Future-Oriented Technology Assessment : A Manager's Guide with Case Applications

• Autore: Yalcin Haydar
• Pubblicazione: Newark : , : John Wiley & Sons, Incorporated, , 2024; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (435 pages)
• Altri autori: DaimTugrul U
• Nota di contenuto: Cover -- Title Page -- Copyright -- Contents -- A Note from the Series Editor -- About the Editors -- List of Contributors -- Preface -- Chapter 1 Technology Assessment: Smart City Development Initiatives and Issues -- 1.1 Introduction -- 1.2 Evolution of the Smart City -- 1.3 Need for Smart Cities -- 1.3.1 Global Smart Cities Initiatives -- 1.3.2 Role of Technology in Smart City Development -- 1.3.3 Technology Adoption and Development of Smart Cities -- 1.3.4 Efforts Toward Overcoming Technological Challenges -- 1.3.5 Future of Smart Cities with Technology Adoption -- 1.4 Conclusion -- 1.5 Implication and Future Research -- References -- Chapter 2 Technology Assessment: Process Optimization Services in the Cement Industry -- 2.1 Introduction -- 2.2 Research Design -- 2.2.1 Model Development -- 2.2.1.1 Hierarchical Model: Client's Point of View -- 2.2.1.2 Hierarchical Model: Staff's Point of View -- 2.2.1.3 Comparative Judgment of the Variables -- 2.2.2 Supporting Qualitative Data -- 2.2.3 Data Analysis -- 2.3 Results of the Survey -- 2.3.1 Simplified External Survey -- 2.3.2 Complete External Survey -- 2.3.3 Internal Survey -- 2.4 Discussion -- 2.5 Conclusions -- References -- Chapter 3 Technology Assessment: Energy Storage Technologies -- 3.1 Introduction -- 3.2 Literature Review -- 3.2.1 Renewable Energy Sources -- 3.2.2 Assessment of the Energy Storage Technologies -- 3.3 Methodology -- 3.3.1 Hierarchical Decision Model -- 3.3.2 HDM Steps -- 3.3.2.1 Creating Model -- 3.3.2.2 Pairwise Comparison -- 3.3.2.3 Inconsistency and Disagreement -- 3.3.3 Technology Development Envelop (TDE) -- 3.4 Model Development -- 3.4.1 Criteria/Perspectives -- 3.4.1.1 Social Perspective -- 3.4.1.2 Technical Perspective -- 3.4.1.3 Economic Perspective -- 3.4.1.4 Environmental Perspective -- 3.4.1.5 Political Perspective -- 3.4.2 Alternative Technologies. ; 3.4.2.1 Flywheels -- 3.4.2.2 Liquid Air Energy Storage Technologies -- 3.4.2.3 Thermoelectric Energy Storage -- 3.4.2.4 Underground Pumped Hydro -- 3.4.2.5 Isothermal Compressed Air Energy Storage (I‐CAES) -- 3.5 Results Analysis and Discussion -- 3.5.1 Model Validation -- 3.5.2 Model Quantification -- 3.5.2.1 Results of the Perspectives and Criteria -- 3.5.3 TDE Diagram -- 3.6 Conclusion -- Acknowledgments -- References -- Chapter 4 Technology Forecasting: A Secure Solar Power Generation Forecasting Framework for Recurrent Neural Networks -- 4.1 Introduction -- 4.2 Proposed Secure Solar Power Generation Forecasting Framework -- 4.3 Deep Learning Techniques -- 4.3.1 Recurrent Neural Networks (RNN) -- 4.3.2 Long Short‐term Memory (LSTM) -- 4.3.3 Bidirectional LSTM -- 4.3.4 Gated Recurrent Units (GRU) -- 4.3.5 LSTM and BiLSTM with Attention -- 4.4 Adversarial Attack and Mitigation Methods -- 4.4.1 Adversarial Attack -- 4.4.2 Adversarial Training -- 4.5 Dataset Description, Feature Selection, and Performance Metrics -- 4.5.1 Dataset Description -- 4.5.2 Feature Selection -- 4.5.3 Performance Metrics -- 4.6 Experiments -- 4.6.1 RNN‐based