Implementing Data-Driven Strategies in Smart Cities
A Roadmap for Urban Transformation
- 1st Edition - September 18, 2021
- Imprint: Elsevier Science
- Authors: Didier Grimaldi, Carlos Carrasco-Farré
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 1 1 2 2 - 9
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 1 1 2 3 - 6
Implementing Data-Driven Strategies in Smart Cities is a guidebook and roadmap for practitioners seeking to operationalize data-driven urban interventions. The book opens by explor… Read more
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Request a sales quoteImplementing Data-Driven Strategies in Smart Cities is a guidebook and roadmap for practitioners seeking to operationalize data-driven urban interventions. The book opens by exploring the revolution that big data, data science, and the Internet of Things are making feasible for the city. It explores alternate topologies, typologies, and approaches to operationalize data science in cities, drawn from global examples including top-down, bottom-up, greenfield, brownfield, issue-based, and data-driven. It channels and expands on the classic data science model for data-driven urban interventions – data capture, data quality, cleansing and curation, data analysis, visualization and modeling, and data governance, privacy, and confidentiality. Throughout, illustrative case studies demonstrate successes realized in such diverse cities as Barcelona, Cologne, Manila, Miami, New York, Nancy, Nice, São Paulo, Seoul, Singapore, Stockholm, and Zurich. Given the heavy emphasis on global case studies, this work is particularly suitable for any urban manager, policymaker, or practitioner responsible for delivering technological services for the public sector from sectors as diverse as energy, transportation, pollution, and waste management.
- Explores numerous specific urban interventions drawn from global case studies, helping readers understand real urban challenges and create data-driven solutions
- Provides a step-by-step and applied holistic guide and methodology for immediate application in the reader’s own business agenda
- Presents cutting edge technology presentation with coverage of innovations such as the Internet of Things, robotics, 5G, edge/fog computing, blockchain, intelligent transport systems, and connected-automated mobility
Urban policymakers, public administrators, city managers, data scientists or consulting companies managing smart city interventions and data-driven urban transformation projects
Early career researchers and graduate students from smart cities, urban research, urban planning, geography, transport, and economics interested in smart city design.
Early career researchers and graduate students from smart cities, urban research, urban planning, geography, transport, and economics interested in smart city design.
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- About the editors
- Foreword
- Preface
- Acknowledgments
- Memoriam
- Chapter 1: From smart city to data-driven city
- Abstract
- 1: Urban challenges
- 2: Definition of a smart city
- 3: Smart city as an opportunity for innovation and entrepreneurship
- 4: Resilient city
- 5: Sustainable city
- 6: Augmented city
- 7: Is a data-driven approach progress?
- 8: Data-driven smart city architecture
- Chapter 2: Governance, decision-making, and strategy for urban development
- Abstract
- 1: Data-driven approaches for smart city
- 2: Smart urban governance
- 3: Big data citizen-centered organization change
- 4: Architecture of a big data citizen-centered urban governance
- Chapter 3: Data Science technologies
- Abstract
- 1: What is data science?
- 2: Organizing for data science
- 3: Managing data science projects to solve urban issues
- 4: Interview with Miami’s CIO
- 5: Indicators for urban retail
- Chapter 4: Roadmap to develop a data-driven city
- Abstract
- 1: The data-driven strategy decision
- 2: Roadmap for developing data-driven smart cities
- 3: Legal, security, and ethical considerations for a data-driven smart city
- 4: Value model in a data-driven smart city
- 5: Case study of Nice (France)
- 6: Case study of Seoul
- A: Appendix I: Questionnaire
- Chapter 5: Enabling technologies for data-driven cities
- Abstract
- 1: Data-driven cities and smart cities: Technology is the tool, not the goal
- 2: Which technologies are needed in a data-driven city? From IoT to big data
- Chapter 6: Data analysis, modeling, and visualization in smart cities
- Abstract
- 1: Introduction
- 2: What is data visualization?
- 3: Data essentials
- 4: Data types
- 5: Methodology
- 6: Charts and data relations
- 7: Data design principles
- 8: Dashboard basics
- 9: A data-driven approach to predict the COVID-19 effect on urban retail
- Chapter 7: Data-driven policy evaluation
- Abstract
- 1: Introduction
- 2: Types of policy evaluations and evaluation questions
- 3: Experimental and quasiexperimental methodologies
- 4: The role of data in urban policy evaluation
- 5: Challenges and opportunities of big data
- 6: Examples of policy evaluation
- 7: Case study: Fudging the nudge: Information disclosure and restaurant grading in New York (Meltzer et al., 2015)
- 8: Case study: Consumer response to the COVID-19 crisis (Andersen, Hansen, Johannesen, & Sheridan, 2020)
- 9: Case study: The impact of public health interventions during the COVID pandemic
- 10: Case study: Effect of smart technology on consumer’s behavior
- 11: Big data contribution to needs assessment
- 12: Case study: Mapping poverty using mobile phone and satellite data
- 13: Conclusions
- Index
- Edition: 1
- Published: September 18, 2021
- Imprint: Elsevier Science
- No. of pages: 254
- Language: English
- Paperback ISBN: 9780128211229
- eBook ISBN: 9780128211236
DG
Didier Grimaldi
Didier Grimaldi, PhD is Associate Professor at the La Salle–Ramon Llull University, Barcelona, Spain. His scholarly interests span novel forms of innovation to develop new or existing businesses by analyzing different models of public-private governance, which offer a more active role to the citizens. Dr. Grimaldi’s research focuses on evaluating the real effect of emerging technologies (big data, Internet of Things, drones, social media, etc.) to promote new services for citizens that improve their quality of life.
Affiliations and expertise
Associate Professor, La Salle-Ramon Llull University, Barcelona, SpainCC
Carlos Carrasco-Farré
Carlos Carrasco-Farré in the Department of Operations, Innovation and Data Science at ESADE Business School, Barcelona, Spain. His research interest is in human-machine interactions and decision-making. More specifically, his research focuses in computational social science, the intersection of technology (artificial intelligence, machine learning, data science) and society (management, decision-making and strategy). He has contributed to various academic and nonacademic publications and books on economics, management, and urban strategy.
Affiliations and expertise
Researcher, ESADE Business School, Ramon Llull University, Barcelona, SpainRead Implementing Data-Driven Strategies in Smart Cities on ScienceDirect