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The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Learning to evolve: A review of contemporary lean thinking

Hines, Peter, Holweg, Matthias, Rich, Nick·2004·International Journal of Operations & Production Management

Abstract

The application of lean thinking has made a significant impact both in academic and industrial circles over the last decade. Fostered by a rapid spread into many other industry sectors beyond the automotive industry, there has been a significant development and “localisation” of the lean concept. Despite successful “lean” applications in a range of settings however, the lean approach has been criticised on many accounts, such as the lack of human integration or its limited applicability outside high‐volume repetitive manufacturing environments. The resulting lack of definition has led to confusion and fuzzy boundaries with other management concepts. Summarising the lean evolution, this paper comments on approaches that have sought to address some of the earlier gaps in lean thinking. Linking the evolution of lean thinking to the contingency and learning organisation schools of thought, the objective of this paper is to provide a framework for understanding the evolution of lean not only as a concept, but also its implementation within an organisation, and point out areas for future research.

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Metadata

Authors
Hines, P., Holweg, M., & Rich, N.
Venue
International Journal of Operations & Production Management
Publisher
Emerald
Published
2004-10-01
Volume
24
Issue
10
Pages
994-1011
ISSN
0144-3577 (ISSN-L)
OpenAlex
W2141592893
Cited by
1,664
References
2
FWCI
33.50
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Learning to evolve: A review of contemporary lean thinking. https://app.cochat.ai/papers/10.1108/01443570410558049
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Hines, P., Holweg, M., & Rich, N. (2004). Learning to evolve: A review of contemporary lean thinking. International Journal of Operations & Production Management. https://doi.org/10.1108/01443570410558049

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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.