Personal Research Database Bibliometric


Title: Technological and Economic Development of Economy



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Title: Technological and Economic Development of Economy


Full Journal Title: Technological and Economic Development of Economy

ISO Abbreviated Title:

JCR Abbreviated Title:

ISSN:


Issues/Year:

Journal Country/Territory:

Language:

Publisher:

Publisher Address:

Subject Categories:

: Impact Factor

? Shan, W., Liu, C. and Yu, J. (2014), Features of the discipline knowledge network: Evidence from China. Technological and Economic Development of Economy, 20 (1), 45-64.

Full Text: 2014\Tec Eco Dev Eco20, 45.pdf

Abstract: Interdisciplinary knowledge exchange constitutes a network with discipline nodes and knowledge flow edges. Using data on Chinese academic literature, the current paper establishes a discipline knowledge network and analyses its structural features. Citation analysis is first used to measure the flow of knowledge between disciplines to build a discipline knowledge network. Subsequently, the features of the network, such as degree distribution, degree correlation, knowledge flow mode and other structure properties, are then analysed based on complex networks and social network theory. The tail of the degree distribution of this discipline knowledge network is in concordance with exponential distribution. The network has also a distinct hierarchical structure. Moreover, the knowledge flow between disciplines is directional. It flows from certain basic and academic disciplines to the applied disciplines.

Keywords: Analyses, Analysis, Bibliometric Analysis, China, Chinese, Citation, Citation Analysis, Complex Network, Complex Networks, Contagion, Correlation, Countries, Data, Discipline Knowledge Network, Disciplines, Distribution, Dynamics, Evidence, Evolution, First, Flow, Hierarchical Structure, Interdisciplinary, Knowledge, Knowledge Flow, Knowledge Network, Literature, Mar, Measure, Mode, Network, Networks, Physics Publications, Properties, Research Collaboration, Science, Social, Social Network, Structure, Theory

? Zavadskas, E.K., Turskis, Z. and Kildiene, S. (2014), State of art surveys of overviews on Mcdm, Madm methods. Technological and Economic Development of Economy, 20 (1), 165-179.

Full Text: 2014\Tec Eco Dev Eco20, 165.pdf

Abstract: Decision-making is primarily a process that involves different actors: people, groups of people, institutions and the state. As a discipline, multi-criteria decision-making has a relatively short history. Since 1950s and 1960s, when foundations of modern multi-criteria decision-making methods have been laid, many researches devoted their time to development of new multi-criteria decision-making models and techniques. In the past decades, researches and development in the field have accelerated and seem to continue growing exponentially. Despite the intensive development worldwide, few attempts have been made to systematically present the theoretical bases and developments of multi-criteria decision-making methods. However, the methodological choices and framework for assessment of decisions are still under discussion. The article describes the situation with reviews of MCDM, MADM methods. Furthermore, there is a need for research to study the strengths and weaknesses of different decision-making methods.

Keywords: Assessment, Classification, Construction, Criteria Decision-Making, Decision Making, Decision-Making, Design, Development, Economics, Field, Framework, Groups, History, Institutions, ISI Web of Science Databases, Management, Mar, Mcdm Methods, Methods, Models, Moora Method, Multi-Criteria Decision Making (Mcdm), Multicriteria, Multiple Criteria, Multiple Objective Decision Making (Modm), Overview, Research, Reviews, Socioeconomic Systems, State, Techniques, Theoretical

Title: Technological Forecasting and Social Change


Full Journal Title: Technological Forecasting and Social Change; Technological Forecasting and Social Change

ISO Abbrev. Title: Technol. Forecast. Soc. Chang.

JCR Abbrev. Title: Technol Forecast Soc

ISSN: 0040-1625

Issues/Year: 9

Language: English

Journal Country/Territory: United States

Publisher: Elsevier Science Inc

Publisher Address: 360 Park Ave South, New York, NY 10010-1710

Subject Categories:

Business: Impact Factor 1.761, 20/77 (2008) SSCI

Planning & Development: Impact Factor 1.761, 4/43 (2008) SSCI

Brusilovsky, B.Y. (1978), Partial and system forecasts in scientometrics. Technological Forecasting and Social Change, 12 (2-3), 193-200.

