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Cited by 264

The DOI matches its Crossref record; 62 of the 62 references it cites were found in a registry or an index.

Towards a Theory of Competitive Progression: Evidence from High‐Tech Manufacturing

Rosenzweig, Eve D., Roth, Aleda V.·2004·Production and Operations Management

Abstract

This study replicates and extends Ferdows and De Meyers' observed ‘sand cone’ model of cumulative competitive capabilities by means of Roth's related competitive progression theory (CPT). Using path analysis, we model and test the relationships among the generic competitive capability constructs of conformance quality, delivery reliability, volume flexibility, and low cost as predicted by CPT. Our results, drawn from a sample of high‐tech manufacturers, provide further evidence that on average, these four capabilities are acquired both cumulatively and in that sequence. We also find that each generic capability increases operational know‐how and reduces non‐value‐added directly and/or indirectly through the enhancement of successive capabilities in the progression, which in turn improves profitability. The paper contributes a theoretical rationale for the observed sand cone effect, describes how the competitive progression acts to influence accelerated organizational learning over an innovation cycle, and offers evidence that combinative capabilities have strategic value for high‐tech manufacturers.

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Crossref · 10.1111/j.1937-5956.2004.tb00223.x

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Metadata

Authors
Rosenzweig, E. D., & Roth, A. V.
Venue
Production and Operations Management
Published
2004-12
Volume
13
Issue
4
Pages
354-368
ISSN
  • 1059-1478 (ISSN-L)
  • 1937-5956
OpenAlex
W2122965070
Cited by
264
References
62
FWCI
33.72
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Towards a Theory of Competitive Progression: Evidence from High‐Tech Manufacturing. https://app.cochat.ai/papers/10.1111/j.1937-5956.2004.tb00223.x
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Rosenzweig, E. D., & Roth, A. V. (2004). Towards a Theory of Competitive Progression: Evidence from High‐Tech Manufacturing. Production and Operations Management. https://doi.org/10.1111/j.1937-5956.2004.tb00223.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.