EconPapers    
Economics at your fingertips  
 

Next-generation consumer innovation search: Identifying early-stage need-solution pairs on the web

Eric von Hippel and Sandro Kaulartz

Research Policy, 2021, vol. 50, issue 8

Abstract: 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.

Keywords: Problem-solving; Need-solution pairs; User innovation; Consumer innovation; Household sector innovation (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0048733320301347
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:respol:v:50:y:2021:i:8:s0048733320301347

DOI: 10.1016/j.respol.2020.104056

Access Statistics for this article

Research Policy is currently edited by M. Bell, B. Martin, W.E. Steinmueller, A. Arora, M. Callon, M. Kenney, S. Kuhlmann, Keun Lee and F. Murray

More articles in Research Policy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:respol:v:50:y:2021:i:8:s0048733320301347