Approaches for Identifying Consumer Preferences for the Design of Technology Products: A Case Study of Residential Solar Panels
This paper investigates ways to obtain consumer preferences for technology products to help designers identify the key attributes that contribute to a product's market success. A case study of residential photovoltaic panels is performed in the context of the California, USA, market within the...
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| Format: | Article |
| Language: | en_US |
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ASME International
2014
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| Online Access: | http://hdl.handle.net/1721.1/86159 https://orcid.org/0000-0002-7776-3423 https://orcid.org/0000-0003-2365-1378 |
| _version_ | 1811092252461629440 |
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| author | Chen, Heidi Qianyi Honda, Tomonori Yang, Maria |
| author2 | Massachusetts Institute of Technology. Department of Mechanical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Mechanical Engineering Chen, Heidi Qianyi Honda, Tomonori Yang, Maria |
| author_sort | Chen, Heidi Qianyi |
| collection | MIT |
| description | This paper investigates ways to obtain consumer preferences for technology products to help designers identify the key attributes that contribute to a product's market success. A case study of residential photovoltaic panels is performed in the context of the California, USA, market within the 2007–2011 time span. First, interviews are conducted with solar panel installers to gain a better understanding of the solar industry. Second, a revealed preference method is implemented using actual market data and technical specifications to extract preferences. The approach is explored with three machine learning methods: Artificial neural networks (ANN), Random Forest decision trees, and Gradient Boosted regression. Finally, a stated preference self-explicated survey is conducted, and the results using the two methods compared. Three common critical attributes are identified from a pool of 34 technical attributes: power warranty, panel efficiency, and time on market. From the survey, additional nontechnical attributes are identified: panel manufacturer's reputation, name recognition, and aesthetics. The work shows that a combination of revealed and stated preference methods may be valuable for identifying both technical and nontechnical attributes to guide design priorities. |
| first_indexed | 2024-09-23T15:15:29Z |
| format | Article |
| id | mit-1721.1/86159 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T15:15:29Z |
| publishDate | 2014 |
| publisher | ASME International |
| record_format | dspace |
| spelling | mit-1721.1/861592022-10-02T01:41:10Z Approaches for Identifying Consumer Preferences for the Design of Technology Products: A Case Study of Residential Solar Panels Chen, Heidi Qianyi Honda, Tomonori Yang, Maria Massachusetts Institute of Technology. Department of Mechanical Engineering Massachusetts Institute of Technology. Engineering Systems Division Yang, Maria Chen, Heidi Qianyi Honda, Tomonori Yang, Maria This paper investigates ways to obtain consumer preferences for technology products to help designers identify the key attributes that contribute to a product's market success. A case study of residential photovoltaic panels is performed in the context of the California, USA, market within the 2007–2011 time span. First, interviews are conducted with solar panel installers to gain a better understanding of the solar industry. Second, a revealed preference method is implemented using actual market data and technical specifications to extract preferences. The approach is explored with three machine learning methods: Artificial neural networks (ANN), Random Forest decision trees, and Gradient Boosted regression. Finally, a stated preference self-explicated survey is conducted, and the results using the two methods compared. Three common critical attributes are identified from a pool of 34 technical attributes: power warranty, panel efficiency, and time on market. From the survey, additional nontechnical attributes are identified: panel manufacturer's reputation, name recognition, and aesthetics. The work shows that a combination of revealed and stated preference methods may be valuable for identifying both technical and nontechnical attributes to guide design priorities. Center for Scalable and Integrated Nanomanufacturing 2014-04-14T17:33:51Z 2014-04-14T17:33:51Z 2013-05 2013-04 Article http://purl.org/eprint/type/JournalArticle 1050-0472 http://hdl.handle.net/1721.1/86159 Chen, Heidi Q., Tomonori Honda, and Maria C. Yang. “Approaches for Identifying Consumer Preferences for the Design of Technology Products: A Case Study of Residential Solar Panels.” Journal of Mechanical Design 135, no. 6 (May 9, 2013): 061007. https://orcid.org/0000-0002-7776-3423 https://orcid.org/0000-0003-2365-1378 en_US http://dx.doi.org/10.1115/1.4024232 Journal of Mechanical Design Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf ASME International Prof. Yang via Angie Locknar |
| spellingShingle | Chen, Heidi Qianyi Honda, Tomonori Yang, Maria Approaches for Identifying Consumer Preferences for the Design of Technology Products: A Case Study of Residential Solar Panels |
| title | Approaches for Identifying Consumer Preferences for the Design of Technology Products: A Case Study of Residential Solar Panels |
| title_full | Approaches for Identifying Consumer Preferences for the Design of Technology Products: A Case Study of Residential Solar Panels |
| title_fullStr | Approaches for Identifying Consumer Preferences for the Design of Technology Products: A Case Study of Residential Solar Panels |
| title_full_unstemmed | Approaches for Identifying Consumer Preferences for the Design of Technology Products: A Case Study of Residential Solar Panels |
| title_short | Approaches for Identifying Consumer Preferences for the Design of Technology Products: A Case Study of Residential Solar Panels |
| title_sort | approaches for identifying consumer preferences for the design of technology products a case study of residential solar panels |
| url | http://hdl.handle.net/1721.1/86159 https://orcid.org/0000-0002-7776-3423 https://orcid.org/0000-0003-2365-1378 |
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