CFP | Simulation and dissimulation

Call for Papers to a special issues of Futures. The journal of policy, planning and futures studies [SSCI 2.769, Scopus, FNEGE**, CABS**] on

Simulation and dissimulation

Guest editors:

Steffen Roth*
Full Professor of Management, La Rochelle Business School, France
Adjunct Professor of Economic Sociology, University of Turku, Finland
*Corresponding proponent

Jari Kaivo-oja
Research Director of Futures Studies, University of Turku, Finland
Adjunct Professor of Planning and Management Sciences, University of Helsinki, Finland

Kristof van Assche
Full Professor of Planning, Governance, and Development, University of Alberta, Canada

Harry F. Dahms
Full Professor of Sociology, University of Tennessee, Knoxville, United States of America


This special issue focuses on the often precarious relationship between evidence and simulation, a topic that has been in need of close examination at least since the early 1970s, when the pioneers of futures studies developed or replicated the first global system dynamics models and computer simulations such as the “World3” model of Meadows et al. (1972).

Ever since, simulations have been applied to a broad spectrum of areas and topics, ranging from business strategy development, to aerospace and aviation engineering, traffic management.

On the one hand, simulations clearly help explore alternatives scenarios (Booth et al., 2009), theorise long waves (Forrester, 1976), anticipate or avoid undesirable short-, medium- or even long-term developments, or replace tests and experiments that would otherwise be unfeasible or dangerous. For example, simulations of nuclear weapons have been deemed sufficiently strong, reliable, and predictive to replace the testing of those weapons.

On the other hand, the 2007-2008 financial crisis had already underscored the tremendous impact and risks of economic models and financial simulations, and simulations also have played a key-role in the 2020 coronavirus crisis, with the results of model or simulation applications often having been confused with, or deliberately presented as evidence. More concretely, in the current crisis, simulations have been or are being used to

  • Detect, define, and assess the risk/extent of the COVID-19 pandemic,
  • Guide and justify the selection and implementation of the risk mitigation strategies, and
  • Assess the efficiency of the risk mitigation strategies.

In situations where problem definition, method choice, and success measurement are all based on simulations, however, we are confronted with the question of how we can at all distinguish between a simulated and an actual crisis. Overreliance on simulations may therefore be associated with the risk of (or suspicion regarding) academic or political dissimulation or immunization strategies that escape conventional forms of control or criticism (Andersen and Pors, 2019; Andersen and Stenner, 2020; Tosini, 2020). If simulations are confused with or replace classical methods, and entire research designs, theories, or fields of research turn into self-confirming networks of simulations, then science may indeed develop immunity against scrutiny and criticism and, thus, once again “become as oppressive as the ideologies it had once to fight” (Feyerabend, 2006, p. 360). Decision-making based on such simulated “truisms” and claims for the future might then result in the implementation of ill-informed or even deceitful policies.

These and similar issues are most critical both in the short-term assessment and management of the current coronavirus crisis and in the medium and long term. In fact, a recent simulation study published in Nature suggests that “prolonged or intermittent social distancing may be necessary into 2022” (Kissler et al., 2020). Given the tremendous extent of different types of collateral damage resulting from lockdowns and other non-pharmaceutical pandemic interventions, the impact simulations currently are having on life in general, and social life, in particular, could hardly be greater.

In the context of Futures Studies, Foresight and Anticipatory Systems, and against this backdrop, we welcome research papers and notes that are cognizant with the thin red lines between simulation and dissimulation, especially if they promise to illuminate general and/or specific aspects of the relationship between dis-/simulation and evidence, or address questions and challenges of the following non-exclusive type:

