It is a common and frequently implicit assumption in the literature on knowledge transfer and organizational learning that imitating practices from high-performing firms has a positive impact on the imitating firm. Although a large body of research has identified obstacles to successful imitation, not much is known about what breadth of imitation is most effective. In this paper, we use a simulation model to explore how context and firm similarity, interdependence among practices, context and firm similarity, and time horizon interact in nontrivial ways to determine the payoffs that arise from different breadths of imitation. The results of the model allow us to qualify and refine predictions of the extant literature on imitation. In particular, the results shed light on the conditions under which increases in imitation breadth, and hence investments that facilitate the faithful copying of more practices, are valuable. In addition, the results of the model highlight that imitation can serve two different functions-mimicking high performers, and generating search by dislodging a firm from its current set of practices-each requiring different organizational routines for its successful implementation. How much to copy? The contingent value of imitation capabilities Abstract: It is a common (and frequently implicit) assumption in the literature on knowledge exchange and organizational learning that imitating practices from high-performing firms has a positive impact on the imitating firm. While a large body of research has pointed out obstacles to successful imitation, very little is known about what degree of imitation is most effective. In this paper, we use a simulation model to explore the role that interdependence among practices, firm-similarity, and time horizon play in influencing the value of different degrees of imitation, and show how they interact in non-trivial ways.For instance, we find that in the presence of interactions, the most effective imitation strategy between similar firms with long time horizons is the worst strategy for short time horizons. One implication of our results is that even if a firm has the capability to copy all practices from a high-performing firm, this will only occasionally be the most appropriate imitation strategy. We also show that imitation can serve two different functions-mimicking high performers and dislodging a firm from its current set of practiceseach one requiring very different organizational routines for its successful implementation. Lastly, we use the model to shed light on three previous disputes in the literature: the controversy between slow and fast learning, whether imitation is effective only at the start of operations or on a continuing basis, and whether firm similarity increases or decreases learning opportunities.

This paper develops a parsimonious process-level theory that connects organizational structure to exploration and exploitation. Toward this end, it develops a mathematical model of organizational decision making that combines an information processing approach in the spirit of Sah and Stiglitz [Sah RK, Stiglitz JE (1986) The architecture of economic systems: Hierarchies and polyarchies. Amer. Econom. Rev. 76(4):716–727] with elements from signal detection theory. The model is first used to explore a “design space” of organizations and identify trade-offs and dominance relationships among alternative organization designs. The paper then studies open questions in the organization design literature, such as the extent to which exploration and exploitation can be produced by one organization and what is the effect of organization size on exploration. More broadly, this research speaks to calls for the introduction of more process-level explanations in the organizations literature. The paper concludes with testable hypotheses and managerially relevant insights.

Sah and Stiglitz (1986).

We study four information aggregation structures commonly used by organizations to evaluate opportunities: individual decision making, delegation to experts, majority voting, and averaging of opinions. Using a formal mathematical model, we investigate how the performance of each of these structures is contingent upon the breadth of knowledge within the firm and changes in the environment. Our model builds on work in the Carnegie tradition and in the group and behavioral decision-making literatures. We use the model to explore when delegation is preferable to other structures, such as voting and averaging. Our model shows that delegation is the most effective structure when there is diversity of expertise, when accurate delegation is possible, and when there is a good fit between the firm's knowledge and the knowledge required by the environment. Otherwise, depending on the knowledge breadth of the firm, voting or averaging may be the most effective structure. Finally, we use our model to shed light on which structures are more robust to radical environmental change and when crowd-based decision making may outperform delegation. This paper was accepted by Jesper Sørensen, organizations.

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The ability to make predictions about strategic outcomes—what we term strategic foresight—is central to most theories of competitive advantage. This paper identifies individual- and organization-level antecedents of strategic foresight by analyzing an exercise taken by 358 MBA students. Among the individual antecedents, we show that two characteristics of mental representations (namely their breadth and agreement with consensus) are positively related to strategic foresight. Comparing individual to group performance reveals that groups exhibit greater strategic foresight than do individuals. Finally, from comparing the performance of real-life groups with “statistical” groups (for which decisions are computed by averaging the predictions of individuals before they become group members), we find that the superiority of group performance is due mostly to aggregating predictions, not representations.

Competitive positioning is a central, yet understudied, topic in strategy. Understanding positioning requires understanding two distinct mappings: how underlying policies are transformed into positions, and how positions are transformed into market performance. A complete treatment of positioning requires incorporating organizational design in the presence of policy interdependence; consumer choice in the presence of trade-offs among multiple product attributes; and competitive interactions among firms. We develop a model that integrates these elements. We show that in a multiattribute setting, trade-offs have critical, nonmonotonic effects on a range of strategy questions including the relationship between positions that are operationally efficient and those that remain viable in the face of competition as well as the concentration of market share in the industry. Of particular interest are implications for firm heterogeneity. We show that increases in business policy interdependence can decrease positioning heterogeneity among firms in an industry, depending on the nature of trade-offs. We also show that the relationship between strategy heterogeneity and positioning heterogeneity is moderated by the extent of policy interdependence. This paper was accepted by Bruno Cassiman, business strategy.

A long-standing question in the organizations literature is whether firms are better off by using simple or complex representations of their task environment. We address this question by developing a formal model of how firm performance depends on the process by which firms learn and use representations. Building on ideas from cognitive science, our model conceptualizes this process in terms of how firms construct a representation of the environment and then use that representation when making decisions. Our model identifies the optimal level of representational complexity as a function of (a) the environment’s complexity and uncertainty and (b) the firm’s experience and knowledge about the environment’s deep structure. We use this model to delineate the conditions under which firms should use simple versus complex representations; in doing so, we provide a coherent framework that integrates previous conflicting results on which type of representation leaves firms better off. Among other results, we show that the optimal representational complexity generally depends more on the firm’s knowledge about the environment than it does on the environment’s actual complexity. We also show that the relative advantage of heuristics vis-à-vis more complex representations critically depends on an unstated assumption of “informedness”: that managers can know what are the most relevant variables to pay attention to. We show that when this assumption does not hold, complex representations are usually better than simpler ones.