Crozier & Luhmann: social theory as a support for a systemic socioterritorial modeling and simulation.

This paper shows how a socioterritorial system could be computationally modeled by means of two social theories, Sociology of Organized Action (SOA) and Social Systems (SS) to study power relations among social actors. It is concluded that both approaches helps the empirical research and that they complement each other, while SOA emphasizes the power relations, the SS focuses on the generative process of communication

Methodological Investigations in Agent-Based Modelling: With Applications for the Social Sciences

This open access book examines the methodological complications of using complexity science concepts within the social science domain. The opening chapters take the reader on a tour through the development of simulation methodologies in the fields of artificial life and population biology, then demonstrates the growing popularity and relevance of these methods in the social sciences. Following an in-depth analysis of the potential impact of these methods on social science and social theory, the text provides substantive examples of the application of agent-based models in the field of demography. This work offers a unique combination of applied simulation work and substantive, in-depth philosophical analysis, and as such has potential appeal for specialist social scientists, complex systems scientists, and philosophers of science interested in the methodology of simulation and the practice of interdisciplinary computing research.

Self-Organising Networks in Complex Infrastructure Projects: The Case of London Bank Station Capacity Upgrade Project

Managing large infrastructure projects remains a thorny issue in theory and practice. This is mainly due to their increasingly interconnected, interdependent, multilateral, nonlinear, unpredictable, uncontrollable, and rapidly changing nature. This study is an attempt to demystify the key issues to the management of large construction projects, arguing that these projects are delivered through networks that evolve in ways that we do not sufficiently understand as yet. The theoretical framework of this study is grounded in Complexity Theory; a theory resulted in a paradigm shift when it was first introduced to project management post-2000 but is yet to be unpacked in its full potential. The original contribution of the study is predicated on perceiving large construction projects as evolving complex systems that involves a high degree of self‐organisation. This is a process that transitions contractually static prescribed roles to dynamic network roles, comprising individuals exchanging information. Furthermore, by placing great emphasis upon informal communications, this study demonstrates how self-organising networks can be married with Complexity Theory. This approach has the potential to make bedfellows around the concept of managing networks within a context of managing projects; a concept that is not always recognised, especially in project management. With the help of social network analysis, two snapshots from Bank Station Capacity Upgrade Project Network were analysed as a case study. Findings suggest that relationships and hence network structures in large construction projects exhibit small-world topology, underlined by a high degree of sparseness and clustering. These are distinct structural properties of self-organising networks. Evidence challenges the theorisation about self-organisation which largely assumes positive outcomes and suggests that self-organising could open up opportunities yet also create constraints. This helps to provide further insights into complexity and the treatment of uncertainty in large projects. The study concludes with detailed recommendations for research and practice

Measuring, Monitoring and Managing Legal Complexity

The American legal system is often accused of being “too complex.” For example, most Americans believe the Tax Code is too complex. But what does that mean, and how would one prove the Tax Code is too complex? Both the descriptive claim that an element of law is complex and the normative claim that it is too complex should be empirically testable hypotheses. Yet, in fact, very little is known about how to measure legal complexity, much less how to monitor and manage it. Legal scholars have begun to employ the science of complex adaptive systems, also known as complexity science, to probe these kinds of descriptive and normative questions about the legal system. This body of work has focused primarily on developing theories of legal complexity and positing reasons for, and ways of, managing it. Legal scholars thus have skipped the hard part—developing quantitative metrics and methods for measuring and monitoring law’s complexity. But the theory of legal complexity will remain stuck in theory until it moves to the empirical phase of study. Thinking about ways of managing legal complexity is pointless if there is no yardstick for deciding how complex the law should be. In short, the theory of legal complexity cannot be put to work without more robust empirical tools for identifying and tracking complexity in legal systems. This Article explores legal complexity at a depth not previously undertaken in legal scholarship. First, the Article orients the discussion by briefly reviewing complexity science scholarship to develop descriptive, prescriptive, and ethical theories of legal complexity. The Article then shifts to the empirical front, identifying potentially useful metrics and methods for studying legal complexity. It draws from complexity science to develop methods that have been or might be applied to measure different features of legal complexity. Next, the Article proposes methods for monitoring legal complexity over time, in particular by conceptualizing what we call Legal Maps—a multi-layered, active representation of the legal system network at work. Finally, the Article concludes with a preliminary examination of how the measurement and monitoring techniques could inform interventions designed to manage legal complexity by using currently available machine learning and user interface design technologies

