Sustainable development is a long-term endeavour involving deep uncertainty and requiring transformative change at multiple scales. To navigate such a grand challenge, new approaches have been developed in various academic fields, such as Policy Analysis and Sustainability Transitions. Two prominent approaches to strategic planning within these two fields are Decision Making under Deep Uncertainty (DMDU) and Transition Management (TM). While DMDU provides analytical concepts and tools to prepare for change (one that happens anyway, whether or not we desire it), TM offers a governance approach to condition change (one that we desire). We argue that the sustainable development agenda could benefit from an explicit cross-fertilisation across the two approaches. We will highlight the commonalities and differences between the two approaches and reflect on potential cross-connections. We argue that DMDU can benefit from the participatory process of TM, and its interventionist approach, which helps to mobilise actors and build networks for sustainability transformations. DMDU can also learn from some of the governance instruments offered by TM, such as visioning, experimentation, and social learning to better prepare for change that can only be dealt with through transformative actions. TM, on the other hand, can be enriched by analytical concepts and tools developed by and widely used in DMDU, such as tipping points and signposts, exploratory scenarios, and Exploratory Modelling, to operationalise transition pathways into actionable policy decisions. An illustrative example is used to demonstrate what a cross-connection between the two approaches might look like.

Modeling is a crucial approach for understanding the past and exploring the future of coupled human-natural systems. However, uncertainty in various forms challenges inferences from modeling results. Model-based support for decision-making has increasingly adopted an emerging exploratory approach. This approach addresses uncertainty explicitly through systematically exploring the implications of modeling assumptions, aiming to enhance the robustness of inferences from models. Despite a variety of applications, the extent and the way(s) that exploratory modeling can deal with the challenges that arise from the uncertainty and complexity of decision-making with stakeholders has not yet been systematically framed. We address this gap in two ways. First, we present a taxonomy of the ways that exploratory modeling can be used to inform robust inferences in coupled human-natural systems by mapping the technical capabilities of this approach in relation to the diversity of past applications. This subsequently guides an investigation of the practical benefits and challenges of these capabilities in handling uncertainty and complexity. Second, we discuss different ways for integrating genuine stakeholder engagement into exploratory modeling through transdisciplinary research. Finally we outline some priorities for future expansion of this research area.

Transition modelling is an emerging but growing niche within the broader field of sustainability transitions research. The objective of this paper is to explore the characteristics of this niche in relation to a range of existing modelling approaches and literatures with which it shares commonalities or from which it could draw. We distil a number of key aspects we think a transitions model should be able to address, from a broadly acknowledged, empirical list of transition characteristics. We review some of the main strands in modelling of socio-technological change with regards to their ability to address these characteristics. These are: Eco-innovation literatures (energy-economy models and Integrated Assessment Models), evolutionary economics, complex systems models, computational social science simulations using agent based models, system dynamics models and socio-ecological systems models. The modelling approaches reviewed can address many of the features that differentiate sustainability transitions from other socio-economic dynamics or innovations. The most problematic features are the representation of qualitatively different system states and of the normative aspects of change. The comparison provides transition researchers with a starting point for their choice of a modelling approach, whose characteristics should correspond to the characteristics of the research question they face. A promising line of research is to develop innovative models of co-evolution of behaviours and technologies towards sustainability, involving change in the structure of the societal and technical systems.

Energy transitions unfold under the influence of socio-technical, political and economic uncertainties. This paper introduces a narrative-informed exploratory approach for analysing future energy transition pathways under these uncertainty conditions. In this approach, exploratory modelling is used to explore the impact of various uncertainties, such as potential installed capacity and supporting policies for different energy options, on the unfolding of transition pathways. The approach produces several sets of scenarios. We complement this quantitative exploration of the future with narratives (storylines) generated based on the concepts in the sustainability transitions field. Narratives are used (i) as a supporting framework for model structure; (ii) to guide the exploration of the future; and (iii) to interpret the ensemble of quantitative scenarios. We describe how synergies between narratives and exploratory modelling inform both the framed and open-ended exploration of future transition pathways. The approach is demonstrated with a case study of the transition in India's electricity sector. We show that the realisation of the 100 GW solar electricity target by 2022 is unlikely, and that the development of solar electricity is highly dependent on the active role of government.