A management system exists to coordinate, control, and make decisions about activities within an organization. These functions are information intensive, and therefore the design of management hierarchy has much to do with information-processing economics. Most economic entities' management structures are described by "an organization chart" which is a network of departments. The goal of this paper is to take an analytical look at management hierarchy modeled as a tree with information-processing departments at nodes. Two key assumptions about information processing are made: first, data's arrival patterns are uncertain as are processing times and that creates queuing delays, and second, data processing rates fall when data come from a variety of sources. Forthcoming results seem to accord more closely to empirical data than past work. Large increases in cost parameters or data flow rates do not change the hierarchy's structure very much. At higher tiers departments have more capacity and operate at lower utilizations, and managers have more subordinates, thus their work is less specialized and more complex. Included case studies support the latter assertion. We find that a large drop in information technology cost, or increased importance of quick customer response due to competition does not reduce the hierarchy height as effectively as decentralization. This implies that the historically recognized delayering of firms is principally due to reorganization to decentralize information processing.

In the past, implementing delivered pricing has been perceived as unrealistic because of practical difficulties in distinguishing between customers, determining an individual’s willingness to pay, and setting different prices to individuals. The rise of e-commerce has introduced the possibility of doing all three. Competitive location with delivered pricing was studied by Lederer and Hurter (1986) but only with inelastic customer demand. This paper extends the literature by allowing price elastic demand. A Nash equilibrium with inelastic demand always exists but examples show that it may not with price elasticity. General sufficient conditions guaranteeing existence of a Nash equilibrium are developed despite the fact that even with these conditions a firm’s profit function is generally not concave, quasi-concave, supermodular or even continuous in location choices. Examples demonstrate how violation of sufficient conditions result in lack of existence. Given price elasticity, equilibrium locations demonstrate properties unlike the inelastic case, for example, as transportation cost rises or firms’ production costs rise, each firm locates closer to its competitor. Given our sufficient conditions for equilibrium’s existence, the interval spanning firms’ ordered equilibrium locations always contains a social welfare optimum pair and a social welfare optimum pair is always contained by an ordered equilibrium.

This paper studies a fundamental management question: how does information economics affect the organization of management? We view management hierarchies as tree-like structures designed to minimize real and opportunity costs related to information processing and decision making. “Line” production activities stand at the end nodes of a hierarchy tree. Data from these bottom nodes are processed and distributed to higher level nodes that combine information from the lower nodes. The question we ask is: “how do the real and opportunity costs of information processing affect the tree”. We solve for the optimal tree which includes the links and capacity at each of the nodes. Models are formulated on two underlying premises: complexity costs arise due to processing different types of data, and queuing effects due to data arrival and processing uncertainties create delay which is an opportunity cost.

Improvement programs of various types have been adopted by many corporations and other organizations. In some cases, multiple programs have been implemented. An important question is whether such programs are complements to each other? In other words, is the value added of a pair of programs larger than value generated by the sum of each instituted separately. This chapter studies that question for some common improvement programs. Complementarity is studied for three program types: uncertainty reduction about customers' values for service, accounting programs like ABC that eliminate biased cost estimates, and operations efforts. Three kinds of operations improvements are considered: reducing variable cost, reducing capacity cost and reducing non-value added time. Research by Milgrom and Roberts (Am Econ Rev 80(3): 511-528, 1990) argue that many modern improvement programs are complementary. But in this theoretical work the conclusion is a direct result of the technical assumptions made. Specifically, their assumption of supermodularity properties directly leads to the results. Missing from this analysis, but explored here, is whether realistic, well understood cost functions lead to complementary properties. Initially we assume that cost is driven by queuing-like production technology. Because batching/lot sizing and fixed charge problems have costs like queuing, the results apply broadly. In this case, the first two programs can be either complements or substitutes. But they are both complementary to direct cost savings and capacity cost reduction. The situation with reduction of cost estimate bias is more complex: it is complementary to direct cost savings and the reduction in non-value added time but is a substitute to reducing capacity cost. Complementarity properties are also studied for general demand and cost functions, with sufficient conditions presented. The managerial conclusion is that care must be taken in assuming the complementarity of real programs, and that more central oversight of improvement efforts probably is warranted to better estimate the value of programs.

