Centralization vs. Decentralization in a Multi-Unit Organization: A Computational Model of a Retail Chain as a Multi-Agent Adaptive System

This paper explores the effect of organizational structure - in terms of the allocation of authority - on the rate of innovation in multi-unit organizations such as retail chains and multi-plant manufacturers. A computational model is developed in which store managers continually search for better practices. In a decentralized organization, a store manager adopts a new practice if it raises her store's profit. Headquarters (HQ) is assumed to observe the new practice and then decides whether to disseminate it to other stores. In a centralized organization, a store manager who generates an idea that would raise her store's profit passes the idea up to HQ for approval. Due to lack of detailed information about stores' markets, HQ decides whether or not to mandate it across the chain on the basis of chain profit. Given that stores are assumed to have heterogenous markets, the obvious virtue to decentralization is that it gives authority to those who have the best information and this allows practices to be tailored to each market. What our analysis reveals, however, is the presence of an implicit cost to decentralization. Allowing stores the freedom to develop very different practices is shown to reduce the amount of inter-store learning; that is, the frequency with which one store's idea is of value to another store. By keeping stores near each other in store practice space, centralization enhances learning spillovers and, in some cases, this results in higher chain profit than is achieved under decentralization. We find that centralization outperforms when stores' markets are not too different, consumer demand is sufficiently sensitive to a store's practices, and markets are changing sufficiently rapidly over time.

Organization of innovation in a multi-unit firm: Coordinating adaptive search on multiple rugged landscapes

In Chang and Harrington (2000a) a computational model of a multi-unit firm is developed in which unit managers continually search for better practices Search takes place over a rugged landscape defined over the space of unit practices There it is shown that a more centralized organization is optimal when markets are not too different and the horizon is not too long The robustness of those results are explored here with respect to the shape of the landscape In particular we find that centralization does better when the search space is larger and there is a stronger correlation in a consumer's preferences across different dimensions A richer description of comparative dynamics is also provided

Agent-based models of organizations

An organization is a collection of agents that interact and produce some form of output. Formal organizations - such as corporations and governments - are typically constructed for an explicit purpose though this purpose needn’t be shared by all organizational members. An entrepreneur who creates a firm may do so in order to generate personal wealth but the worker she hires may have very different goals. As opposed to more amorphous collections of agents such as friendship networks and societies at large, organizations have a formal structure to them (though informal structures typically emerge as well) with the prototypical example being a corporation’s organizational chart. This structure serves to define lines of communication and the distribution of decision-making. Organizations are also distinguished by their well-defined boundaries as reflected in a clear delineation as to who is and who is not a member. This boundary serves to make organizations a natural unit of selection; for example, corporations are formed and liquidated though they can also morph into something different through activities like mergers

The impact of a corporate leniency program on antitrust enforcement and cartelization

To explore the efficacy of a corporate leniency program, a Markov process is constructed which models the stochastic formation and demise of cartels. Cartels are born when given the opportunity and market conditions are right, while cartels die because of internal collapse or they are caught and convicted by the antitrust authority. The likelihood that a cartel, once identified, is convicted depends inversely on the caseload of the antitrust authority due to an implicit resource constraint. The authority also chooses an enforcement policy in terms of the fraction of non-leniency cases that it prosecutes. Using numerical analysis, the impact of a leniency program on the steady-state cartel rate is investigated. Holding the enforcement policy of the antitrust authority fixed, a leniency program lowers the frequency of cartels. However, the additional caseload provided by the leniency program induces the antitrust authority to prosecute a smaller fraction of cartel cases identified outside of the program. Because of this less aggressive enforcement policy, it is possible that the cartel rate is higher when there is a leniency program

Discovery and diffusion of knowledge in an endogenous social network

We explore the evolution of the structure and performance of a social network in a population of individuals who search for local optima in diverse and dynamic task environments. Individuals choose whether to innovate or imitate and, in the latter case, from whom to learn. The probabilities of these possible actions respond to an individual's past experiences using reinforcement learning. Among some of our more interesting findings is that a population's performance is not monotonically increasing in either the reliability of the communication network or the productivity of innovation

Consumer Search, Competition, and the Organizational Structure of Multi-Unit Firms

A computational model of competing multi-unit firms, such as a retail chain, is developed in which unit managers and corporate staff continually search for better practices while consumers search among units to find a better match. The main objective of this research is to determine how the amount of discretion given to unit managers, as to how they run their units, influences the rate of innovation. A primary finding is that the presence of competition enhances the relative performance of the centralized form though an increased rate of consumer search differentially benefits the decentralized form.Search, Organizational Structure, Multi-Unit Firms

Modeling the Birth and Death of Cartels with an Application to Evaluating Competition Policy

One of the primary challenges to measuring the impact of antitrust or competition policy on collusion is that the cartel population is unobservable; we observe only the population of discovered cartels. To address this challenge, a model of cartel creation and dissolution is developed to endogenously derive the populations of cartels and discovered cartels. With this theory, one can infer the impact of competition policy on the population of cartels by measuring its impact on the population of discovered cartels. In particular, changes in the duration of discovered cartels can be informative in assessing whether a new policy is reducing the latent rate of cartels