Applied Evolutionary Economics and Complex Systems

Contracts as Systems

Complexity science offers many theories such as chaos theory and coevolutionary theory. These theories illustrate a large set of real life systems and help decipher their nonlinear and unpredictable behaviours. Categorizing an observed Complex System among these theories depends on the aspect that we intend to study, and it can help better understand the phenomena that occur within the system. This article aims to give an overview on Complex Systems and their modelling. Therefore, we compare these theories based on their main behavioural characteristics, e.g. emergence, adaptability, and dynamism. Then we compare the methods used in the literature to model and simulate Complex Systems, and we propose and discuss simple guidelines to help understand one's Complex System and choose the most adequate model to simulate it.

This chapter examines the combined potential of the constructs of intentionality and Complex Systems Theory, as a new theoretical direction for language learning psychology. The chapter begins with theoretical discussion of the properties of complex systems. This leads to the definition of a Complex System of Intentions, a conceptual model for understanding intentionalities that are present at individual, small group and societal levels, as well as their interrelations. Following that, key properties of the system are illustrated by juxtaposing empirical data from two research projects in Norway and Greece. First, we document the emergence of a ‘performance intentionality’ in learners’ interaction in an English L2 classroom in Norway. Next, we discuss how a ‘competition intentionality’ in a private language school in Greece emerged from interaction with the state school system, and we document its effects on language learning activity. In both cases, a data-driven analysis is used to demonstrate the emergence of the intentionalities and their generative effects, i.e., the ways in which they recursively shaped the system from which they had emerged. We conclude by revisiting the organisational openness of the system, and the processes of emergence and morphogenesis that were traced in the data, and by connecting them to Complex Systems Theory, while exploring the implications of a complexity outlook for language learning research.

Cormac McCarthy: A Complexity Theory of Literature

The complexity of problems facing society continues to grow, and decision-makers and problem-solvers are finding many of today's emerging problems to be beyond their capability to adequately address. There is agreement in the literature that problems of this nature are complex system problems, inextricably linked to some highly complex system of systems. Establishing a clear understanding of the specific complex system context is fundamental to the process of understanding and analyzing complex systems and complex system problems across all of the different systems-based disciplines. While complex system context is widely referred to in systems literature, there is no clear characterization of exactly what system context is, making this foundational system concept ambiguous. This research addressed this gap in the systems body of knowledge by providing the needed detail and clarity to the concept of complex system context. A rigorous research methodology, employing the grounded theory method, was used to analyze data collected through a series of semi-structured interviews conducted with individuals reflecting a wide range of systems education and practical experience. Two research questions were identified as integral to increasing the understanding of context within complex systems. (1) What are the constituent elements of complex system context, and what attributes and dimensions characterize these elements? (2) What systems-based framework can be developed for constructing and articulating complex system context? Using the grounded theory method, a theory of system context was constructed, adding to the systems body of knowledge and substantiating a comprehensive and unambiguous theoretical construct for system context within complex systems. Then, based on this theory, a conceptual model to articulate and capture system-specific complex system context was developed---the Complex System Contextual Framework (CSCF). The CSCF shows significant promise for contribution to systems practitioners by supporting the future development of tools to help practitioners capture system context as a part of complex system problem formulation. The research also made a contribution in the area of research methodologies by furthering the use of the grounded theory method in the engineering management and systems engineering domain, an area where its application has been very limited.

