Slop: A Strategic Multiple Store Location Model for a Dynamic Environment

A model is provided that allows optimum choice of store location in the present and in the future. Choice of location is based on optimum location that will work with the best present scenario and the best future scenario. Basis for the model is market demand data from consumer surveys and sales performance data

Impact of trade area environment on bank's comparative advantages

This article analyses the relationship between the comparative advantages of bank branches and the trade area environment. Bank branches are points of sale whose trade environment influences their activities and performance. Comparative advantages are defined, for each output mix, by the strict dominance of a production technology in a specific trade area over the production technologies of other environments. Using Shephard's output distance functions on a sample of 728 bank branches, we compare the production technologies for different output mixes and different trade environments. We show that none of the production technologies strictly dominates the others and none of them is strictly dominated. Therefore, each trade area benefits from comparative advantages that we try to highlight. Finally, we evaluate the performance of the central banks regarding their ability to provide the right incentives on output mixes to their bank branches so that the latter may benefit from their comparative advantages.

Designing and evaluating a health care delivery system through the use of interactive computer graphics

During the past decade an awareness has emerged for the necessity of planning the efficient delivery of regional health care services. This paper focuses on the implementation of an analytical tool to aid health planners in evaluating current and prescribing future health care facility and service locations. The analysis was performed under the rubric of an interactive computer graphic approach permitting optimal man-machine interaction. Although a considerable theoretical and methodological literature already exists in this area, the solution techniques tend to be mathematically complex and highly specific. The proposed system will place in the hands of an experienced decision-maker, the health planner, a set of easily manipulated models, supported by a set of powerful mathematical tools, which provide flexibility for changing planning objectives, results that are easily interpreted, and a relatively low cost technique.

The Benefits of Advance Booking Discount Programs: Model and Analysis

Consider a retailer who sells perishable seasonal products with uncertain demand. Due to the short sales season and long replenishment lead times associated with such products, the retailer is unable to update demand forecasts by using actual sales data generated from the early part of the season and to respond by replenishing stocks during the season. To overcome this limitation, we examine the case in which the retailer develops a program called the "advance booking discount" (ABD) program that entices customers to commit to their orders at a discount price prior to the selling season. The time between placement and fulfillment of these precommitted orders provides an opportunity for the retailer to update demand forecasts by utilizing information generated from the precommitted orders and to respond by placing a cost-effective order at the beginning of the selling season. In this paper, we evaluate the benefits of the ABD program and characterize the optimal discount price that maximizes the retailer's expected profit.retailing, marketing/manufacturing interfaces, pricing

Asymmetric Store Positioning and Promotional Advertising Strategies: Theory and Evidence

Asymmetrically positioned retailers, who vary in the quality/in-store service offered, are increasingly using promotional advertising—the practice of advertising sale prices on familiar merchandise lines—to compete for customers who are willing to comparison shop. The objective of this paper is to examine the role of promotional advertising for stores that vary in their quality positioning in competing for customers using a game-theoretic model. Our focus is on two key retail promotional advertising decisions: the frequency with which to advertise price reductions and the accompanying depth of discount. We consider a stylized duopolistic retail market with the two stores that differ in their service positioning. We assume that each store enjoys a relative advantage in serving a subset or segment of customers who regularly visit it and whom we call “patrons” of the store. We assume that it costs more to shop at the less-frequented store. We further assume that consumers are only partially informed about the prevailing retail prices—while they perfectly know the posted price at the store that they patronize, they are uncertain about the price at the other store and have rational expectations about these prices. Consumers in this market differ on three dimensions: preference for service, shopping costs, and store switching costs. We explicitly consider two consumer segments differing in their willingness to pay for service. Furthermore, we assume store switching is more costly for the high-valuation segment. We allow for within-segment heterogeneity by assuming that consumers differ in their shopping costs. Our analysis shows that if promotional advertising is not “too costly,” the equilibrium strategies of the competing retailers entail occasionally posting its “regular” price but not advertising that price and on other occasions posting its “sale” price and advertising that price. The analysis also suggests that promotional advertising is driven by “offensive” (traffic-building) as well as “defensive” (consumer-retention) considerations. Furthermore, the relative importance of offensive and defensive considerations is influenced by the service positioning of the stores. Specifically, relative to the low-service store, promotional advertising by the high-service store is driven more by offensive consideration than defensive consideration. Finally, a store's service positioning impacts its frequency of promotional advertising and the depth of discount that it offers during “sale.” Specifically, relative to the low-service store, the high-service store offers advertised sales more frequently but with shallower discounts. These results follow from the fact that differences in service positioning lead to a natural consumer “self-selection.” Specifically, the consumer-mix of the high-service store comprises a higher fraction of the high-valuation consumers who are less sensitive to promotional advertising due to their higher store switching costs. Thus, if the low-service retailer were to build store traffic by targeting the customer mix of the high-service retailer (motivated by offensive consideration), it has to offer deeper discounts; yet the demand enhancement is lower. Thus, relative to the high-service store, promotional advertising is not that attractive for the low-service store. However, the low-service store still relies on offering discounted prices occasionally to retain its customer base. Thus when using promotional advertising to attract and retain customers, the high-service store should rely more on the “frequency cue,” while the low-quality store should rely more on the “magnitude cue.” We provide empirical support for the key predictions of our analytical model by collecting and analyzing retail promotional advertisements for stores that vary in their level of in-store service, published in major newspapers in a large U.S. metropolitan city. We collected data from 813 advertisements across 14 different product groups in the men’s and women's categories. The data are consistent with the model's predictions. Our theory and empirical analysis should be of interest to both academics and practitioners, particularly those in the area of channel management and promotional advertising.Retail Competition, Store Positioning, Promotional Advertising, Shopping Cost, Traffic Building, Customer Retention