Isbn: 9783319818061 - anticipating future innovation pathways through large data analysis (11 risultati)

Lingua: Inglese
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Lingua: Inglese
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Serie: Libro 39 di 63 - Innovation, Technology, and Knowledge Management
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Condizione: New. pp. 380 Softcover reprint of the original 1st ed. 2016 edition NO-PA16APR2015-KAP.
Altre immaginiLingua: Inglese
Editore: Springer, 2018
Serie: Libro 39 di 63 - Innovation, Technology, and Knowledge Management
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Taschenbuch. Condizione: Neu. Anticipating Future Innovation Pathways Through Large Data Analysis | Tugrul U. Daim (u. a.) | Taschenbuch | Innovation, Technology, and Knowledge Management | xviii | Englisch | 2018 | Springer | EAN 9783319818061 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Lingua: Inglese
Editore: Springer, 2018
Serie: Libro 39 di 63 - Innovation, Technology, and Knowledge Management
- Brossura
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book aims to identify promising future developmental opportunities and applications for Tech Mining. Specifically, the enclosed contributions will pursue three converging themes:The increasing availability of electronic text data resources relating to Science, Technology and Innovation (ST&I).The multiple methods that are able to treat this data effectively and incorporate means to tap into human expertise and interests.Translating those analyses to provide useful intelligence on likely future developments of particular emerging S&T targets.Tech Mining can be defined as text analyses of ST&I information resources to generate Competitive Technical Intelligence (CTI). It combines bibliometrics and advanced text analytic, drawing on specialized knowledge pertaining to ST&I. Tech Mining may also be viewed as a special form of 'Big Data' analytics because it searches on a target emerging technology (or key organization) of interest in global databases. One then downloads, typically, thousands of field-structured text records (usually abstracts), and analyses those for useful CTI. Forecasting Innovation Pathways (FIP) is a methodology drawing on Tech Mining plus additional steps to elicit stakeholder and expert knowledge to link recent ST&I activity to likely future development.A decade ago, we demeaned Management of Technology (MOT) as somewhat self-satisfied and ignorant. Most technology managers relied overwhelmingly on casual human judgment, largely oblivious of the potential of empirical analyses to inform R&D management and science policy. CTI, Tech Mining, and FIP are changing that. The accumulation of Tech Mining research over the past decade offers a rich resource of means to get at emerging technology developments and organizational networks to date. Efforts to bridge from those recent histories ofdevelopment to project likely FIP, however, prove considerably harder. One focus of this volume is to extend the repertoire of information resources; that will enrich FIP.Featuring cases of novel approaches and applications of Tech Mining and FIP, this volume will present frontier advances in ST&I text analytics that will be of interest to students, researchers, practitioners, scholars and policy makers in the fields of R&D planning, technology management, science policy and innovation strategy.…

Lingua: Inglese
Editore: Springer, 2018
Serie: Libro 39 di 63 - Innovation, Technology, and Knowledge Management
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Lingua: Inglese
Editore: Springer, 2018
Serie: Libro 39 di 63 - Innovation, Technology, and Knowledge Management
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Lingua: Inglese
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Serie: Libro 39 di 63 - Innovation, Technology, and Knowledge Management
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book aims to identify promising future developmental opportunities and applications for Tech Mining. Specifically, the enclosed contributions will pursue three converging themes:The increasing availability of electronic text data resources relating to Science, Technology and Innovation (ST&I).The multiple methods that are able to treat this data effectively and incorporate means to tap into human expertise and interests.Translating those analyses to provide useful intelligence on likely future developments of particular emerging S&T targets.Tech Mining can be defined as text analyses of ST&I information resources to generate Competitive Technical Intelligence (CTI). It combines bibliometrics and advanced text analytic, drawing on specialized knowledge pertaining to ST&I. Tech Mining may also be viewed as a special form of 'Big Data' analytics because it searches on a target emerging technology (or key organization) of interest in global databases. One then downloads, typically, thousands of field-structured text records (usually abstracts), and analyses those for useful CTI. Forecasting Innovation Pathways (FIP) is a methodology drawing on Tech Mining plus additional steps to elicit stakeholder and expert knowledge to link recent ST&I activity to likely future development.A decade ago, we demeaned Management of Technology (MOT) as somewhat self-satisfied and ignorant. Most technology managers relied overwhelmingly on casual human judgment, largely oblivious of the potential of empirical analyses to inform R&D management and science policy. CTI, Tech Mining, and FIP are changing that. The accumulation of Tech Mining research over the past decade offers a rich resource of means to get at emerging technology developments and organizational networks to date. Efforts to bridge from those recent histories of development to project likely FIP, however, prove considerably harder. One focus of this volume is to extend the repertoire of information resources; that will enrich FIP.Featuring cases of novel approaches and applications of Tech Mining and FIP, this volume will present frontier advances in ST&I text analytics that will be of interest to students, researchers, practitioners, scholars and policy makers in the fields of R&D planning, technology management, science policy and innovation strategy. 380 pp. Englisch.…