Solar Power Generation Forecasting -- 4.6.2 Adversarial Machine Learning Attack Against RNN‐based Models -- 4.6.3 RNN‐based Solar Power Generation Forecasting with Adversarial Machine Learning Training -- 4.7 Results and Discussion -- 4.8 Summary -- References -- Chapter 5 Technology Intelligence: Transformative Trends and Technological Synergies for the Smart Grid -- 5.1 Introduction -- 5.2 Cluster Analysis -- 5.3 Authors Productivity -- 5.4 Co‐word Analysis -- 5.5 Discussion -- References -- Chapter 6 Technology Intelligence: Cryptocurrencies and Emerging Technologies -- 6.1 Introduction -- 6.2 Data and Method -- 6.2.1 Cluster Analysis -- 6.2.2 Burst Analysis and Emerging Topics. ; 6.2.3 Intertopic Distance Maps and Topic Detection on Cryptocurrency Research Landscape -- 6.2.4 Topic 1: Cryptocurrency Universe and Blockchain Technology -- 6.2.5 Topic 2: Blockchain‐Based Supply Chain Management and Security Optimization -- 6.2.6 Topic 3: Emerging Trends in Internet Science and Security -- 6.2.7 Topic 4: Innovations in Financial Technology and Blockchain Solutions -- 6.2.8 Topic 5: Advanced Systems Analysis and Governance in Current Issues -- 6.3 Discussion -- References -- Chapter 7 Technology Intelligence: Geothermal Energy -- 7.1 Introduction -- 7.2 Impacts of Geothermal Energy -- 7.2.1 Economic Impacts of Geothermal Energy -- 7.2.2 Environmental Impacts of Geothermal Energy -- 7.2.3 Technological Impacts of Geothermal Energy -- 7.2.4 Green Sustainable Science Technology -- 7.2.5 Energy Fuels -- 7.2.6 Thermodynamics -- 7.2.7 Regulation -- 7.2.8 Critical Global Gap of Geothermal Energy -- 7.3 Methodology -- 7.3.1 Data Collection -- 7.3.2 Extraction of Life Cycle of Geothermal Energy Technologies Based on the Number of Cumulative Patents (Foster Curve Model) -- 7.3.3 Mann‐Kendall Test -- 7.3.4 Sen's Slope Test -- 7.3.5 Data Preprocessing -- 7.3.6 Latent Dirichlet Allocation (LDA) Topic Modeling -- 7.3.7 Principal Component Analysis (PCA) -- 7.3.8 LDAvis Software Package -- 7.3.9 Text Similarity Calculation -- 7.3.10 Association Rule Mining -- 7.3.11 Social Network Analysis -- 7.4 Results of Data Analysis -- 7.4.1 Data Collection Initial Results -- 7.4.2 Mann‐Kendall Test Result -- 7.4.3 Sen's Slope Test Results -- 7.4.4 Results of Dividing Technology Steps -- 7.4.5 Results of Data Pre‐processing -- 7.4.6 Results of Coherence Score of Topic -- 7.4.7 Latent Dirichlet Allocation (LDA) Topic Modeling with the Number of Optimal Topic Clusters -- 7.4.8 Analysis of Research and Development Status of Geothermal Energy Technologies. ; 7.4.9 Breakthrough Inventions and Technologies of Geothermal Energy -- 7.4.9.1 Results of Association Rules Mining -- 7.4.9.2 Results of Analysis for Indicators Related to Social Networks -- 7.5 Discussion -- 7.6 Conclusions -- 7.7 Limitations and Future Research -- References -- Chapter 8 Technology Intelligence: Heat Pump Water Heaters -- 8.1 Introduction -- 8.2 Literature Review -- 8.2.1 Heat Pump Water Heater Technology -- 8.2.2 Bibliometric Analysis -- 8.3 Social Network Analysis -- 8.4 Methodology -- 8.4.1 Data Collection -- 8.4.2 Findings -- 8.4.3 Co‐authorship Network Analysis: WoS, Scopus, Sumobrain -- 8.4.4 Top Institutions, Countries, Authors, Papers, and Patent -- 8.4.4.1 Scholarly Data -- 8.4.4.2 Patents -- 8.5 Heat