Shelby H. McIntyre

A decision support system for vendor managed inventory

Abstract Recently, vendors and retailers have begun to forge cooperative agreements to manage inventory, which requires sharing demand information and setting mutually agreed upon performance targets for the supply chain. This paper describes the market forecasting and inventory management components of a Vendor Managed Inventory (VMI) decision support system and how this system was implemented by a major apparel manufacturer and over 30 of its retail partners. The DSS also helped the vendor and retailers arrive at jointly agreed upon customer service level and inventory turnover targets. As a result of implementing this VMI system, customer service levels improved dramatically, often coupled with a significant improvement in inventory turnover. The VMI performance results relative to the existing system and related insights for supply chain coordination are discussed.

The E-Marketing Mix: A Contribution of the E-Tailing Wars

In the context of the wars between the upstart Internet retailers and the existing bricks-and-mortar retailers, many e-marketing techniques were invented. This article develops a single unifying and theoretically based taxonomy for e-marketing techniques: the e-marketing mix. Drawing on the paradigms of exchange, relationships, and digital interactions in networks, 11 e-marketing functions are identified that form the elements of the e-marketing mix. Nine of the 11 e-marketing functions are considered basic, while 7 functions moderate the effects of others and are termedoverlapping. The 11 e-marketing functions provide a categorization of the e-marketing techniques. Compared to the conventional marketing mix, the e-marketing mix has more overlapping elements and directly represents personalization, an aspect of segmentation, as a basic function. The existence of multiple elements that are basic and overlapping in the e-marketing mix indicates that integration across elements should be more commonplace compared to the traditional marketing mix.

Forecasting Methods for Marketing: Review of Empirical Research

This paper reviews the empirical research on forecasting in marketing. In addition, it presents results from some small scale surveys. We offer a framework for discussing forecasts in the area of marketing, and then review the literature in light of that framework. Particular emphasis is given to a pragmatic interpretation of the literature and findings. Suggestions are made on what research is needed.

Preferential Treatment in Preselection Decisions According to Sex and Race

Resumes of fictitious applicants for entry-level professional positions were mailed to 458 potential employers, and the responses were analyzed. A three-group experimental design permitted control ...

The Selection and Pricing of Retail Assortments: An Empirical Approach

Abstract Determining the best assortment to carry is one of the most central problems in retailing. The key decisions are what items to stock and how to price them. In this article, we develop and test an empirical (or nonparametric) approach that simultaneously addresses the selection and pricing problems. The approach is then applied to the problem of selecting an optimal assortment of backpacks from a field of eight available items. The empirical procedure generates data from a calibration sample of shoppers that we use to determine supposedly optimal assortments (of size k = 2, 3, 4, and 5). In a validation analysis on a new sample of shoppers, from the same parent population, it is shown that in this instance the new approach does yield significantly more profitable retail assortments, in all cases (e.g., for all assortment sizes), when compared with more traditional approaches. Additionally, the experimental approach predicts sales and profitability more accurately than traditional approaches.

Applying case-based reasoning to forecasting retail sales☆

Abstract This article describes the development and testing of a forecasting system for retailers who plan periodic promotions. When the number of variables describing the promotion is large relative to the historical database of past promotions, traditional forecasting approaches cannot be applied. In such cases, retailers must rely on the expertise of their buyers to subjectively estimate promotional unit sales. This research develops a Case-Based Reasoning system that allows all buyers to forecast promotional sales as accurately as the organizations expert buyer and, by making the subjective process explicit, also provides an avenue to improve forecast performance over time. The system (1) selects the historical analogs that are most similar to the planned promotion, (2) adjusts the sales of each analog to account for any differences between the analog and the planned promotion, and (3) combines the forecasts derived from the multiple analogs to arrive at a single sales projection. The performance of the system was tested and found to compare favorably to the performance of an expert buyer in a large national retail organization.

Return on Reputation in Online Auction Markets

This research develops an assurances framework to assess the effect of a seller’s feedback “reputation” on the closing price of an online auction. The framework treats bidders as if they were ‘intuitive statisticians’ in their use of reputation cues. The framework leads to hypotheses about how information-based assurances (particularly feedback scores and the seller’s provision of information about the product) may be used by buyers to reduce their trading risks. The hypotheses are tested using data collected from the eBay web site on auctions of Palm Pilot personal digital assistants. It is found that the higher the seller’s reputation the higher is the average closing price of the auction, which constitutes a return on reputation (ROR). Thus the reputation infrastructure rewards good behavior with positive economic outcomes and helps to sustain a virtuous cycle in the online ecosystem. More specifically, it is found that: (a) negative comments are weighted more heavily than positive ones (b) negative feedback is subject to diminishing returns (c) the assurance offered by reputation is more salient among risk-averse buyers and (d) a high level of information about the merchandise also provides another form of assurance. However, when faced with a high level of information, risk-averse buyers seem to rely less on the sellers reputation score for assurance (a three way negative interaction between risk aversion, reputation and high information). The economic impact of these findings is that the seller of a Palm Pilot who has a high reputation can expect to receive as much as 12.6% more for the item than if he had a low reputation score. Of course, eBay also participates in this upside through its commission structure as well as the wider impact that the feedback seems to have. It is argued that the market for assurances is a contributor to eBay’s success and is also essential to the optimal functioning of any online market.

Obstacles to corporate innovation

Shelby H. Mcln tyre is an assistant professor of market ing at the Univers i ty of Santa Clara in California. He was formerly an industrial engineer for General Electric and vice pres ident of operat ions for two manufac tur ing companies . He is the author of numerous articles. It is difficult for large corporations to be innovative because of characteristics inherent in their structure. But, with determination and the proper emphasis from top management, it can be done.

Social Utility and Fashion Behavior

This article reports the exploratory results of a computer-based behavioral simulation that examines the role of social utility in fashion behavior. Social utility is defined as those benefits of a product or service that satisfy interpersonal needs (e.g., conformity, individuality relative to others). These exploratory results suggest that social utility is a prime determinate of fashion behavior, and that selected personality traits moderate behavioral responses to social influence in the fashion domain.

What Focus Groups Can and Cannot Do: A Reply to Seymour

In their reply to Seymour, Edward McQuarrie and Shelby McIntyre address the question of the advantages and disadvantages of focus groups as a research technique. They argue that the biases incurred with focus groups are no greater than those that result from any other market research technique, but caution that polls of focus group members cannot be extrapolated to estimate the incidence of some response in the population. What is unique to group discussions is the social interaction among respondents. This interaction can help to resolve some of the questions that occupy the attention of new products managers. The authors conclude with suggestions for empirical research which could advance our understanding of the use of focus groups.