  • Simulation and ontology: What is (a) simulation? Prediction, discussion framework, plausible future?
  • Types of simulation: cognitive, prognostic, and crowdsourcing simulations (Zackery et al., 2016). What next?
  • Simulation and evidence: Since evidence of future developments and conditions is unavailable, can simulations even reliable predictive tools, and if, how?
  • Simulation, counter-factual reasoning, and the social construction of the future (Booth et al., 2009; Fuller and Loogma, 2009).
  • Simulation and risk perception: Post-normal science, risk assessment, and risk acceptance in times of uncertain facts and disputed values (Fuller, 2017; Funtowicz & Ravetz, 1993).
  • Simulation and normality: The role(s) of simulations in old normal, new normal, and/or post-normal science.
  • Open, closed, dynamic, anticipatory, or autopoietic: The impact of systems paradigms on predictive model designs and simulation outcomes (Fuller, 2017).
  • Simulations and extrapolation: How to overcome forecasting challenges via multidisciplinary approaches (Orrell and McSharry, 2009)?
  • Simulation and social differentiation (Grothe-Hammer and Berthod, 2016; Roth, Schwede, et al., 2019; Ward, 2003)?
  • Trust WHO: Dis-/simulation, dissemination, and mis-/trust (Luhmann, 2013, p.13).
  • The Great Reset: The role of simulations in “resetting our future state” (WEF, 2020).
  • Simulation, speculation, and abduction: Truth and inference in the age of big data and the digital transformation of theories (Deacon et al., 2018; Kitchin, 2014; Roth et al., 2019a; 2019b).
  • Simulation and gamification: How is learning organised in real-life simulation studies? What are tipping points when simulations feel or turn real?
  • Prospects and limitations of the use of simulations for understanding, visioning, and forecasting the complex post-coronavirus world.

Manuscript submission is open from 01 October 2020 to 30 June 2021. Manuscripts must constitute original research and comply with the Futures author guidelines. In the online system please ensure you submit your paper within Manuscript Type: ‘Virtual Special Issue: Simulation and Dissimulation’. Once accepted, articles submitted to our virtual special issue are published in a regular issue of Futures. Simultaneously, each accepted manuscript is added to the virtual special issue, which is gradually built up as individual manuscripts are published online in Futures. The advantage of this procedure is that it speeds up the publication of individual articles.

This virtual special issue is supported by members and convenors of the 14-02 and 12-03 tracks at the EURAM 2021 Conference in Montréal, the International Social Theory Consortium, and the Niklas Luhmann Conference series at the Inter-University Center Dubrovnik. Membership or participation in these networks or events is not a prerequisite for contributions to this virtual special issue.

Please do not hesitate to send an email to the corresponding proponent for informal enquiries on the virtual special issue.

See the CFP on the official journal website.

Author biographies:

Steffen Roth is Full Professor of Management at the La Rochelle Business School, France, and Adjunct Professor of Economic Sociology at the University of Turku, Finland. He holds a Habilitation in Economic and Environmental Sociology awarded by the Italian Ministry of Education, University, and Research; a PhD in Sociology from the University of Geneva; and a PhD in Management from the Chemnitz University of Technology. He is the field editor for social systems theory of Systems Research and Behavioral Science and has recently co-guest edited a special issue of Technological Forecasting and Social Change on the “Digital Transformation of Social Theory”. The journals his research has been published in include Journal of Business Ethics; Journal of Cleaner Production; Administration and Society; Technological Forecasting and Social Change; Journal of Organizational Change Management; European Management Journal; Sustainability Accounting, Management and Policy Journal; and Futures. His ORCID profile is available at

Michael Grothe-Hammer is Associate Professor of Organization and Technology at the Department of Sociology and Political Science of the Norwegian University of Science and Technology (NTNU) in Trondheim, Norway. His research interests include organization, digitalization, societal differentiation, and the sociology of crisis. He is a senior editor of the journal M@n@gement. His works have been published in journals such as Current Sociology, Journal of Public Administration Research and Theory, Public Administration, European Management Journal, and Organizational Research Methods.

Jari Kaivo-oja is Research Director at the Finland Futures Research Centre of the Turku School of Economics, University of Turku, as well as an Adjunct Professor at the University of Helsinki and at the University of Lapland. He is research professor at the Kazimieras Simonavičius University in Vilnius, Lithuania. He has worked for the European Commission (FP5-FP7 and Horizon 2020), the European Foundation, the Nordic Innovation Center (NIC), the Finnish Funding Agency for Technology and Innovation (TEKES), EUROSTAT, RAND Europe, the European Regional Development Fund, ERDF and for the European Parliament. Currently Dr Jari Kaivo-oja is a researcher at RISCAPE (Horizon 2020), at EL-TRAN (the Academy of Finland) and at MANUFACTURING 4.0 (the Academy of Finland). His research was published in journals such as Technological Forecasting and Social Change, Kybernetes, Sustainability, Journal of Cleaner Production, International Journal of Technology Management, European Journal of Futures Research, Long Range Planning, Foresight, Energy Policy, and Futures.

