Abstract

This paper treats organizations as adaptive systems that have to match the complexity of their environments. The nature of this complexity is analyzed by linking an institutional Information-Space (I-Space) framework to the work of complexity theorists. The I-Space framework identifies the codification, abstraction, and diffusion of information as cultural attributes. Codification involves the assignment of data to categories, thus giving them form. Abstraction involves a reduction in the number of categories to which data needs to be assigned for a phenomenon to be apprehended. Information is diffused through populations of data-processing agents, thus constituting the diffusion dimension. Complexity theorists have identified the stability and structure of algorithmic information complexity in a way that corresponds to levels of codification and abstraction. Their identification of system parts and the richness of cross-coupling draws attention to the fabric of information diffusion. We discuss two modes of adaptation to complex environments: complexity reduction and complexity absorption. Complexity reduction entails getting to understand the complexity and acting on it directly, including attempts at environmental enactment. Complexity absorption entails creating options and risk-hedging strategies, often through alliances.The analysis, and its practical utility, is illustrated with reference to China, the world's largest social system. Historical factors have shaped the nature of complexity in China, giving it very different characteristics than those typical of Western industrial countries. Its organizations and other social units have correspondingly handled this complexity through a strategy of absorption rather than the reduction strategy characteristic of Western societies. Western firms operating in China therefore face a choice between maintaining their norms of complexity reduction or adopting a strategy of complexity absorption that is more consistent with Chinese culture. The specifics of these policy alternatives are explored, together with their advantages and disadvantages.The paper concludes with the outlines of a possible agenda for future research, focusing on the investigation of complexity-handling modes and the contingencies which may bear upon the choice between them.

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