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Bill McKelvey frames a quasi-natural organization science intended to redirect the focus of organization science from idiosyncratic detail and selectionist/ positivist/post-positivist debates to focus more on background laws which might explain the evolution and dynamics of organizational phenomena. The new direction offered by this paper is to view organizations from a microevolutionary perspective of selectionist naturally caused phenomena in interaction with macrocoevolution and intentionally caused phenomena.McKelvey looks to the scientific enterprise of 20th century natural science and its research paradigm, which is characterized by theorizing, based on idealized models, empirical testing of the models and contextual contingency, as an approach for developing the natural side of organization science and as a means of facing up to the assumption of idiosyncratic behavior in organizations. In a sense, he takes us back to the founding of the Administrative Science Quarterly and J. D. Thompson's inaugural essay which argued for the development of a "science" of organizations on par, in the form of its scientific power and rigor, to the natural sciences and which gave rise to the dominant "logical empiricist" practice of justification logic via empirical testability of theoretical propositions. McKelvey draws on the "semantic conception of theories" from modern philosophy of science to recast organization studies as a "model-focused science" in which the development of idealized models is interposed between theory development and understanding empirical phenomena.It is my belief that this paper will serve as the opening volley toward building the natural science side of organization science-focusing on explicating background laws and developing new empirical approaches for testing these idealized models and associated probabilistic laws. This paper is not an argument for or against positivist, post-positivist, contextual research or selectionist views. It is an argument for an approach to organization science paralleling the assumptions and methods of 20th century natural science by developing the neglected components of a quasi-natural organization science: background laws, rates at which process events take place, and complexity theory. It will have profound implications for theorizing and empirical studies in many subfields of organization science, such as strategy, organization theory, entrepreneurship, organization learning, new organization forms, and computational organization theory.Arie Y. Lewin AbstractPositing that organizational phenomena result from both individual human intentionality and natural causes independent of individuals' intended behavior, the need for a quasinatural organization science is identified. The paradigm war is defined in terms of positivism and postpositivism, with the suggestion that a more relevant epistemology might be scientific realism. The current unconstructive paradigm proliferation is seen as resulting from an underlying cause, idiosyncratic organizational microstates...

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Can firms and coevolutionary groups suffer from too much interdependent complexity? Is complexity theory an alternative explanation to competitive selection for the emergent order apparent in coevolutionary industry groups? The biologist, Stewart Kauffman, suggests a theory of complexity catastrophe offering universal principles explaining phenomena normally attributed to Darwinian natural selection theory. Kauffman's complexity theory seems to apply equally well to firms in coevolutionary pockets. Based on complexity theory, four kinds of complexity are identified. Kauffman's "NK[C] model" is positioned "at the edge of chaos" between complexity driven by "Newtonian" simple rules and rule-driven deterministic chaos. Kauffman's insight, which is the basis of the findings in this paper, is that complexity is both a consequence and a cause. Multicoevolutionary complexity in firms is defined by moving natural selection processes inside firms and down to a "parts" level of analysis, in this instance Porter's value chain level, to focus on microstate activities by agents. The assumptions of stochastically idiosyncratic microstates and coevolution in firms are analyzed. Competitive advantage, as a dependent variable, is defined in terms of Nash equilibrium fitness levels. This allows a translation of Kauffman's theory to firms, paying particular attention to: (1) how value chain landscapes might be modeled; (2) assumptions underlying Kauffman's models making them amenable to firms; and (3) a delineation of seven of Kauffman's computational experiments. As part of the translation, possible parallels between the application of complexity catastrophe theory to coevolutionary pockets and studies by institutional theorists and social network analysts are discussed. The models derive from spinglass microstate models resulting in Boolean games. Kauffman's "Boolean statistical mechanics is introduced in developing the logic underlying the somewhat simplified NK[C] model. The model allows the use of computational experiments to better understand how the dependent variable-value chain fitness-is affected by changes in the number of internal interdependencies K, the number of coevolutionary links with opponents C, the size of the coevolutionary pocket S, and the number of simultaneous adaptive changes, among other things. Various computational experiments are presented that suggest strategic organizing approaches most likely to foster competitive advantage. High or low Nash equilibrium fitness levels are shown to result from internal and external coevolutionary densities as a function of links among value chain competencies within a firm and between a firm and an opponent. Complexity phenomena appear to suggest a number of expected (and thus validating) and surprising strategies with respect to complex organizational interdependencies. For example, moderate complexity fares best and external coevolutionary complexity sets an upper bound to advantages likely to be gained from internal complexity. Various complexity "lessons" are di...

The misalignment of information systems (IS) components with the rest of an organization remains a critical and chronic unsolved problem in today's complex and turbulent world. This paper argues that the coevolutionary and emergent nature of alignment has rarely been taken into consideration in IS research and that this is the reason behind why IS alignment is so difficult. A view of IS alignment is presented about organizations that draws and builds on complexity theory and especially its focus on coevolution-based selforganized emergent behaviour and structure, which provides important insights for dealing with the emergent nature of IS alignment. This view considers Business/IS alignment as a series of adjustments at three levels of analysis: individual, operational, and strategic, and suggests several enabling conditions -principles of adaptation and scale-free dynamicsaimed at speeding up the adaptive coevolutionary dynamics among the three levels.

A lthough normal distributions and related current quantitative methods are still relevant for some organizational research, the growing ubiquity of power laws signifies that Pareto rank/frequency distributions, fractals, and underlying scale-free theories are increasingly pervasive and valid characterizations of organizational dynamics. When they apply, researchers ignoring power-law effects risk drawing false conclusions and promulgating useless advice to practitioners. This is because what is important to most managers are the extremes they face, not the averages. We show that power laws are pervasive in the organizational world and present 15 scale-free theories that apply to organizations. Next we discuss research implications embedded in Pareto rank/frequency distributions and draw statistical and methodological implications.

Purpose-Existing literature acknowledges information systems development (ISD) to be a complex activity. This complexity is magnified by the continuous changes in user requirements due to changing organizational needs in changing external competitive environments. Research findings show that, if this increasing complexity is not managed appropriately, information systems fail. The paper thus aims to portray the sources of complexity related to ISD and to suggest the use of complexity theory as a frame of reference, analyzing its implications on information system design and development to deal with the emergent nature of IS. Design/methodology/approach-Conceptual analysis and review of relevant literature. Findings-This article provides a conceptual model explaining how top-down "official" and bottom-up "emergent" co-evolutionary adaptations of information systems design with changing user requirements will result in more effective system design and operation. At the heart of this model are seven first principles of adaptive success drawn from foundational biological and social science theory: adaptive tension, requisite complexity, change rate, modular design, positive feedback, causal intricacy, and coordination rhythm. These principles, translated into the ISD context, outline how IS professionals can use them to better enable the co-evolutionary adaptation of ISD projects to changing stakeholder interests and broader environmental changes. Originality/value-This paper considers and recognizes the different sources of complexity related to ISD before suggesting how they could be better dealt with. It develops a framework for change to deal with the emergent nature of ISD and enable more expeditious co-evolutionary adaptation.