scholarly journals Challenges of Complexity in the 21st Century. An Interdisciplinary Introduction

2009 ◽  
Vol 17 (2) ◽  
pp. 219-236 ◽  
Author(s):  
Klaus Mainzer
Keyword(s):  
Nonlinear Dynamics ◽  
Complex Systems ◽  
Social Economic ◽  
Evolutionary Economics ◽  
Systems Science ◽  
Homo Oeconomicus ◽  
Economic Agents ◽  
Modern Engineering ◽  
Innovation Dynamics ◽  
Non Gaussian

The theory of nonlinear complex systems has become a proven problem-solving approach in the natural sciences from cosmic and quantum systems to cellular organisms and the brain. Even in modern engineering science self-organizing systems are developed to manage complex networks and processes. It is now recognized that many of our ecological, social, economic, and political problems are also of a global, complex, and nonlinear nature. Modern evolutionary economics can be modelled in the framework of complex systems and nonlinear dynamics. Historically, evolutionary economics was inspired by Schumpeterian concepts of business cycles and innovation dynamics. What are the laws of sociodynamics? What can we learn from nonlinear dynamics for complexity management in social, economic, financial and political systems? Is self-organization an acceptable strategy to handle the complexity in firms, institutions and organizations? The world-wide crisis of financial markets and economies is a challenge for complexity research. Misleading concepts of linear thinking and mild randomness (e.g. Gaussian distributions of Brownian motion) must be overcome by new approaches of nonlinear mathematics (e.g. non-Gaussian distribution), modelling the wild randomness of turbulence at the stock markets. Systemic crises need systemic answers. Nevertheless, human cognitive capabilities are often overwhelmed by the complexity of nonlinear systems they are forced to manage. Traditional mathematical decision theory assumed perfect rationality of economic agents (homo oeconomicus). Herbert Simon, Nobel Prize laureate of economics and one of the leading pioneers of systems science and cognitive science, introduced the principle of bounded rationality. Therefore, we need new insights into the factual microeconomic behaviour of economic agents by methods of humanities, cognitive and social sciences, which are sometimes called ‘experimental economics’. Social and economic dynamics are interdisciplinary challenges of modern complexity research.

scholarly journals Toward Reverse Engineering to Economic Analysis: An Overview of Tools and Methodology

2021 ◽  
Author(s):  
Marisa Faggini ◽  
Bruna Bruno ◽  
Anna Parziale
Keyword(s):  
Complex System ◽  
Nonlinear Dynamics ◽  
Economic Analysis ◽  
Complex Systems ◽  
Reverse Engineering ◽  
Underlying Mechanism ◽  
Economic Data ◽  
Agent Based ◽  
Economic Agents ◽  
Advantages And Disadvantages

AbstractFollowing the reverse engineering (RE) approach to analyse an economic complex system is to infer how its underlying mechanism works. The main factors that condition the difficulty of RE are the number of variable components in the system and, most importantly, the interdependence of components on one another and nonlinear dynamics. All those aspects characterize the economic complex systems within which economic agents make their choices. Economic complex systems are adopted in RE science, and they could be used to understand, predict and model the dynamics of the complex systems that enable to define and to control the economic environment. With the RE approach, economic data could be used to peek into the internal workings of the economic complex system, providing information about its underling nonlinear dynamics. The idea of this paper arises from the aim to deepen the comprehension of this approach and to highlight the potential implementation of tools and methodologies based on it to treat economic complex systems. An overview of the literature about the RE is presented, by focusing on the definition and on the state of the art of the research, and then we consider two potential tools that could translate the methodological issues of RE by evidencing advantages and disadvantages for economic analysis: the recurrence analysis and the agent-based model (ABM).

scholarly journals The emergence of consensus: a primer

2018 ◽  
Vol 5 (2) ◽  
pp. 172189 ◽  
Author(s):  
Andrea Baronchelli
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Complex Systems ◽  
Social Systems ◽  
Short Review ◽  
Systems Science ◽  
Social Consensus ◽  
Population Scale ◽  
Complex Systems Science

The origin of population-scale coordination has puzzled philosophers and scientists for centuries. Recently, game theory, evolutionary approaches and complex systems science have provided quantitative insights on the mechanisms of social consensus. However, the literature is vast and widely scattered across fields, making it hard for the single researcher to navigate it. This short review aims to provide a compact overview of the main dimensions over which the debate has unfolded and to discuss some representative examples. It focuses on those situations in which consensus emerges ‘spontaneously’ in the absence of centralized institutions and covers topics that include the macroscopic consequences of the different microscopic rules of behavioural contagion, the role of social networks and the mechanisms that prevent the formation of a consensus or alter it after it has emerged. Special attention is devoted to the recent wave of experiments on the emergence of consensus in social systems.

scholarly journals ARE HIGHER WAGES GOOD FOR BUSINESS? AN ASSESSMENT UNDER ALTERNATIVE INNOVATION AND INVESTMENT SCENARIOS

2018 ◽  
Vol 24 (1) ◽  
pp. 191-230 ◽  
Author(s):  
Alessandro Caiani ◽  
Alberto Russo ◽  
Mauro Gallegati
Keyword(s):  
Technological Progress ◽  
Evolutionary Economics ◽  
Middle Level ◽  
Closed Economy ◽  
Beneficial Effects ◽  
Growth Regime ◽  
Long Run ◽  
Innovation Dynamics ◽  
Macroeconomic Environment

