A spatial interaction model for deriving joint space maps of bundle compositions and market segments from pick-any/J data: An application to new product options

We propose an approach for deriving joint space maps of bundle compositions and market segments from three-way (e.g., consumers x product options/benefits/features x usage situations/scenarios/time periods) pick-any/J data. The proposed latent structure multidimensional scaling procedure simultaneously extracts market segment and product option positions in a joint space map such that the closer a product option is to a particlar segment, the higher the likelihood of its being chosen by that segment. A segment-level threshold parameter is estimated that spatially delineates the bundle of product options that are predicted to be chosen by each segment. Estimates of the probability of each consumer belonging to the derived segments are simultaneously obtained. Explicit treatment of product and consumer characteristics are allowed via optional model reparameterizations of the product option locations and segment memberships. We illustrate the use of the proposed approach using an actual commercial application involving pick-any/J data gathered by a major hi-tech firm for some 23 advanced technological options for new automobiles.     

Modeling Methods for Discrete Choice Analysis

This paper introduces new forms, sampling and estimation approaches fordiscrete choice models. The new models include behavioral specifications oflatent class choice models, multinomial probit, hybrid logit, andnon-parametric methods. Recent contributions also include new specializedchoice based sample designs that permit greater efficiency in datacollection. Finally, the paper describes recent developments in the use ofsimulation methods for model estimation. These developments are designed toallow the applications of discrete choice models to a wider variety ofdiscrete choice problems.     

Latent class metric conjoint analysis

A latent class methodology for conjoint analysis is proposed, which simultaneously estimates market segment membership and part-worth utilities for each derived market segment using mixtures of multivariate conditional normal distributions. An E-M algorithm to estimate the parameters of these mixtures is briefly discussed. Finally, an application of the methodology to a commercial study (pretest) examining the design of a remote automobile entry device is presented.     

Market segmentation with choice-based conjoint analysis

Choice-based conjoint analysis has increased in popularity in recent years among marketing practitioners. The typical practice is to estimate choice-based conjoint models at the aggregate level, given insufficient data for individual-level estimation of part-worths. We discuss a method for market segmentation with choice-based conjoint models. This method determines the number of market segments, the size of each market segment, and the values of segment-level conjoint part-worths using commonly collected conjoint choice data. A major advantage of the proposed method is that current (incomplete) data collection approaches for choice-based conjoint analysis can still be used for market segmentation without having to collect additional data. We illustrate the proposed method using commercial conjoint choice data gathered in a new concept test for a major consumer packaged goods company. We also compare the proposed method with ana priori segmentation approach based on individual choice frequencies.     

Explaining Downstream Integration

We examine the downstream integration decision by businesses, deriving hypotheses from the transaction cost literature which are empirically tested for a sample of 1392 businesses operating in a wide spectrum of industries. Our results provide corroboration for each dimension of the transaction cost framework in explaining why firms might integrate their downstream business activities. Given the large cross-sectional sample, our results provide some evidence of the general validity of the transaction cost framework within the context of downstream integration.     

Coupon characteristics and redemption intentions: A segment-level analysis

The authors investigate how different segments of consumers react to different coupon characteristics, such as face value and method of distribution. They utilize a latent segmentation approach to identify the underlying segments. The empirical analysis suggests that different segments of consumers place varying emphasis with regard to economic benefits, psychic benefits, effort costs, and substitution costs. A further examination of the derived segments with respect to consumer correlates such as psychological, attitudinal, behavioral, and demographic characteristics reveals that coupon-related consumer characteristics, rather than demographics, exhibit significant and meaningful differences across these segments. Implications of the segment-level analysis for evaluating coupon drops and managing promotional expenditures are also discussed. © 1998 John Wiley & Sons, Inc.     

Going direct to market: The influence of exchange conditions

When faced with the strategic choice of going direct to market versus the option of using intermediaries, a firm is posited to evaluate the benefits to customers from going direct to market, and the transaction costs involved in using intermediaries. In this paper, we discuss how these evaluations might differ depending upon the microcharacteristics of the exchange domain. Based on these theoretical considerations, specific propositions are offered regarding the conditions under which firms might rely more heavily on direct channels. These propositions are tested by conducting a cross'sectional empirical analysis using a large sample of manufacturing firms operating in diverse exchange domains. We also control for the impact of macrolevel environmental characteristics, as well as firm-level characteristics that may influence the direct to market decision. Our empirical results confirm that customer benefits and transaction costs are important considerations in going direct to market.