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Cited by 591

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A Structural Analysis of the Effectiveness of Buying Firms' Strategies to Improve Supplier Performance

Krause, Daniel R., Scannell, Thomas V., Calantone, Roger J.·2000·Decision Sciences

Abstract

Many manufacturing firms have increased the amount of component parts and services they outsource, while refocusing on their core capabilities. Outsourcing parts and services to independent, external suppliers means that suppliers' performance is increasingly critical to the long‐term success of these buying firms. Buying firms are increasingly using disparate supplier development strategies to improve supplier performance including supplier assessment, providing incentives for improved performance, instigating competition among suppliers, and direct involvement of the buying firm's personnel with suppliers through activities such as training of suppliers' personnel. Using resource‐based theory, internalization theory, and structural equation modeling, we examine the impact of these supplier development strategies on performance. We conclude that direct involvement activities, where the buying firm internalizes a significant amount of the supplier development effort, play a critical role in performance improvement.

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Crossref · 10.1111/j.1540-5915.2000.tb00923.x

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Metadata

Authors
Krause, D. R., Scannell, T. V., & Calantone, R. J.
Venue
Decision Sciences
Publisher
Wiley
Published
2000-03
Volume
31
Issue
1
Pages
33-55
ISSN
  • 0011-7315 (ISSN-L)
  • 1540-5915
OpenAlex
W2068917698
Cited by
591
References
4
FWCI
12.81
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A Structural Analysis of the Effectiveness of Buying Firms' Strategies to Improve Supplier Performance. https://app.cochat.ai/papers/10.1111/j.1540-5915.2000.tb00923.x
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Krause, D. R., Scannell, T. V., & Calantone, R. J. (2000). A Structural Analysis of the Effectiveness of Buying Firms' Strategies to Improve Supplier Performance. Decision Sciences. https://doi.org/10.1111/j.1540-5915.2000.tb00923.x

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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.