Full Text: 1960-80\Tec for Soc Cha12, 193.pdf

Abstract: Science itself can be considered as a ‘fuzzy system.’ In attempting to deal with possible laws of scientific development we formulate a simple, partial model and illustrate its use as a means to control the strategy of investments in science.

? Kostoff, R.N. (1994), Quantitative/qualitative federal research impact evaluation practices. Technological Forecasting and Social Change, 45 (2), 189-205.

Full Text: 1994\Tec for Soc Cha45, 189.pdf

Abstract: This paper describes the quantitative and qualitative practice of federal research impact evaluation. Evaluation of research impact is described for three cases: Research selection, where the work has not yet been performed; research review, where work and results are ongoing; and ex-post research assessment, where research has been completed and results can be tracked. Qualitative methods (such as peer review) and quantitative methods (such as cost-benefit analysis and bibliometrics) are described. Although peer review in its broadest sense is the most widely used method in research selection, review, and ex-post assessment, it has its deficiencies, and there is no single method that provides a complete impact evaluation.

Keywords: Analysis, Assessment, Bibliometrics, Evaluation, Impact, Methods, Peer Review, Peer-Review, Quantitative Methods, Research, Research Assessment, Research Impact Evaluation

Porter, A.L. and Detampel, M.J. (1995), Technology opportunities analysis. Technological Forecasting and Social Change, 49 (3), 237-255.

Full Text: 1995\Tec for Soc Cha68, 237.pdf

Abstract: We present an approach to efficiently generate effective intelligence on emerging technologies. This approach draws on monitoring and bibliometrics to mine the wealth of information available in major public electronic databases. The approach uses new software to expedite secondary analyses of database searches on topics of interest. We illustrate the range of information profiles possible by examining research and development (R&D) publications and patents pertaining to electronics assembly and, more specifically, to multichip module development.

Watts, R.J. and Porter, A.L. (1997), Innovation Forecasting. Technological Forecasting and Social Change, 56 (1), 25-47.

Full Text: 2005\Tec for Soc Cha56, 25.pdf

Abstract: Technological forecasting is premised on a certain orderliness of the innovation process. Myriad studies of technological substitution, diffusion, and transfer processes have yielded conceptual models of what matters for successful innovation, but most technological forecasts key on limited empirical measures quite divorced from those innovation process models. We glean a number of concepts from various innovation models, then present an array of bibliometric measures that offer the promise of operationalizing these concepts. Judicious combination of such bibliometrics with other forms of evidence offers an enriched form of technological forecasting we call ‘innovation forecasting.’ This provides a good means to combine technological trends, mapping of technological interdependencies, and competitive intelligence to produce a viable forecast. We illustrate by assessing prospects for ceramic engine technologies.

Keywords: Assessing, Bibliometric, Bibliometrics, Diffusion, Engine, Evidence, Forecasting, Innovation, Mapping, Models, Substitution, Technologies, Trends

Mitchell, G.R. (1999), Global technology policies for economic growth. Technological Forecasting and Social Change, 60 (3), 205-214.

Full Text: 1999\Tec for Soc Cha60, 205.pdf

Abstract: With the end of the Cold War, nations throughout the world are placing ever greater emphasis on economic growth. Over the last 50 years, advances in technology have been the single most important factor in creating growth in many economies, and thus policies to promote technological innovation rank high on the list of priorities for both developed and developing countries. In general, as countries progress up the economic ladder, national R&D intensity, (i.e., R&D/GDP), tends to increase along with per capita income. In addition, nations move through a discernible sequence of technology policies from an initial focus on infrastructure, through a set of actions designed to encourage technology acquisition from more advanced economies, to comprehensive education and research agendas targeted to the creation and development of new technology. In the United States, national technology policy for economic growth focuses on education, building a 21st century infrastructure, and creating a business climate that encourages growth, technological innovation, and risk taking.

