Patent Valuation

Patents and patent portfolios are valuable assets. Companies need a conceptual structure to assess the value of their patent portfolio. This paper develops a practical and reproducible framework that can support scholars and practitioners to leverage the value of patents and to extract all possible strategic information from patent portfolio. The patent assessment process aims at comparing and contrasting the management of patents to the company’s technologic and innovative strategy. The framework employs determinants of patent value that are elicited from patent databases, such as claims, citations, and market coverage, and that are expressed in terms of judgments achieved by interviewing involved managers, such as strategic relevance and economic relevance. The paper examines the main methodological issues in assessing patent portfolio value then, it describes the characteristics of the framework; subsequently, it illustrates the implementation of the proposed framework into two companies which operate in the aerospace and defense sector. The two implementations show that the framework can be used for strategic planning and strategic technology management.

In the modern days business is centred on technological development, with patents recognised as valuable assets. These are transferable in nature; hence it is necessary to determine their fair market price, thus valuation. Worldwide several methods exist for determination of financial worth of patents. After a review of relevant literature like serious books, journals, newspaper articles, whitepapers, and websites, it has been found that there are plenty of methods of patent valuation. These methods are either outcome of academic research or they are proprietary assets of specialist firms involved in patent valuation. Some of these models are adopted for valuation, while others remain stand-alone. The existence of such large number of methods is like a jungle, where the practitioners and academic researchers find themselves lost. In this paper an attempt has been made to map this jungle, through presenting a classification of the existing methods. The review of a large number of relevant documents given confidence, that the main approaches have been captured. The existing methods are classified into two broad groups' viz. praxis models and academic models, indicating their advantages and disadvantages.

Traditional Knowledge (TK) is a central component for the daily life of millions of people in developing countries, including India where access to “modern” health care services and medicine is limited due to economic and cultural constraints. Some TK is codified, that is, formalized in some way (eg Ayurveda) however, a great part of it is non-codified, such as, “folk”, “tribal” or “indigenous” medicine which is based on traditional beliefs, norms and practices accumulated during centuries old experiences of trial and error, and passed to successive generations through oral tradition. The protection under Intellectual Property Rights (IPRs) of traditional and indigenous knowledge has received growing attention since the adoption of the Convention on Biological Diversity (CBD) in 1992. However, the concept of Protection in case of TK is understood and interpreted in different ways by different groups; hence there exist two schools of thought-as per one belief protection essentially means to exclude the unauthorized use by third parties; whereas others regard protection as a tool to preserve traditional knowledge from uses that may erode it or negatively affect the life or culture of the communities who are in possession of such knowledge and have developed / applied it.

PLEASE CITE AS Noto La Diega G (2016) Patents on Computer-Related Inventions in India. Intel Prop Rights. S1:009. doi: 10.4172/2375-4516.1000S1-009

In India, sec. 3(k) of the Patents Act 1970 clearly excludes the patentability of computer programmes per se. For many years, the regime of computer-implemented inventions has been unclear, until the Controller General of Patents, Designs and Trade Marks (the India Intellectual Property Office) issued its Guidelines on the examination of computer-related inventions. Notably, this gave rise the civil society’s protests; indeed, there was the fear that the government was surreptisciously allowing the patentability of computer programmes per se. Therefore, the guidelines have been withdrawn and recently a new version has been published. It openly reaffirms the exclusion of the software patents and introduces a three-step test to determine the applicability of sec. 3(k) of the Patents Act to computer-related inventions. This opinion focuses the new guidance, by placing it in the context of the leading role of India in the technological and social developments revolving around the Internet of Things.

In the changing environment of the 21st century, universities should develop very innovative ecosystems by doing right investments on human capital, research and development, buildings, laboratories, dorms, and other facilities on the campus while decreasing their costs and expenses in order to increase scientific and technological oriented innovations and outputs. For that reason, most of them are looking toward Big Data Management (BDM), which is a very new and dynamic subject to conduct properly and to make right decisions at the universities.Data analytics and data mining have increased and attracted the attention of most of the leaders, managers, administrators, researchers, and even educators who try to make massive data-related investments and decisions. More importantly, since the funding of higher education has become important issues for most of the governments and higher education management, the importance of BDM will increase in higher education much more than ever before. However, not all the universities are so successful in managing their small or medium-sized data.In this research, how universities are investing by improving their data was analyzed in three different universities in Istanbul.More strategically, how data analytics and mining can make changes and transformation higher education institutions by investing right resources under the promise of Big Data Management was critically studied. In this study, the impacts of big data mining and management on higher education institutions’ sustainable funding, financing, planning, success, research and development, and innovation were critically studied. By taking into account the perceptions and the experiences of the experienced experts (6), faculty members (12), managers (4), and technical people (12), who were charged in using data analytics and mining at two state and one private universities, the investment of the universities had analyzed in order to understand critically the effects of the BDM. In the study, the phenomenological analysis was used by asking thirty-one research questions in the semi-structured interviews. While taking into account the observations of the researchers, the collected data of this study were systematically studied in data analysis software-program NVivo 10. The results showed that a few number of the investments had correctly done by using data mining and data analysis. As the participants had mentioned that the data would not have done anything if the higher education management had not taken into account and applied.So, according to the participants (75%), the university management understanding and policies should be changed in order to take in consideration the results of the big data.Even though a great amount of data had produced through the systems of the universities, the analysis, the segmentation, and the selected attention of the data had become dependent on the higher education management.The participants (28%), who were active in planning, funding, and investing, agreed that the investments done according to the results of the big data had better educational, financial, socio-economic, cultural, technological,environmental, and even individual benefits and outcomes. In conclusion, although a little data mining and analysis has properly used in making right investments, the universities are highly convinced on the positive effects of the BDM in their short-term and long-term investments in order to increase their impacts.

The analysis of intellectual property value plays an important role in managerial economic and business strategy, in that it helps estimate the value of the innovative and productive capacity of R&D. The issue of valuing intellectual property has often received considerable critical attention. Studies on the contribution of intellectual assets to the competitive advantage of firms have encouraged researchers to reflect on the effectual value of intellectual property and, consequently, their measurement. Most of the contributions on intellectual property value assessment can be allocated to four different categories: a) those that use the measure of intellectual property value as a dependent variable; b) those that adopt particular sampling strategies; c) those that consider the number and type of explanatory variables, i.e. the potential value determinants d) those that suggest subjective evaluations of intellectual property value through interviews, and measurements from perceptive observations. The aim of this special issue is to collect innovative, original and explorative contributions from different disciplines on intellectual property value encompassing varied viewpoints and considering different scales. Relevant research areas include those concerning science, technology, innovation, scientometrics, R&D, etc.; investigations on patent life-cycle phases, from invention to commercialisation; and works at country, regional or firm-specific levels. In the theme of patent value, there are some areas that have been insufficently explored and that could be furtherly investigated. Future research should concentrate on the following: • Advancing qualitative measurements to be easily applicable by firms that cannot access patent information databases • Concentrating on the definition of further indicators that refer to patent intelligence and quantify the strategic-technologic positioning of patents • Measuring the business opportunities of the technology or, more generally, the potential value of the patented technology • Determining assessment approaches able to account for the commercial value of intellectual property and the commercial performance of products and technologies • Proposing measurement tools based on intellectual property financial quantities through intangible valuations or firm analyses, based on managers' perceptions • Assessing the strategic positioning of intellectual property by means of intelligence instruments or analysis of the competitive landscape