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In India’s slums, toilets are commonly shared among households, which creates a collective action problem for the provision of toilet cleanliness and maintenance. We study the effect of heterogeneity and leading by example on cooperation in a framed field experiment with 120 slumdwellers from Hyderabad, India. Endowment heterogeneity has a negative effect on contributions. In contrast to previous studies, leading by example decreases average contributions. However, the effect of leadership is positive and large for participants with leadership experience in real life. We conclude that framed field experiments must acknowledge the mediating role of real-life experience and social identities.
There is an increasing use of models and games as interventions in participatory processes. Those interventions facilitate exploration and learning in a safe simulated environment. However, how do we measure if learning takes place, whether it results in behavioral change and whether it persists? We review the existing literature on social learning through participatory processes and how the impact of those interventions are measured. We identify a number of challenges and present a framework that aims to explicitly specify operational measurements into different levels of learning.
We report on experiments with a spatial explicit dynamic resource where individuals make incentivized real-time decisions when and where to harvest the resource units. We test how individuals make decisions when they manage the resource on their own, or share a resource twice the size with another person. We find that most individuals do not harvest resources close to the optimal strategy when they manage the resource individually, and this relates to their understanding of the instructions and their social orientation. Cooperators let resources grow even when there is no social dilemma. In group rounds, there is more overharvesting, especially if participants are selfish and have a low understanding of the instructions. The results show that a better understanding of the motivations of participants is needed to explain the observed behavior.
Network-theoretic tools contribute to understanding real-world system dynamics, e.g., in wildlife conservation, epidemics, and power outages. Network visualization helps illustrate structural heterogeneity; however, details about heterogeneity are lost when summarizing networks with a single mean-style measure. Researchers have indicated that a hierarchical system composed of multiple metrics may be a more useful determinant of structure, but a formal method for grouping metrics is still lacking. We develop a hierarchy using the statistical concept of moments and systematically test the hypothesis that this system of metrics is sufficient to explain the variation in processes that take place on networks, using an ecological systems example. Results indicate that the moments approach outperforms single summary metrics and accounts for a majority of the variation in process outcomes. The hierarchical measurement scheme is helpful for indicating when additional structural information is needed to describe system process outcomes.
This paper is a study of collective action in asymmetric access to a common resource. An example is an irrigation system with upstream and downstream resource users. While both contribute to the maintenance of the common infrastructure, the upstream participant has rst access to the resource. Results of our two-player asymmetric commons game show that privileged resource access player invest more than the downstream players. Investments by the downstream player into the common resource are rewarded by a higher share from the common resource by the upstream player. Decisions are mainly explained by the levels of trust and trustworthiness. Introducing uncertainty in the production function of the common resource did not aect the results in a signicant way.
Global sustainable use of natural resources confronts our society as a collective action problem at an unprecedented scale. Past research has provided insights into the attributes of local social-ecological systems that enable effective self-governance. In this note, we discuss possible mechanisms to scale up those community-level insights to a larger scale. We do this by combining insights from social-psychology on the role of information feedback with the increasing availability of information technology. By making use of tailored social feedback to individuals in social networks we may be able to scale up the strengths of self-governance at the community level to address global sustainability challenges from the bottom up.
Keywords: Collective Action, Information, Feedback, Social Influence, Social Networks
Tuberculosis is a common and deadly disease that annually causes about two million deaths, mainly in developing countries. It is believed that the ineffectiveness of tuberculosis vaccines can be attributed to the presence of intestinal parasites and that campaigns to protect people from tuberculosis will fail in areas with endemic helminth infestation. Reducing helminth loads requires a combined intervention involving altered individual behavior—improved hygiene practices—and collective action—sanitation infrastructure. Traditionally the focus of tuberculosis research is on treatment, which will remain unsuccessful if it does not address behavioral and collective action problems.