What follows is an account of the concepts of information and noise as they apply to an analysis of high-frequency trading according to ‘heterodox economics’. The text proposes a framework according to which finance can best be understood as a complex technical system tightly coupled to other social, economic systems. To be more precise, the paper attempts to show how finance is not just any complex system but it can be understood as an ecology of evolving socio-technical systems, sub-systems such as investment banks, hedge funds, high-frequency trading traders, retail investors, pensions funds, etc. All of these are the technical building blocks of our financial markets. Moreover, we attempt to show how concepts from other disciplines, such as entropy, information and noise, can be useful in opening up the world of finance from its traditional economic milieu. Although the following text is confined to the discursive realm of humanities/social sciences, it echoes the analytical approaches of econophysics and experimental economics and particularly the ongoing research around ‘computational evolutionary economics’ [Mirowski, P. 2007. “Markets Come to Bits: Evolution, Computation and Markomata in Economic Science.” Journal of Economic Behavior & Organization 63: 209–242; Mirowski, P. 2010. “Inherent Vice: Minsky, Markomata, and the Tendency of Markets to Undermine Themselves.” Journal of Institutional Economics 6: 415–443]. This becomes particularly relevant in the context of the so-called robot phase transition from human-dominated trading to the more automatic electronic trading. The current microstructure of automatic market-making can be understood as an ‘ecological niche’ developed by ultra-fast trading algorithms which ‘feed’ on the asymmetries and disparities of the wider ‘financial ecology’. They do this by dissipating noise and adding to the complexity of market microstructure a behaviour that can push the whole ecology to critical thresholds, sometimes referred to as flash crashes. This whole process can ultimately be described by Philip Mirowski's notion of ‘inherent vice’, as well as by Sir Robert May's concept of instability ‘which develops in ecosystems upon increasing bio-diversity’ [Caccioli, F., M. Marsili, and P. Vivo. 2007. “Eroding Market Stability by Proliferation of Financial Instruments.” The European Physical Journal B – Condensed Matter and Complex Systems 71: 467–479 ; Haldane, A., and R. May. 2011. “Systemic Risk in Banking Ecosystems.” Nature 469: 351–355].

Linguistic Geometry for autonomous navigation

Within the field of systems theory, the term robustness has typically been applied to different contexts such as automatic control, genetic networks, metabolic pathways, morphogenesis, and ecosystems. All these systems involve either man-made machines, or living organisms. In this chapter, we will consider music as a peculiar complex system, involving both the realm of machines (the musical instrument) and the realm of biology (the player and the listeners). We will discuss some of the properties of music experience in terms of different attributes of robustness, focusing in particular on stability, the property enabling a complex system to maintain its function against a wide range of external and internal changes. We will provide examples of the human ability of isolating and maintaining stable information within the perceptual flow and despite changes in the external world that reach our perceptions, leading towards a characterization of robustness in music perception as referred both to the search for regularities and to the range of tolerance that perception admits to regularities. Finally, we will list four multiple interaction cycles that typically characterize music experience and that involve both internal properties of the organism and the environment.

Regional complex system simulation optimization through linking governance and environment performance: A case study of water environmental carrying capacity based on the SDES model

Change in a complex system—for example, to its technology, procedures, or information flows— no matter how small, has the potential to create large effects and ripples of disruption. A complex system’s dynamics cannot be fully known, and the effects and disruptions produced by change are difficult to predict. Nonetheless, complex systems can be at least partly understood in terms of patterns in their dynamics, generalizable principles, and mechanisms of control, balance, and adaptation. This panel will focus on complex systems research and what they suggest about how to introduce change into a complex system such that the work system resilience and health are disrupted minimally. Case studies may be discussed, as well; examples of changes to established complex work systems. These changes include introducing remotely piloted aircraft systems (RPAS) into the National Airspace System (NAS), additional automation into air traffic control, and new technology into military air combat training.

The 17 Sustainable Development Goals (SDGs) are a complex system comprising 169 targets and about 230 indicators. Urban Health could be considered a complex system since it deals with 15 out of 17 SDGs, excluding the two related to life below water and life on land. According to the World Health Organization, to achieve the SDGs, countries have committed to organize Urban Health initiatives to improve the social, economic, and physical environments promoting health and sustainability globally. Cities will become more inclusive, safer and more sustainable, which are important driving forces to implement the development equation. To set up a framework to point out that Urban Health is a complex system oriented to the achievement of the SDGs. It has been conducted an extensive literature review on databases (PubMed, Embase, Web of Science and Scopus) using keywords in 3 strings combined with Boolean operators: SDGs and Urban Health, Urban Health as Complex System and Urban Health, Environmental Health and Public Health as Complex Systems. In addition, a grey literature review has been carried out. Out of 1005 publications, 21 were eventually included: 14 publications relate to the interdependent relationships between SDGs and Urban Health, with regard to the association between Urban Health and complex system, 3 publication studied the effects and implications of such correlation, 4 focused on Environmental Health and Public Health in relation with the complex system. The selected publications suggested methodologies aimed at setting up an urban health framework to achieve SDGs. There is an initial orientation focused on the study of Urban Health problems aimed at achieving SDGs from the perspective of complex systems. We highlight the need to conduct further studies on a more detailed framework in order to address this type of approach.

