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Social Network Analysis and the Diffusion of the Strict Liability Rule for Manufacturing Defects, 1963-87


Robert C. Bird


University of Connecticut - Department of Marketing

Donald J. Smythe


California Western School of Law

February 22, 2011

Law & Social Inquiry, Forthcoming

Abstract:     
This article reports the results of a study that uses social network analysis to compare the persuasiveness of legal precedents in the diffusion of the strict liability rule for manufacturing defects. This new study tests which legal precedents were most influential and also whether certain state judicial variables influenced the diffusion process. The results are striking. The federal circuit regions appear to define an important reference group in the diffusion process and social network effects dominate economic and political variables. In addition, the de facto separation of powers in the enactment of new state legislation appears to influence courts’ propensities to adopt the strict liability rule. When the executive and legislative branches were controlled by the same political party – regardless of whether it was the Republican or Democratic Party – state courts were more inclined to adopt the strict liability rule.

Number of Pages in PDF File: 47

Keywords: Social Network Analysis, Legal Precedents, Judicial Discretion, Manufacturing Defects, Products Liability

JEL Classification: K10, K13, K20

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Date posted: February 23, 2011 ; Last revised: March 4, 2011

Suggested Citation

Bird, Robert C. and Smythe, Donald J., Social Network Analysis and the Diffusion of the Strict Liability Rule for Manufacturing Defects, 1963-87 (February 22, 2011). Law & Social Inquiry, Forthcoming. Available at SSRN: http://ssrn.com/abstract=1767505

Contact Information

Robert C. Bird
University of Connecticut - Department of Marketing ( email )
Storrs, CT 06269
United States
860-486-6136 (Phone)
Donald J. Smythe (Contact Author)
California Western School of Law ( email )
225 Cedar Street
San Diego, CA 92101
United States
Feedback to SSRN (Beta)


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