<p>Shiv Nadar University is a comprehensive, multidisciplinary, research-focused, and student-centric University offering a full range of academic programs at the undergraduate, postgraduate and doctoral level. With state-of-the-art infrastructure, the University comprises of academic wings, sophisticated labs, international standard sports facilities, amphitheaters, auditorium, conference rooms and smart classrooms. The University&rsquo;s goal is to become internationally recognized for the quality of its research and creative endeavors and their applicability to improving quality of life, generating new insights and expanding the boundaries of human knowledge creativity. Committed to excellence in teaching, research and service, the University aims to serve the higher education needs of India and the world beyond.</p>

Shiv Nadar University

In an age when data is regarded as the most essential commodity, organizations are racing to use it for better decision making. The quality of the patent portfolio is an important indicator of technological innovation in an organization and its analysis can reveal several indicators linked to the growth of a company. The advancement of machine learning along with the access to large amounts of patent data has led to a paradigm shift from traditional patent data analysis methodologies to novel approaches. A lot of research has been done in this direction for analysing data on patent citations, patent text, IPC class etc. However, much less has been explored regarding the forecast of patent grant duration and its significance for decision making with an even lower focus on data collected from developing countries. This work is built upon our existing study on patent grant duration prediction by devising a novel methodology of encoding the data using a combination of augmented one-hot encoding and label-encoding. Thereafter, methodologies such as Outlier Detection have been applied to this data to yield an improved result vis-à-vis our baseline results. In addition, we identify some of the important factors which impact the decision on grant duration of patent applications using the raw data from the Indian Patent Office. © 2020 Elsevier Ltd

General Management

(SME) School of Management and Entrepreneurship

World Patent Information

Novel mixed-encoding for forecasting patent grant duration

Strategic patenting in the last decades has been studied extensively to reflect on the trends in patenting motives of firms though mostly for large firms and from developed countries. Studies point to the numerous emerging roles of patents. How firms apply their patenting strategy, is still a fragmented area as major variation across sectors exists. Small- and medium-sized firms, rarely studied in detail have been taken up for study by exploring the pharmaceutical sector where patents are integral to success in business. A survey cum secondary data-based study generates insights on firms' ranking of patenting motives and the impact of firms' characteristics on these motives. Protection of invention is reaffirmed as the primary motive, though licensing motive has slipped in rank. Further, inter-firm differences through regressions show that the number of granted patents and firm age positively and significantly impact firm's patenting motives but firm size has no impact. Copyright © 2021 Inderscience Enterprises Ltd.

World University root node

International Journal of Intellectual Property Management

Patenting motives of pharmaceutical firms: A perspective on changing role of patents and firms' strategy in business

<p>Purpose: Patents as one of the important components of intellectual capital are emerging as a new source for mining insights on open innovation (OI) practice of the organizations. Their role in value creation through collaboration and the inter-firm differences is yet to be explored in depth. Design/methodology/approach: To achieve the aim, survey data is analyzed to rank OI practices (collaboration) of the firms, while patent data are analyzed to carry out descriptive and bivariate analysis to study the inter-firm differences in collaboration. Findings: The survey findings highlight mergers and acquisitions (M&amp;A) and patent pooling as the top two preferred modes of OI, while from patent data M&amp;A has emerged as a predominant OI practice for mainly nonresident firms. At the firm level characteristics, out of firm age, number of granted patents and firm size, firm age has been found to be somewhat significant in few cases of OI practices. Research limitations/implications: It provides an alternative source, in this case patent data to study open innovation capabilities of firms in India. There is contribution to the patent value theory from profit motive to deriving strategic decisions on collaboration. Practical implications: The managerial implications of this study lie in realizing granted patents as important business tools for seeking collaboration, tracing competitive intelligence and the geography of innovation of the firms' competitors. Originality/value: The dataset of granted patents at the Indian Patent office (2005–2017), the sample of pharmaceutical firms drawn from this list of patents, patent data– based OI insights and the use of multiple imputation technique to missing data for meaningful insights are some of the unique aspects of this paper. © 2020, Emerald Publishing Limited.</p>

Fulltext

Journal of Intellectual Capital

Modes of collaboration in open innovation practice of pharmaceutical firms in India: the analysis of survey and patent data

Research on pharmaceuticals has mainly focused on the needs of developed countries while the scenario in developing countries is unclear. This industry is knowledge-intensive and unusually sensitive to intellectual property rights (IPRs). Patents play very important role in their business and this entails good management practices by the firms from various aspects of patent management. Two dimensions viz. commercialization of patents and renewal of patents are studied in this paper. There is dearth of in-depth research studies on these dimensions of patent management in India. A random sample of 300 granted pharmaceutical patents for patent renewal and another sample of 300 patents selected through purposive sampling for patent commercialization have been drawn from the population of granted pharmaceutical patents by the Indian Patent Office between 2005-06 and 2013-14. The information on working of patents has been taken from Form-27 submitted by the patent assignees of the selected patents. Some of the main findings are: a weak but positive and significant correlation between patent renewal & commercialization, blocking motive is the top most barrier to commercialization, direct contact with the partners is the chief mode of commercialization, no potential for technology is the main reason for non-renewal of patents, and enhancement of reputation is the main reason for renewal. © 2017, Hiroshima University. All rights reserved.

Journal of Intellectual Property Rights

Commercialization and renewal aspects of patent management in Indian pharmaceutical industry

Managing patents is a core issue in the intellectual property management (IPM) of the firms. It entails two important activities: the patenting of new innovations and the renewal of patents. With the research on renewal data gaining momentum, this paper tries to study the renewal of patents in the pharma sector in India. Adopting a unique approach of studying both active and ceased patents of non-resident applicants in India, with the aid of descriptive methods and statistical tools as SPSS following trends, has been found. Business firms are the dominant patentees and single inventorship an emerging trend in India. While renewal patterns are quite applicant category specific, grant period is independent of the applicant category. In case of the patents category (ceased or active), maintenance duration is independent of the number of inventors but effective life of the patents varies with category of patents. The higher propensity to patent and maintenance show linkage with specific technology fields and the portfolio size. Copyright © 2015 Inderscience Enterprises Ltd.