The purpose of this paper is to develop a systems theory–based construct for pathologies within the context of complex system problem formulation. Problem formulation is arguably one of the most critical phases of any endeavour to improve systems. However, there is relatively little research utilising systems theory during problem formulation. A possible extension of the systems research is the introduction of systems theory (i.e., laws, principles and concepts) as a foundation for exploration, innovation, transformation, evaluation and evolution of complex systems. Specifically, this paper is concerned with how we might use systems theory to articulate pathologies - circumstances, conditions, factors, patterns and/or issues acting to impede system performance. The paper examines the importance of problem formulation for issues related to complex systems. A multidisciplinary literature review is then provided to synthesise insights on pathologies. A systems theory–based construct for pathologies is then developed. Finally, the paper provides implications for the systems theory–based pathologies construct related to complex system governance. The paper concludes with possible future research directions.

Applied Evolutionary Economics and Economic Geography edited by Koen Frenken

Public health evaluation methods have been criticized for being overly reductionist and failing to generate suitable evidence for public health decision-making. A "complex systems approach" has been advocated to account for real world complexity. Qualitative methods may be well suited to understanding change in complex social environments, but guidance on applying a complex systems approach to inform qualitative research remains limited and underdeveloped. This systematic review aims to analyze published examples of process evaluations that utilize qualitative methods that involve a complex systems perspective and proposes a framework for qualitative complex system process evaluations. We conducted a systematic search to identify complex system process evaluations that involve qualitative methods by searching electronic databases from January 1, 2014-September 30, 2019 (Scopus, MEDLINE, Web of Science), citation searching, and expert consultations. Process evaluations were included if they self-identified as taking a systems- or complexity-oriented approach, integrated qualitative methods, reported empirical findings, and evaluated public health interventions. Two reviewers independently assessed each study to identify concepts associated with the systems thinking and complexity science traditions. Twenty-one unique studies were identified evaluating a wide range of public health interventions in, for example, urban planning, sexual health, violence prevention, substance use, and community transformation. Evaluations were conducted in settings such as schools, workplaces, and neighborhoods in 13 different countries (9 high-income and 4 middle-income). All reported some utilization of complex systems concepts in the analysis of qualitative data. In 14 evaluations, the consideration of complex systems influenced intervention design, evaluation planning, or fieldwork. The identified studies used systems concepts to depict and describe a system at one point in time. Only 4 evaluations explicitly utilized a range of complexity concepts to assess changes within the system resulting from, or co-occurring with, intervention implementation over time. Limitations to our approach are including only English-language papers, reliance on study authors reporting their utilization of complex systems concepts, and subjective judgment from the reviewers relating to which concepts featured in each study. This study found no consensus on what bringing a complex systems perspective to public health process evaluations with qualitative methods looks like in practice and that many studies of this nature describe static systems at a single time point. We suggest future studies use a 2-phase framework for qualitative process evaluations that seek to assess changes over time from a complex systems perspective. The first phase involves producing a description of the system and identifying hypotheses about how the system may change in response to the intervention. The second phase involves following the pathway of emergent findings in an adaptive evaluation approach.

Lean production (LP) has been increasingly adopted in complex systems, such as healthcare and construction sites. However, little is known of the extent to which the lean philosophy matches the nature of those systems, which have different characteristics of complexity in comparison with manufacturing plants, in which LP was originated. This article analyses the extent to which LP is compatible with the nature of complex systems, as a basis for the identification of learning opportunities for LP from complex systems theory (CST). As a framework for this analysis, both the prescriptions from LP and CST for designing systems are compared in terms of their potential impact on a set of characteristics of complex systems. Examples of how LP may learn from CST are identified as well as examples of how CST may help to tackle common difficulties in LP implementation.