The Value of Moderate Obsession: Insights from a New Model of Organizational Search

Abstract

T his study presents a new model of search on a rugged landscape, which employs modeling techniques from fractal geometry rather than the now-familiar NK-modeling technique. In our simulations, firms search locally in a twodimensional fitness landscape, choosing moves in a way that responds both to local payoff considerations and to a more global sense of opportunity represented by a firm-specific preferred direction. The latter concept provides a simple device for introducing cognitive or motivational considerations into the formal account of search behavior, alongside payoff considerations. After describing the objectives and the structure of the model, we report a first experiment that explores how the ruggedness of the landscape affects the interplay of local payoff and cognitive considerations (preferred direction) in search. We show that an intermediate search strategy, combining the guidance of local search with a moderate level of nonlocal obsession, is distinctly advantageous in searching a rugged landscape. We also explore the effects of other considerations, including the objective validity of the preferred direction and the degree of dispersion of firm strategies. We conclude by noting available features of the model that are not exercised in this experiment. Given the inherent flexibility of the model, the range of questions that might potentially be explored is extremely large.

Dealing with Complexity: Integrated vs. Chunky Search Processes

“…Thus, the term "team" could also be replaced by the term "designer" or, more generally, "problem solver." 3 The value of the NK model does not stem primarily from how it serves to generate complex systems, as other stochastic techniques might be also applied for this purpose (see, e.g., Winter et al 2007). Rather, it conveys the advantage that its general properties are already well understood, which makes it easier to evaluate and understand the findings of models that build on the basic structure.…”

A Behavioral Theory of the Firm—40 Years and Counting: Introduction and Impact

“…Winter, Cattani, and Dorsch (2007) use computational models to examine hypotheses advanced in A Behavioral Theory of the Firm about the interplay of local and nonlocal search and the consequences of cognition versus local feedback. The Winter et al (2007). paper advances the use of simulation, a tool introduced to the organizational sciences by A Behavioral Theory.…”

Hierarchical Structure and Search in Complex Organizations

“…Examples include finding and defining a strategy (Rivkin 2000, Winter et al 2007), adapting to industry life cycles (Doty et al 1993, Levinthal 1997, Nelson and Winter 1982, building organizational capabilities (Bruderer andSingh 1996, Gavetti 2005), and new product development (Fleming and Sorenson 2001, Mihm et al 2003, Yassine et al 2003. Search may contain elements of local optimization by intelligent local agents (e.g., Gavetti 2005, Gavetti and Levinthal 2000, Knudsen and Levinthal 2007, Sorenson 2002, Winter et al 2007), but in general, it is search and not optimization that dominates complex problem solving. For complex problems, the search process cannot be performed with regard to the whole problem at once because no actor or resource has enough informationprocessing capacity to consider all aspects of the problem (Loch and Terwiesch 2007, Simon 1969, Van Zandt 1999.…”