This paper explores the economics of information-processing in managerial hierarchy when queuing phenomena and task complexity are considered. Task complexity of processing multiple data types introduces a new issue: data-processing scope. This new factor is important as it helps understand limits or advantages of broadening a firm’s portfolio of different activities such as product offerings. Using queuing theory to model delay, we highlight the scale economies found in hierarchy. To model information-processing with complexity, multiple differentiated data sources are assumed and information extracted from the data is used to coordinate production. As in past literature, our objective in hierarchy design is to find a topological tree with endogenously chosen capacitated processing nodes that minimizes the sum of time and capacity costs. The problem is formulated using calculus of variations. Optimal hierarchy is analyzed along two different dimensions. The first states two possible purposes of the hierarchy: i.) to perform decentralized data-processing (where all information is processed by an upward flow to the apex) or ii.) to perform decentralized decision-making (where information flow may cease at intermediate nodes). The second dimension concerns how scope affects the cost of delay: when total delay cost does not depend on the number of data sources and when it does. Results are presented for all four cases. The case most often studied in the literature corresponds to decentralized decision-making with delay cost that does not depend on the number of data sources. In this case, diseconomies of scope arise at small scope, but economies of scope hold at middling to high scope. This implies that to minimize control cost, low scope firms ought to divide into the smallest units possible or to expand scope to levels that exhibit economies of scope. However, for decentralized decision-making, diseconomies of scope prevail at all levels. For a firm with this characteristic in a competitive market, increasing marginal cost of managerial control can have an impact on the extent of the firm’s activities. Descriptive results about the effect of cost changes on the shape of the hierarchy are developed. For example, if the cost of delay per unit time rises, then with decentralized data-processing the hierarchy flattens, but the opposite effect occurs with decentralized decision-making. It is also shown that when the hierarchy performs both data-processing and decision-making functions, the latter tends to dominate. This would imply that increased time urgency would cause a hierarchy to add tiers and to reduce the number of work groups at each tier, a surprising result.

In a service environment a service provider needs to determine the amount and kinds of capacity to meet customers needs over many periods. To make good decisions, she needs to know the probability distribution of her customers demand in each period. We study a situation in which customers demand for a given service is random in each period, but inelastic, or modeled well by this assumption, and cannot be delayed to the next period. This article presents a mechanism that allows a service provider to learn the distribution of a customer's demand by offering him a set of contracts through which he can partially prepay for future service for a reduced cost for units of service based on anticipated needs. We describe the form of a set of contracts that will cause the customer to reveal his demand distribution as he minimizes his expected costs. To justify the effort of organizing and offering contracts, we present an application that demonstrates the cost savings to the service provider with better capacity planning using the truthfully elicited distribution.

Mail-order and internet sellers must decide how customers pay shipping charges. Typically, these sellers choose between two pricing policies: either “uniform pricing,” where the firm delivers to any customer at a fixed delivery charge (that may be volume dependent), or “mill pricing,” where the firm bills the customer a distance-related shipping charge. This paper studies price competition between a mail-order (or internet) seller and local retailers, and the mail-order firm’s choice of pricing policy. The price policy choice is studied when retailers do not change price in reaction to the mail-order firm’s policy choice, and when they do. In the second case, a two-stage non-cooperative game is used and it is found that for low customer willingness to pay, mill pricing is favored but as willingness to pay rises, uniform pricing becomes more attractive. These results are generalized showing that larger markets, higher transportation rates, higher unit production cost, and greater competition between retailers all increase profit under mill pricing relative to uniform pricing (and vice versa). On the other hand, cost asymmetries that favor the mail-order firm will tend to induce uniform rather than mill pricing. Some empirical data on retail and mail-order sales that confirm these results are presented.

Internet sellers must decide how customers pay shipping charges. Typically, these sellers choose between "uniform pricing," where the firm delivers to any customer at a fixed delivery charge, or "mill pricing," where the firm bills the customer a distance-related shipping charge. This paper studies price competition between an internet seller and local retailers, and the internet seller's choice of pricing policy. It is found that for low customer willingness to pay, mill pricing is favored but as willingness to pay rises, uniform pricing becomes more attractive. These results are generalized showing that larger markets, higher transportation rates, higher unit production cost, and greater competition between retailers all increase profit under mill pricing relative to uniform pricing (and vice versa). Cost asymmetries that favor the internet seller will tend to induce uniform rather than mill pricing. Some empirical data on retail and web retail sales that are consistent with these results are presented.

