3620 Locust Walk
Philadelphia, PA 19104
Research Interests: competitive advantage, firm capabilities, technological change
PhD, Yale University, 1964; MA, Yale University, 1957; BA, Swarthmore College, 1956
Fellow of the American Econometric Society, 1978; Fellow of the American Association for the Advancement of Science, 1990
Wharton: 1993-present (named Deloitte and Touche Professor of Management, 1993; Co-Director, Reginald H. Jones Center for Management Policy, Strategy, and Organization, 1999-2007). Previous appointments: Yale University; University of Michigan; University of California, Berkeley
Chief Economist, U.S. General Accounting Office, 1989-93; Research Economist, The RAND Corporation 1966-68, 1959-61; Staff Member, Council of Economic Advisers, 1961-62
Scientific Advisory Board, Danish Research Unit on Industrial Dynamics (DRUID); Associate Editor, Industrial & Corporate Change
T. Knudsen and Sidney G Winter (Work In Progress), Hidden but in Plain Sight: The Role of Scale Adjustment in Industry Dynamics.
Thorbjorn Knudsen, Daniel A Levinthal, Sidney G Winter (2017), Systematic differences and random rates: Reconciling Gibrat’s Law with firm differences, Strategy Science, 2 (2), pp. 111-120.
Abstract: A fundamental premise of the strategy field is the existence of persistent firm-level differences in resources and capabilities. This property of heterogeneity should express itself in a variety of empirical “signatures,” such as firm performance and arguably systematic and persistent differences in firm-level growth rates, with low cost firms outpacing high cost firms. While this property of performance differences is a robust regularity, the empirical evidence on firm growth and Gibrat’s law does not support the later conjecture. Gibrat’s law, or the “law of proportionate effect,” states that, across a population of firms and over time, firm growth at any point is, on average, proportionate to size of the firm. We develop a theoretical argument that provides a reconciliation of this apparent paradox. The model implies that in early stages of an industry history. firm growth may have a systematic component, but for much of an industry’s and firm’s history should have a random pattern consistent with the Gibrat property. The intuition is as follows. In a Cournot equilibrium, firms of better “type” (i.e., lower cost) realize a larger market share, but act with some restraint on their choice of quantity in the face of a downward sloping demand curve and recognition of their impact on the market price. If firms are subject to random firm-specific shocks, then in this equilibrium setting a population of such firms would generate a pattern of growth consistent with Gibrat’s law. However, if broader evolutionary dynamics of firm entry, and the subsequent consolidation of market share and industry shake-out is considered, then during early epochs of industry evolution, one would tend to observe systematic differences in growth rates associated with firm’s competitive fitness. Thus, it is only in these settings far from industry equilibrium that we should see systematic deviations from Gibrat’s law.
Thorbjorn Knudsen, Daniel A Levinthal, Sidney G Winter (2014), Hidden but in plain sight: The role of scale adjustment in industry dynamics, Strategic Management Journal, 35, pp. 1569-1584.
Abstract: While much is understood about the general pattern of industry dynamics, a critical element underlying these dynamics, the rate of the expansion of individual firms, has been largely overlooked. We argue that the rate at which firms can reliably increase their scale of operations is a critical factor in understanding the structure of industries. Further, success at scaling-up the firm's operations provides a dynamic-isolating mechanism that insulates established firms from new competition. We show that the bases of profitability in the industry (monopoly-like profits stemming from the restriction of output, efficiency rents based on firm-specific productivity differences, or transitory Schumpeterian profits) can be traced to the scale adjustment process. We explore these issues in a computational model of industry dynamics. Copyright © 2013 John Wiley & Sons, Ltd.
Sidney G Winter and David J. Bryce (2009), A General Relatedness Index, Management Science, 55: 1570-1585.
Abstract: The article discusses general interindustry relatedness. Empirical research on the resource-based view of a business enterprise involves the categorization of resources which have been determined to be responsible for the growth of the corporation and this is difficult as resources may be ambiguous. A general interindustry relatedness index is developed in order to empirically assess the relatedness of resources that characterize the direction of the business' growth, with particular focus being paid to the U.S. manufacturing economy.
Paul S. Adler, Mary Benner, David J. Brunner, John Paul MacDuffie, Emi Osono, Bradley Staats, Hirotaka Takeuchi, Michael L. Tushman, Sidney G Winter (2009), Perspectives on the Productivity Dilemma, Journal of Operations Management, 27 (2), pp. 99-113.
Sidney G Winter and M. Jacobides (2005), The Co-evolution of Capabilities and Transaction Costs: Explaining the Institutional Structure of Production, Strategic Management Journal, 26: 395-413.
Abstract: This paper proposes that transaction costs and capabilities are fundamentally intertwined in the determination of vertical scope, and identifies the key mechanisms of their co-evolution. Specifically, we argue that capability differences are a necessary condition for vertical specialization; and that transaction cost reductions only lead to specialization when capabilities along the value chain are heterogeneous. Furthermore, we argue that there are four evolutionary mechanisms that shape vertical scope over time. First, the selection process, itself driven by capability differences, dynamically shapes vertical scope; second, transaction costs are endogenously changed by firms that try to reshape the transactional environment to increase their profit and market share; third, changes in vertical scope affect the nature of the capability development process, i.e., the way in which firms improve their operations over time; and finally, the changes in the capability development process reshape the capability pool in the industry, changing the roster of qualified participants. These dynamics of capability and transaction cost co-evolution are illustrated through two contrasting examples: the mortgage banking industry in the United States, which shows the shift from integrated to disintegrated production; and the Swiss watch-manufacturing industry, which went from disintegration to integration.
Sidney G Winter (2003), Understanding Dynamic Capabilities, Strategic Management Journal, 24: 991-995 (Co-winner of the Strategic Management Journal Best Paper Prize, 2009).
Abstract: 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. 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.
M. Zollo and Sidney G Winter (2002), Deliberate Learning and the Evolution of Dynamic Capabilities, Organization Science, 13: 339-351.
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. 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.
Sidney G Winter and G. Szulanski (2001), Replication as Strategy, Organization Science, 12: 730-743.
Abstract: 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 side-stepping 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.
G. Dosi, R. R. Nelson, Sidney G Winter, The Nature and Dynamics of Organizational Capabilities (Oxford University Press, 2000)
A sense that they failed to see the financial crisis brewing has led to soul searching among many economists. While some did warn that home prices were forming a bubble, others confess to a widespread failure to predict the damage the bubble would cause when it burst. Some economists are harsher, arguing that a free-market bias in the profession, coupled with outmoded and simplistic analytical tools, blinded many of their colleagues to the danger. A recent paper from a conference of economists calls for changes in the way they are trained.…Read MoreKnowledge at Wharton - 5/13/2009