Published February 21, 2025 | Version v1
Journal article Open

Calculating punitive damage multiplier in intellectual property cases: An empirical study and the enhanced model

  • 1. Shanghai University of Political Science and Law
  • 2. Fudan University
  • 3. University of Chicago

Description

The application of punitive damages in intellectual property cases in China has encountered notable deficiencies within the judicial context. These deficiencies, including a limited range of applicability, frequent recourse to statutory damages, difficulties in ascertaining the appropriate damages base, and a marked reliance on subjective factors in calculating multipliers, undermine judicial consistency and fairness. In this study, we conducted a comprehensive quantitative analysis by selecting 79 pertinent judgments from a dataset of 3,478 intellectual property rulings. Initially, we developed a multiple linear regression model to assess punitive damages. Upon encountering negative estimated coefficients, we improved the model to a Beta Generalized Linear Model. The efficacy of the new model was validated through an improved R-squared value compared to the original model and by analyzing an additional 45 cases. Both models highlight the scope of infringement and the reputation of intellectual property assets as critical variables. They suggest that wider infringements lead to greater economic penalties and emphasize the significant market value and potential financial losses of intellectual property. Significantly, this study represents a pioneering initiative in China, establishing a model to assist in the legal determination of punitive damages in IP cases.

Data availability

All relevant data are within the paper and its Supporting Information files.

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journal.pone.0308447.pdf

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Additional details

Identifiers

DOI
10.1371/journal.pone.0308447
Other
oai:uchicago.tind.io:14679

Funding

China Law Society
Research on the Multiplicative Standards for Punitive Damages in Chinese Intellectual Property Law

UChicago Information

Division(s)
Physical Sciences Division
Department(s)
Statistics