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The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

The Effects of Business and Political Ties on Firm Performance: Evidence from China

Sheng, Shibin, Zhou, Kevin Zheng, Li, Julie Juan·2011·Journal of Marketing

Abstract

Despite increasing attention to the role of social ties in emerging economies, few studies have explicitly distinguished the differential roles of business versus political ties. Drawing on relational governance and institutional theories, this study offers a contingent view of business and political ties in China. The findings from a survey of 241 Chinese firms indicate that business ties have a stronger positive effect on performance than political ties, and both effects depend on institutional and market environments. Business ties are more beneficial when legal enforcement is inefficient and technology is changing rapidly, whereas political ties lead to greater performance when general government support is weak and technological turbulence is low. These findings indicate that firms operating in China should be cautious in their use of business and political ties and adapt their tie utilization to changing institutional and market environments.

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Metadata

Authors
Sheng, S., Zhou, K. Z., & Li, J. J.
Venue
Journal of Marketing
Published
2011-01
Volume
75
Issue
1
Pages
1-15
ISSN
  • 0022-2429 (ISSN-L)
  • 1547-7185
OpenAlex
W4239116780
Cited by
942
References
7
FWCI
40.30
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Effects of Business and Political Ties on Firm Performance: Evidence from China. https://app.cochat.ai/papers/10.1509/jm.75.1.1
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Sheng, S., Zhou, K. Z., & Li, J. J. (2011). The Effects of Business and Political Ties on Firm Performance: Evidence from China. Journal of Marketing. https://doi.org/10.1509/jm.75.1.1

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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.