Online ISSN: 2372-8590
Volume 1, Number 2, Fall 2014
The PSO is pleased to announce a new open access journal to be published twice a year, which began in the Spring of 2014. The peer-reviewed journal provides a platform whereby researchers, policy makers, experts in relevant disciplines, and modelers can join together to offer scientifically valid and societally appropriate solutions to challenging problems facing the world today, from the perspective of systems and complexity science.
Aims and Scope
- Promote professional and public understanding of the relationship between policy studies and complex systems thinking, evolving greater understanding and engagement.
- Establish a venue for reporting results of exploring, developing, and evaluating policies using cutting edge computational approaches to policy research, including complexity theory, agent-based modeling/simulation, chaos theory, fractals, dynamical systems, and the science of networks.
- Establish a repository of data and systems developed through research efforts reported in the journal.
- Bring together a community of multi-disciplinary and inter-disciplinary scholars to address common societal concerns; including social scientists, natural scientists, computational scientists, humanists, policy analysts, public administrators, and policy makers.
The world around us is a complex web of relationships connecting people, companies, countries, cells, or species into a system that provides the context for our daily existence. Given this complexity, it is hard to imagine any interesting problem that can be solved in isolation, i.e. without taking into consideration the adequate representation of both system constituent components and their mutual influences. Under such circumstances, it is imperative that our policies at all levels (local, state, country, the world), intended to regulate such systems, take into consideration this richness of both relevant system elements and relationships among them.
Events get even more complicated when we are faced with natural and social systems that include transitions and oscillations among their various phases. A new phase begins when the system reaches a threshold that marks the point of no return. These threshold effects are found all around us. In economics, this could be movement from a bull market to a bear market; in sociology, it could be the spread of political dissent, culminating in rebellion; in biology, the immune response to infection or disease as the body moves from sickness to health; in ecology, it could be an unchecked growth of species due to the removal of a top-level predator in the system; in healthcare, it could be an uneven access to services due to the poorly devised policy regulating health insurance policies. Companies, societies, markets, or humans rarely stay in a stable, predictable state for long. Randomness, power laws, and human behavior ensure that the future is both unknown and challenging. How do events unfold? When do they take hold? Why do some initial events cause an avalanche while others do not? What characterizes these events? What are the thresholds that differentiate a sea change from insignificant variation? And, most importantly, what can we do at the policy level to promote activities that will bring about positive, long-term, and sustainable changes in the system of interest?
Many methods and techniques have been developed to deal with the complexity of systems, including systems dynamics, fractals, chaos theory, science of networks, and complexity theory. They provide a powerful set of tools to model and/or simulate phenomena that are characterized by their scale-free and/or small-world network structure, sensitivity to initial conditions, power-law distributions, adaptability, self-organization, feedback loops, and emergent properties. However, applying such tools on any real-world problem will require the mastery of intricacies of both public policy and a wide variety of discipline-specific expertise, working together to uncover principles that both transcend and complement disciplinary contributions.
Consequently, we are proposing a new journal, Journal of Policy and Complex Systems, focused on providing the platform where policy makers, experts in relevant disciplines, and modelers will come together to offer scientifically valid and societally appropriate solutions to the most challenging problems facing the world today.
Mirsad Hadžikadić, Complex Systems Institute, UNC Charlotte
Liz Johnson, Complex Systems Institute, George Washington University
Pietro Terna, University of Turin, Italy
Adrian Palacios, Instituto de Sistemas Complejos de Valparaiso and Universidad de Valparaiso, Chile
Joseph Whitmeyer, UNC Charlotte
Robert Geyer, Lancaster University, UK
Michael Givel, University of Oklahoma
Jaehwa Choi, George Washington University
Calestous Juma, Harvard University
Caroline Wagner, Battelle Center for Science & Technology Policy
Ugo Merlone, University of Torino, Italy
Riccardo Boero, Los Alamos National Laboratory
Mark Esposito, Harvard University and University of Cambridge
Ismael Rafols, Universitat Politècnica de València, Spain
Nicoletta Corrocher, Department of Management and Technology, Bocconi University
George A. Kaplan, Center for Social Epidemiology & Population Health, University of Michigan
Ricardo Hausmann, Harvard University and Santa Fe Institute
Daniel Kim, Bouvé College of Health Sciences, Northeastern University
Magda Fontana, Collegio Carlo Alberto
Public Policy, Political science, Public administration, Economics, Public health, International development, Globalization, United States, South America, Africa, Europe, Complexity, Complex adaptive systems, Information technology, Computer science, Applied mathematics, Artificial intelligence, Neuroscience, Sociology, Counseling, Human development and learning, Educational leadership, Applied philosophy, Ethics.
Simulations, Agent-based modeling, Network science, Neural networks, Advanced statistics (structural equation modeling and latent growth models), Case study, Qualitative research in complexity context, Game theory.