Using Data on Social Influence and Collective Action for Parameterizing a Geographically-Explicit Agent-Based Model for the Diffusion of Soil Conservation Efforts

Social influence affects individual decision-making on soil conservation. Understanding the emergent diffusion of collective conservation effort is relevant to natural resource management at the river basin level. This study focuses on the effect of subjective norms and collective action on the diffusion of Soil Conservation Effort (SCE) in the Lake Naivasha basin (Kenya) for the period 1965–2010. A geographically-explicit Agent-Based Model (ABM) version of the CONSUMAT model was developed: the CONSERVAT model. In our model, we have represented heterogeneity in the physical environment and in the social network using empirical data. To parameterize the model, physical data, and social data from a household survey (n = 307) were used. Model simulation results show that it is possible to reproduce empirical spatiotemporal diffusion patterns of SCE levels which are quite sensitive to the way in which social survey data are used to initialize the model. Overall, this study demonstrates (i) that social survey data can effectively be used for parameterization of a geographically-explicit ABM, and (ii) that empirical knowledge on natural environment characteristics and social phenomena can be used to build an agent-based model at the river basin level. This study is an important first step towards including subjective norms for evaluating the effectiveness of alternative policy strategies for natural resource management.</p

Transition to low-carbon economy: Assessing cumulative impacts of individual behavioral changes

© 2018 The Authors Changing residential energy demand can play an essential role in transitioning to a green economy. Environmental psychology suggests that behavioral changes regarding energy use are affected by knowledge, awareness, motivation and social learning. Data on various behavioral drivers of change can explain energy use at the individual level, but it provides little information about implications for macro energy demand on regional or national levels. We address this challenge by presenting a theoretically-based and empirically-driven agent-based model to track aggregated impacts of behavioral changes among heterogeneous households. We focus on the representation of the multi-step changes in individual energy use behavior and on a quantitative assessment of their aggregated impacts on the regional level. We understand the behavioral complexity of household energy use as a dynamic process unfolding in stages, and explore the barriers for utilizing the full potential of a region for emissions reduction. We suggest a policy mix that facilitates mutual learning among consumers

A review of agent-based modelling of climate-energy policy

Unidad de excelencia María de Maeztu CEX2019-000940-MAltres ajuts: Russian Science Foundation. Grant Number: 19-18-00262Agent-based models (ABMs) have recently seen much application to the field of climate mitigation policies. They offer a more realistic description of micro behaviour than traditional climate policy models by allowing for agent heterogeneity, bounded rationality and non-market interactions over social networks. This enables the analysis of a broader spectrum of policies. Here, we review 61 ABM studies addressing climate-energy policy aimed at emissions reduction, product and technology diffusion, and energy conservation. This covers a broad set of instruments of climate policy, ranging from carbon taxation and emissions trading through adoption subsidies to information provision tools such as smart meters and eco-labels. Our treatment pays specific attention to behavioural assumptions and the structure of social networks. We offer suggestions for future research with ABMs to answer neglected policy question

Investigating the Role of Occupants, Complex Contextual Factors, and Norms on Residential Energy Consumption.

Human behavior in the built environment has repeatedly been found to have significant meaningful impact on energy consumption. As a consequence researchers have spent considerable efforts investigating various approaches to induce improved occupant behavior, with much recent attention on the use of normative approaches. However, it still remains unclear as to how occupants behave in buildings, how complex factors influence behavioral interventions, and what the long term effects of intervening are. With this background in mind, there are three broad goals in this research: (1) to improve our understanding of the impact of occupant decision making in residential energy consumption, (2) to enhance our understanding of how individual characteristics and complex contextual factors influence change in individual behavior and its diffusion through communities when subjected to normative intervention, and (3) to identify more effective normative behavioral strategies for reducing energy consumption in the built environment. In order to achieve these diverse research objectives, I conducted four interrelated studies based on an iterative research framework that applies an interdisciplinary research approach integrating field experiments with computational modeling. Through these studies it was found that: (1) vast quantities of energy are spent in unoccupied residences and that the percentage of energy consumed while unoccupied in a residence is unrelated to total use; (2) when applying behavior interventions social network structure can meaningfully affect how behavior diffuses and intervention outcome; (3) normative messaging duration positively influenced the durability of behavior change; (4) not all individuals were equally influenced by normative messaging with high norm individuals reducing energy consumption and low norm individuals increasing consumption; (5) by exploiting behavioral responses to normative messaging significant reductions in energy consumption could conceptually be achieved. These findings improve our understanding of occupant behavior, how occupants are influenced by social forces in the built environment, and how complex contextual factors moderate the diffusion of behavior. Further, the findings provide insight into how to improve the environmental sustainability of buildings through behavioral approaches.PhDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113508/1/kyleand_1.pd

Sustainable consumption: towards action and impact. : International scientific conference November 6th-8th 2011, Hamburg - European Green Capital 2011, Germany: abstract volume

This volume contains the abstracts of all oral and poster presentations of the international scientific conference „Sustainable Consumption – Towards Action and Impact“ held in Hamburg (Germany) on November 6th-8th 2011. This unique conference aims to promote a comprehensive academic discourse on issues concerning sustainable consumption and brings together scholars from a wide range of academic disciplines. In modern societies, private consumption is a multifaceted and ambivalent phenomenon: it is a ubiquitous social practice and an economic driving force, yet at the same time, its consequences are in conflict with important social and environmental sustainability goals. Finding paths towards “sustainable consumption” has therefore become a major political issue. In order to properly understand the challenge of “sustainable consumption”, identify unsustainable patterns of consumption and bring forward the necessary innovations, a collaborative effort of researchers from different disciplines is needed

