scholarly journals Complexity and Evolution

Two widely heralded yet contested approaches to economics have emerged in recent years. One follows an older, rather neglected approach which emphasizes evolutionary theory in terms of individuals and institutions. The other emphasizes economies as complex adaptive systems. Important concepts from evolutionary theory include the distinction between proximate and ultimate causation, multilevel selection, cultural change as an evolutionary process, and human psychology as a product of gene–culture coevolution. Relevant concepts from complexity theory include self-organization, fractals, chaos, sensitive dependence, basins of attraction, and path dependence. This book explores these two bodies of theory and their potential impact on economics. Central themes include the challenges that emerge through integration, evolutionary behavioral economics, and the evolution of institutions. Practical applications are provided and avenues for future research highlighted.

2018 ◽  
Vol 49 (6) ◽  
pp. 18-38 ◽  
Author(s):  
Roger Sweetman ◽  
Kieran Conboy

While agile approaches can be extremely effective at a project level, they can impose significant complexity and a need for adaptiveness at the project portfolio level. While this has proven to be highly problematic, there is little research on how to manage a set of agile projects at the project portfolio level. What limited research that does exist often assumes that portfolio-level agility can be achieved by simply scaling project level agile approaches such as Scrum. This study uses a complex adaptive systems lens, focusing specifically on the properties of projects as agents in a complex adaptive portfolio to critically appraise current thinking on portfolio management in an agile context. We then draw on a set of 30 expert interviews to develop 16 complex adaptive systems (CAS)-based propositions as to how portfolios of agile projects can be managed effectively. We also outline an agenda for future research and discuss the differences between a CAS-based approach to portfolio management and traditional approaches.


2017 ◽  
pp. 335-360
Author(s):  
Arash Najmaei ◽  
Zahra Sadeghinejad

Business models define configurations of activities that jointly enable a firm to create and capture value. The value paradigm is shifting from sharing created value to creating shared value in which firms and societies jointly create and share value to nurture more benefits for a sustainable business-environment symbiosis. Drawing on this logic, we develop a framework for designing business models that enable creation and capture of shared value. Our model builds on the practice theory and activity system and depicts business models as complex adaptive systems that co-evolve with markets. Using the shared value framework proposed by Porter and Kramer (2011) we propose three design themes namely the Product-Market Design (PMD), the Value Chain Design (VCD) and the Social Cluster Design (SCD). We specify features of each school from the activity perspective. Subsequently, we will discuss implications of our framework for theory, practice and management education and illuminate some directions for future research.


Author(s):  
Gaetano R Lotrecchiano ◽  
Shalini Misra

Aim/Purpose: Transdisciplinarity is considered as a framework for understanding knowledge producing teams (KPTs). Features of transdisciplinary knowledge producing teams (TDKPTs) are provided using a complex adaptive systems (CAS) lens. TDKPT features are defined and linked to complexity theory to show how team participants might develop skills that more truly express complex adaptive conditions. Background: TDKPTs are groups of stakeholder participants tasked with producing knowledge across disciplinary, sectoral, and ecological boundaries. TDKPTs reflect components of complex adaptive systems (CAS) and exemplify how CAS behave and function. Methodology: The paper accesses literature from the Science-of-Team-Science (SciTS), complexity theory, and systems theory to construct a typology of the features of TDKPTs. Contribution: This paper provides a list of features developed from a diverse body of literature useful for considering complexity within TDKPTs. Findings: The paper proposes a series of features of transdisciplinary knowledge producing teams. In addition, the authors identify important skill building aspects needed for TDKPTs to be successful. Recommendations for Practitioners: The paper provides a framework by which team functioning can be considered and enhanced within TDKPTs. Recommendation for Researchers: The paper suggests categorical features of transdisciplinary teams for research on the collaborative processes and outcomes of TD teams. Future Research: Knowledge producing team members need to engage in theoretical, episte-mological, and methodological reflections to elucidate the dynamic nature of TD knowledge producing teams. Understanding how conflict, dissonance, and reciprocal interdependencies contribute to knowledge generation are key areas of future research and inquiry.


Author(s):  
G. S. Nitschke ◽  
M. C. Schut ◽  
A. E. Eiben

Specialization is observable in many complex adaptive systems and is thought by many to be a fundamental mechanism for achieving optimal efficiency within organizations operating within complex adaptive systems. This chapter presents a survey and critique of collective behavior systems designed using biologically inspired principles. Specifically, we are interested in collective behavior systems where specialization emerges as a result of system dynamics and where emergent specialization is used as a problem solver or means to increase task performance. The chapter presents an argument for developing design methodologies and principles that facilitate emergent specialization in collective behavior systems. Open problems of current research as well as future research directions are highlighted for the purpose of encouraging the development of such emergent specialization design methodologies.


Author(s):  
David S. Wilson ◽  
Alan Kirman ◽  
Julia Lupp

How are we to understand economic institutions that are comprised of multiple, interacting individuals who operate on various spatial and temporal scales, all of which are impacted by a myriad of factors? Economics has based its efforts largely on general equilibrium theory, yet this dominant paradigm has two fundamental flaws: it assumes that economic systems are at equilibrium and utilizes Homo economicus (a fictitious being) to define preferences, behavior, and abilities. Because these assumptions deviate so drastically from reality, there is doubt whether incremental changes can ever render it effective. Thus, alternative approaches have emerged. Evolutionary theory has brought novel insight to explain the behavior of individuals and institutions, and complexity theory has provided context to understand economies as complex adaptive systems. To permit greater understanding of economics and public policy, this Ernst Strüngmann Forum explored the integration of concepts from complexity theory and evolutionary theory. The hope was that this discourse would spur a synthesis and lead to the creation of a new economic framework—one capable of modeling economic systems as complexly adaptive and frequently out of equilibrium, based on the preferences, behavior, and abilities of real human beings and the diverse processes involved.