Based on a traditional epidemic model of tuberculosis within a networked population of agents, we introduce factors that affect helminth loads. Agents with helminths have an increased probability to derive the active stage of tuberculosis and are more likely to die from the disease. Public health infrastructure improvements can reduce the environmental occurrence of helminths, and improved individual hygiene (e.g. hand washing and the wearing of shoes) reduces the infection rates of tuberculosis and helminths. In order to identify trade-offs between solving public-health collective action problems (public health and prevention or group level behavioral changes) vs. failing to solve those problems (medical treatment or individual reliance of treatment of active TB), we analyze the model for different levels of solutions to collective action problems. We show that in social networks with more long-distance interactions, which are increasingly experienced in a globalizing world, tuberculosis cannot be effectively reduced with treatment only and require a significant behavioral change.
Keywords: public health, sanitation, collective action, agent-based modeling, network
Traditional research in construction safety focused on accident data analysis, identification of root cause factors, and safety climate modeling. These research efforts did not study the dynamic repetitive interaction among multiple root cause factors. Recently safety research focuses on developing accident causation models. These models attempt to explain how the interaction among multiple project factors gets translated into safety incidents. Agent-based modeling and simulation (ABMS) is an appropriate technique to develop computational models of accidents causation because of its ability to model human factors and repetitive decentralized interactions. This paper presents a conceptual framework for developing agent-based models of construction safety. The key components of the model such as construction crew, management, work environment, material and equipment related quality issues, project/process level complexities, interaction rules, and adaptation have been discussed. Further, the adaptation of agents in response to the safety culture has been demonstrated using a simple ABMS experiment.
Keywords: Construction safety, agent based modeling and simulation, construction accidents causation
We investigate nongovernment public service providers within an agent-based computational model of bureaucrats, citizens, and elected officials. Our analysis explores the relationships of all four types of agents in a single, dynamic model. Specifically, we focus on the delivery of public goods to the citizenry through elected officials and bureaucrats. In our computational model citizens have diverse preferences for a variety of public goods. Political parties adapt their programs to get elected. Bureaucrats implement the priorities provided by the elected officials, who try to get reelected. Failure to provide the promised public goods affects the satisfaction of the citizens which may lead to the creation of nongovernment service providers, including for-profit firms and non-profit organizations. The model enables us to analyze how well the preferences of citizens are met for different assumptions of the strategies of elected officials and bureaucrats.
Keywords: local political economy, nongovernmental organizations, preferences, agent- based modeling
Why are shares of the motion picture market so unequally distributed? Do the different qualities of the movies account for such an enormous difference in the market shares? Are mass media campaigns so effective to convince almost all movie visitors to see the same movies? Or are there social processes that affect the movie visitors’ decision making and direct them to visit the same movies? In this paper, we propose an agent-based model based on micro movie goers decision-making that generates the observed macro characteristics of the market. The model is calibrated using a survey conducted on moviegoers and it explains the stylized characteristics of the market in terms of social influence and coordinated consumption. Simulation results indicate that (1) the chances for successful movies to become a hit are higher in entertainment consumption markets than in art consumption markets and (2) if the marketing efforts of movie labels increase, then market shares become more unequally distributed and the differences between the two markets tend to disappear.
Keywords: motion picture market, market shares, marketing effort, social influence, coordinated consumption.
In this paper, we present the initial results of an agent-based model of foraging of hominids. The model represents foraging activities in a landscape that is based on detailed measurements of food availability in the modern East African environments. These current landscapes are used as a model for the environment of the hominids one million years ago. We explore the spatial and temporal consequences of foraging patterns in different types of semi-arid landscapes and different types of hominids (Homo ergaster and Australopithecus boisei) who are defined with different abilities and preferences.
Keywords: foraging, hominids, field data
The effect of increased monitoring and rule-enforcement in National Hockey League (NHL) games is analyzed at two levels (player and team). The economic theory of crime predicts a reduction of rule-breaking due to increased deterrence. No change is observed in behavior at the player level. At the team level, however, we find a change in composition in the type of players. Private rule enforcers, the goons, become more costly and less necessary when official monitoring is increased. We observe a decrease in the salaries of the players with a high level of goonnesss as our game-theoretic model predicted.
