This paper investigates the mechanisms through which organizations develop dynamic capabilities, defined as routinized activities directed to the development and adaptation of operating routines. It addresses the role of (1) experience accumulation, (2) knowledge articulation, and (3) knowledge codification processes in the evolution of dynamic, as well as operational, routines. The argument is made that dynamic capabilities are shaped by the coevolution of these learning mechanisms. At any point in time, firms adopt a mix of learning behaviors constituted by a semiautomatic accumulation of experience and by deliberate investments in knowledge articulation and codification activities. The relative effectiveness of these capability-building mechanisms is analyzed here as contingent upon selected features of the task to be learned, such as its frequency, homogeneity, and degree of causal ambiguity. Testable hypotheses about these effects are derived. Somewhat counterintuitive implications of the analysis include the relatively superior effectiveness of highly deliberate learning processes such as knowledge codification at lower levels of frequency and homogeneity of the organizational task, in contrast with common managerial practice. The authors would like to acknowledge the support received from INSEAD's R&D department and the Reginald H. Jones Center of the Wharton School. We are also grateful for the many suggestions, comments and critiques generously offered by Ron Adner, Max Boisot, Tim Folta, Anna Grandori, Bruce Kogut, Arie Lewin, Bart Nooteboom, Gabriel Szulanski, Christoph Zott and three anonymous reviewers Of course, we remain responsible for any remaining error and omissions. In its working paper version, this paper was titled "From Organizational Routines to Dynamic Capabilities." 2 Deliberate Learning and the Evolution of Dynamic Capabilities Abstract:This paper investigates the mechanisms through which organizations develop dynamic capabilities, defined as routinized activities directed to the development and adaptation of operating routines, and reflects upon the role of (1) experience accumulation, (2) knowledge articulation and (3) knowledge codification processes in the evolution of dynamic, as well as operational, routines. The argument is made that dynamic capabilities are shaped by the co-evolution of these learning mechanisms. At any point in time, firms adopt a mix of learning behaviors constituted by a semi-automatic accumulation of experience and by deliberate investments in knowledge articulation and codification activities. The relative effectiveness of these capability-building mechanisms is analyzed here as contingent upon selected features of the task to be learned, such as its frequency, homogeneity and degree of causal ambiguity, and testable hypotheses are derived. Somewhat counterintuitive implications of the analysis include the relatively superior effectiveness of highly deliberate learning processes, such as knowledge codification, at lower levels of frequency and homo...

Defining ordinary or "zero-level" capabilities as those that permit a firm to "make a living" in the short term, one can define dynamic capabilities as those that operate to extend, modify or create ordinary capabilities. Logically, one can then proceed to elaborate a hierarchy of higher-order capabilities (Collis 1994). However, it is argued here that the strategic substance of capabilities involves patterning of activity, and that costly investments are typically required to create and sustain such patterning-for example, in product development. Firms can accomplish change without reliance on dynamic capability, by means here termed "ad hoc problem solving. " Whether higher order capabilities are created or not depends on the costs and benefits of the investments relative to ad hoc problem solving, and so does the "level of the game" at which strategic competition effectively occurs.

Appropriating t he Returns from Industrial Research and Development To HAVE the incentive to undertake research and development, a firm must be able to appropriate returns sufficient to make the investment worthwhile. The benefits consumers derive from an innovation, however, are increased if competitors can imitate and improve on the innovation to ensure its availability on favorable terms. Patent law seeks to resolve this tension between incentives for innovation and widespread diffusion of benefits. A patent confers, in theory, perfect appropriability (monopoly of the invention) for a limited time in return for a public We are grateful for the support of the National Science Foundation and especially to Rolf Piekarz of the NSF's Division of Policy Research and Analysis. We also wish to thank the 650 respondents to our survey and the R&D executives who helped us pretest it-especially Ralph Gomory,

Replication, a familiar phenomenon sometimes referred to as the “McDonalds approach,” entails the creation and operation of a large number of similar outlets that deliver a product or perform a service. Companies pursuing this strategy are now active in over 60 industries. Although replicators are becoming one of the dominant organizational forms of our time, they have been neglected by scholars interested in organizations. As a result of this neglect, replication is typically conceptualized as little more than the exploitation of a simple business formula. Such a view clouds the strategic subtlety of replication by sidestepping the exploration efforts to uncover and develop the best business model as well as the ongoing assessment that precedes large-scale replication of it. Empirical evidence supports an alternative view of replication strategy as a process that involves a regime of exploration in which the business model is created and refined, followed by a phase of exploitation in which the business model is stabilized and leveraged through large-scale replication. In this paper we present the key elements of a theory of replication strategy. We discuss key aspects of a replication strategy, namely the broad scope of knowledge transfer and the role of the central organization, and the analytical concepts of template and Arrow core as a preamble for specifying hypotheses about the conditions under which a replication strategy is more likely to succeed in a competitive setting. Replication strategy provides unusually transparent examples of the process of leveraging knowledge assets; we exploit this in our concluding discussion.

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