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Intellectual property regulation, and software piracy, a predictive model

D'Rosario, Michael 2016, Intellectual property regulation, and software piracy, a predictive model, International journal of strategic decision sciences (IJSDS), vol. 7, no. 4, pp. 21-34, doi: 10.4018/IJSDS.2016100102.

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Title Intellectual property regulation, and software piracy, a predictive model
Author(s) D'Rosario, Michael
Journal name International journal of strategic decision sciences (IJSDS)
Volume number 7
Issue number 4
Start page 21
End page 34
Total pages 14
Publisher IGI Global
Place of publication Hershey, Pa.
Publication date 2016-10
ISSN 1947-8569
1947-8577
Keyword(s) artificial neural network
intellectual property
software piracy
TRIPS
Summary In recent years, a number of studies have considered the impact of IPRs on software piracy, specifically TRIPS and more recently U.S. USTR 301 reporting, pursuant to the Trade Act. The work of Shadlen (2005) supports the assertion that a number of recent IPR reforms directly influence rates of copyright infringement. Shadlen (2005) is a significant study into the impact of the IPRs such as TRIPS, Out of Cycle reviews and USTR 301 reporting on software piracy. The study identified a number of key IPR reforms and sought to determine the impact of IPR reform differentials on observed piracy rates. The current study extends upon Shadlen (2005), comparing the pooled panel model framework to an alternative model of prediction, a backward propagation, multilayer perceptron network model. The analysis conducted herein focuses specifically on ASEAN member countries. The study employs the Garson (1991) and Goh (1995) methods of independent variable analysis to offer further insight into relative importance of the IPR reform variables.
Language eng
DOI 10.4018/IJSDS.2016100102
Field of Research 1801 Law
Socio Economic Objective 0 Not Applicable
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2016, IGI Global
Persistent URL http://hdl.handle.net/10536/DRO/DU:30093001

Document type: Journal Article
Collection: Department of Finance
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