Keywords: National Hockey League, monitoring, rule-breaking, team composition, goons
Within the field of innovation diffusion, many empirical studies have been conducted on the factors that influence the propagation of new ideas and products. From the natural sciences, percolation theory has been used as a starting point to explore the dynamics of innovation diffusion, in particular the occurrence of hits and flops (Solomon et al., 2000). Whereas the latter model is based on a regular network connecting individual consumers and assumes that consumers have only individual preferences, innovation diffusion theory, as well as empirical data, suggests that consumers differ concerning the number of contacts they have and the degree to which social preferences determine their choice to adopt. To test the impacts of these assumptions on the simulated diffusion dynamics, we replicated the Solomon et al. (2000) model and experimented with scale-free networks and social preferences. Results indicate that network shape and social preferences have large impacts on the chances that an innovation either becomes a hit or a flop. To increase the empirical validity of simulated diffusion dynamics we suggest assessing the network structure between consumers as well as the social relevance of the markets.
Keywords: Innovation diffusion, percolation, social networks, preferences.
The Targets IMage Energy Regional simulation model, TIMER, is described in detail. This model was developed and used in close connection with the Integrated Model to Assess the Global Environment (IMAGE) 2.2. The system-dynamics TIMER model simulates the global energy system at an intermediate level of aggregation. The model can be used on a stand-alone basis or integrated within the framework of the integrated assessment model IMAGE 2.2. The model simulates the world on the basis of 17 regions. The main objectives of TIMER are to analyze the long-term dynamics of energy conservation and the transition to non-fossil fuels within an integrated modeling framework and explore long-term trends for energy-related greenhouse gas emissions. Important components of the various submodels are price-driven fuel and technology substitution processes, cost decrease as a consequence of accumulated production (‘learning-by-doing’), resource depletion as a function of cumulated use (long-term supply cost curves), and price-driven fuel trade. The first chapter gives a brief overview of the model objective, set-up, and calibration method. In subsequent chapters, the various submodels are discussed, with the introduction of introduced concepts, equations, input assumptions, and calibration results. Chapter 3 deals with the Energy Demand submodel, Chapter 4 with the Electric Power Generation submodel, and Chapters 5 and 6 with the Fuel Supply submodels. Chapter 7 describes fuel trade and technology transfer modeling; Chapter 8, the Emissions submodel. In the last chapter, a few general concepts are discussed in some detail to improve the user’s understanding of the model. The TIMER-model has played a role in the following: the Special Report on Emission Scenarios (SRES) for the Intergovernmental Panel on Climate Change (IPCC), the European AirClim-project, the construction of global mitigation scenarios, and the Policy Options for CO2 Emission Mitigation in China project.
In this paper, we focus on the cognitive costs that are involved in more reasoned decision-making strategies. We argue that a lower investment of cognitive effort may be beneficial both for the individual as for the sustainability of the population as a whole. We further argue that the most effective distribution of decision-strategies will be related to the stability of the environment people live in. Hence personality factors that determine the preference for a certain distribution are subject to evolutionary pressures. Experiments with a simulation model show that sustainability can be reached when cognitive costs are included in the model. Moreover, it is being demonstrated that evolutionary pressures favor a mix of cognitive strategies. Finally, we demonstrate that an unstable environment favors the development of a smaller population investing more cognitive effort in their decision-making process.
The relationship between trade and material flows is examined by viewing the global economy from the perspective of international material-product chains (MPC). The international MPC covers the complete lifecycle of a material or a product in two or more regions, including extraction, production, consumption, waste management, and transport. Products, waste, and associated material flows in the international MPC can run vertically or horizontally between segments. It is demonstrated how differences in factor requirements across segments of the international MPC in combination with factor productivity differences across developed and developing countries can cause specific trade patterns of inter-industry and intra-industry flows of materials and products. The implications of considering various trade theories in the context of the idea of an international MPC are examined. This interpretation of international trade sheds a new light especially on the physical dimension of international specialization.
