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Cited by 713

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FROM EXPERIENCE: Developing New Product Concepts Via the Lead User Method: A Case Study in a “Low‐Tech” Field

Open access
Cornelius Herstatt, Eric von Hippel·1992·Journal of Product Innovation Management

Abstract

Conventional market research methods do not work well in the instance of many industrial goods and services, and yet, accurate understanding of user need is essential for successful product innovation. Cornelius Herstatt and Eric von Hippel report on a successful field application of a “lead user” method for developing concepts for needed new products. This method is built around the idea that the richest understanding of needed new products is held by just a few users. It is possible to identify these “lead users” and then draw them into a process of joint development of new product concepts with manufacturer personnel. In the application described, the lead user method was found to be much faster than traditional ways of identifying promising new product concepts as well as less costly. It also was judged to provide better outcomes by the firm participating in the case. The article includes practical detail on the steps that were used to implement the method at Hilti AG, a leading manufacturer of products and materials used in construction.

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OpenAlex · 10.1016/0737-6782(92)90031-7

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Metadata

Authors
Herstatt, C., & von Hippel, E.
Venue
Journal of Product Innovation Management
Publisher
Wiley
Published
1992-09-01
Volume
9
Issue
3
Pages
213-221
ISSN
0737-6782 (ISSN-L)
OpenAlex
W2166043165
Cited by
713
References
1
FWCI
16.68
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: FROM EXPERIENCE: Developing New Product Concepts Via the Lead User Method: A Case Study in a “Low‐Tech” Field. https://app.cochat.ai/papers/10.1016/0737-6782(92)90031-7
The paper
Herstatt, C., & von Hippel, E. (1992). FROM EXPERIENCE: Developing New Product Concepts Via the Lead User Method: A Case Study in a “Low‐Tech” Field. Journal of Product Innovation Management. https://doi.org/10.1016/0737-6782(92)90031-7

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.