This paper aims at investigating the interplay between inequality, innovation dynamics, and investment behaviors in shaping the long-run patterns of growth of a closed economy. By extending the analysis proposed in Caiani et al. [(2018) Journal of Evolutionary Economics], we explore the effects of alternative wage regimes under different investment and technological change scenarios. Experimental results seem to de-emphasize the role of technological progress as a possible source of greater inequality. Overall, simulation results are consistent with the predominance of a wage-led growth regime in most of the scenarios analyzed: A faster growth of low- and middle-level workers’ wages, relative to managers’, generally exert beneficial effects on the economy and allows to counteract the labor-saving effects of technological progress. Furthermore, a distribution more favorable to workers does not compromise firms’ profitability, but rather strengthen it by creating a more favorable macroeconomic environment, which encourages further innovations, stimulates investment, and sustains economic growth.

scholarly journals FOUNDATIONS OF cHINESE SYSTEMS SCIENCE

2021 ◽  
Author(s):  
Hans Kuijper
Keyword(s):  
Complex Systems ◽  
Systems Thinking ◽  
Systems Science ◽  
Ancient China ◽  
Complex Systems Thinking

The fast developments of (complex) systems thinking cannot be understood without taking the cultural and philosophical context into consideration. In this article, An attempt is made to explain the foundation of thriving CHINESE systems thinking, because China seems to fully undertand the significance and importance of thinking (and engineering) systemically. The conclusion of the paper is two-pronged: (a) the Chinese have been system thinkers (or pattern seekers) from the very beginning of their turbulent history and (B) Western system thinkers, who disagree with each other on many fronts, could, nay should learn something from ancient China, particularly from that amazing, almost forgotten classical book called the Yijing, a book about systems science in a nutshell.

Complex Systems Science

2021 ◽  
pp. 243-256
Author(s):  
Matt Kasman ◽  
Nancy Breen ◽  
Ross A. Hammond
Keyword(s):  
Complex Systems ◽  
Systems Science ◽  
Complex Systems Science

How Complex Systems Science Can Revolutionize Population Health Theory

2020 ◽  
pp. 73-88
Author(s):  
Patricia Goodson
Keyword(s):  
Complex Systems ◽  
Population Health ◽  
Policy Development ◽  
Theory Building ◽  
Public Health Workforce ◽  
Systems Science ◽  
Complex Health Problems ◽  
Complex Systems Science ◽  
Health Theory ◽  
And Training

This chapter discusses whether and how complex systems science (CSS) can revolutionize population health theory. First, the chapter defines theory and the practice of theory-building (or theorizing); second, it outlines some of the difficulties found in current population health theorizing; lastly, it characterizes the mechanisms through which CSS can influence, change, and revolutionize current theorizing efforts. The chapter also describes two examples of scholars who used CSS to challenge currently held assumptions and reframe complex health problems. Lastly, the author addresses the implications—of adopting a CSS approach to theorizing—for practice, policy development, and training of the future public health workforce.

Bridging the Divide

2020 ◽  
pp. 3-14
Author(s):  
Yorghos Apostolopoulos
Keyword(s):  
Risk Factor ◽  
Complex Systems ◽  
Population Health ◽  
Health Science ◽  
The Other ◽  
Systems Science ◽  
Shared Understanding ◽  
Key Concepts ◽  
The One ◽  
Complex Systems Science

This chapter contextualizes the volume and describes its organization. It begins by delving into the limitations of the prevailing reductionist paradigm in population health science and the need for a transition from a typically risk factor–based science to a science that recognizes the whole and relationships among parts of pressing population health problems. Next, it walks readers through distinctions between public and population health on the one hand and key concepts of complexity on the other, while offering a shared understanding of population health science and complex systems science. The chapter also lays out the design of and potential audiences for this book.

Crossing the Chasm

2012 ◽  
pp. 280-289
Author(s):  
Theresa M. Vitolo
Keyword(s):  
Complex Systems ◽  
Serious Games ◽  
Social Economic ◽  
Serious Game ◽  
Scientific Methods ◽  
Current State ◽  
Gaming Technology ◽  
The Future

Serious games are technology with unrealized potential as an innovation for reasoning about complex systems. The technology is enticing to technologically-savvy individuals, but the acceptance of serious games into mainstream processes requires addressing several systemic issues spanning social, economic, behavioral, and technological aspects. First, deployment of gaming technology for critical processes needs to embrace statistical and scientific methods appropriate for valid, accurate, and verifiable simulation of such processes. Second, identifying the correct instance and application breadth for a serious game within an organization needs to be articulated and supported with research. Third, funding for serious-games initiatives will need to be won as the funding will displace monies previously allocated and championed for other projects. Last, the endeavor faces the problem of negative connotations about its appropriateness as a viable technology for mainstream processes rather than for entertainment and diversion. The chapter examines the chasm serious games must traverse by examining the issues and posing approaches to minimize their effect on the adoption of the technology. The histories of other technologies that faced similar hurdles are compared to the current state of serious games, offering a perspective on the hurdle’s resolution. In the future, the hurdles can be minimized as curricula are developed with the solutions to the issues incorporated in the content.

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