Preference Learning and Demand Forecast
Understanding consumer preferences is important for new product management, but isfamously challenging in the absence of actual sales data. Stated-preferences data are rel-atively cheap but less reliable, whereas revealed-preferences data based on actual choicesare reliable but expensive to obtain...
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| Diğer Yazarlar: | |
| Materyal Türü: | Makale |
| Dil: | English |
| Baskı/Yayın Bilgisi: |
Institute for Operations Research and the Management Sciences (INFORMS)
2021
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| Online Erişim: | https://hdl.handle.net/1721.1/130372 |
| _version_ | 1826209912674320384 |
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| author | Zhang, Juanjuan |
| author2 | Sloan School of Management |
| author_facet | Sloan School of Management Zhang, Juanjuan |
| author_sort | Zhang, Juanjuan |
| collection | MIT |
| description | Understanding consumer preferences is important for new product management, but isfamously challenging in the absence of actual sales data. Stated-preferences data are rel-atively cheap but less reliable, whereas revealed-preferences data based on actual choicesare reliable but expensive to obtain prior to product launch. We develop a cost-effectivesolution. We argue that people do not automatically know their preferences, but canmake an effort to acquire such knowledge when given sufficient incentives. The methodwe develop regulates people’s preference-learning incentives using a single parameter,re-alization probability, meaning the probability with which an individual has to actuallypurchase the product she says she is willing to buy. We derive a theoretical relation-ship between realization probability and elicited preferences. This allows us to forecastdemand in real purchase settings using inexpensive choice data with small to moderaterealization probabilities. Data from a large-scale field experiment support the theory, anddemonstrate the predictive validity and cost-effectiveness of the proposed method. |
| first_indexed | 2024-09-23T14:35:07Z |
| format | Article |
| id | mit-1721.1/130372 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T14:35:07Z |
| publishDate | 2021 |
| publisher | Institute for Operations Research and the Management Sciences (INFORMS) |
| record_format | dspace |
| spelling | mit-1721.1/1303722022-09-29T09:55:20Z Preference Learning and Demand Forecast Zhang, Juanjuan Sloan School of Management Understanding consumer preferences is important for new product management, but isfamously challenging in the absence of actual sales data. Stated-preferences data are rel-atively cheap but less reliable, whereas revealed-preferences data based on actual choicesare reliable but expensive to obtain prior to product launch. We develop a cost-effectivesolution. We argue that people do not automatically know their preferences, but canmake an effort to acquire such knowledge when given sufficient incentives. The methodwe develop regulates people’s preference-learning incentives using a single parameter,re-alization probability, meaning the probability with which an individual has to actuallypurchase the product she says she is willing to buy. We derive a theoretical relation-ship between realization probability and elicited preferences. This allows us to forecastdemand in real purchase settings using inexpensive choice data with small to moderaterealization probabilities. Data from a large-scale field experiment support the theory, anddemonstrate the predictive validity and cost-effectiveness of the proposed method. 2021-04-05T18:36:40Z 2021-04-05T18:36:40Z 2020-04 2020-05 2021-04-05T14:11:20Z Article http://purl.org/eprint/type/JournalArticle 1526-548X https://hdl.handle.net/1721.1/130372 Cao, Xinyu and Juanjuan Zhang. “Preference Learning and Demand Forecast.” Marketing Science, 40, 1 (April 2020) © 2020 The Author(s) en 10.1287/MKSC.2020.1238 Marketing Science Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute for Operations Research and the Management Sciences (INFORMS) MIT web domain |
| spellingShingle | Zhang, Juanjuan Preference Learning and Demand Forecast |
| title | Preference Learning and Demand Forecast |
| title_full | Preference Learning and Demand Forecast |
| title_fullStr | Preference Learning and Demand Forecast |
| title_full_unstemmed | Preference Learning and Demand Forecast |
| title_short | Preference Learning and Demand Forecast |
| title_sort | preference learning and demand forecast |
| url | https://hdl.handle.net/1721.1/130372 |
| work_keys_str_mv | AT zhangjuanjuan preferencelearninganddemandforecast |