Pump Water Heaters Bibliometrics Application -- 8.6 Overall Affiliation Ranking 2010-2021 -- 8.7 Co‐word Results -- 8.7.1 Keywords Related to Use of Heat Pump Water Heater and Measures of Development Degree -- 8.8 Interview Results -- 8.9 Conclusion and Discussion -- References -- Chapter 9 Technology Intelligence: Burst Analysis for RFID in Hospitals -- 9.1 Introduction -- 9.2 Methodology -- 9.3 Data -- 9.4 Burst Analysis -- 9.5 Cluster Analysis -- 9.6 Conclusion -- References -- Chapter 10 Technology Roadmapping: Data Science Roadmapping of Networked Organizations' Strategic Planning for Artificial Intelligence -- 10.1 Introduction -- 10.2 Literature Review -- 10.2.1 Data Science Roadmapping -- 10.2.1.1 Technology Roadmapping Applications, Methods, and Tools -- 10.2.1.2 Toward Sustainable DSR -- 10.2.2 Strategic Planning for Data‐driven Scenarios -- 10.2.2.1 Big Data, Data Science, and AI -- 10.2.2.2 The Need for Data‐integrated Strategic Planning -- 10.2.2.3 Data Science and AI Challenges at the Organizational Level -- 10.2.2.4 Data Science and AI Challenges Beyond the Organizational Level. ; 10.2.2.5 Opportunities for Using DSR -- 10.2.3 Related Studies -- 10.3 A Case Study of Networked Organizations' Strategic Planning for AI -- 10.3.1 Kickoff and Planning -- 10.3.2 Pre‐workshop -- 10.3.3 Workshops -- 10.3.4 Post‐workshop and Final Review -- 10.3.5 Keeping Roadmapping Alive to Implement Data and AI Governance -- 10.4 Discussion -- 10.5 Conclusion -- References -- Chapter 11 Technology Roadmapping: Nano Technology in Construction in Saudi Arabia -- 11.1 Introduction -- 11.2 Research Methodology -- 11.3 Background of Nanotechnology -- 11.3.1 What Is Nano? -- 11.3.2 Nanotechnology and Nanomaterials -- 11.3.3 Role of Nanotechnology -- 11.3.4 Application of Nanotechnology in Sustainable Building Designs -- 11.4 Nanoarchitecture: Definition and Its Applications -- 11.4.1 Definition of Nanoarchitecture -- 11.4.2 Application of Nanoarchitecture -- 11.4.2.1 Nanocement -- 11.4.2.2 Nanotechnology and Steel -- 11.4.2.3 Nano‐glass -- 11.4.2.4 Nanotechnology and Wood -- 11.4.2.5 Nanotechnology and Coating Materials -- 11.5 Building Sector and Sustainable Development Issues -- 11.5.1 Cost‐saving Productive Processes and Environmental Remediation -- 11.5.2 Green Building Concept -- 11.6 Using Nanomaterials in the Production of Concrete‐based Composites -- 11.6.1 Carbon Nanotubes (CNTs) -- 11.6.2 Polymer Cement -- 11.6.3 Advantage of Nanotechnology in the Construction Industry -- 11.6.3.1 Enhanced Thermal Insulation -- 11.6.3.2 Lightweight Materials with Enhanced Strength -- 11.6.3.3 Self‐cleaning and Photocatalytic Properties -- 11.6.3.4 Reduction of Air Pollution -- 11.6.4 Drawbacks of Nanotechnology in the Construction Industry -- 11.7 Nanoarchitecture Application in Saudi Arabia -- 11.8 Technology Road Mapping for Green Architecture -- 11.8.1 Introduction -- 11.8.2 Steps in Technology Roadmapping -- 11.8.3 Market Drivers. ; 11.8.3.1 QFD Market Segments and Drivers.
• Titolo autorizzato: Future-Oriented Technology Assessment
• ISBN: 1-119-90988-0; 1-119-90987-2; 1-119-90986-4
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910888086303321
• Lo trovi qui: Univ. Federico II
• Serie: IEEE Press Series on Technology Management, Innovation, and Leadership Series