Model-based governance in a sustainable world

Computer modelling and simulation are increasingly used to support decision-makers in developing, testing, and implementing policies and strategies in real-world business domains.

This Special Issue (hereafter SI), entitled “Model-Based Governance in a Sustainable World”, specifically aims at establishing whether, and under which conditions, computer models and simulations effectively and accurately deal with complexity in policy-making and strategy development and implementation. The impacts generated by policy/strategy implementations have historically been very difficult to anticipate, due to the many complex and interconnected phenomena surrounding them (IPCC, 2014). Among them, factors such as dynamic complexity, causal ambiguity, and path dependency may severely hamper the ability of decision-makers to design and implement effective strategies and policies aimed at obtaining organisational resilience and hence sustainable results (Sterman, 2000).

The general notion of “sustainability” has been associated with environment, society, and politics. The definition of the 17 Sustainable Development Goals from the UN General Assembly (2015) has further widened the scope of this area. Therefore, one of the sources of inspiration for this SI is related to understanding the deep structural relationships underpinning the dynamics of sustainability in the different domains in which it operates. In this context, different paradigms, techniques, and approaches to computer modelling and simulation may play a relevant role, spanning from System Dynamics and Systems Thinking (Forrester, 1961, 1968; Richardson & Pugh, 1981; Senge, 1990; Meadows, 2008), to Agent-Based Modelling (Edmonds & Meyer, 2017), Discrete Event Simulations, etc. (Kunc, Morecroft et al., 2018). Among them, System Dynamics (SD) and Agent-Based Modelling (ABM) have demonstrated their validity for decades (Meadows et al., 1972), supplying models and tools particularly well suited to establish the basis for strategy development and implementation. They also enhance meaningful learning experiences about the relationships between structure and dynamics of complex systems (Miller & Page, 2009).

To address challenges in this area, and to deal with the main issues of “sustainability” and “effective impacts achievement” (also see Kunc, Mortenson et al., 2018), there are various areas in which further research is needed. The following list is not exhaustive, but provides an example of some of the most relevant of these research areas:

1. understanding and representing dynamic complexity and interdependencies;

2. promoting the understanding of short, medium- and long-term consequences of the implemented policies;

3. performing scenario analysis;

4. exploiting, in and through simulation, the growing amount of available data (big data), that presents significant problems in their analysis, interpretation and consequent managerial actions for policy makers;

5. combining the many modelling tools and techniques available today, so to capture the sometime intrinsic multidisciplinary nature of problems (i.e. combining ABM to describe agents behaviour with SD, to describe the behaviour of strategic level variables in a certain multilayered system), in order to be also able to share and exploit the knowledge of different domain specialists;

6. building and using simulation models and games to support long-term policy analysis and decision making;

7. developing advanced simulation tools for testing the resilience of business and governance systems;

8. managing unpredictability and uncertainty;

9. performing the evaluation of outcomes that are difficult to measure;

10. assessing (and hence support achieving) effective impacts through organisational resilience and sustainable governance;

11. supporting sustainable development through policy-modelling and simulation.

The SI attracted papers in almost all of the areas in the list above. While each paper has emphasised different aspects of these topic areas, the SI as a whole is concerned with all of them.

The SI’s related call for papers circulated widely among simulation communities and a total of 15 papers were received, 10 of which were accepted and feature into this SI, one more is published in a regular issue of the Journal of Simulation, while the remaining four were rejected. This very high acceptance rate is common for research that presents simulation work. In fact, since this type of research requires significant time and resources, and submitted papers usually make these efforts visible. In this editorial, we cover those papers that have been ultimately included in the SI.

Table 1 summarises the clusterization of these papers around four main topics related to the analysis and evaluation of policies in the sustainability arena, and aggregates them also according to the methodologies used in the various papers published in this SI. The categorisation is not to be intended such that papers belong necessarily to one only area, but they do map prominently on one of them. The four areas reflect a traditional sustainability triple-bottom line, with education being a focus on societal issues and finance being part of the wider economic area.

Table 1. Policy topics Vs used modelling & simulation methodologies

	Sustainability policies’ topics
Methodology	Environment	Society	Education	Finance
Agent-Based (ABM)	Madsen et al.	Dula et al. Secchi & Herath	Diaz et al.	Ermolova et al.
System Dynamics (SD)	Armenia et al. Carnohan et al. Perissi	Marafioti et al.	Andalib	-

Let us then move to present the structure of the SI. First of all, we should warn our readers that the included articles are published across the first two issues of the Journal of Simulation at the beginning of 2021: Volume 15, Issues 1 and 2. Each of the two issues includes five articles that, as mentioned above, effectively address key topics areas, and span across several modelling paradigms (i.e., System Dynamics, Agent-Based Modelling, and Discrete Event Simulations).

More specifically, the first of the two issues includes 4 articles that employ System Dynamics principles and tools and one employing ABM, to address a variety of decision-making issues, mostly on environmental sustainability-related topic areas.

The SI is introduced by the paper “Climate change adaptation in rural South Africa: Using stakeholder narratives to build system dynamics models in data-scarce environments” by Carnohan, Clifford-Holmes, Retief, McKnight and Pollard. The study uses stakeholder participatory modelling and introduces ResiMod, a System Dynamics model. Water management is one of the most relevant challenges that a sustainable world faces, hence building a consistent bridge between scientific knowledge and policy implementation is absolutely necessary. In their article, authors attempt to explain how this can be done via stakeholder engagement.

