Modeling Decision of Choice Among Finite Alternative: Applications to Marketing and to Transportation Demand Theory
A methodology to improve the effectiveness of the design of innovation is proposed based on knowledge in the fields of psychometrics, utility theory and stochastic choice modeling. It is comprised of a consumer response and a managerial design process. The design process is one of idea generation, e...
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| Format: | Working Paper |
| Language: | en_US |
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Massachusetts Institute of Technology, Operations Research Center
2004
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| Online Access: | http://hdl.handle.net/1721.1/5354 |
| _version_ | 1811070172206727168 |
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| author | Hauser, John R. |
| author_facet | Hauser, John R. |
| author_sort | Hauser, John R. |
| collection | MIT |
| description | A methodology to improve the effectiveness of the design of innovation is proposed based on knowledge in the fields of psychometrics, utility theory and stochastic choice modeling. It is comprised of a consumer response and a managerial design process. The design process is one of idea generation, evaluation, and refinement while the consumer response is based on consumer measurement, an individual choice model, and aggregation of the individual choices. The consumer model interacts with the design process by providing diagnostics on consumer perceptions, preference, choice, and segmentation, as well as prediction of the share of choices. The individual response model processes the consumer measures by "reducing" them to an underlying set of perceptual dimensions. "Abstraction" defines homogeneous groups based on perceptions and preference. "Compaction" describes how the reduced space performance measures are combined to produce a scalar measure of goodness for each consumer and for each choice alternative. This goodness measure is linked to probability of choice for the new and old alternatives. In each step, theoretical, empirical, and statistical issues are identified and various techniques are described for each phase. The techniques are demonstrated based on survey data collected at MIT to support the design of a health maintenance organization (HMO). After discussing the issues of testing the model, the managerial design implications are shown by application to the MIT HMO case. |
| first_indexed | 2024-09-23T08:29:44Z |
| format | Working Paper |
| id | mit-1721.1/5354 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T08:29:44Z |
| publishDate | 2004 |
| publisher | Massachusetts Institute of Technology, Operations Research Center |
| record_format | dspace |
| spelling | mit-1721.1/53542019-04-09T18:20:08Z Modeling Decision of Choice Among Finite Alternative: Applications to Marketing and to Transportation Demand Theory Hauser, John R. A methodology to improve the effectiveness of the design of innovation is proposed based on knowledge in the fields of psychometrics, utility theory and stochastic choice modeling. It is comprised of a consumer response and a managerial design process. The design process is one of idea generation, evaluation, and refinement while the consumer response is based on consumer measurement, an individual choice model, and aggregation of the individual choices. The consumer model interacts with the design process by providing diagnostics on consumer perceptions, preference, choice, and segmentation, as well as prediction of the share of choices. The individual response model processes the consumer measures by "reducing" them to an underlying set of perceptual dimensions. "Abstraction" defines homogeneous groups based on perceptions and preference. "Compaction" describes how the reduced space performance measures are combined to produce a scalar measure of goodness for each consumer and for each choice alternative. This goodness measure is linked to probability of choice for the new and old alternatives. In each step, theoretical, empirical, and statistical issues are identified and various techniques are described for each phase. The techniques are demonstrated based on survey data collected at MIT to support the design of a health maintenance organization (HMO). After discussing the issues of testing the model, the managerial design implications are shown by application to the MIT HMO case. Supported in part by the U.S. Army Research Office (Durham) under Contract No. DAHC04-73-C-0032 2004-05-28T19:35:19Z 2004-05-28T19:35:19Z 1974-10 Working Paper http://hdl.handle.net/1721.1/5354 en_US Operations Research Center Working Paper;OR 038-74 1746 bytes 2791090 bytes application/pdf application/pdf Massachusetts Institute of Technology, Operations Research Center |
| spellingShingle | Hauser, John R. Modeling Decision of Choice Among Finite Alternative: Applications to Marketing and to Transportation Demand Theory |
| title | Modeling Decision of Choice Among Finite Alternative: Applications to Marketing and to Transportation Demand Theory |
| title_full | Modeling Decision of Choice Among Finite Alternative: Applications to Marketing and to Transportation Demand Theory |
| title_fullStr | Modeling Decision of Choice Among Finite Alternative: Applications to Marketing and to Transportation Demand Theory |
| title_full_unstemmed | Modeling Decision of Choice Among Finite Alternative: Applications to Marketing and to Transportation Demand Theory |
| title_short | Modeling Decision of Choice Among Finite Alternative: Applications to Marketing and to Transportation Demand Theory |
| title_sort | modeling decision of choice among finite alternative applications to marketing and to transportation demand theory |
| url | http://hdl.handle.net/1721.1/5354 |
| work_keys_str_mv | AT hauserjohnr modelingdecisionofchoiceamongfinitealternativeapplicationstomarketingandtotransportationdemandtheory |