Next-generation consumer innovation search: Identifying early-stage need-solution pairs on the web
© 2020 The Author(s) All innovations consist of a need paired with a responsive solution - a need-solution pair (von Hippel and von Krogh 2016). Today, technical advances in machine learning techniques for natural language understanding, such as semantic word space models and semantic network analyt...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier BV
2021
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| Online Access: | https://hdl.handle.net/1721.1/134143 |
| _version_ | 1811093519194914816 |
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| author | von Hippel, Eric Kaulartz, Sandro |
| author_facet | von Hippel, Eric Kaulartz, Sandro |
| author_sort | von Hippel, Eric |
| collection | MIT |
| description | © 2020 The Author(s) All innovations consist of a need paired with a responsive solution - a need-solution pair (von Hippel and von Krogh 2016). Today, technical advances in machine learning techniques for natural language understanding, such as semantic word space models and semantic network analytics, have made it practical to capture descriptions of early-stage, need-solution pairs mentioned anywhere in the open, textual content of the Internet. Producers - and anyone - can now thus look for user innovations posted on the web that may involve either known or newly defined needs coupled to new solutions that are gaining traction. This is important because, as is now understood, users, rather than producers, tend to pioneer functionally new products and services for which both the need and the solution may be novel. In this paper, we demonstrate via a case study both the practicality and the value of searching for early-stage need-solution pairs via machine learning methods and assessing the likely general interest in each usergenerated innovation by also identifying the trends in posting and query frequencies related to it. The new need-solution pair search method we describe and test here can, we claim, serve as a very valuable complement to traditional market research techniques and practices. |
| first_indexed | 2024-09-23T15:46:23Z |
| format | Article |
| id | mit-1721.1/134143 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T15:46:23Z |
| publishDate | 2021 |
| publisher | Elsevier BV |
| record_format | dspace |
| spelling | mit-1721.1/1341432021-10-28T03:19:30Z Next-generation consumer innovation search: Identifying early-stage need-solution pairs on the web von Hippel, Eric Kaulartz, Sandro © 2020 The Author(s) All innovations consist of a need paired with a responsive solution - a need-solution pair (von Hippel and von Krogh 2016). Today, technical advances in machine learning techniques for natural language understanding, such as semantic word space models and semantic network analytics, have made it practical to capture descriptions of early-stage, need-solution pairs mentioned anywhere in the open, textual content of the Internet. Producers - and anyone - can now thus look for user innovations posted on the web that may involve either known or newly defined needs coupled to new solutions that are gaining traction. This is important because, as is now understood, users, rather than producers, tend to pioneer functionally new products and services for which both the need and the solution may be novel. In this paper, we demonstrate via a case study both the practicality and the value of searching for early-stage need-solution pairs via machine learning methods and assessing the likely general interest in each usergenerated innovation by also identifying the trends in posting and query frequencies related to it. The new need-solution pair search method we describe and test here can, we claim, serve as a very valuable complement to traditional market research techniques and practices. 2021-10-27T19:58:19Z 2021-10-27T19:58:19Z 2021 2021-03-22T15:31:01Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/134143 en 10.1016/J.RESPOL.2020.104056 Research Policy Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/pdf Elsevier BV Elsevier |
| spellingShingle | von Hippel, Eric Kaulartz, Sandro Next-generation consumer innovation search: Identifying early-stage need-solution pairs on the web |
| title | Next-generation consumer innovation search: Identifying early-stage need-solution pairs on the web |
| title_full | Next-generation consumer innovation search: Identifying early-stage need-solution pairs on the web |
| title_fullStr | Next-generation consumer innovation search: Identifying early-stage need-solution pairs on the web |
| title_full_unstemmed | Next-generation consumer innovation search: Identifying early-stage need-solution pairs on the web |
| title_short | Next-generation consumer innovation search: Identifying early-stage need-solution pairs on the web |
| title_sort | next generation consumer innovation search identifying early stage need solution pairs on the web |
| url | https://hdl.handle.net/1721.1/134143 |
| work_keys_str_mv | AT vonhippeleric nextgenerationconsumerinnovationsearchidentifyingearlystageneedsolutionpairsontheweb AT kaulartzsandro nextgenerationconsumerinnovationsearchidentifyingearlystageneedsolutionpairsontheweb |