The Value of Moderate Obsession: Insights from a New Model of Organizational Search
构建了一个基于分形几何的二维适应度景观搜索模型，模拟企业在局部搜索中结合全局偏好方向（代表认知或动机因素）的策略，发现适度非局部执着的中等搜索策略在崎岖景观中表现最优。
This 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 two-dimensional 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.