Jacobian Spillovers in Environmental Technological Proximity: The Role of Mahalanobis Index on European Patents within the Triad
In the world of rapidly developing Science and Technology (S&T), with increasing volumes of S&T-related data and greater interdisciplinary and collaborative research, technology mining (TM) helps to acquire intelligence about emerging trends and future S&T developments. The task is becoming crucial not only for high-tech startups and large organizations, but also for venture capitalists and other companies, which make decisions about S&T investments. Governments and Public Research Institutions are also among the main stakeholders and potential users of TM to set up R&D priorities, plans and programs according to the current and future state of S&T development. Term clusters built by TM and bibliometric tools based on co-occurrence of authors’ keywords or terms processed from titles and abstracts of scientific documents combine totally different types of objects: research fields, major problems and challenges, methods, inventions, products, technologies and etc. Specific expertise in the field may allow a researcher to identify key objects of the study. However, objects themselves and their frequency dynamics over the time period alone do not fully indicate S&T developments and emerging trends in the area. In order to improve the process of the identification of emerging S&T trends and developments, the paper focuses on dynamic term clustering and suggests a systemic approach to combine TM, bibliometrics, NLP and semantic analysis as part of the unified analytical framework. The approach proposed utilizes existing clustering methods and tools along with the analysis of term linguistic dependencies in order to study changes of objects over the time along with their semantic meanings.
In this study, we investigate how to identify and extract patent-related information from Facebook, the largest online social network. In the first step, we identified a list of trustworthy sources we started search from. Then, we developed algorithms for extracting and filtering information, and based on them software tool that is able to identify and deliver a patent, the Facebook post where it is mentioned and news / blog article which discuss it. We did a pilot test and collected more than 50 examples of articles (and Facebook posts) that add value to the patent they refer to. We classified collected articles and discussed how they can be used. Finally, we outlined where developed tool can be applied.
In light of globalisation of knowledge generation, Science and Technology have opened up previously distinct borderlines now favoring overlapping if not merged fields. Hence innovation becomes more complex by bundling different technological solutions in new products, processes, services and business models, which stem from different scientific and technological roots. Thus spillovers are an essential precondition towards the establishment of new interdisciplinary fields of knowledge, science and technology. The paper reviews and synthesizes literature on spillovers, introduces a typology of spillovers and a taxonomy of spillover channels, estimates the economic impact of spillovers. Special attention is paid to assessing recipient’s capabilities to absorb new knowledge thus gaining advantages for own development. The author concludes that knowledge spillovers have a positive impact on performance of a recipient (company, country or region) as long as it possesses sufficient absorptive capacity. Spillovers might under certain circumstances lead to strengthening competition between knowledge recipients at the cost of the place of origin. Nonetheless the latter still is in a position to use instruments of legal protection of own knowledge (under certain circumstances), build on the existing competences and capacities and invest in the next frontier of knowledge and technology in certain fields and moreover create a boom in the field of knowledge and technology generated using marketing instruments extensively.
Tech Mining, a special form of “Big Data” analytics, aims to generate Competitive Technical Intelligence (CTI) using bibliometric and text-mining software (e.g., VantagePoint, TDA) as well as other analytical & visualization applications for analyses of Science, Technology & Innovation (ST&I) information resources. The goal of the conference is to ENGAGE cross-disciplinary networks of analysts, software specialists, researchers, policymakers, and managers toADVANCE the use of textual information in multiple science, technology, and business development fields. The conference program will address key CHALLENGES in:
DataSourcing, preparing, and interpreting data sources including patents, publications, webscraping, and other novel data sources
Text-mining tools and methodsBest practices in software-based topic modeling, clumping, association rules, term manipulation, text manipulation, etc. Visualization
Applied researchFuture-Oriented Technology Analysis (FTA) Intelligence gathering to support decision-making in the private sector (e.g., Management of Technology)
This conference is intended for researchers and students across multiple fields, especially Scientometrics, Public Policy, Management of Technology and Information Science.
The significance of biotechnologies for solving global problems and making social and economic progress is recognized in many countries, including Russia. Managing this field requires up-to-date and reliable information about technological trends and the emergence and diffusion of innovations. This paper examines the possibility of applying a patent-based methodological approach to the study of biotechnologies in Russia, and assesses its explanatory potential.
We develop a new distance-based test of localized knowledge spillovers that embeds the concept of control patents. Using microgeographic data, we identify localization distance for each technology class while allowing for spillovers across geographic units. We revisit the debate between Thompson and Fox-Kean (2005a, 2005b) and Henderson, Jaffe, and Trajtenberg (2005) on the existence of localized knowledge spillovers and find solid evidence supporting localization even when using finely grained controls. Unless biases induced by imperfect matching between citing and control patents due to unobserved heterogeneity are extremely large, our distance-based test detects localization for the majority of technology classes.
The paper studies a problem of optimal insurer’s choice of a risk-sharing policy in a dynamic risk model, so-called Cramer-Lundberg process, over infinite time interval. Additional constraints are imposed on residual risks of insureds: on mean value or with probability one. An optimal control problem of minimizing a functional of the form of variation coefficient is solved. We show that: in the first case the optimum is achieved at stop loss insurance policies, in the second case the optimal insurance is a combination of stop loss and deductible policies. It is proved that the obtained results can be easily applied to problems with other optimization criteria: maximization of long-run utility and minimization of probability of a deviation from mean trajectory.