Kristof van Assche is Full Professor of Planning, Governance, and Development at the University of Alberta, Canada. He is particularly interested in evolution and innovation in governance, with focus areas in spatial planning and design, development and environmental policy. He worked in various countries, and often combines fieldwork with theoretical reflection: systems theories, interpretive policy analysis, institutional economics, post- structuralism. He held visiting positions at McGill University, Krakow Agricultural University, Wageningen University, Bonn University. Geographically, his work spans Europe, the America’s, Central Asia and the Caucasus. He published widely on these topics in journals such as Futures, Journal of Environmental Planning and Management, Land Use Policy, Society and Natural Resources, or Planning Theory.

Harry F. Dahms is Full Professor of Sociology, co-director of the Center for the Study of Social Justice, and co-chair of the Committee on Social Theory at the University of Tennessee, USA. Dahms’s primary research and teaching areas are theoretical sociology (social, sociological, and critical theory), economic sociology, globalization, social inequality, and social justice. He is the editor of Current Perspectives in Social Theory, and director of the International Social Theory Consortium (ISTC). His research was published in such journals as Sociological Theory, Critical Sociology, Basic Income Studies, Bulletin of Science, Technology, & Society, Fast Capitalism, Soundings:  An Interdisciplinary Journal, and numerous edited volumes.


  • Andersen, N. Å., & Pors, J. G. (2019). When no is not an option: The immunization against silence in a motivational interview about marijuana use. Social Theory & Health17(4), 443-462.
  • Andersen, N. Å., & Stenner, P. (2020). Social immune mechanisms: Luhmann and potentialization technologies. Theory, Culture & Society37(2), 79-103.
  • Booth, C., Rowlinson, M., Clark, P., Delahaye, A., & Procter, S. (2009). Scenarios and counterfactuals as modal narratives. Futures41(2), 87-95.
  • Deacon, L., Van Assche, K., Papineau, J., & Gruezmacher, M. (2018). Speculation, planning, and resilience: Case studies from resource-based communities in Western Canada. Futures104, 37-46.
  • Feyerabend, P. (2006). How to defend Society against Science?’ In Selinger, E. and Crease, R. P. (eds.) The Philosophy of Expertise. New York: Columbia University Press, pp. 358-369
  • Forrester, J. W. (1976). Business structure, economic cycles, and national policy. Futures8(3), 195-214.
  • Fuller, T., & Loogma, K. (2009). Constructing futures: A social constructionist perspective on foresight methodology. Futures41(2), 71-79.
  • Fuller, T. (2017). Anxious relationships: The unmarked futures for post-normal scenarios in anticipatory systemsTechnological Forecasting and Social Change124, 41-50.
  • Funtowicz, S. O., & Ravetz, J. R. (1993). Science for the post-normal age. Futures. 25, 739-
  • Kissler, S. M., Tedijanto, C., Goldstein, E., Grad, Y. H., & Lipsitch, M. (2020). Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period. Science. DOI: 10.1126/science.abb5793.
  • Kitchin, R. (2014). Big Data, new epistemologies and paradigm shifts. Big Data & Society1(1), 2053951714528481.
  • Meadows, D. H., Meadows, D. L.; Randers, J., and Behrens III, W. W (1972). The Limits to Growth; A Report for the Club of Rome’s Project on the Predicament of Mankind. New York: Universe Books.
  • Orrell, D., & McSharry, P. (2009). System economics: Overcoming the pitfalls of forecasting models via a multidisciplinary approach. International Journal of Forecasting25(4), 734-743.
  • Roth, S., Dahms, H. F., Welz, F., & Cattacin, S. (2019). Print theories of computer societies. Introduction to the digital transformation of social theoryTechnological Forecasting and Social Change149, 119778.
  • Roth, S., Schwede, P., Valentinov, V., Pérez-Valls, M., & Kaivo-Oja, J. (2020). Harnessing big data for a multifunctional theory of the firmEuropean Management Journal38(1), 54-61.
  • Roth, S., Schwede, P., Valentinov, V., Žažar, K., & Kaivo-oja, J. (2019). Big data insights into social macro trends (1800–2000): A replication studyTechnological Forecasting and Social Change149, 119759.
  • Tosini, D. (2020). Social immunology: A theory of the immune processes of social systems. Systems Research and Behavioral Science, DOI: 10.1002/sres.2664.
  • Ward, S. (2003). Honesty and dissimulation in upper-class interaction in early modern France: Madame and the old German sincerity. Seventeenth-Century French Studies25(1), 247-258.
  • WEF (2020). How we’re resetting our future state. Available at:
  • Zackery, A., Shariatpanahi, P., Zolfagharzadeh, M. M., & Pourezzat, A. A. (2016). Toward a simulated replica of futures: classification and possible trajectories of simulation in futures studies. Futures81, 40-53.

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