Managing Urban Sustainability in a Cooperative Interactive Learning Environment

Striving to contribute to the current debate on how facing the challenge of managing limited resources in a sustainable way, this paper focuses on the issue or urban sustainability. As many reports clearly state or underline (e.g., EEA 2015 and EU 2018), our urban environments are on the shrink of a huge collapse. Several reasons are at the basis of the problem (e.g., overcrowded population, pollution, traffic congestion, CO2 emissions, etc.) and a systemic approach to identify and understand their effects is advocated and at the center of a lively debate that engages both academics and practitioners (e.g., Sterman et al. 2015). Such approach is also recommended when organizing and running educational programs, not only in order to raise the students’ awareness about the complexity of urban sustainability (including the non-linearity of socio-technological processes and the need to consider multiple levels of the community and multiple sectors of governance and their interdependencies), but also to train properly the “policy-makers of tomorrow” in the context of urban sustainability. Interestingly, these issues are core to the lively debate swirling around the UN Sustainable Development Goals (in detail, the SDG n. 11 “Sustainable Cities and Communities” is particularly relevant for this study) and the Agenda 2030. By reproducing in a Stella environment a simulated city, this paper aims to: 1. investigate and discuss how strategically relevant resources can be identified, formally represented and managed in a simulated urban environment, in this case, a System Dynamics computer model mimicking the management of a medium-sized city; 2. test the System Dynamics simulation model in the form of an Interactive Learning Environment and with specific scenarios, in order to sustain knowledge acquisition and awareness on how we can achieve sustainable urban management and a balanced societal metabolism while taking into account formal decision-making. Two streams of research are used as the main theoretical references for this paper. First, the paper builds on the concept of “urban metabolism” (Pincetl et al. 2012; EU 2018). The model of urban metabolism aims to identify and analyze the interactions between the natural and the human systems in a specific region (or environment); therefore, this approach not only allows describing how the human-environment interaction takes place, but also explaining how this interaction entails and informs strategic decisions related to the management of the resources at disposal, subsequently generating an array of impacts and consequences (even in terms of harmful side-effects). Second, the paper builds on the concept of “anticipatory governance” (Fuerth, 2009; Quay, 2009; Guston, 2014). Recognizing the existence of high degrees of uncertainty and complexity in modern systems (e.g., social and environmental ones), anticipatory governance is a new model of decision making based on concepts of foresight and flexibility that “uses a wide range of possible futures to anticipate adaptation strategies, and then monitors change and uses these strategies to guide decision making” (Quay, 2010, p. 496). From a methodological point of view, the paper relies on System Dynamics principles and modelling tools (Forrester 1961 and 1968, Richardson and Pugh 1981, Sterman 2000). Specifically, a System Dynamics computer model is used to portray the urban environment (i.e., the simulated city) under analysis and considers several sectors to be administrated and managed, as follows: urban planning, energy, transport, water management, waste management, and investment decisions. The SD model is then transformed into an Interactive Learning Environment (see Davidsen 2000, Davidsen and Spector 2015; Alessi and Kopainsky 2015) subsequently used to explore the effects of managerial decisions related to the concepts of urban metabolism and anticipatory governance as aforementioned. The focus of the SD-based ILE is mainly an educational one (see Morecroft and Sterman 2000) and the “game” provided within the ILE presents the following characteristics: a) the game can be played as a single or a multiplayer simulation; b) if played as a multiplayer game, it is an asymmetric one; c) the game is meant to be a cooperative one, with the players (if more than one) called to collaborate to manage the urban environment sustainably. In terms of expected findings and contribution, the paper highlights how ILE-supported simulations allow exploring the effects generated by the players’ decisions related to the urban environment, with specific regard to the link that brings routinely human and business activities carried out in an urban environment to (positively and negatively) impact on the urban environment itself (e.g., in terms of new job opportunities which are offered, but also in terms of CO2 emissions that are generated). Subsequently, the main expected contribution of this study lies in its ability to increase players’ (i.e., students’) awareness about urban sustainability-related issues, and acquire a better ability to imagine, therefore anticipate, recurrent dynamics on the basis of common feedback structures, such widespread learning in a public organization can foster an anticipatory approach to governance, rather than reactive. Notably, the SD model and the SD-based ILE are two of the outputs of a research project named “SUSTAIN”: specifically, SUSTAIN is an ERASMUS+ project with an innovative perspective on urban sustainability, whose main goal is to promote the importance of sustainability on the everyday problems of the cities among the students of Higher Education institutions, which are the ones that will shape the future.