Corinne A. Coen

Investing in Capabilities: The Dynamics of Resource Allocation

In this research, we examine the dynamic capability of resource allocation to invest in operational capabilities. Using a computer simulation, we model a process of firms competing in factor markets for opportunities to invest in existing capabilities and acquire new ones. Based on the simulation results, we derive a set of propositions about the conditions under which there are and are not performance benefits from possessing a superior ability to search for new capabilities. Because the definition of what constitutes a new capability is based on a firms preexisting capabilities, we also incorporate differences in initial endowments into the analysis. We find that endowment and search ability both matter, and that in many circumstances, the effects of possessing a superior endowment dominate the effects of superior search ability.

Simple but not simpler

As I attend conferences with modelers and visit various schools to interact with management scholars using computer simulation methods to model dynamic systems, I am struck by a powerful philosophical difference affecting our model design. Some scholars feel strongly that models should follow the “Keep it simple, stupid” (KISS) principle. They claim that models should be used to assist our intuition by showing proof about processes and mechanisms. Others see the value of realistic models— ones that can make predictions and deal with highly specified problems. While the two sides each make substantial contributions to our nascent area of computational organization studies, the two sides rarely integrate their work or lay out when one side’s approach is more or less useful than the others’. I put together a panel of speakers at the 2004 North American Association for Computational Social and Organization Sciences (NAACSOS) conference held at Carnegie-Mellon University to stimulate discussion on this topic. This special issue of Computational and Mathematical Organization Studies arose from that initial panel. For thousands of years, philosophers of science have explored this issue without reaching any satisfactory resolution. The debate shows up framed in terms of Occam’s Razor, Realist vs. Anti-Realist programs, Realism vs. Constructive Empiricism and more (see for example, http://plato.stanford.edu/entries/models-science/ #ModReaVerAntDeb, July 24, 2008; http://www.hps.cam.ac.uk/research/realism. html, July 24, 2008). These debates note that simple models are idealized and thus

Understanding the Role of Worker Interdependence in Team Selection

In this paper, we evaluate the effectiveness of policies for assigning interdependent workers to teams. Using a computational simulation, we contrast distributing workers equitably across teams based on prior individual performance with policies that distribute workers based on how well people work together. First, we test a policy that clusters workers into teams by finding natural breakpoints among them where their mutual support is weak. Then we test two other policies that both protect the strongest interdependent core of high performers but differ in that one policy separates workers who give little support to interdependent partners and the other separates workers who receive little support from their partners. All three policies outperform the equitable-distribution approach in some circumstances. We make recommendations to managers for harnessing interdependence when forming teams, whether the managers are familiar or unfamiliar with how well their people work together.

Contrast or assimilation: choosing camps in simple or realistic modeling

The contrast effect is a psychological phenomenon in which people exaggerate their differences. When making social comparisons, people cope with the discomforts associated with negative comparisons by criticizing others and splitting into smaller groups of similar others or by assimilation, depending on whether they perceive themselves as the member of a majority or minority group, respectively. This contrast or assimilation phenomena can explain the exaggeration of differences among computational simulation scholars. Those exaggerations are discussed in this paper as well as some realistic reasons for differences. Recognition of our status as minority group members and the virtues of assimilation and mutual support are advocated.

Mixing rules: When to cooperate in a multiple-team competition

Abstract In the study of social dilemmas, there has been a strong divide between empirical studies of how people behave and simulation experiments focusing on how people ought to behave. This study bridges that gap by deducing rules-in-use by participants in a human experiment in a multiple-team social dilemma. It then uses a computer simulation to evaluate which of the identified rules-in-use generates the best performance. The results suggest that participants use either a Win-Stay/Lose-Revert strategy or a Win-Cooperate/Lose-Defect strategy. While a mean-Win-Stay/Lose-Revert strategy dominates most often, the Win-Cooperate/Lose-Defect strategy performs better in a two-team than in a single-team setting.