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A Complex Adaptive System Approach for Anticipating Technology Diffusion, Income Inequality and Economic Recovery

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Technology progress challenges equilibrium structures of human, social, cultural and behavioral systems. These are seen in ‘new normals’ of discontinuous market changes and nonlinear trend dynamics underpinning new individual behavior and human connectivity. Here we instantiate an agent based model integrated in a CAS framework of micro individual socio-economic transactions games empowered by technology and played on different economic network structures and market sophistication for anticipating macroeconomic and social equality outcomes. We explore scenario comparisons across GDP shocks and their impact on inequality, market behavior and recovery patterns. Several different V, U, L and W-shaped macro recovery patterns are categorized specifically dependent on such CAS structures. More sophisticated markets with preferential connectivity tend to offer lower levels of inequality and are more economically robust than less developed, randomly connected, transactional markets. High resolution computational approaches such as this can offer policymakers deeper insights and more actionable policy levers to achieve desired socio-economic outcomes in times of crisis.

Original languageEnglish
Title of host publicationComputational Science and Its Applications – ICCSA 2021 - 21st International Conference, Proceedings
EditorsOsvaldo Gervasi, Beniamino Murgante, Sanjay Misra, Chiara Garau, Ivan Blecic, David Taniar, Bernady O. Apduhan, Ana Maria Rocha, Eufemia Tarantino, Carmelo Maria Torre
PublisherSpringer Science and Business Media Deutschland GmbH
Pages251-262
Number of pages12
ISBN (Print)9783030869595
DOIs
StatePublished - 2021
Externally publishedYes
Event21st International Conference on Computational Science and Its Applications, ICCSA 2021 - Virtual, Online
Duration: Sep 13 2021Sep 16 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12950 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference21st International Conference on Computational Science and Its Applications, ICCSA 2021
CityVirtual, Online
Period09/13/2109/16/21

Keywords

  • Agent-based Modeling (ABM)
  • Co-evolution
  • Complex adaptive system
  • Economic growth
  • Economic recovery
  • Technology adoption

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