The Advent of Practice Theories in Research on Sustainable Consumption: Past, Current and Future Directions of the Field

The application of practice theories in the domain of sustainability research in consumer studies is increasingly advocated based on the premise that this allows to analyse consumption as a social phenomenon. Consequently, the applications of social practice theories to this field are expanding geometrically and to date, little retrospective work on this evolution has been made. We conduct a bibliometric analysis of applications of practice theories in the domain of sustainability research in consumer studies. Our results show a temporal succession of research trends: ‘consumer identity’ dominated the field between 2009 and 2012, ‘business and governance’ between 2012 and 2014, ‘sustainable consumption and production’ between 2013 and 2014, ‘urban living and policy’ between 2014 and 2015 and ‘household energy’ from 2015 until the present. We see a high potential of future applications of practice theories in the fields of the sharing and circular economy, as well as in research on smart cities. We provide new insights into the evolution and future trends of applications of social practice theory to domains that are relevant for research on sustainability and consumer studies

Effective strategies for multi-sectoral research using large-scale models

Large-scale integrated assessment models (IAMs) have become critical knowledge objects and tools for global-scope simulation of energy, economic, engineering, and environmental systems. IAMs are widely used in assessment of climate change mitigation (for instance, within the IPCC) and other Sustainable Development Goals (SDGs). In order to sharpen the relevance of insights from large-scale modeling, researchers often link them into multi-model frameworks together with detailed sectoral (sub-)models of, for instance, transport and mobility; the building stock; critical materials; or water use—or with models of narrower scope (e.g. national or sub-national) but finer resolution. These links capture feedbacks and interactions that may strongly shape transitions to comprehensive sustainability. This presentation begins with current expectations that guide IAM-based research. In particular, it is no longer satisfactory that individual models and 1-to-1 frameworks can analyse, for instance, (a) possible recoveries from the COVID-19 pandemic; (b) the long-term evolution of transport and mobility; and (c) the energy and climate impacts of changing materials flows. Increasingly, stakeholders require assessments that are both integrated *and* highly detailed in multiple sectors/areas such as these. Teams are challenged to produce this knowledge while also progressing in openness, transparency, reproducibility, and validity of research. I argue that meeting these challenges requires systems researchers and modelers to acknowledge that they are engaged in processes of collaborative software development: models are, in an important sense, also complex, long-lived, and evolving pieces of software. This perspective motivates the use of strategies that are common in professional software development, yet woefully underutilized in academia and research: standardization, testing, modularity and reuse, an emphasis on documentation, and iterative workflows with short cycle times. Using the example of the MESSAGEix-GLOBIOM family of models developed by the IIASA Energy, Climate, and Environment (ECE) Program, I demonstrate how adopting best practices of development translates to better science that uses people and resources more efficiently. For instance, the practice of unit-testing code is also a scientific strategy for ensuring internal validity: when code implements research methods, then automated tests ensure that those methods are correct representations of the phenomena represented. This in turn avoids exhausting researchers' time in performing manual validity checks. Next, the practice of modularity entails clearly-defined interfaces: in multi-sectoral or cross-domain integrated assessment frameworks, this is achieved through clear definitions of the background concepts, measures, scales, and system boundaries. Making these items explicit helps researchers see quickly and precisely what translation is required to make (sub-)models interoperable with one another. Finally, sustainability requires the very research processes that support the transition to be equitable and inclusive. I explain how the practices of making software free and open source, writing complete documentation, and continuous development lower barriers to understanding and participating in IAM-based research, especially for those not privileged to work at the few institutions that have the resources to maintain large-scale models. As well, a broad user base translates to a flow of contributions, improved model quality, and ultimately improved perceptions of legitimacy for modeling work

Rate-Induced Transitions in Networked Complex Adaptive Systems: Exploring Dynamics and Management Implications Across Ecological, Social, and Socioecological Systems

Complex adaptive systems (CASs), from ecosystems to economies, are open systems and inherently dependent on external conditions. While a system can transition from one state to another based on the magnitude of change in external conditions, the rate of change -- irrespective of magnitude -- may also lead to system state changes due to a phenomenon known as a rate-induced transition (RIT). This study presents a novel framework that captures RITs in CASs through a local model and a network extension where each node contributes to the structural adaptability of others. Our findings reveal how RITs occur at a critical environmental change rate, with lower-degree nodes tipping first due to fewer connections and reduced adaptive capacity. High-degree nodes tip later as their adaptability sources (lower-degree nodes) collapse. This pattern persists across various network structures. Our study calls for an extended perspective when managing CASs, emphasizing the need to focus not only on thresholds of external conditions but also the rate at which those conditions change, particularly in the context of the collapse of surrounding systems that contribute to the focal system's resilience. Our analytical method opens a path to designing management policies that mitigate RIT impacts and enhance resilience in ecological, social, and socioecological systems. These policies could include controlling environmental change rates, fostering system adaptability, implementing adaptive management strategies, and building capacity and knowledge exchange. Our study contributes to the understanding of RIT dynamics and informs effective management strategies for complex adaptive systems in the face of rapid environmental change.Comment: 25 pages, 4 figures, 1 box, supplementary informatio

The Green Experiment: Cities, Green Stormwater Infrastructure, and Sustainability

Green infrastructure is a unique combination of economic, social, and environmental goals and benefits that requires an adaptable framework for planning, implementing, and evaluating. In this study, we propose an experimental framework for policy, implementation, and subsequent evaluation of green stormwater infrastructure within the context of sociotechnical systems and urban experimentation. Sociotechnical systems describe the interaction of complex systems with quantitative and qualitative impacts. Urban experimentation—traditionally referencing climate change programs and their impacts—is a process of evaluating city programs as if in a laboratory setting with hypotheses and evaluated results. We combine these two concepts into a singular framework creating a policy feedback cycle (PFC) for green infrastructure to evaluate municipal green infrastructure plans as an experimental process within the context of a sociotechnical system. After proposing and discussing the PFC, we utilize the tool to research and evaluate the green infrastructure programs of 27 municipalities across the United States. Results indicate that green infrastructure plans should incorporate community involvement and communication, evaluation based on project motivation, and an iterative process for knowledge production. We suggest knowledge brokers as a key resource in connecting the evaluation stage of the feedback cycle to the policy phase. We identify three important needs for green infrastructure experimentation: (i) a fluid definition of green infrastructure in policy; (ii) maintenance and evaluation components of a green infrastructure plan; and (iii) communication of the plan to the community