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Cited by 278

The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.

Some Economic Considerations in the Intellectual Property Protection of Software

Dam, Kenneth W.·1995·The Journal of Legal Studies

Abstract

Intellectual property has frequently had to confront the issue of how to protect new technologies. The rise of software as a major industry is one such new challenge. An economic approach to the protection of software adds to the already extensive legal analysis. On the one hand, existing copyright and patent law provides a sound basis for an economically efficient system of protection. Copyright law deals with the appropriability problem without creating significant monopoly or rent-seeking problems. Copyright law also provides a sound basis for preserving a balance between innovation today and innovation tomorrow. These conclusions depend crucially, however, on maintaining the distinctions between attachment and replacement and between transformative and substitutive uses. Software-related patents are economically sound. However, as actually administered, the system may generate too many invalid patents. Sui generis protection is less desirable than copyright and patent protection.

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Metadata

Authors
Dam, K. W.
Venue
The Journal of Legal Studies
Published
1995-06
Volume
24
Issue
2
Pages
321-377
ISSN
  • 0047-2530 (ISSN-L)
  • 1537-5366
OpenAlex
W2015115039
Cited by
278
References
16
FWCI
158.76
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Some Economic Considerations in the Intellectual Property Protection of Software. https://app.cochat.ai/papers/10.1086/467962
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Dam, K. W. (1995). Some Economic Considerations in the Intellectual Property Protection of Software. The Journal of Legal Studies. https://doi.org/10.1086/467962

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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.