Overview

This book presents the effects of integrating information and communication technologies (ICT) and economic processes in macroeconomic dynamics, finance, marketing, industrial policies, and in government economic strategy. The text explores modeling and applications in these fields and also describes, in a clear and accessible manner, the theories that guide the integration among information technology (IT), telecommunications, and the economy, while presenting examples of their applications. Current trends such as artificial intelligence, machine learning, and big data technologies used in economics are also included. This volume is suitable for researchers, practitioners, and students working in economic theory and the computational social sciences. 

Full Product Details

Author:   Federico Cecconi ,  Marco Campennì
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   2019 ed.
Weight:   0.477kg
ISBN:  

9783030226046

ISBN 10:   3030226042
Pages:   198
Publication Date:   08 August 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand  
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Table of Contents

PartI: Theory.- Chapter1: Agent-based Computational Economics and Industrial Organization Theory.- Chapter2: Towards a big-data based economy.- Chapter3: Real worlds: simulating non-standard rationality in microeconomics.- Chapter4: The many faces of crowdfunding: a brief classification of the systems and a snapshot of Kickstarter.- PartII: Applications.- Chapter5: Passing-on in Cartel Damages Action: an Agent-Based Model.- Chapter6: Modeling the dynamics of reward-based crowdfunding systems: an agent-based model of Kickstarter.- Chapter7: Fintech: The recovery activity for non-performing loans.- Chapter8: CDS MANAGER: An educational tool for credit derivative market.- Chapter9: A decision-making model for critical infrastructures in conditions of deep uncertainty.- Chapter10: SPIDER: the statistical approach to value assignment problem.- Chapter11: BIG DATA for fraud detection

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