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Transforming Public Services—Combining Data and Algorithms to Fulfil Citizen’s Expectations

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  • © 2024

Overview

Editors:
  1. Christophe Gaie

    1. French Prime Minister Services, Paris 07, France

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  2. Mayuri Mehta

    1. Department of Computer Engineering, Sarvajanik College of Engineering and Technology, Sarvajanik University, Surat, India

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    You can also search for this editor in PubMed   Google Scholar

  • Proposes an in-depth analysis towards the transformation of public services
  • Focuses on use of novel technologies including machine learning, artificial intelligence, and its innovative capability
  • Presents a new, innovative phase of e-Government that aims to fulfil citizen’s expectations in multiple domains

Part of the book series: Intelligent Systems Reference Library (ISRL, volume 252)

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About this book

This book provides a precise portrayal of the current trends and future perspectives of e-Government. It outlines new approaches that optimize public services across diverse sectors. Going beyond traditional boundaries, it offers mathematical models for public services supported by convincing case studies. This book significantly enhances various government services, such as education, healthcare, safety, security, and culture. It also strongly emphasizes safeguarding citizens' personal data, ensuring privacy, and obtaining explicit consent.

Tailored for students and academics, the book is an invaluable reference for teaching graduate courses in e-Government, Process Modelling, or Artificial Intelligence. Its impact extends beyond the classroom; civil servants from all domains can find practical insights to navigate the ongoing modernization of public services. Even citizens curious about the transformation in their public services can find this book enlightening. Researchers working in the area of e-Governance can use this book to discover the recent developments in e-Government.


Keywords

Table of contents (10 chapters)

  1. Front Matter

    Pages i-viii
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  2. Digital Transformation of Public Services: Introduction, Current Trends and Future Directions

    • Christophe Gaie, Mayuri Mehta
    Pages 1-28

  3. Enhancing Citizen Satisfaction Using Citizen-Facing Process Mining

    • Shreekanth M. Prabhu, Natarajan Subramanyam, V. Jagadishwari
    Pages 29-86

  4. Thinking Inside the Sandbox: Beyond Public Services Digitalization with Co-Production

    • Polyana Batista da Silva, Fabrício Ramos Neves
    Pages 87-106

  5. Assessing Sustainable Development of e-Government Services Towards Citizen Satisfaction Through Continuous Improvement Approach

    • D. Vimala, S. Vasantha, A. Shanmathi
    Pages 107-130

  6. Usage of Modern API for Automization of Government Procedures

    • Rahul Arvindkumar Vaghela, Kamini Solanki, Rimpal R. Popat, Ila Rahul Vaghela, Nidhi Chhangani
    Pages 131-150

  7. Epidemiology Inspired Cybersecurity Threats Forecasting Models Applied to e-Government

    • Jean Langlois-Berthelot, Christophe Gaie, Jean-Fabrice Lebraty
    Pages 151-174

  8. The Provision of e-Services by Public Administration Bodies and Their Cybersecurity

    • Christophe Gaie, Mirosław Karpiuk
    Pages 175-188

  9. Modernizing the Processes for Human Resources Through Artificial Intelligence to Optimize a Variety of e-Government Responsibilities

    • Christophe Gaie, Markus Mueck
    Pages 189-205

  10. Fuzzy Logic Architecture for Availing E-Governance Healthcare Services by Rural Citizens

    • M. Bhuvana, A. Ramkumar
    Pages 207-222

  11. Enhancing the Efficiency and the Security of e-Government: The French Case Study of Human Resources Applications

    • Christophe Gaie
    Pages 223-239
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Editors and Affiliations

  • French Prime Minister Services, Paris 07, France

    Christophe Gaie

  • Department of Computer Engineering, Sarvajanik College of Engineering and Technology, Sarvajanik University, Surat, India

    Mayuri Mehta

Bibliographic Information

  • Book Title: Transforming Public Services—Combining Data and Algorithms to Fulfil Citizen’s Expectations

  • Editors: Christophe Gaie, Mayuri Mehta

  • Series Title: Intelligent Systems Reference Library

  • DOI: https://doi.org/10.1007/978-3-031-55575-6

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024

  • Hardcover ISBN: 978-3-031-55574-9Published: 05 May 2024

  • Softcover ISBN: 978-3-031-55577-0Due: 05 June 2024

  • eBook ISBN: 978-3-031-55575-6Published: 04 May 2024

  • Series ISSN: 1868-4394

  • Series E-ISSN: 1868-4408

  • Edition Number: 1

  • Number of Pages: VIII, 239

  • Number of Illustrations: 30 b/w illustrations, 39 illustrations in colour

  • Topics: Data Engineering, Computational Intelligence, Big Data

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