Agliardi, Elettra
(2009)
The fuzzy value of patent litigation under imprecise information.
Bologna:
Dipartimento di Scienze economiche DSE,
p. 14.
DOI
10.6092/unibo/amsacta/4568.
In: Quaderni - Working Paper DSE
(677).
ISSN 2282-6483.
Full text available as:
Abstract
The vague notion of "probabilistic patents" is formalized through a model which combines real option theory and a fuzzy methodology. The imprecise estimates the patent holder possesses about her future profits, the validity and scope of the patent, the litigation costs, the
court's decision etc. under a regime of imperfect inforcement of property rights are specified modelling uncertainty with fuzzy sets. Such methodology is embedded within a real option approach, where the value of a patent includes the option value of litigation. We study how the value of a patent is affected by the timing and incidence of litigation. The main results are compared
with the empirical findings of previous results.
Abstract
The vague notion of "probabilistic patents" is formalized through a model which combines real option theory and a fuzzy methodology. The imprecise estimates the patent holder possesses about her future profits, the validity and scope of the patent, the litigation costs, the
court's decision etc. under a regime of imperfect inforcement of property rights are specified modelling uncertainty with fuzzy sets. Such methodology is embedded within a real option approach, where the value of a patent includes the option value of litigation. We study how the value of a patent is affected by the timing and incidence of litigation. The main results are compared
with the empirical findings of previous results.
Document type
Monograph
(Working Paper)
Creators
Keywords
probabilistic patents; real options; litigation risk; imprecise information; fuzzy sets
Subjects
ISSN
2282-6483
DOI
Deposit date
09 Feb 2016 10:04
Last modified
09 Feb 2016 10:04
URI
Other metadata
Document type
Monograph
(Working Paper)
Creators
Keywords
probabilistic patents; real options; litigation risk; imprecise information; fuzzy sets
Subjects
ISSN
2282-6483
DOI
Deposit date
09 Feb 2016 10:04
Last modified
09 Feb 2016 10:04
URI
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