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Wayne S. Desarbo Venkatram Ramaswamy Michel Wedel Tammo Bijmolt 《Marketing Letters》1996,7(2):131-145
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. 相似文献
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For insurance companies, tournaments are one of the most important incentives to motivate and control insurance sales agents. We analyse the efficiency of tournaments for insurance sales agents and show that the level of prize and its exclusiveness, as well as the presentation of rank during the tournament, increase efficiency. 相似文献
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Prasad Naik Michel Wedel Lynd Bacon Anand Bodapati Eric Bradlow Wagner Kamakura Jeffrey Kreulen Peter Lenk David M. Madigan Alan Montgomery 《Marketing Letters》2008,19(3-4):201-213
Modern businesses routinely capture data on millions of observations across subjects, brand SKUs, time periods, predictor variables, and store locations, thereby generating massive high-dimensional datasets. For example, Netflix has choice data on billions of movies selected, user ratings, and geodemographic characteristics. Similar datasets emerge in retailing with potential use of RFIDs, online auctions (e.g., eBay), social networking sites (e.g., mySpace), product reviews (e.g., ePinion), customer relationship marketing, internet commerce, and mobile marketing. We envision massive databases as four-way VAST matrix arrays of Variables?×?Alternatives?×?Subjects?×?Time where at least one dimension is very large. Predictive choice modeling of such massive databases poses novel computational and modeling issues, and the negligence of academic research to address them will result in a disconnect from the marketing practice and an impoverishment of marketing theory. To address these issues, we discuss and identify the challenges and opportunities for both practicing and academic marketers. Thus, we offer an impetus for advancing research in this nascent area and fostering collaboration across scientific disciplines to improve the practice of marketing in information-rich environment. 相似文献
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While the broad and growing sector of leisure, culture and entertainment is rapidly adapting to marketing, little is known about segmentation in this field. The sector has customer and transaction databases of very good quality, but usage-based segmentation in this new field poses new problems, as hedonic consumption goods are importantly different from other consumption goods. The type of consumer choice behavior suggested in the literature demands a segmentation of category purchase incidence identified transaction data based on Latent Class Analysis. We illustrate such an approach to a library transaction database. The article concludes with a reflection on the results and suggests further directions for research. 相似文献
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List augmentation with model based multiple imputation: a case study using a mixed-outcome factor model 总被引:1,自引:0,他引:1
This study concerns list augmentation in direct marketing. List augmentation is a special case of missing data imputation. We review previous work on the mixed outcome factor model and apply it for the purpose of list augmentation. The model deals with both discrete and continuous variables and allows us to augment the data for all subjects in a company's transaction database with soft data collected in a survey among a sample of those subjects. We propose a bootstrap-based imputation approach, which is appealing to use in combination with the factor model, since it allows one to include estimation uncertainty in the imputation procedure in a simple, yet adequate manner. We provide an empirical case study of the performance of the approach to a transaction data base of a bank. 相似文献
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Concomitant variables in finite mixture models 总被引:1,自引:0,他引:1
Michel Wedel 《Statistica Neerlandica》2002,56(3):362-375
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J. W. de Beus Harry Garretsen J. J. Graafland M. M. G. Fase J. R. Pruntel J. C. Siebrand V. R. Okker Gerard H. Kuper C. G. de Vries J. de Haan Y. S. Brenner Peter A. G. van Bergeijk S. W. Douma Jan Oosterhaven J. A. Kregel Dave Furth J. F. Kiviet J. Th. Degenkamp M. Wedel Bart van Ark N. van Hulst W. van Voorden A. Bosman M. W. F. Treub 《De Economist》1990,138(3):340-387
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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. 相似文献
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