Anticipating Future Innovation Pathways Through Large Data Analysis
Daim, Tugrul U.|Chiavetta, Denise|Porter, Alan L.|Saritas, Ozcan
Lingua: Inglese
Editore: Springer International Publishing, 2018
Serie: Libro 39 di 63 - Innovation, Technology, and Knowledge Management
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Da: moluna, Greven, Germaniamoluna
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Identifies promising future developmental opportunities and applications for Tech MiningPresents frontier advances in Science, Technology & Innovation (ST&I) text analytics and other approachesCombines multiple data resources and.…

Lingua: Inglese
Editore: Springer, 2018
Serie: Libro 39 di 63 - Innovation, Technology, and Knowledge Management
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New. Print on Demand pp. 380.

Lingua: Inglese
Editore: Springer, 2018
Serie: Libro 39 di 63 - Innovation, Technology, and Knowledge Management
- Brossura
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND pp. 380.

Lingua: Inglese
Editore: Springer, Springer Mai 2018, 2018
Serie: Libro 39 di 63 - Innovation, Technology, and Knowledge Management
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book aims to identify promising future developmental opportunities and applications for Tech Mining. Specifically, the enclosed contributions will pursue three converging themes:The increasing availability of electronic text data resources relating to Science, Technology and Innovation (ST&I).The multiple methods that are able to treat this data effectively and incorporate means to tap into human expertise and interests.Translating those analyses to provide useful intelligence on likely future developments of particular emerging S&T targets.Tech Mining can be defined as text analyses of ST&I information resources to generate Competitive Technical Intelligence (CTI). It combines bibliometrics and advanced text analytic, drawing on specialized knowledge pertaining to ST&I. Tech Mining may also be viewed as a special form of 'Big Data' analytics because it searches on a target emerging technology (or key organization) of interest in global databases. One then downloads, typically, thousands of field-structured text records (usually abstracts), and analyses those for useful CTI. Forecasting Innovation Pathways (FIP) is a methodology drawing on Tech Mining plus additional steps to elicit stakeholder and expert knowledge to link recent ST&I activity to likely future development.A decade ago, we demeaned Management of Technology (MOT) as somewhat self-satisfied and ignorant. Most technology managers relied overwhelmingly on casual human judgment, largely oblivious of the potential of empirical analyses to inform R&D management and science policy. CTI, Tech Mining, and FIP are changing that. The accumulation of Tech Mining research over the past decade offers a rich resource of means to get at emerging technology developments and organizational networks to date. Efforts to bridge from those recent histories ofdevelopment to project likely FIP, however, prove considerably harder. One focus of this volume is to extend the repertoire of information resources; that will enrich FIP.Featuring cases of novel approaches and applications of Tech Mining and FIP, this volume will present frontier advances in ST&I text analytics that will be of interest to students, researchers, practitioners, scholars and policy makers in the fields of R&D planning, technology management, science policy and innovation strategy.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 380 pp. Englisch.…