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About this book

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.

Table of Contents




Chapter 1. Agent-Based Computational Economics and Industrial Organization Theory

Agent-based computational economics (ACE) is “the computational study of economic processes modeled as dynamic systems of interacting agents.” This new perspective offered by agent-based approach makes it suitable for building models in industrial organization (IO), whose scope is the study of the strategic behavior of firms and their direct interactions. Better understanding of industries’ dynamics is useful in order to analyze firms’ contribution to economic welfare and improve government policy in relation to these industries.
Claudia Nardone

Chapter 2. Towards a Big-Data-Based Economy

On the threshold of 2020, we find ourselves in the middle of an extremely chaotic social and market scenario but at the same time with countless opportunities for emancipation relatively to everything we have so far considered as traditional.
The redemption of “standards” is an irreversible process that goes through behaviours increasingly distant from the experiential logic and increasingly guided by those who hold the knowledge of how our behaviours change.
Andrea Maria Bonavita

Chapter 3. Real Worlds: Simulating Non-standard Rationality in Microeconomics

In this chapter, the differences between the standard notion of rationality, used in neoclassical economic model, and the notion of “non-standard” rationality are highlighted. The notion of non-standard rationality has been used in an attempt to address the discrepancies found between the ideal cognitive attitudes of the homo economicus and limited rational abilities of real decision-makers. By contrast, this notion is not supported by any adequate nor exhaustive theoretical account of “non-standard” preferences and therefore doesn’t provide useful applications for real-world simulations in microeconomics.
Giuliana Gerace

Chapter 4. The Many Faces of Crowdfunding: A Brief Classification of the Systems and a Snapshot of Kickstarter

In this chapter, we present the complex phenomenon of crowdfunding and its origin, briefly providing some useful definitions and concepts. We then present two different types of analysis: (i) a simple descriptive statistics showing interesting results about the most successful categories of Kickstarter campaigns; (ii) the potentials of adopting a time-series analysis approach to better understand trends in Kickstarter and to perform a simple forecast of future trends of successful campaigns.
Marco Campennì, Marco Benedetti, Federico Cecconi



Chapter 5. Passing-on in Cartel Damages Action: An Agent-Based Model

When there are infringements causing a price increase, such as cartels, one of the effects on direct purchaser’s profit is the so-called passing-on effect. Passing-on rate is the proportion of the illegal price increase that cartel direct purchasers, in turn, translate into an increase in their own final price. In this chapter, we develop an agent-based model of a supply chain, where agents are firms who lay on different levels of the chain and are engaged in trading.
Claudia Nardone, Federico Cecconi

Chapter 6. Modeling the Dynamics of Reward-Based Crowdfunding Systems: An Agent-Based Model of Kickstarter

In this chapter, we present an agent-based model of Kickstarter, maybe the most successful crowdfunding platform available nowadays. We aim to use the model to better understand cognitive strategies and behavioral dynamics governing Kickstarter, considered as a multi-actor system where agents adopting different strategies interact. The model shows how the success of agents is affected by the strategy they adopt and provide interesting insight about non-linear dynamics resulting from the interactions among agents.
Marco Campennì, Federico Cecconi

Chapter 7. Fintech: The Recovery Activity for Non-performing Loans

In this chapter we present an algorithmic evaluation method for valuing loans secured by real estate. The model described represents the synthesis of the various components that qualify non-performing loans: the legal aspect, the real estate aspect, and the financial aspect. We have developed an algorithm capable of simulating the mechanism of the judicial auction, which relates the various quantities that qualify a credit, both in the supply phase and in the litigation phase. The model can be used to optimize a financial portfolio.
Alessandro Barazzetti, Angela Di Iorio

Chapter 8. CDS Manager: An Educational Tool for Credit Derivative Market

How could we teach the dynamics of new financial instruments, not very much understood and potentially dangerous? In this work we show some limitations of classical financial learning framework, which uses a description of the dynamics through mathematical models, and we propose an alternative approach, based on the agent-based modeling framework. In the model presented, an operator observes, through a simulation, the behavior of other artificial agents in its own market (Liu et al., J Manag Inf Syst 7(1):101–122, 1990; Radicchi et al., Proc Natl Acad Sci USA 101(9):2658–2663, 2004; Yang et al., Int J Electron Commer 6(1):101–102, 2001).
Federico Cecconi, Alessandro Barazzetti

Chapter 9. A Decision-Making Model for Critical Infrastructures in Conditions of Deep Uncertainty

In this work, we develop a set of tools able to analyse different options in a generic case of critical infrastructure development with the consideration of climate change adaptation needs. As an example that will guide us through the process, we refer to a decision problem related to the hydraulic regulation of a strategic infrastructure (e.g. an airport, a power plant, a train station or a logistic centre) exposed to uncertain future climatic extremes.
Juliana Bernhofer, Carlo Giupponi, Vahid Mojtahed

Chapter 10. Spider: The Statistical Approach to Value Assignment Problem

In the era of “Big Data,” with the advent of the artificial intelligence algorithms, a different type of real estate valuation has found its own market niche: the AVM (automated valuation method), evolution of the simplest statistical evaluation. The Spider-based approach starts from the consideration that the value of a property is certainly influenced by innumerable variables, possibly coming from different databases, but these variables can be grouped into homogeneous categories, which we will call vectors.
Luigi Terruzzi

Chapter 11. Big Data for Fraud Detection

Fraud is domain-specific, and there is no one-solution-fits-all method among fraud detection techniques. To make this chapter more specific and concrete, we provide examples concerning a common type of fraud which is food fraud. Food fraud has irreversible effects since it imposes risks to human life. The aim of this chapter is thus to present a conceptual and methodological solution for real-time fraud detection that can be implemented in the food sector by global food producers, regulatory bodies, or retailers but is generalizable to other domains.
Vahid Mojtahed


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