William L. Moore

Individual Differences in Search Behavior For a Nondurable

Subjects acquired information on, chose, and consumed one of five health breads once a week for six weeks. The effects of individual differences on information acquisition and recall of package information were studied. Experience during the experiment was highly related to the amount of external search and recall of package information. Information-processing style was also related to external search.

The Role of Market Information in New Product Success/Failure

Abstract Although no single variable holds the key to new product performance, many of the widely recognized success factors share a common thread: the processing of market information. Understanding customer wants and needs ultimately comes down to a companys capabilities for gathering and using market information. And another well-acknowledged success factor the integration of marketing, R&D, and manufacturing focuses on the sharing of information. In other words, a firms effectiveness in market information processing—the gathering, sharing, and use of market information—plays a pivotal role in determining the success or failure of its new products. Brian D. Ottum and William L. Moore describe the results of a study that examines the relationship between market information processing and new product success. They also explore the organizational factors that facilitate successful processing of market information, and thus offer ideas for better managing the development of new products. The respondents—marketing, R&D, and manufacturing managers from Utah-based computer and medical device manufacturers—provided information about 58 new products, including equal numbers of succeses and failures. The survey responses reveal strong relationships between product success and market information processing, with success most closely linked to information use. In other words, the gathering and sharing of information are important, but only if the information is used effectively. In 80 percent of the product successes studied, the respondents ultimately possessed and used a greater than average amount of market information. And in 75 percent of the failures, the respondents knew less than average about the market at project inception, and gathered or used less than the average amount of market information during the project. For the projects in this study, the integration of marketing, R&D, and manufacturing contributed not only to the sharing and use of information, but also to overall project success. However, the results of the study suggest that the way in which a project is organized plays only an indirect role in determining new product success—most likely by improving the processing of market information. From a managerial perspective, the most important variables identified in the study are market information shared, market information used, and financial success.

Feature Interactions in Consumer Judgments of Verbal versus Pictorial Presentations

In consumer judgments of product designs, the numbers of additive and configural feature effects are apt to differ between verbal and pictorial stimulus presentations. A study of judgmental responses to sweater designs suggests the significant occurrence of feature interactions, a tendency for pictorial (versus verbal) displays to evoke more main effects, and a tendency for pictorial displays to promote cue configurality when one controls for type of information-processing strategy.

Using Conjoint Analysis to Help Design Product Platforms

Abstract This article illustrates how one can combine different conjoint analysis studies, each containing a core of common attributes, to help design product platforms that serve as the foundation for multiple derivative products. The illustration is based on actual, but disguised, data from a small company that makes electronic test equipment. This article demonstrates that decisions that consider products individually are likely to be suboptimal and can be significantly different than those based on product platforms. Suboptimality can occur either when preferences for product features differ across markets or when a technology is more important to the overall company than it is to an individual product. Additionally, we show the importance of considering both fixed and variable costs when performing this type of analysis as sales, contribution, and profit-maximizing products are quite different. Finally, sensitivity analyses show that these results are robust with respect to assumptions about price sensitivity, fixed costs, and timing of entry.

The Effects of Positive and Negative Online Customer Reviews: Do Brand Strength and Category Maturity Matter?

Research has shown brand equity to moderate the relationship between online customer reviews (OCRs) and sales in both the emerging Blu-ray and mature DVD player categories. Positive (negative) OCRs increase (decrease) the sales of models of weak brands (i.e., brands without significant positive brand equity). In contrast, OCRs have no significant impact on the sales of the models of strong brands, although these models do receive a significant sales boost from their greater brand equity. Higher sales lead to a larger number of positive OCRs, and increased positive OCRs aid a brands transition from weak to strong. This creates a positive feedback loop between sales and positive OCRs for models of weak brands that not only helps their sales but also increases overall brand equity, benefiting all models of the brand. In contrast to the view that brands matter less in the presence of OCRs, we find that OCRs matter less in the presence of strong brands. Positive OCRs function differently than marketing communications in that their effect is greater for weak brands.