Throughout the last 50 years there have been significant changes in the competitive position of nations. In recent years, U.S. corporations have regained some of the competitive leadership they lost in the 1980s. This has been accompanied by significantly increased R&D spending by U.S. industry, particularly in the information and health care related sectors. U.S. industry funding of R&D overtook that from the government in the early 1980s and accounts for almost two-thirds of the national total. (C) 1999 Elsevier Science Inc.

? Coates, V., Farooque, M., Klavans, R., Lapid, K., Linstone, H.A., Pistorius, C. and Porter, A.L. (2001), On the future of technological forecasting. Technological Forecasting and Social Change, 67 (1), 1-17.

Full Text: 2001\Tec for Soc Cha67, 1.pdf

Abstract: Technological forecasting is now poised to respond to the emerging needs of private and public sector organizations in the highly competitive global environment. The history of the subject and its variant forms, including impact assessment, national foresight studies, roadmapping, and competitive technological intelligence, shows how it has responded to changing institutional motivations. Renewed focus on innovation, attention to science-based opportunities, and broad social and political factors will bring renewed attention to technological forecasting in industry, government, and academia. Promising new tools are anticipated, borrowing variously from fields such as political science, computer science, scientometrics, innovation management, and complexity science.

Keywords: Assessment, Forecasting, Foresight, Foresight Activities, Future, History, Impact, Impact Assessment, Innovation, Innovation Management, Intelligence, Management, Roadmapping, Science, Scientometrics, Tools

Kostoff, R.N., Toothman, D.R., Eberhart, H.J. and Humenik, J.A. (2001), Text mining using database tomography and bibliometrics: A review. Technological Forecasting and Social Change, 68 (3), 223-253.

Full Text: 2001\Tec for Soc Cha68, 223.pdf

Abstract: Database tomography (DT) is a textual database analysis system consisting of two major components: (1) algorithms for extracting multiword phrase frequencies and phrase proximities (physical closeness of the multiword technical phrases) from any type of large textual database, to augment (2) interpretative capabilities of the expert human analyst. DT has been used to derive technical intelligence from a variety of textual database sources, most recently the published technical literature as exemplified by the Science Citation Index (SCI) and the Engineering Compendex (EC). Phrase frequency analysis (the occurrence frequency of multiword technical phrases) provides the pervasive technical themes of the topical databases of interest, and phrase proximity analysis provides the relationships among the pervasive technical themes. In the structured published literature databases, bibliometric analysis of the database records supplements the DT results by identifying: the recent most prolific topical area authors; the journals that contain numerous topical area papers; the institutions that produce numerous topical area papers; the keywords specified most frequently by the topical area authors; the authors whose works are cited most frequently in the topical area papers; and the particular papers and journals cited most frequently in the topical area papers. This review paper summarizes: (1) the theory and background development of DT; (2) past published and unpublished literature study results; (3) present application activities; (4) potential expansion to new DT applications. In addition, application of DT to technology forecasting is addressed.

Keywords: Bibliometric, Bibliometric Analysis, Bibliometrics, Citation Analysis, Cluster, Database Tomography, Databases, Information Extraction, Information Retrieval, Innovation, Journals, SCI, Science, System, Taxonomies, Technical Intelligence, Technology, Technology Forecasting, Text Mining

Kostoff, R.N., Antonio del Río, J., Cortés, H.D., Smith, C., Smith, A., Wagner, C., Leydesdorff, L., Karypis, G., Malpohl, G. and Tshiteya, R. (2005), The structure and infrastructure of Mexico’s science and technology. Technological Forecasting and Social Change, 72 (7), 798-814.

Full Text: 2005\Tec for Soc Cha72, 798.pdf

Abstract: the structure and infrastructure of the Mexican technical literature was determined. A representative database of technical articles was extracted from the Science Citation Index for the year 2002, with each article containing at least one author with a Mexican address. Many different manual and statistical clustering methods were used to identify the structure of the technical literature (especially the science and technology core competencies). One of the pervasive technical topics identified from the clustering, thin films research, was analyzed further using bibliometrics, in order to identify the infrastructure of this technology.