The paper “From reactive towards anticipatory fishing agents” by Madsen, Bailey, Carrella, and Koralus presents an individual-based approach to sustainability. Specifically, the authors use an agent-based simulation, POSEIDON, to model different cognitive frames that fishers may use when operating their boats in an area along the Californian coast in the USA. Depending on the mental frame, fishers exhibit different behaviours, hence informing potential policies aimed at preserving Marine Protected Areas.

The article by Andalib, “Simulation of the leaky pipeline: Gender diversity in U.S. K-graduate education”, aims at exploring the future trend of gender (dis)parity in the U.S. higher education and workforce populations by means of a system dynamics simulation model that explicitly addresses education pipelines for males and females and includes several mechanisms that reinforce interest in higher education, affect university admission, or dropout rates. The model forecasts that women will be the majority of university degree holders in the United States by 2035, hence reverting a trend which had historically been always in favour of men. The produced forecasts are in line with those produced by the US National Center of Education Statistics (NCES) even if the model provides a more informative forecast than other methods used by NCES. These benefits include better short- to mid-term forecasts than statistical methods and provide more flexibility in producing forecasts under various scenarios.

In the paper “Highlighting the archetypes of sustainability management by means of simple dynamics models” , Perissi introduces a set of simple system dynamics models with the aim of helping the understanding and the teaching of sustainability and sustainable dynamics to young people and non-specialist. In particular she focuses on modelling the dynamics of energy transition from fossil fuels to renewables energy, which is recognised as a priority in fighting climate change and in granting the future society with a clean and long-lasting energy supply.

The article by Armenia, Bellomo, Medaglia, Nonino, and Pompei, “Water resource management through systemic approach: The case of Lake Bracciano”, allows exploring and discussing how systemic simulation techniques can be effectively used to analyse water resource management issues. In more detail, the System Dynamics model developed by the authors was used for the evaluation of different strategies and policies in order to reduce environmental impacts, at the same time considering different climatic and context scenarios. The results of the simulations shown in the paper reveal relevant consequences that may derive from water management policies already in place – or planned for the future –, and may inform administrators, agencies and regulators to identify and carry out feasible policies.

The second issue discusses how modelling techniques and paradigms different from System Dynamics may contribute to the analysis and management of complex and dynamic domains. Topic areas are more concerned with socio-economic sustainability and, in particular, these articles assign specific relevance to Agent-Based Modelling.

The opening article “Agent-based model of the Russian banking system: Calibration for maturity, interest rate spread, credit risk, and capital regulation” by Ermolova, Leonidov, Nechitailo, Penikas, Pilnik, and Serebryannikova is concerned with policy implementation in the context of Basel III regulation. The logic of this article is somehow reverse to what seen in Issue 1 of this SI in that the starting point is a specific policy implementation. Using an agent-based simulation, the authors attempt at modelling various financial rules to allow the system as a whole to produce a more sustainable economy. The case is data-driven and it features the Russian banking system.

The article by Dula, Videira and Größler, titled “Degrowth dynamics: Modelling policy proposals with system dynamics”, focuses on a topic that has characterised the academic debate over the last few years, i.e., “degrowth” – commonly defined as a socially sustainable and equitable reduction of society’s throughput. Using the information gathered with an online questionnaire contacting experts in the field of degrowth, the Authors developed a System Dynamics model to better understand the underlying causal structure and subsequently to model policy-making. Results from this research confirm many of the experts’ predictions but also allow identifying potential unexpected consequences to be discussed and analysed further.

Díaz, Jiménez, and Larroulet’s article “An agent-based model of school choice with information asymmetries” takes the SI into a different domain, still relevant to both policy making and sustainability. The focus on education is applied with a data-driven approach, where authors use the school system in Santiago, Chile, to explore how different choice policies affect enrolment and, ultimately, achievement. This mix of empirical data and simulation modelling presents a relevant case to readers due to the immediacy of its applications to policy making.

In the paper “Parallel society: Myth or reality? A question for policy makers”, by Secchi and Herath, the authors explore the concept of parallel societies (areas displaying societal values that are “alternative” to those of actual civil society) by means of an agent-based computational modelling (ABM) approach. The authors argue on whether programmatic policy indications have some actual reflection on the formation of these “alternative values” areas such as, for example, in the case of location-based house pricing policies. In such a case, a fine tuning of pricing policies (in terms of price ranges and caps) may negatively affect residential segregation hence reducing, in turn, the possibility of establishing “alternative values” areas. Results ultimately show how modelling and simulation can effectively support policy making by means of investigating and assessing the potential impacts of such policies.

The article by Marafioti, Mollona and Perretti, titled “Long-term sustainability of clusters: A dynamic theory of declusterisation”, presents a System Dynamics model used to study the long-term counterintuitive consequences of internationalisation strategies of machinery producers in industrial clusters and proposes an explanation for declusterization. Overall, the paper provides findings and an original contribution as follows: 1. the article proposes an evolutionary perspective that highlights the need to understand the development of clusters’ lifecycle; 2. The study suggests that long-term, possibly undesired, consequences of clusters’ internationalisation may arise and should be considered carefully.

Overall, it is the Guest Editors’ opinion that all the articles included in this SI contributed to an effective analysis and consideration of the various topics we called for. In particular, it is striking to notice that all the authors attempted to make simulations relevant to actual cases, with a variety of approaches, perspectives, and applications. One of the strengths of this SI is that it presents a collection of technical options that modellers have when approaching policy modelling, especially in a sustainability context.

Notably, a wide range of ideas for further research and calls for more action in the field can be found in this SI and throughout the several articles included here. This will certainly open up magnificent opportunities for future research.