Measuring, Monitoring and Managing Legal Complexity

The American legal system is often accused of being “too complex.” For example, most Americans believe the Tax Code is too complex. But what does that mean, and how would one prove the Tax Code is too complex? Both the descriptive claim that an element of law is complex and the normative claim that it is too complex should be empirically testable hypotheses. Yet, in fact, very little is known about how to measure legal complexity, much less how to monitor and manage it. Legal scholars have begun to employ the science of complex adaptive systems, also known as complexity science, to probe these kinds of descriptive and normative questions about the legal system. This body of work has focused primarily on developing theories of legal complexity and positing reasons for, and ways of, managing it. Legal scholars thus have skipped the hard part—developing quantitative metrics and methods for measuring and monitoring law’s complexity. But the theory of legal complexity will remain stuck in theory until it moves to the empirical phase of study. Thinking about ways of managing legal complexity is pointless if there is no yardstick for deciding how complex the law should be. In short, the theory of legal complexity cannot be put to work without more robust empirical tools for identifying and tracking complexity in legal systems. This Article explores legal complexity at a depth not previously undertaken in legal scholarship. First, the Article orients the discussion by briefly reviewing complexity science scholarship to develop descriptive, prescriptive, and ethical theories of legal complexity. The Article then shifts to the empirical front, identifying potentially useful metrics and methods for studying legal complexity. It draws from complexity science to develop methods that have been or might be applied to measure different features of legal complexity. Next, the Article proposes methods for monitoring legal complexity over time, in particular by conceptualizing what we call Legal Maps—a multi-layered, active representation of the legal system network at work. Finally, the Article concludes with a preliminary examination of how the measurement and monitoring techniques could inform interventions designed to manage legal complexity by using currently available machine learning and user interface design technologies

Sustainability of marketing systems: systeming interpretation of hybrid car manufacturer and consumer communications

The purpose of this qualitative macromarketing investigation is to explore the issue of the sustainability of marketing systems. Drawing on complex systems thinking, an alternative logic of marketing systems and a methodological basis for interpreting communicated meanings are developed. The alternative logic of marketing systems recognises the unity of a difference between a marketing system and its environment. This insight has become a cornerstone for synthesising the systeming methodology. Systeming comprises the philosophy, the model, and the method of interpreting communication-as-self-observation of marketing system agents. Data, communication by hybrid car manufacturers and consumers, were collected from netnographic sources such as corporate websites, reports posted online, weblogs, and consumer forums. The interpretation of these data was accomplished using systeming procedures, e.g. communication analysis, distinction identification, re-entry description, and logical level tracking. The systeming analysis of the hybrid car marketer and consumer communications illustrates that meaning-creation in the system is underpinned by purposeful human behaviour in reducing complexity of marketplace experience into a meaningful pattern, sustainability. Both manufacturers and consumers claim to become sustainable in reference to being unsustainable by creating self-referential differences, operating in different interaction contexts, and expanding meaning paradoxes. The interpretation shows that interactive meaning-creation in the system is inherently contradictory. Manufacturers expand (give a logical form to) contradictions through introducing hierarchical meaning structures, temporality, new functions, and communicative transvection. Consumers deal with the contradictions through enriching co-creation experiences and learning the proper continuation of specific hybrid car driving practices. The significant insight gained from this investigation is that the hybrid car marketing system is not a passive entity; it is the locus of purposefully expanding meanings. Two modes of sustainability with regard to the hybrid car marketing system can be distinguished: the content of communication that denotes enacted meanings of sustainability and the form of communication that indicates how sustainable these sustainability enactments are. The content/form distinction implies that the sustainability of the hybrid car marketing system is a matter of interactive meaning-creation between system agents. The sustainable development process, in at least a mobility domain, is driven by purposeful social interaction rather than static product attributes. This investigation is innovative because it a) offers a conceptualisation of a marketing system as a meaning flow; b) synthesises and compiles a methodology and method for interpreting communication in a marketing system; c) reveals systemic insights into the hybrid car marketing system; d) characterises the sustainability dimension of the hybrid car marketing system; e) explains a conceptual ground for reconciling the marketing system and society; f) provides a general macromarketing perspective to scrutinise recent conceptual developments in the marketing discipline; g) unifies marketing systems thinking with recent advancements in the marketing discipline, such as the service-dominant logic, and consumer culture theory; and, also, h) provides recommendations for a number of micro-managerial situations from a holistic perspective