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Cited by 1,415

The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

The Effects of Organizational Differences and Trust on the Effectiveness of Selling Partner Relationships

Smith, J. Brock, Barclay, Donald W.·1997·Journal of Marketing
DOI 10.1177/002224299706100102
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Abstract

Selling alliances that are formed to cooperatively develop and maintain customer relationships are among the new organizational forms that marketing managers utilize for competitive advantage. To be successful, these alliances require sales representatives from allied organizations to work effectively as selling partners. The authors develop a trust-based model of effective selling partner relationships and test it in the context of the computer industry. Partial Least Squares analysis of 103 dyadic relationships found that organizational differences were modest predictors of three dimensions of mutual perceived trustworthiness, which in turn differentially affected three trusting behaviors. Trusting behaviors were found to have a somewhat greater effect on perceived task performance than on mutual satisfaction, whereas dimensions of trustworthiness had both direct and indirect effects on satisfaction. The authors discuss the managerial and theoretical implications of these results.

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Citations

Cites

Show all 12 references

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Cited by

Metadata

Authors
Smith, J. B., & Barclay, D. W.
Venue
Journal of Marketing
Publisher
SAGE Publications
Published
1997-01
Volume
61
Issue
1
Pages
3-21
ISSN
  • 0022-2429 (ISSN-L)
  • 1547-7185
DOI
10.1177/002224299706100102
OpenAlex
W2043880827
Cited by
1,415
References
12
FWCI
31.40
Type
journal article
Language
en
Open access
closed
Licence
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)

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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.