scispace - formally typeset

Assessing the impact of patent attributes on the value of discrete and complex innovations

Reads0
Chats0
TLDR
In this paper , the authors assess the degree to which patent social value can be connected to the private value of patents across discrete and complex innovation, and they have used a variety of logit regression model for the impact assessment analysis.
Abstract
This study assesses the degree to which the social value of patents can be connected to the private value of patents across discrete and complex innovation. The underlying theory suggests that the social value of cumulative patents is less related to the private value of patents. We use the patents applied between 1995 and 2002 and granted on or before December 2018 from the Indian Patent Office (IPO). Here, the patent renewal information is utilised as a proxy for the private value of the patent. We have used a variety of logit regression model for the impact assessment analysis. The results reveal that the technology classification (i.e., discrete vs. complex innovations) plays an important role in patent value assessment, and some technologies are significantly different than the others even within the two broader classifications. Moreover, the non-resident patents in India are more likely to have a higher value than the resident patents. According to the conclusions of this study, only a few technologies from the discrete and complex innovation categories have some private value. There is no evidence that patent social value indicators are less useful in complicated technical classes than in discrete ones.

read more

Content maybe subject to copyright    Report

References
More filters
Journal ArticleDOI

Appropriating the Returns from Industrial Research and Development

TL;DR: A patent confers, in theory, perfect appropriability (monopoly of the invention) for a limited time in return for a public benefit as mentioned in this paper, however, the benefits consumers derive from an innovation, however, are increased if competitors can imitate and improve on the innovation to ensure its availability on favorable terms.
Journal ArticleDOI

Regression Models for Ordinal Data

TL;DR: In this article, a general class of regression models for ordinal data is developed and discussed, which utilize the ordinal nature of the data by describing various modes of stochastic ordering and this eliminates the need for assigning scores or otherwise assuming cardinality instead of ordinality.
Journal ArticleDOI

Generalized ordered logit/partial proportional odds models for ordinal dependent variables

TL;DR: Gologit2 as discussed by the authors is a generalized ordered logit model inspired by Vincent Fu's gologit routine (Stata Technical Bulletin Reprints 8: 160-164).
Journal ArticleDOI

Citation Frequency and the Value of Patented Innovation

TL;DR: In this article, economic value estimates were obtained on 962 inventions made in the United States and Germany and on which German patent renewal fees were paid to full-term expiration in 1995.
Journal ArticleDOI

Assessing proportionality in the proportional odds model for ordinal logistic regression.

TL;DR: The proportional odds model for ordinal logistic regression provides a useful extension of the binary logistic model to situations where the response variable takes on values in a set of ordered categories.