Keywords: Bibliometrics, Bibliometrics, Citation, Cluto, Computational Linguistics, Concept Clustering, Core Competencies, Data Compression, Database Tomography, Document Clustering, Factor Analysis, Greedy String Tiling, Leximancer, Mexico, Network Analysis, Programs, Research, Research Evaluation, Roadmaps, Science and Technology, Science Citation Index, Technical Intelligence, Trends

? Porter, A.L. (2005), QTIP: Quick technology intelligence processes. Technological Forecasting and Social Change, 72 (9), 1070-1081.

Full Text: 2005\Tec for Soc Cha72, 1070.pdf

Abstract: Empirical technology analyses need not take months; they can be done in minutes. One can thereby take advantage of wide availability of rich science and technology publication and patent abstract databases to better inform technology management. To do so requires developing templates of innovation indicators to answer standard questions. Then, one can automate routines to generate composite information representations (‘one-pagers’) that address the issues at hand, the way that the target users want. (c) 2005 Elsevier Inc. All rights reserved.

Keywords: Bibliometrics, Innovation, Knowledge Discovery In Databases, Publication, Rapid Technology Analyses, Tech Mining, Technical Intelligence, Technology Foresight, Technology Management, Text Mining

? Bengisu, M. and Nekhili, R. (2006), Forecasting emerging technologies with the aid of science and technology databases. Technological Forecasting and Social Change, 73 (7), 835-844.

Full Text: 2006\Tec for Soc Cha73, 835.pdf

Abstract: Short term forecasting was applied to 20 emerging technologies under the ‘Machine and Materials’ category based on the Vision 2023 foresight study previously conducted for Turkey. This scientometric approach uses the most suitable keywords linked to the technology in question and determines the number of publications and patents in those fields for a given year. Database analysis of publications and patents in the previous 11 years indicates that while the majority of the top 20 technologies identified by the experts are indeed emerging (i.e. The number of research and/or patenting in these technologies is increasing), some of them have not actually attracted too much interest in the science and technology (S&T) community. Forecasts based on S-curves indicate steady growth in some of the selected technologies. There is a high correlation between the number of scientific publications and patents in most of the technologies investigated. The method is proposed as a simple and efficient tool to link national foresight efforts to international S&T activities and to obtain quantitative information for prioritized technologies that could be used for technology management and decision making for research funding and technology investment.

Keywords: Forecasting, S-Curves, Foresight, Emerging Technologies

? Kostoff, R.N. (2006), Systematic acceleration of radical discovery and innovation in science and technology. Technological Forecasting and Social Change, 73 (8), 923-936.

Full Text: 2006\Tec for Soc Cha73, 923.pdf

Abstract: A systematic two-component approach (front-end component, back-end component) to bridging unconnected disciplines and accelerating potentially radical discovery and innovation (based wholly or partially on text mining procedures) is presented. The front-end component has similar objectives to those in the classical literature-based discovery (LBD) approach, although it is different mechanistically and operationally. The front-end component will systematically identify technical disciplines (and their associated leading experts) that are directly or indirectly-related to solving technical problems of high interest. The back-end component is actually a family of back-end techniques, only one of which shares the strictly literature-based analysis of the classical LBD approach. The non-LBD back-end techniques (literature-assisted discovery) make use of the human experts associated with the disparate literatures (disciplines) uncovered in the front-end to generate radical discovery and innovation. Specifically, in the literature-assisted discovery operational mode, these disparate discipline experts could be used as: 1. Recipients of solicitation announcements (BAA, SBIR, MURI, journal Special Issue calls for papers, etc.), 2. Participants in Workshops, Advisory Panels, Review Panels, Roadmaps, and War Games, 3. Points of Contact for Field Science Advisors, Foreign Field Offices, Program Officer site visits, and potential transitions. (c) 2005 Elsevier Inc. All rights reserved.