A Comparison of Quality Function Deployment and Conjoint Analysis in New Product Design

Abstract In this work, we compare two product design approaches, quality function deployment (QFD) and conjoint analysis, by applying each to the design of a new all-purpose climbing harness for the beginning/intermediate ability climber that would complement a leading manufacturer’s existing product line. While many of the optimal design features were the same under both approaches, the differences allow us to highlight the strengths of each approach. With conjoint analysis, it was easier to compare the most preferred features (i.e., ones that maximized sales) to profit maximizing features and also to develop designs that optimize product line sales or profits. On the other hand, QFD was able to highlight the fact that certain engineering characteristics or design features had both positive and negative aspects. This tradeoff could point the way to “out of the box” solutions. QFD also highlighted the importance of starting explicitly with customer needs, regardless of which method is used. Rather than competing, we view them as complementary approaches that should be conducted simultaneously; each providing feedback to the other. When the two approaches differed on the optimal level or importance of a feature, it appeared that conjoint analysis better captured customers’ current preferences for product features while QFD captured what product developers thought would best satisfy customer needs. Looking at the problem through these different lenses provides a useful dialogue that should not be missed. QFD’s ability to generate creative or novel solutions should be combined with conjoint analysis’ ability to forecast market reaction to design changes.

Experiments in Constrained Choice

This article examines the relative importance of a variety of factors in influencing hierarchical choice. In our first experiment, we test some implications of Tversky and Sattaths (1979) Hierarchical Elimination Model (HEM) relating to a choice set in which an external constraint has been imposed. (An external constraint changes the decision process by partitioning the brands in a different way than the consumer naturally would.) Our experimental results and the theoretical predictions do not converge. While they agree that external partitions do affect choice probabilities, they differ on the nature of the effect. Next, we run a second experiment to test alternative explanations of our empirical results. Using these results, we propose managerial implications for positioning a #1 and #2 brand.

Effective Design of Products/Services: An Approach Based on Integration of Marketing and Operations Management Decisions

This paper presents an integrated framework for designing profit-maximizing products/ services, which can also be produced at reasonable operating difficulty levels. Operating difficulty is represented as a function of product and process attributes, and measures a firms relative ease or difficulty in meeting customer demand patterns under specified operating conditions. Earlier optimum product design procedures have not considered. operational difficulty. We show that optimum profit, market share, cost, and product profiles are dependent on operating difficulty level. Empirical results from the pizza delivery industry demonstrate the value of the proposed Effective Product/Service Design approach.

A Cross-Validity Comparison of Conjoint Analysis and Choice Models at Different Levels of Aggregation

Several (ratings-based) conjoint analysis and experimental choice (choice-based conjoint) models are compared on their ability to predict both aggregate choice shares among the sample and individual choices in an availability validation task. While there was a weak relationship between validations at the individual and aggregate levels, several models stand out. In general, models capturing individual differences validated well at both the individual and aggregate level. The hierarchical Bayes choice and conjoint models validated particularly well.Among choice models, the hierarchical Bayes choice model had the highest aggregate and individual level-validations. It was followed by the hybrid and seven segment latent segment choice models. Overall, the highest validating ratings-based conjoint model was the hierarchical Bayes model. However, the seven segment latent segment conjoint model produced better aggregate choice share validations than any other conjoint model. These results indicate that validations can be improved either by using benefit segment models and/or merging different types of data to estimate more individualized models.In most cases, rescaling improved the ratings-based, but not the choice-based choice share validations. This suggests that one might adjust for differences between ratings and choice tasks before making choice share predictions.

Constructing Joint Spaces from Pick-Any Data: A New Tool for Consumer Analysis

The recently developed “pick-any” approach to data collection and analysis is described and illustrated by examples that support its face validity, reliability, and convergent validity with other multidimensional scaling techniques. Some solutions to problems that arise in applying the pick-any procedure are suggested, and potential extensions are proposed for use of the procedure in perceptual mapping applications.