During the past two decades firms have adopted many types of functional improvement programs. A goal of this paper is to study interactions of operations programs with improvement programs in other functions. An important issue is whether these programs are complements (or substitutes): that is, whether implementation of a pair of programs adds more value (or loses value) than the sum of the individual programs. Recent advances based upon Topkis’s (1998) theory of supermodularity have created a framework to establish sufficient conditions to guarantee that two interacting activities or programs are complementary. But not all programs can be characterized by supermodularity. In particular, I show that programs that involve uncertainty reduction do not fit the supermodularity framework with respect to other programs. In the absence of supermodularity, complementarity properties can sometimes be established, but some assumption about the production function must be assumed. Assuming that production is based upon queuing technology, three programs are studied and I show that complement/substitute properties can be established. The three programs are uncertainty reduction about a key demand parameter, elimination of biased estimates of cost and direct cost savings. I show that uncertainty reduction and bias removal can be complements or substitutes; but, uncertainty reduction and cost estimation bias elimination are both complementary to direct cost savings. Also, several operations improvement programs are shown to be complementary to each other. The fact that the operations improvement programs are complementary to all other programs is significant for the organizational design of capital budgeting, as this assures that the true project value is higher than its standalone net present value. Results are generalized by presenting conditions that assure the complementarity or substitutability of these three types of programs. Because batching/lot sizing and any fixed charge problem (such as facility location) have cost structures similar to queuing, the results are shown to apply to a broad range of technologies.

Uniform spatial pricing means that a firm delivers its product to any customer at a fixed price, independent of location. Economic theory explains the use of uniform pricing by the added profit generated by absorbing freight charges of distant customers. I extend this insight by demonstrating that when demand elasticity and transportation cost are positively enough correlated, uniform pricing generates higher profits than mill pricing. I show that this result can better explain observed patterns of price policy choice by mail order and web firms. A second result is application of this idea to firms with many shipping facilities.

Information and banking technology have combined to throw the retail banking business model into disarray. Many predicted that lower cost online-oriented services such as Citibank's Citi f/i venture would dominate the retail banking market and drive out high cost old technologies. The subsequent failure of Citi f/i and other virtual banks raises questions about how technology choice affects retail banking competition: Under what conditions would an online-only banking strategy be successful? When can a bank deploy both old and new technologies and still be competitive? Can an ATM network substitute for a branch network? Do customers' attitudes about technology affect banking strategy? We use an economic model of a competitive retail banking market to address those and other questions. Our model allows banks to choose their technology, including establishing separate branch and ATM networks or relying on third party ATM networks. We also include customers that have differing attitudes toward technology. Our analysis suggests that customer preferences, rather than technology cost structure, drive the evolution of banks' strategic technology choices. Also, banks in our model tend to deploy ATMs in the same numbers as branches, despite ATM's cost advantages. Finally we show that virtual banks will remain unprofitable until a much larger proportion of the population is comfortable with online bank transaction technology. These results suggest that banks should carefully study their customers' preferences to align major strategy shifts with customer attitudes.

We study the effect of financial risk on the economic evaluation of a project with capacity decisions. Capacity decisions have an important effect on the project̂s value through the up‐front investment, the associated operating cost, and constraints on output. However, increased scale also affects the financial risk of the project through its effect on the operating leverage of the investment. Although it has long been recognized in the finance literature that operating leverage affects project risk, this result has not been incorporated in the operations management literature when evaluating projects. We study the decision problem of a firm that must choose project scale. Future cash flow uncertainty is introduced by uncertain future market prices. The firm's capacity decision affects the firm's potential sales, its expected price for output, and its costs. We study the firm's profit maximizing scale decision using the CAPM model for risk adjustment. Our results include that project risk, as measured by the required rate of return, is related to the inverse of the expected profit per unit sold. We also show that project risk is related to the scale choice. In contrast, in traditional discounted cash flow analysis (DCF), a fixed prescribed rate is used to evaluate the project and choose its scale. When a fixed rate is used with DCF, a manager will ignore the effect of scale on risk and choose suboptimal capacity that reduces project value. S/he will also misestimate project value. Use of DCF for choosing scale is studied for two special cases. It is shown that if the manager is directed to use a prescribed discount rate that induces the optimal scale decision, then the manager will greatly undervalue the project. In contrast, if the discount rate is set to the risk of the optimally‐scaled project, the manager will undersize the project by a small amount, and slightly undervalue the project with the economic impact of the error being small. These results underline the importance of understanding the source of financial risk in projects where risk is endogenous to the project design.

This paper contributes to the literature by studying price and production competition between spatially distributed profit maximizing firms. Firms compete by setting delivered prices, planning production, and sending output to each market. Both elastic demand and non-linear production costs are assumed. A non-cooperative game is defined, and its properties are characterized. We find spatial pricing patterns similar to those found by Hoover (1936). Existence and general properties of the Nash price and production equilibrium are shown and sufficient conditions that guarantee the existence of an unique price-production-transportation equilibrium are presented. A convergent algorithm is shown to find the equilibrium and is demonstrated with an example.

