Essays on Integrating Product Design and Marketing Research.
dc.contributor.author | Feit, Eleanor McDonnell | en_US |
dc.date.accessioned | 2010-01-07T16:32:35Z | |
dc.date.available | NO_RESTRICTION | en_US |
dc.date.available | 2010-01-07T16:32:35Z | |
dc.date.issued | 2009 | en_US |
dc.date.submitted | en_US | |
dc.identifier.uri | https://hdl.handle.net/2027.42/64766 | |
dc.description.abstract | Engineers and product designers have developed sophisticated models to predict the technical performance of their designs, yet they seldom quantify how performance affects the desirability of the resulting products to consumers. Without this information, managers have difficulty judging which products are most likely to succeed in the marketplace. The essays in this dissertation develop quantitative marketing research methods that use choice experiments to provide designers with quantitative predictions of market share and revenue for new product designs. Although choice experiments have been used in product design for some time, there remain many hurdles that limit the ability of market research to inform product designs. In the first essay, we address concerns about the reliability of choice experiments for making predictions about the performance of new products in the marketplace. In it we develop a new method for combining choice data and use it to combine data from choice experiments with data from the market, providing designers with a model that can predict consumer demand for new product attributes, yet is consistent with the preferences for existing attributes observed in the market. The second essay, which is methodologically related to the first through the notion of error scale, investigates the relationship between how well the attributes predict respondents' choices and their expertise in the product category. Understanding this relation will lead to better predictions about consumer behavior, particularly in situations where the expertise of consumers is changing, e.g., new categories of products. Together these essays contribute to the ultimate goal of developing quantitative market research tools that can inform product design decisions. In the conclusions, we turn to the question of whether information about the product design problem can inform market research and propose a new approach to creating choice surveys that, unlike past approaches, incorporates information on costs and constraints of the design problem and chooses the survey questions that will maximize the profit of the ultimate product design. | en_US |
dc.format.extent | 1662215 bytes | |
dc.format.extent | 1373 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | en_US |
dc.subject | Choice Modeling | en_US |
dc.subject | Bayesian Statistics | en_US |
dc.subject | Product Design | en_US |
dc.subject | Marketing Research | en_US |
dc.title | Essays on Integrating Product Design and Marketing Research. | en_US |
dc.type | Thesis | en_US |
dc.description.thesisdegreename | PhD | en_US |
dc.description.thesisdegreediscipline | Business Administration | en_US |
dc.description.thesisdegreegrantor | University of Michigan, Horace H. Rackham School of Graduate Studies | en_US |
dc.contributor.committeemember | Feinberg, Fred M. | en_US |
dc.contributor.committeemember | Beltramo, Mark A. | en_US |
dc.contributor.committeemember | Lenk, Peter J. | en_US |
dc.contributor.committeemember | Manchanda, Puneet | en_US |
dc.contributor.committeemember | Papalambros, Panos Y. | en_US |
dc.subject.hlbsecondlevel | Marketing | en_US |
dc.subject.hlbsecondlevel | Engineering (General) | en_US |
dc.subject.hlbsecondlevel | Economics | en_US |
dc.subject.hlbtoplevel | Business | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/64766/1/efeit_1.pdf | |
dc.owningcollname | Dissertations and Theses (Ph.D. and Master's) |
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