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Sustainability policy in the early 2000s is based on and therefore influenced by scientific literature on "transition". The importance of this link has inspired the authors to explore the structure of cooperating authors and citation networks in the field. In order to understand "transition" literature, we compare it with an alternative term for change, "transformation", which is also used in the context of socio-technical shifts towards sustainability. We expose the different structures of these fields with an overview of keywords, key references, key authors, and the coherence between references and authors. By analysing co-author and citation networks, we find large differences in these groups of documents. The transition literature is characterised by a large network of directly and indirectly cooperating authors with clear clusters; transformation literature contains smaller author networks. Key transition authors are predominantly Dutch. They repeatedly write together and cite each other's work. The transition literature is tightly knit with high degrees of internal references and a clearly distinguishable core. Transformation literature has fewer connections between authors and articles. The connecting articles, each with many global citations, form its basis. This analysis can be used as a step to continue the debate on the role of transition and transformation literature in sustainability and renewable energy policy. The transformation literature teaches us that older streams of thought are still relevant and may be used as "glue" for linking change with respect to sustainable energy to wider developments. Rediscovering existing literature in new combinations may lead to promising new views on sustainable energy.
The buildings sector accounts for more than 30% of global greenhouse gas emissions. Despite the well-known economic viability of many energy-efficient renovation measures which offer great potential for reducing greenhouse gas emissions and meeting climate protection targets, there is a relatively low level of implementation. We performed a citation network analysis in order to identify papers at the research front and intellectual base on energy-efficient renovation in four areas: technical options, understanding decisions, incentive instruments, and models and simulation. The literature was reviewed in order to understand what is needed to sufficiently increase the number of domestic energy-efficient renovations and to identify potential research gaps. Our findings show that the literature on energy-efficient renovation gained considerable momentum in the last decade, but lacks a deep understanding of the uncertainties surrounding economic aspects and non-economic factors driving renovation decisions of homeowners. The analysis indicates that the (socio-economic) energy saving potential and profitability of energy-efficient renovation measures is lower than generally expected. It is suggested that this can be accounted for by the failure to understand and consider the underpinning influences of energy-consuming behaviour in calculations. Homeowners׳ decisions to renovate are shaped by an alliance of economic and non-economic goals. Therefore, existing incentives, typically targeting the economic viability of measures, have brought little success. A deeper understanding of the decisions of homeowners is needed and we suggest that a simulation model which maps the decision-making processes of homeowners may result in refining existing instruments or developing new innovative mechanisms to tackle the situation.
Societal transitions involve multiple actors, changes in institutions, values and technologies, and interactions across multiple sectors and scales. Given this complexity, this paper takes on the view that the societal transitions research field would benefit from the further maturation and broader uptake of modelling approaches. This paper shows how modelling can enhance the understanding of and support stakeholders to steer societal transitions. It discusses the benefits modelling provides for studying large societal systems and elaborates on different ways models can be used for transitions studies. Two model applications are presented in some detail to illustrate the benefits. Then, limitations of modelling societal transitions are discussed, which leads to an agenda for future activities: (1) better cooperation in the development of dynamic models, (2) stronger interaction with other transition scholars and stakeholders, and (3) use of additional modelling approaches that we think are relevant to and largely unexplored in transitions studies.
Heating behavior of households is key for reducing domestic energy demand and mitigating climate change. Recently, various technical devices have been developed, providing households with feedback on their heating behavior and supporting energy conservation behavior.
The impact of such devices on overall energy consumption depends on (1) the impact of a device within a household, (2) the diffusion of devices to other households and the number of adopters, and (3) the diffusion of the induced behavioral change beyond these households. While the first two processes are currently established in assessments of sustainable household devices, we suggest that adding behavior diffusion is essential when assessing devices that explicitly target behavioral change. We therefore propose an assessment framework that includes all three processes. We implement this framework in an agent-based model by combining two existing simulation models to explore the effect of adding behavior diffusion. In three simulation experiments, we identify two mechanisms by which behavior diffusion (1) spreads the effect of such devices from adopters to non-adopters and (2) increases the average speed of behavioral change of households. From these results we conclude that behavior diffusion should be included in assessments of behavior-changing feedback devices.
Insulating existing buildings offers great potential for reducing greenhouse gas emissions and meeting Germany's climate protection targets. Previous research suggests that, since homeowners' decision-making processes are inadequately understood as yet, today's incentives aiming at increasing insulation activity lead to unsatisfactory results. We developed an agent-based model to foster the understanding of homeowners' decision-making processes regarding insulation and to explore how situational factors, such as the structural condition of houses and social interaction, influence their insulation activity. Simulation experiments allow us furthermore to study the influence of socio-spatial structures such as residential segregation and population density on the diffusion of renovation behavior among homeowners. Based on the insights gained, we derive recommendations for designing innovative policy instruments. We conclude that the success of particular policy instruments aiming at increasing homeowners' insulation activity in a specific region depends on the socio-spatial structure at hand, and that reducing financial constraints only has a relatively low potential for increasing Germany's insulation rate. Policy instruments should also target the fact that specific renovation occasions are used to undertake additional insulation activities, e.g. by incentivizing lenders and craftsmen to advise homeowners to have insulation installed.
A key factor to energy-efficiency of heating in buildings is the behavior of households, in particular how they ventilate rooms. Energy demand can be reduced by behavioral change; devices can support this by giving feedback to consumers on their behavior. One such feedback device, called the "CO2 meter", shows indoor air-quality in the colors of a traffic light to motivate so called "shock ventilation", which is energy-efficient ventilation behavior. The following effects of the "CO2 meter" are analyzed: (1) the effect of the device on ventilation behavior within households, (2) the diffusion of "CO2 meter" to other households, and (3) the diffusion of changed behavior to households that do not adopt a "CO2 meter". An agent-based model of these processes for the city of Bottrop (Germany) was developed using a variety of data sources. The model shows that the "CO2 meter" would increase adoption of energy-efficient ventilation by c. 12% and reduce heating demand by c. 1% within 15 years. Technology diffusion was found to explain at least c. 54% of the estimated energy savings; behavior diffusion explains up to 46%. These findings indicate that the "CO2 meter" is an interesting low-cost solution to increase the energy-efficiency in residential heating.