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COMPETITION AND THE OPTIMAL ORGANIZATIONAL STRUCTURE OF MULTI-UNIT FIRMS

Joseph Harrington () and Myong-Hun Chang ()

No 22, Computing in Economics and Finance 2000 from Society for Computational Economics

Abstract: In the context of a multi-unit organization such as a retail chain, this paper explores the interaction of organizational structure - in terms of the allocation of authority - and market structure - in terms of the number of competing firms - on the rate of innovation in unit-level practices and overall firm performance. A computational model is developed that has multi-unit/multi-level firms searching for better practices and consumers searching for better stores. Multiple retail chains, each with several stores, serve a set of heterogeneous markets. Store managers search for better practices by engaging in hill-climbing over a rugged and changing landscape which is generated by a population of consumers. A decentralized organization is one in which store managers have the authority to adopt a new practice. A store manager adopts an idea if it raises store profit and discards it otherwise. If a store manager adopts one of these ideas, corporate headquarters (HQ) observes the new practice with some probability and then decides whether to disseminate the idea to other stores in the firm. In a centralized organization, a store manager who generates an idea that would raise store profit passes the idea up to HQ for approval. Due to lack of detailed information about stores' markets, HQ is presumed incapable of selectively implementing a new idea. Rather, it mandates it across the chain if doing so raises firm profit and otherwise discards the idea. What is important for the analysis is that practices are less tailored to the market under centralization than under decentralization. Just as a store can learn from other stores in its chain, it can also learn from competing stores in its market. With some probability, a newly adopted idea by a store is observed by a competing store in that same market and, with some probability, by the HQ of another chain. These probabilities, along with the probability that HQ observes a newly adopted practice of one of its own stores, controls the relationship between intra-chain spillovers and inter-chain spillovers. Advances in information technology affect the relationship between the spillover parameters as does the span of control within a chain. As chains search for better practices, consumers are simultaneously searching for better stores. Consumers are endowed with preferences over store practices and the distribution of consumer types moves stochastically over time. At any point in time, a consumer has a "preferred store." A consumer buys from the preferred store with probability q and with probability 1-q experiments by buying from a randomly chosen store. In the latter case, if the resulting surplus for the consumer is higher than what the consumer received previously from the preferred store then this new store becomes the consumer's preferred store. If not, then the consumer's preferred store remains unchanged and, in the next period, the process is repeated. Higher values of q correspond to greater store loyalty. With this structure we explore the relative performance of various organizational structures and their dependence on market competition, spillover rates, and the rate of change in the population of consumers. Given that markets are assumed to be heterogeneous, 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 units the freedom to develop different practices is shown to reduce the amount of intra-chain learning; that is, the frequency with which one store's idea is of value to another store in the chain. By keeping stores near each other in the space of practices, centralization enhances intra-chain learning and this can result in higher firm profit than under decentralization. As a second interesting result and in contrast to accepted wisdom, we find that greater volatility in consumers' preferences makes centralization more attractive. The greater rate of intra-chain learning that it produces is important for responding to a changing market. The performance differential in favor of centralization is sensitive, however, to the extent of competition and inter-chain spillovers. If inter--chain spillovers are sufficiently great then a chain that pursues a decentralized form is able to substitute inter-chain learning for intra-chain learning. Competition may also enhance the attractiveness of decentralization as it makes it more detrimental to be out of line with one's market and thus more important to allow store managers to tailor practices to the market.

Date: 2000-07-05
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More papers in Computing in Economics and Finance 2000 from Society for Computational Economics CEF 2000, Departament d'Economia i Empresa, Universitat Pompeu Fabra, Ramon Trias Fargas, 25,27, 08005, Barcelona, Spain. Contact information at EDIRC.
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