Keywords: International material-product chains; Trade theories; Environmental policy; Recycling.
In this paper, we report on a series of computer simulation experiments on the management of a common resource. We were particularly interested in the effects of uncertainty and satisfaction on the harvesting behaviour of simulated agents. Because the experimental study of the long-term dynamics of resources that are being depleted to a serious extend can hardly be done using real human subjects, we experimented with simulated consumers. These simulated consumers, or ‘consumats’, have been developed using a multi-theoretical framework integrating various theories that appear to be relevant in understanding consumer behaviour. The consumat is equipped with needs and abilities, and may engage in different cognitive processes, such as deliberating, social comparison, imitation, and repeating previous behaviour. In the first series of experiments, we tested these cognitive processes on their functioning. In a later series, we experimented with the consumat attributes and the resource characteristics. It was found that an increased uncertainty resulted in an increased ‘optimism’ of consumats regarding future outcomes, an increased likelihood of imitative behaviour, and a lesser adaptation during resource depletion. These ‘process-effects’ caused higher uncertainty resulting in higher levels of harvesting, an effect that has been demonstrated previously in experiments with real human subjects. The paper concludes with a discussion on the ecological validity of the simulation results.
A model framework, SIMBIOSES, is presented which describes economic activities and related material, substance, and energy flow in a multi-region and multi-sector economic system. The conceptual design of the framework is discussed in relation to current issues on “dematerialization” and “decoupling”.
Three types of models to implement SIMBIOSES are discussed: a static equilibrium model, a dynamic optimization model, and a system dynamics model. The static model determines the static equilibrium of extraction, production, recycling, and energy recovery from waste. The dynamic model determines the long-term investment decision that optimizes the total discounted utility of consumption. The dynamic model incorporates technological change, allocation of resources, and damage costs due to the accumulation of substances in the environment. The system dynamic model generates endogenous economic growth and technology development and includes the bounded rationality of economic agents.
Keywords: dematerialization, mass balance, integrated models, Environmental Kuznets curve, equilibrium analysis, dynamic optimization, system dynamics.
In order to explore long-term policy options for controlling climate change, there is a need to develop and evaluate long-term emission scenarios. If these scenarios are to be policy-relevant, they should, account for differences between world regions with respect to their contribution to the problem, their stage of economic development, their vulnerability to climate change, and their ability to control emissions. The scenarios should also deal with the question of fair distribution of future emission budgets. Therefore it is important to involve policymakers in the development of these scenarios. On the basis of requests and comments from policymakers participating in the Delft Science Policy Dialogue workshops, a new software tool called the Interactive Scenario Scanner (ISS), has been constructed at RIVM. ISS is a computer model that assists in the interactive construction and evaluation of long-term emission scenarios using the parameters of the Kaya Identity to define scenarios and the climate indicators of the Safe Landing Approach to scan their likely consequences for global climate change and its impacts. This tool can be used to construct proto-scenarios, which can then be further elaborated and analyzed with such sophisticated energy and climate change models as IMAGE 2. Recent experiences with the application of ISS indicate that it indeed can be a useful tool to involve policymakers in the development of emission scenarios. Moreover, ISS has also been shown useful in educating policymakers on the complexity of the problem and enhancing communication between, and among, scientists and policymakers.
Keywords: Science/Policy Dialogue, Climate Change, Integrated Assessment Models, Scenario Development
This report contains an integrated analysis of the Targets/IMage Energy (TIME) model. In a previous report (De Vries and Van den Wijngaart, 1995) the five submodels of the energy model were described in detail. Here, we describe a number of applications with the (stand-alone) TIME model.
After the introduction and a brief outline of the TIME framework in Chapter 2, Chapter 3 describes the calibration of the world version for the period 1900-1990. Given the exogenous drivers like population size and economic activities, the energy demand, fuel mix, fuel prices, energy investments- and C02 emissions are calculated and compared with observed values. We discuss what assumptions had to be made to derive a suitable fit with the observed values.