Ten questions concerning integrating smart buildings into the smart grid

Recent advances in information and communications technology (ICT) have initiated development of a smart electrical grid and smart buildings. Buildings consume a large portion of the total electricity production worldwide, and to fully develop a smart grid they must be integrated with that grid. Buildings can now be ‘prosumers’ on the grid (both producers and consumers), and the continued growth of distributed renewable energy generation is raising new challenges in terms of grid stability over various time scales. Buildings can contribute to grid stability by managing their overall electrical demand in response to current conditions. Facility managers must balance demand response requests by grid operators with energy needed to maintain smooth building operations. For example, maintaining thermal comfort within an occupied building requires energy and, thus an optimized solution balancing energy use with indoor environmental quality (adequate thermal comfort, lighting, etc.) is needed. Successful integration of buildings and their systems with the grid also requires interoperable data exchange. However, the adoption and integration of newer control and communication technologies into buildings can be problematic with older legacy HVAC and building control systems. Public policy and economic structures have not kept up with the technical developments that have given rise to the budding smart grid, and further developments are needed in both technical and non-technical areas

Simulation based decision support for strategic communication and marketing management concerning the consumer introduction of smart energy meters

Communication and marketing professionals make strategic decisions in highly complex and dynamic contexts. These decisions are highly uncertain on the outcome and process level when, for example, consumer behaviour is at stake. Decision support systems can provide insights in these levels of uncertainty and the professional process of decision making. However, literature describing decision support tools for strategic communication and marketing management that provide clear insights in uncertainty levels is lacking. This study therefore aims at developing a consumer behaviour simulation module as an important element of such a future decision support tool. The consumer behaviour simulation we propose in this paper is based on data collected from a survey among 386 households with which a behavioural change model was calibrated. We show how various decision scenarios for strategic communication and marketing challenges can be explored and how such a simulation based decision support system can facilitate strategic communication and marketing management concerning the introduction of a smart energy meter

Modelling and Simulation of Human-Environment Interactions

Computational models provide intelligent environmental decision support systems to understand how human decisions are shaped by, and contribute to changes in, the environment. These models provide essential tools to tackle the important issues raised by climate change, including migrations and conflicts due to resource scarcity (e.g., water resources), while accounting for the necessity of co-managing ecosystems across a population of stakeholders with diverse goals. Such socio-environmental systems are characterized by their complexity, which is reflected by an abundance of open questions. This book explores several of these open questions, based on the contributions from over 50 authors. While several books account for methodological developments in modeling socio-environmental systems, our book is unique in combining case studies, methodological innovations, and a holistic approach to training the next generation of modelers. One chapter covers the ontological, epistemological, and ethical issues raised at the intersection of sustainability research and social simulation. In another chapter, we show that the benefits of simulations are not limited to managing complex eco-systems, as they can also serve an educational mission in teaching essential rules and thus improve systems thinking competencies in the broader population

Barriers and Motivators of Household Water-Conservation Behavior: A Bibliometric and Systematic Literature Review

Water scarcity, aggravated by growing demands, represents a significant challenge for humanity. Promoting household sustainable water-consumption behaviors has become vital. The Community-Based Social Marketing (CBSM) framework stands out among many strategies to promote water conservation. However, many interventions in this domain often neglect significant theoretical insights, leading to gaps in addressing key social and contextual drivers of behavior. This study conducts a systematic and bibliometric literature review aimed at identifying determinants underlying household water-conservation behaviors. This review encompasses 155 papers published from 1984 to early 2023. Our findings show that this is a highly multidisciplinary field of study with a marked increase in research attention discerned post-2010, particularly from water-stressed regions. Furthermore, our findings also reveal an often-overlooked integration of guiding theories and an over-reliance on self-reported measures in prior research. Factors such as attitude, perceived efficacy, emotions, and habits emerge as pivotal in understanding water conservation. However, while attitudes have been extensively analyzed in previous research, the other factors deserve greater attention from researchers. Inconsistencies in demographic predictors further hint at potential moderating roles. This paper offers valuable insights for designing effective household water-conservation interventions through a social marketing lens.This research was funded by Generalitat Valenciana (Emerging Project GV2022 number: CIGE/2022/051), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) doctoral research scholarship, and Universidad Católica de Córdoba (Argentina)

Testing Scenarios to Achieve Workplace Sustainability Goals : Using Backcasting and Agent-Based Modeling

[Abstract] Pro-environmental behaviors have been analyzed in the home, with little attention to other important contexts of everyday life, such as the workplace. The research reported here explored three categories of pro-environmental behavior (consumption of materials and energy, waste generation, and work-related commuting) in a public large-scale organization in Spain, with the aim of identifying the most effective policy options for a sustainable organization. Agent-based modeling was used to design a virtual simulation of the organization. Psychologically informed profiles of employees were defined using data gathered through a questionnaire, measuring knowledge, motivations, and ability. Future scenarios were developed using a participatory backcasting scenario development methodology, and policy tracks were derived. Dynamic simulations indicated that, to be effective, organizational policy should strengthen worker participation and autonomy, be sustained over time, and should combine different measures of medium intensity for behavior change, instead of isolated policies of high intensity