The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Sources of Power: Their Impact on Intrachannel Conflict
Abstract
The sources of power that auto manufacturers use to obtain control over their dealer network are shown to have a significant impact on the level of conflict that dealers have with their manufacturers. Coercive sources tend to increase the level of intrachannel conflict whereas noncoercive sources tend to decrease it. Auto manufacturers need to be cognizant of this fact in order to use intelligently their available sources of power.
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Citations
Cites
The norm of reciprocity: A preliminary statement
Gouldner, A. W. (1960) · American Sociological Review · doi:10.2307/2092623 · Cited by 12,001
Cited by
The commitment-trust theory of relationship marketing
Morgan, R. M., & Hunt, S. D. (1994) · Journal of Marketing · doi:10.1177/002224299405800302 · Cited by 22,355
Determinants of Long-Term Orientation in Buyer-Seller Relationships
Ganesan, S. (1994) · Journal of Marketing · doi:10.1177/002224299405800201 · Cited by 6,741
Power and control in international retail franchising – Evidence from theory and practice
Quinn, B., & Doherty, A. M. (2000) · International Marketing Review · doi:10.1108/02651330010339897 · Cited by 169
Control and support in an international franchise network
Quinn, B. (1999) · International Marketing Review · doi:10.1108/02651339910281884 · Cited by 73
Metadata
- Authors
- Lusch, R. F.
- Venue
- Journal of Marketing Research
- Publisher
- SAGE Publications
- Published
- 1976-11
- Volume
- 13
- Issue
- 4
- Pages
- 382-390
- ISSN
- 0022-2437 (ISSN-L)
- 1547-7193
- OpenAlex
- W2313027996
- Cited by
- 464
- References
- 1
- FWCI
- 13.69
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