Keywords: Advisory Panels, Analysis, Bibliometrics, Connections, Database Tomography, Discovery, Disparate Disciplines, Family, Fish-Oil, Information, Information Retrieval, Innovation, Interdisciplinary, Journal, Literature-Assisted Discovery, Literature-Based Discovery, Literatures, Magnesium, Migraine, Multidisciplinary, Papers, Radical Discovery, Radical Innovation, Raynauds, Review Panels, Roadmaps, Roadmaps, Science, Science and Technology, Solicitations, Special Issues, Technology, Text Mining, Text-Mining, Unconnected Disciplines, War Games, Workshops

? Shapira, P. and Youtie, J. (2006), Measures for knowledge-based economic development: Introducing data mining techniques to economic developers in the state of Georgia and the US South. Technological Forecasting and Social Change, 73 (8), 950-965.

Full Text: 2006\Tec for Soc Cha73, 950.pdf

Abstract: the contribution of knowledge to economic growth and competitiveness has attracted increased attention. Publications with a topical focus on areas related to innovation have risen dramatically from 1963 to 2005, but more slowly in local and regional development journals. In contrast to the wide use of aggregate measures of innovation, this paper presents four cases presenting disaggregated knowledge-based approaches into the policy- and decision-making processes of economic developers in the state of Georgia and the US South. The first case uses information obtained from patents and publications to inform traditional out-of-area economic development recruitment strategies in a more knowledge-oriented direction. The second case exemplifies the use of data mining to identify top researchers as part of a strategic state economic development effort. The third case illustrates how local knowledge-based capabilities can be identified in cities not traditionally viewed as innovative. Nanotechnology-related knowledge assets in the southern United States are mapped and assessed in the fourth case. Disaggregated methods used in traditional strategies were most intuitively understood and used, but new knowledge measures were found to encourage local and state economic developers to begin to embrace new paradigms.

Keywords: Economic Development, Innovation, Knowledge Measurement, Data Mining, Bibliometrics

? Daim, T.U., Rueda, G., Martin, H. and Gerdsri, P. (2006), Forecasting emerging technologies: Use of bibliometrics and patent analysis. Technological Forecasting and Social Change, 73 (8), 981-1012.

Full Text: 2006\Tec for Soc Cha73, 981.pdf

Abstract: It is rather difficult to forecast emerging technologies as there is no historical data available. In such cases, the use of bibliometrics and patent analysis have provided useful data. This paper presents the forecasts for three emerging technology areas by integrating the use of bibliometrics and patent analysis into well-known technology forecasting tools such as scenario planning, growth curves and analogies. System dynamics is also used to be able to model the dynamic ecosystem of the technologies and their diffusion. Technologies being forecasted are fuel cell, food safety and optical storage technologies. Results from these three applications help us to validate the proposed methods as appropriate tools to forecast emerging technologies.

? Will, N. (2006), Data-mining: Improvement of university library services. Technological Forecasting and Social Change, 73 (8), 1045-1050.

Full Text: 2006\Tec for Soc Cha73, 1045.pdf

Abstract: Delft University Press has been contacted by the International Water History Association (client) in order to study the relevancy of starting a new journal on a particular topic of interest to its members. This periodical would publish most of the articles relating to this field. Before starting, the client and the publisher want to know if such a journal would find enough authors for the articles and a sufficient audience. How many potential authors exist? What amount of articles in that field exists in other journals? In order to get an answer, the Delft University of Technology Library performed basic bibliometric analyses.

A study of all articles published in 6 relevant existing periodicals, selected by the client, shows that most of the authors were unknown to the client. An analysis of the publications of the members of the association revealed that only one-third has published in the past 10 years, and very few publications were in the client’s field of interest. This would imply that a future periodical could not be supported only by contributions of the members. These preliminary analyses allowed the publisher and the client to get a clearer idea of the possible contribution of its members for a future periodical. The main contributors will have to be recruited from a larger population.

Keywords: Analysis, Bibliometric, Journal, Management, New Journal, Periodicals, Population, Publications

Notes: CCountry

? Kostoff, R.N., Bhattacharya, S. and Pecht, M. (2007), Assessment of China’s and India’s science and technology literature - introduction, background, and approach. Technological Forecasting and Social Change,



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