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Cited by 239

The DOI matches its OpenAlex record; 5 of the 5 references it cites were found in a registry or an index.

Practices that Support Team Learning and Their Impact on Speed to Market and New Product Success

Gary S. Lynn, Richard B. Skov, Kate D. Abel·1999·Journal of Product Innovation Management

Abstract

Competition is fierce today. Businesses are feeling extreme pressure to innovate and do so quickly. If they take too long in bringing a product to market or make a mistake along the way, they can be preempted by a faster moving competitor. One technique gaining popularity to help companies compete is establishing learning teams—teams that create and use knowledge rapidly and effectively. But how do teams learn? By studying the learning practices of 95 new product teams, we have uncovered several factors that improve a new product team's ability to learn, innovate faster, and be more successful. These factors include thoroughly reviewing project information, having stable project goals, and following a rigorous new product development process.

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OpenAlex · 10.1016/s0737-6782(98)00071-x

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Metadata

Authors
Lynn, G. S., Skov, R. B., & Abel, K. D.
Venue
Journal of Product Innovation Management
Publisher
Wiley
Published
1999-09-01
Volume
16
Issue
5
Pages
439-454
ISSN
0737-6782 (ISSN-L)
OpenAlex
W2151956647
Cited by
239
References
5
FWCI
17.77
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Practices that Support Team Learning and Their Impact on Speed to Market and New Product Success. https://app.cochat.ai/papers/10.1016/s0737-6782(98)00071-x
The paper
Lynn, G. S., Skov, R. B., & Abel, K. D. (1999). Practices that Support Team Learning and Their Impact on Speed to Market and New Product Success. Journal of Product Innovation Management. https://doi.org/10.1016/s0737-6782(98)00071-x

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.