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Modelling the Costs and Benefits of Delayed Product Differentiation

Lee, Hau L., Tang, Christopher S.·1997·Management Science

Abstract

Expanding product variety and high customer service provision are both major challenges for manufacturers to compete in the global market. In addition to many ongoing programs, such as lead-time reduction, redesigning products and processes so as to delay the point of product differentiation is becoming an emerging means to address these challenges. Such a strategy calls for redesigning products and processes so that the stages of the production process in which a common process is used are prolonged. This product/process redesign will defer the point of differentiation (i.e., defer the stage after which the products assume their unique identities). In this paper, we develop a simple model that captures the costs and benefits associated with this redesign strategy. We apply this simple model to analyze some special cases that are motivated by real examples. These special cases enable us to formalize three different product/process redesign approaches (standardization, modular design, and process restructuring) for delaying product differentiation that some companies are beginning to pursue. Finally, we analyze some special theoretical cases that enable us to characterize the optimal point of product differentiation and derive managerial insights.

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Metadata

Authors
Lee, H. L., & Tang, C. S.
Venue
Management Science
Published
1997-01
Volume
43
Issue
1
Pages
40-53
ISSN
  • 0025-1909 (ISSN-L)
  • 1526-5501
OpenAlex
W2009674972
Cited by
605
References
0
FWCI
17.26
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Modelling the Costs and Benefits of Delayed Product Differentiation. https://app.cochat.ai/papers/10.1287/mnsc.43.1.40
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Lee, H. L., & Tang, C. S. (1997). Modelling the Costs and Benefits of Delayed Product Differentiation. Management Science. https://doi.org/10.1287/mnsc.43.1.40

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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.