Nils C. Newman

Patent overlay mapping: Visualizing technological distance

This paper presents a new global patent map that represents all technological categories and a method to locate patent data of individual organizations and technological fields on the global map. This overlay map technique may support competitive intelligence and policy decision making. The global patent map is based on similarities in citing‐to‐cited relationships between categories of the International Patent Classification (IPC) of European Patent Office (EPO) patents from 2000 to 2006. This patent data set, extracted from the PATSTAT database, includes 760,000 patent records in 466 IPC‐based categories. We compare the global patent maps derived from this categorization to related efforts of other global patent maps. The paper overlays the nanotechnology‐related patenting activities of two companies and two different nanotechnology subfields on the global patent map. The exercise shows the potential of patent overlay maps to visualize technological areas and potentially support decision making. Furthermore, this study shows that IPC categories that are similar to one another based on citing‐to‐cited patterns (and thus close in the global patent map) are not necessarily in the same hierarchical IPC branch, thereby revealing new relationships between technologies that are classified as pertaining to different (and sometimes distant) subject areas in the IPC scheme.

Clustering scientific documents with topic modeling

Topic modeling is a type of statistical model for discovering the latent “topics” that occur in a collection of documents through machine learning. Currently, latent Dirichlet allocation (LDA) is a popular and common modeling approach. In this paper, we investigate methods, including LDA and its extensions, for separating a set of scientific publications into several clusters. To evaluate the results, we generate a collection of documents that contain academic papers from several different fields and see whether papers in the same field will be clustered together. We explore potential scientometric applications of such text analysis capabilities.

INNOVATION FORECASTING USING BIBLIOMETRICS

Counting research and development publication and patent activity can help generate competitive technical intelligence. Combining such counts with content analyses oriented toward “innovation success factors” can greatly enrich the intelligence value. The authors offer a framework of three types of technological innovation indicators—life cycle, contextual influences, and value chain/market prospects. They illustrate how these aid a case analysis of the application of ceramics to tank and automotive engines. The case demonstrates how use of these types of indicators can efficiently and effectively scan broad domains of the competitive landscape, and justify strategic decisions.

International high tech competitiveness: does China rank number 1?

This paper compares three selected indicator series that address national, technology-based competitiveness. The ‘traditional’ Georgia Tech High Tech Indicators (HTI) have been comparing 33 nations with respect to current and future prospects at exporting high tech products since the late 1980s. Those indicators blend expert opinion with statistical time series data. Second, we introduce ‘statistics only’ HTI, a revised formulation that addresses knowledge-based service export capabilities as well as high tech products, biennially. Third, the World Economic Forum annually generates its Global Competitiveness Index (GCI), treating 125 countries. The traditional HTI reported China supplanting the USA as the top-ranking economy as of 2007. That has generated some controversy. In striking contrast, the 2006–2007 GCI reported China as No. 54. This paper explores the bases for these differences. To a substantial degree, they derive from whether one normalises based on a nations size. We conclude that these indicator series provide multiple perspectives that complement each other. In the case of China, all of these indicators point to continuing dramatic increase in technology-based economic competitiveness. If not yet, then within not too many years, the USA will likely be supplanted by China as the leading technology-based economy.

Patent Profiling for Competitive Advantage

This chapter introduces text mining of patents in support of technology management. Technological innovation models point to empirical measures that relate to prospects for successful commercialisation. We present an 8-step process for analysing entire patent sets on a given topic to generate such ‘innovation indicators.’l We illustrate for the case of fuel cells.

Differences over a decade: high tech capabilities and competitive performance of 28 nations

People often look to technology-based advancement as the key to achieving and maintaining economic competitiveness. This belief often resonates through national policy at the highest levels. Does investing in high technology really provide a competitive advantage? Since 1986, researchers at Georgia Techs Technology Policy and Assessment Center have been systematically monitoring national high technology-based industrial competitiveness to help address this question. This paper reports on a longitudinal assessment of high technology capability and resulting competitive standing across 28 countries from 1993 through 2003. Copyright , Beech Tree Publishing.

Distance and velocity measures: using citations to determine breadth and speed of research impact

Research that integrates the social and natural sciences is vital to address many societal challenges, yet is difficult to arrange, conduct, and disseminate. This paper compares diffusion of the research supported by a unique U.S. National Science Foundation program on Human and Social Dynamics (“HSD”) with a matched group of heavily cited papers. We offer a measure of the distance of cites between the Web of Science Category (“WoSC”) in which a publication appears and the WoSC of the journal citing it, and find that HSD publications are cited more distantly than are comparison publications. We provide another measure—citation velocity—finding that HSD publications are cited with similar lag times as are the comparison papers. These basic citation distance and velocity measures enrich analyses of research knowledge diffusion patterns.

High Tech Indicators: Assessing the Competitiveness of Selected European Countries

Western European nations, along with the USA and Japan, have been recognised as the worlds most competitive economies. Eastern European nations have generally been considered to lag. This paper explores whether these descriptions remain accurate and the prospects for change over the coming decade. The Georgia Tech ‘High Tech Indicators’ (HTI) contribute to the US National Science Foundation (NSF) Science & Engineering Indicators. We cover 33 highly developed and rapidly industrialising countries. Our model of technological competitiveness contains four components – National Orientation, Socioeconomic Infrastructure, Technological Infrastructure, and Productive Capacity – contributing to ‘Technological Standing.’ We present indicator values, derived from survey and statistical panel data, for 13 European nations (plus the USA as a benchmark), for 1993–2005, and draw inferences about future high tech competitiveness. We see limited technological progress of the Eastern European nations. European prospects appear somewhat uncertain given the dramatic competitive thrusts from Asia.

Technology opportunities analysis for Malaysia

Summary form only given. Management of national research and development balances scientific freedom to explore areas of greatest excitement with economic payoff potential. To the extent that government funds R&D with taxpayer monies, the focusing of these efforts on domains of national priority may be in order. This analysis examines how Malaysian R&D fits with the national industrial activity, especially that directed toward exports.

A measure of staying power: Is the persistence of emergent concepts more significantly influenced by technical domain or scale?

This study advances a four-part indicator for technical emergence. While doing so it focuses on a particular class of emergent concepts—those which display the ability to repeatedly maintain an emergent status over multiple time periods. The authors refer to this quality as staying power and argue that those concepts which maintain this ability are deserving of greater attention. The case study we consider consists of 15 subdatatsets within the dye-sensitized solar cell framework. In this study the authors consider the impact technical domain and scale have on the behavior of persistently emergent concepts and test which of these has a greater influence.