Author(s):  
Peter R. Monge ◽  
Noshir Contractor

Chapter 3 discussed the emergence of communication networks from the perspective of complexity theory. Specifically, we described complexity as a network of agents, each with a set of attributes, who follow rules of interaction, which produces emergent structure. Complexity arose from the fact that there were numerous agents with extensive relations. Some complex systems but by no means all, we argued, were self-organizing, meaning that they created and sustained internal structure in response to the flow of matter and energy around them. Some readers, particularly those with some familiarity with the complex adaptive systems literature, may have noticed that the discussion of complexity in chapter 3 did not include processes of adaptation, evolution, or coevolution. The reason for this is that it is possible to view these as theoretical mechanisms that operate in at least some complex, self-organizing systems, though not necessarily all. Thus, we have chosen to treat adaptation and the coevolutionary perspective as theoretical mechanisms in the same manner as the other theoretical mechanisms we have examined in chapters 5 through 8. In the present chapter we examine adaptive and coevolutionary processes as the basis for building MTML models of emergent communication networks that form the basis for organizational populations and communities. Modern interest in evolutionary theory as a basis for studying human social processes can be traced to the work of Amos Hawley (1950, 1968, 1986). Much of the interest in applying this perspective to studying organizational structures is credited to Donald Campbell (1965, 1974). Over much of his professional life Campbell explored the application of evolutionary theory to a wide array of sociocultural processes, including organizations (Baum & McKelvey, 1999). Campbell is perhaps best known throughout the social sciences for his work on experimental and quasi-experimental design (Campbell and Stanley, 1966; Cook & Campbell, 1980) and multimethod triangulation (Campbell & Fiske, 1959). Nonetheless, McKelvey and Baum (1999) point to Campbell’s enormous influence in organizational science via the early work of Aldrich (1972) on organizational boundaries, Weick’s (1979) formulation of an evolutionary model of organizing, Hannan and Freeman’s (1977, 1983) development of population ecology theory (and inertial theory), McKelvey’s (1982) work on organizational taxonomies, and Nelson and Winter’s (1982) evolutionary theory of economics.


2015 ◽  
Vol 15 (1) ◽  
pp. 55-68 ◽  
Author(s):  
Yeqing Zhao

Abstract The Sznajd model of sociophysics can describe the mechanism of making a decision in a closed community. The Complex Agent Networks (CAN) model is studied, based on the adaptability, autonomy and activity of the individuals, as well as the complex interactions of individuals in an open community for probing into evolution of the public opinion. With the help of the theory of complex adaptive systems and the methods of complex networks, the structure of agents, the dynamic networks scenarios and the evolutionary process of the agents are described. The simulation results of CAN model show that all individuals cannot reach a final consensus through mutual consultations when the small world networks rewiring probability p is less than a specified threshold. But when the rewiring probability p is larger than the given threshold, all individuals will eventually come to a finial consensus, and that the rewiring probability p increases, whereas the time of emergence of the public opinion will be significantly reduced. It is quite obvious that in real community the mass media and many other mechanisms have an effect on the evolutionary process of the public opinion.


Author(s):  
Timothy A. Kohler

Echoes of all the major approaches to applying evolutionary theory and method to the archaeological record can be found in the Southwest. Prior to about 1980, cultural evolutionary approaches were quite common; after that time, until the mid-1990s, selectionism was the dominant approach. More recently, human behavioral ecology and, to a smaller degree, dual inheritance theory have oriented most evolutionary research, while at the same time, research that draws on the theories and methods of complex adaptive systems has become more prominent. All of these approaches are likely to contribute to solving the grand challenges facing archaeology in the Southwest.


Author(s):  
Arash Najmaei ◽  
Zahra Sadeghinejad

Business models define configurations of activities that jointly enable a firm to create and capture value. The value paradigm is shifting from sharing created value to creating shared value in which firms and societies jointly create and share value to nurture more benefits for a sustainable business-environment symbiosis. Drawing on this logic, we develop a framework for designing business models that enable creation and capture of shared value. Our model builds on the practice theory and activity system and depicts business models as complex adaptive systems that co-evolve with markets. Using the shared value framework proposed by Porter and Kramer (2011) we propose three design themes namely the Product-Market Design (PMD), the Value Chain Design (VCD) and the Social Cluster Design (SCD). We specify features of each school from the activity perspective. Subsequently, we will discuss implications of our framework for theory, practice and management education and illuminate some directions for future research.


Author(s):  
Vassilios Ziakas ◽  
Vladimir Antchak ◽  
Donald Getz

The landscape of the event sector is dramatically changing as a result of the COVID-19 pandemic crisis. The crisis has accelerated structural change and aggravated the instability of what has traditionally been a highly volatile, disruptive and erratic sector. Crises are becoming the new normal. The probability of the advent of further crises should be considered and carefully evaluated by the event industry and the entire visitor economy sector. It is critical for event organizers and host communities to learn how to cooperate and manage their events under conditions of constant or episodic crises and turbulence. A holistic mindset in crisis management needs to be developed to create tools and strategies for enabling the effective adaptability, recovery, and resilience of events. In this concluding chapter, we outline the pillars of a holistic crisis management perspective that makes use of complex adaptive systems, event portfolio and resilience theories. We encapsulate major issues in the crisis management of events and put forward an integrative framework that brings together crucial elements and processes. Finally, we discuss key trends and transformations of the sector, and in this context, suggest directions for future research.


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