Chapter 4 present the methodology for scenario construction. Furthermore, we discuss uncertainties and assumptions on structural change, energy efficiency improvements, long-term supply cost curves of fossil fuel resources, and technology in energy supply options.
An application of the methodology of Chapter 4 is discussed in Chapter 5 where a reference scenario is constructed based on the IS92a scenario of the IPCC. In Chapter 6 some scenarios from other institutions are investigated by assessing their outcomes in terms of the underlying assumptions. In Chapter 7, we will discuss energy futures according to alternative perspectives or world views. Finally, in Chapter 8, we give some results of optimized mitigation strategies using the CYCLES module of TARGETS to assess the impacts of scenarios. We especially address the role of technological change in meeting climate change policy targets.
As the resistance of the malaria parasite to antimalarial drugs continues to intensify, as does that of the malarial mosquito to insecticides, efforts to adequately control the malaria situation in many tropical countries are coming under strain. This, together with a projected climate change may substantially increase malaria risks in the coming decades. In this paper, we introduce genetic algorithms to simulate the adaptation (development of resistance) of mosquitoes and parasites. By coupling genetic algorithms with a dynamic malaria-epidemiological model we derive a complex adaptive system that is used to analyze strategies of malaria management for high and low endemic regions. Our results show that control programs can be used successfully in low endemic regions although increased effort will be necessary in case of climate change. However, in high endemic regions, the inefficient use of insecticides and antimalarial drugs may eventually increase the incidence of malaria by decreasing the high levels of natural immunity of the population in these regions.
Keywords: malaria, climate change, genetic algorithms, adaptation
Current (integrated) modelling efforts aimed at scanning the future do not allow for the learning and adaptive behaviour of agents in a world of uncertainty. In this paper, a framework is presented which might prove to provide a starting point in scanning the feasibility of coping with the dynamics of an ever-evolving interaction between the global system and the relevant agents, whereby the latter are assumed to view the global system from various perspectives. These perspectives may change over time in the event of surprises appearing in the observations. The agents’ favoured management styles, which are assumed to be related to the perspectives, may therefore likewise change over time. Incorporation of the ‘battle of perspectives’ enables us to embark modelling the interaction of decision-making with the complex global system in a world of uncertainty.
The example which is worked out here is the climate change issue, whereby a simple dynamic system for the economy and the climate system is used. This enables us to derive images of the future which take the notion of learning and adaptation into account.
Keywords: climate change, integrated assessment modelling, perspectives, learning behaviour, surprises
In order to reduce the risks of climate change, a major problem in developing an effective international policy is the allocation of the responsibility for reducing green house gas emissions among regions.
This report presents two approaches to provide for the allocation problem of emission reductions in the most important greenhouse gas C02. The first deals with a description of the emission debt concept. We use an equity rule by which all past and future dwellers on earth are permitted to emit an equal C02 quotum per year. Furthermore, the level of the equal emission quotum is dependent on the policy-related C02-equivalent concentration targets. The regional emission debt is the amount of C02, based on an equal share per capita, emitted in a region in the past exceeding the amount allowed. The resulting initial allocation of emission rights may be used as a start for a concept of tradable emission rights.
In the second approach, the allocation problem is formulated as an optimization problem. This contains an ‘optimal’ trade-off between rough estimates for social and economic consequences of reducing fossil C02-emissions in order to meet policy targets, as expressed in a C02-equivalent concentration level. The optimization algorithm developed is a first attempt in solving the optimization problem, where restrictions are dependent on simulation runs with IMAGE (an Integrated Model to Assess the Greenhouse Effect). The algorithm is used to find an allocation of regional fossil C02-emissions in order to maximize the welfare of future generations, given a maximum allowable concentration level.
Results of both approaches indicate that if the world community is to accept constraints on C02-emissions, industrialized regions will have to take the main responsibility in reducing C02-emissions either by reducing emissions in their own regions and in developing regions.