Managerial decision making involves searches for alternative courses of action, including searches for technological innovations or new knolwedge. We introduce the attractor-based (AB) fitness landscape model, the core model based on this method. We then describe search using this model, and consider issues in implementing the search process, and provide an example of applying the model to studying exploration and exploitation. We compare the AB landscape to the more widely used NK landscape approach, and identify some advantages and disadvantages of each. Advantages of the AB model include control over the shape of the fitness landscape, the generalizability of the search problem, and visualization. We then consider customizations and generalizations of the model, including applications to coordinated exploration and resource partitioning processes.
 
This research was conducted by staff at The Computational Organizational Theory Lab, in combination with researchers at the University of Texas at Dallas, and Norwegian University of Science and Technology. The paper was initially published in the IEEE explore.
 
Link to Publisher: ieeexplore/abstract/8125307
 
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