Design of a retail banking distribution strategy is an important issue in that industry. This paper shows the effect of new electronic distribution technologies such as PC banking on the choice of a bank's distribution strategy. We present a competitive model of distribution strategy choice, including heterogeneous consumers and banks, that allows a rich variety of customer preference and technology cost parameters. Sensitivity analysis shows how several parameters affect the competitive outcome. This analysis suggests that changing consumer behavior and attitudes, instead of banks' cost structure with new technologies significantly affects the bank's distribution strategy choice. If the segment of consumers that prefers PC banking remains small relative to the segment that prefers branches, then there will still be a market for specialized branch banks. Branch banking without PC banking services will be a viable strategy until the segment that prefers PC banking grows larger (amounting to about 40 percent of all transactions). Banks offering both branch and PC banking services can prevent successful and profitable entry by virtual banks (Internet banks offering only PC banking services) as long as the segment of customers that prefer PC banking remains relatively small (less than two-thirds of all transactions). Beyond this fraction, virtual banks will be profitable. This analysis suggests that it may be a long time (if ever) before virtual banks turn a profit.

The paper applies an economic model of a competitive market for retail banking services to generate insights into the following relevant questions. Is the cost structure of electronic distribution systems sufficient to justify choosing the kiosk/PC banking distribution strategy? That is, is it reasonable that market pressures and technological advances will allow banks to virtually eliminate branches? How does competition from other banks and non-bank firms affect the choice of distribution strategy? We find that in a wide variety of experiments that banks will retain their branch networks, along with a PC banking capability.

This paper studies the design of the performance evaluation system in a decentralized firm where units are organized as cost centers and lead time has an important effect on demand or cost. The paper has two conclusions. First, performance measurement systems exist and lead the firm to a profit maximum if correct weight is assigned to a cost centers' lead time performance. However, computation of the proper weight requires that general managers have specific knowledge of the cost centers' tradeoff between cost and lead time. Second, an iterative procedure leads to a profit optimum if accurate estimates of marginal cost, which include opportunity costs, are available. Two potential difficulties cause suboptimal profits under decentralization: the cost center's performance measurement system is not optimal, and inaccurate estimates of marginal cost are used by general managers when setting production levels. The first problem is solved if general management knows customers' value of lead time and the tradeoff of cost and lead time. Different types of investments can be used to gain this knowledge, such as engineering studies about the technical relationship between cost and lead time, marketing research studies, cycle time reduction programs, just-in- time programs, quality improvement programs and customer satisfaction surveys. The second problem can be solved by using lead time measures to estimate marginal cost.

This paper develops an analytic model to study the effect of network design on an airline's cost and passengers' service level. Four different types of networks are considered: direct, hub and spoke, tour and subtour. Service levels are measured by the cost borne by passengers due to travel time, schedule delay (the time difference between the ideal departure time and the actual departure time) and late arrival. Airline cost is the carrier's cost of operating its network. Results of the paper include that the schedule frequency that minimizes total airline and passenger costs is a function of the network, and that direct service has lower schedule frequency than the other networks. If passengers are sensitive to schedule delay, than a tour can be optimal, but if not, direct service can be optimal. Parametric studies are performed on the effect of distance between cities, demand rate and the number of cities served on the optimal network. If the distance between cities is small, direct service is optimal; if it is large, a tour is optimal; and for intermediate values, hub and spoke is optimal. If the number of cities is small, direct service dominates; if it is large, hub and spoke is optimal; and for intermediate values other networks are best. An airline's schedule includes time as a buffer against delays. This planned delay time increases passengers' travel time and airline cost since more aircraft are required, but reduces passengers' chances of arrival after the schedule time. It is shown that if schedule reliability is chosen to minimize total airline and passengers' costs, schedule reliability is highest for direct routing. This explains the superior on- time performance of non-hub carriers such as Southwest Airlines. An example shows that congestion at the hub does not change optimal network design unless delays at the hub are very much larger than at spoke city airports.

This paper studies price and production competition between spatially distributed firms. Firms compete by choosing delivered prices, a pricing regime which is often observed for goods with high transportation costs. The model is a very general one: customers have price elastic demand and firms have increasing marginal production and transportation costs. To study this competitive situation, a non-cooperative game is proposed. Existence and general properties of the Nash price and production equilibrium are shown and sufficient conditions that guarantee the existence of a unique price-production-transportation equilibrium are presented. It is shown that the only pricing patterns that can result from equilibrium are basing point, monopoly or mill pricing. A convergent algorithm is shown and demonstrated with an example.