Informational Complexity and the Flow of Knowledge across social boundaries

Scholars from a variety of backgrounds – economists, sociologists, strategists, and students of technology management – have sought a better understanding of why some knowledge disperses widely while other knowledge does not. In this quest, some researchers have focused on the characteristics of the knowledge itself (e.g., Polanyi, 1966; Reed and DeFillippi, 1990; Zander and Kogut, 1995) while others have emphasized the social networks that constrain and enable the flow of knowledge (e.g., Coleman et al., 1957; Davis and Greve, 1997). This chapter examines the interplay between these two factors. Specifically, we consider how the complexity of knowledge and the density of social relations jointly influence the movement of knowledge. Imagine a social network composed of patches of dense connections with sparse interstices between them. The dense patches might reflect firms, for instance, or geographic regions or technical communities. When does knowledge diffuse within these dense patches circumscribed by social boundaries but not beyond them? Synthesizing social network theory with a view of knowledge transfer as a search process, we argue that knowledge inequality across social boundaries should reach its peak when the underlying knowledge is of moderate complexity. To test this hypothesis, we analyze patent data and compare citation rates across three types of social boundaries: within versus outside the firm, geographically near to versus far from the inventor, and internal versus external to the technological class. In all three cases, the disparity in knowledge diffusion across these borders is greatest for knowledge of an intermediate level of complexity.evolutionary economics, informational complexity, knowledge flow, social boundaries

Organizing to Strategize in the Face of Interactions: Preventing Premature Lock-In

Motivated by real examples that run contrary to conventional wisdom, we examine how firms organize themselves to strategize well. Interactions among decisions make strategizing difficult. They raise the spectre that a firm\u27s strategizing efforts will get stuck in a web of conflicting constraints prematurely, before managers explore a wide enough range of possibilities. A key role of organizing is to free strategizing efforts and encourage broad search. At the same time, organizing must ensure that strategizing efforts are stabilized once the firm discovers an effective set of choices. The need to balance search and stability, we argue, is a central challenge of organizing. We explore this challenge with an agent-based simulation of firms that organize to strategize in the face of interactions. The results shed light on our counterintuitive examples. They show why and when firms may benefit from unnecessary overlap between departments; how and when firms can increase firm-wide search by reining in the search efforts of individual managers; and how and when a change in organizational structure — e.g., a shift from decentralization to integration — may reflect an effective sequence of organizing, rather than a reversal of early mistakes. The disparate examples share an underlying logic. The unnecessary overlap, the reining-in of managers, the period of decentralization — all can be seen as organizational mechanisms that help ensure the broad, early search that a firm needs when interactions among strategic decisions raise the danger of locking-in on a strategy prematurely

Strategy Making in Novel and Complex Worlds: The Power of Analogy

We examine how firms discover effective competitive positions in worlds that are both novel and complex. In such settings, neither rational deduction nor local search is likely to lead a firm to a successful array of choices. Analogical reasoning, however, may be helpful, allowing managers to transfer useful wisdom from similar settings they have experienced in the past. From a long list of observable industry characteristics, analogizing managers choose a subset they believe distinguishes similar industries from different ones. Faced with a novel industry, they seek a familiar industry which matches the novel one along that subset of characteristics. They transfer from the matching industry high-level policies that guide search in the novel industry. We embody this conceptualization of analogy in an agent-based simulation model. The model allows us to examine the impact of managerial and structural characteristics on the effectiveness of analogical reasoning. With respect to managerial characteristics, we find, not surprisingly, that analogical reasoning is especially powerful when managers pay attention to characteristics that truly distinguish similar industries from different ones. More surprisingly, we find that the marginal returns to depth of experience diminish rapidly while greater breadth of experience steadily improves performance. Both depth and breadth of experience are useful only when one accurately understands what distinguishes similar industries from different ones. We also discover that following an analogy in too orthodox a manner—strictly constraining search efforts to what the analogy suggests—can be dysfunctional. With regard to structural characteristics, we find that a well-informed analogy is particularly powerful when interactions among decisions cross policy boundaries so that the underlying decision problem is not easily decomposed. Overall, the results shed light on a form of managerial reasoning that we believe is prevalent among practicing strategists yet is largely absent from scholarly analysis of strategy

Advanced Competitive Strategy: Integrating The Enterprise (9-706-452)

Introduce

Patterned Interactions in Complex Systems: Implications for Exploration

Scholars who view organizational, social, and technological systems as sets of interdependent decisions have increasingly used simulation models from the biological and physical sciences to examine system behavior. These models shed light on an enduring managerial question: How much exploration is necessary to discover a good configuration of decisions? The models suggest that, as interactions across decisions intensify and local optima proliferate, broader exploration is required. The models typically assume, however, that the interactions among decisions are distributed randomly. Contrary to this assumption, recent empirical studies of real organizational, social, and technological systems show that interactions among decisions are highly patterned. Patterns such as centralization, small-world connections, power-law distributions, hierarchy, and preferential attachment are common. We embed such patterns into an NK simulation model and obtain dramatic results: Holding fixed the total number of interactions among decisions, a shift in the pattern of interaction can alter the number of local optima by more than an order of magnitude. Thus, the long-run value of broader exploration is significantly greater in the face of some interaction patterns than in the face of others. We develop simple, intuitive rules of thumb that allow a decision maker to examine two interaction patterns and determine which warrants greater investment in broad exploration. We also find that, holding fixed the interaction pattern, an increase in the number of interactions raises the number of local optima regardless of the pattern. This validates prior comparative static results with respect to the number of interactions, but highlights an important implicit assumption in earlier work--that the underlying interaction pattern remains constant as interactions become more numerous.exploration, simulation model, pattern of interaction

HBS Survey on U.S. Competitiveness (2012-2015)

The HBS survey on U.S. Competitiveness (2012-2015) was conducted with ~11,000 HBS alumni between August 29, 2012 and September 27, 2012, in December 2013, and between April 23, 2015 and May 26, 2015. These surveys examine the perceptions and experiences of alumni from HBS’s MBA and Exec Ed programs on the ability of U.S. firms to compete successfully in the global economy. It was conducted via web or paper, and was based on HBS alumni with email addresses. The final sample frame contained a total of 11,499 records, which was presumed to be a census of HBS alumni