integrate applications in order to overcome the efficiency‐innovation dilemma.

Citation

Tilebein, M. (2006), "A complex adaptive systems approach to efficiency and innovation", Kybernetes, Vol. 35 No. 7/8, pp. 1087-1099. https://doi.org/10.1108/03684920610688333