Abstract
The governance of common-pool resources can be meaningfully examined from the somewhat broader perspective of the governance of social-ecological systems (SESs). Governance of SESs invariably involves trade-offs; trade-offs between different stakeholder objectives, trade-offs between risk and productivity, and trade-offs between short-term and long-term goals. This is especially true in the case of robustness in social-ecological systems – i.e. the capacity to continue to meet a performance objective in the face of uncertainty and shocks. In this paper we suggest that effective governance under uncertainty must include the ongoing analysis of trade-offs between robustness and performance, and between investments in robustness to different types of perturbations. The nature of such trade-offs will depend on society’s perception of risk, the dynamics of the underlying resource, and the governance regime. Specifically, we argue that it is impossible to define robustness in absolute terms. The choice for society is not only whether to invest in becoming robust to a particular disturbance, but rather, what suit of disturbances to address and what set of associated vulnerabilities is it willing to accept as a necessary consequence.
Keywords: resilience, robustness, social-ecological system, common-pool resources, trade-offs, irrigation
Abstract
A critical challenge faced by sustainability science is to develop strategies to cope with highly uncertain social and ecological dynamics. This article explores the use of the robust control framework toward this end. After briefly outlining the robust control framework, we apply it to the traditional Gordon–Schaefer fishery model to explore fundamental performance–robustness and robustness–vulnerability trade-offs in natural resource management. We find that the classic optimal control policy can be very sensitive to parametric uncertainty. By exploring a large class of alternative strategies, we show that there are no panaceas: even mild robustness properties are difficult to achieve, and increasing robustness to some parameters (e.g., biological parameters) results in decreased robustness with respect to others (e.g., economic parameters). On the basis of this example, we extract some broader themes for better management of resources under uncertainty and for sustainability science in general. Specifically, we focus attention on the importance of a continual learning process and the use of robust control to inform this process.
Keywords: natural resources; resource management; vulnerability; policy design; environmental policy
Abstract
In the context of governance of human-environment interactions, a panacea refers to a blueprint for a single type of governance system (e.g., government ownership, privatization, community property) that is applied to all environmental problems. The aim of this special feature is to provide theoretical analysis and empirical evidence to caution against the tendency, when confronted with pervasive uncertainty, to believe that scholars can generate simple models of linked social-ecological systems and deduce general solutions to the overuse of resources. Practitioners and scholars who fall into panacea traps falsely assume that all problems of resource governance can be represented by a small set of simple models, because they falsely perceive that the preferences and perceptions of most resource users are the same. Readers of this special feature will become acquainted with many cases in which panaceas fail. The articles provide an excellent overview of why they fail. Furthermore, the articles in this special feature address how scholars and public officials can increase the prospects for future sustainable resource use by facilitating a diagnostic approach in selecting appropriate starting points for governance and monitoring, as well as by learning from the outcomes of new policies and adapting in light of effective feedback.
Keywords: resources; social–ecological systems; sustainability
Abstract
In Janssen et al. (2006), we presented a bibliometric analysis of the resilience, vulnerability, and adaptation knowledge domains within the research activities on human dimensions of global environmental change. We have updated the analysis because 2 years have gone by since the original analysis, and 1113 more publications can now be added to the database. We analyzed how the resulting 3399 publications between 1967 and 2007 are related in terms of co-authorship and citations. The rapid increase in the number of publications in the three knowledge domains continued over the last 2 years, and we still see an overlap between the knowledge domains. We were also able to identify the “hot” publications of the last 2 years.
Keywords: adaptation; bibliometric analysis; citations; resilience; vulnerability
Abstract
Deforestation often has been studied in terms of land-use models, in which natural processes such as ecological succession, physical disturbance and human decision-making are combined. In many land-use models, landowners are assumed to make decisions that maximize their utilities. However, since human understanding of ecological and social dynamics is clouded by uncertainty, landowners may not know true utility values, and may learn these values from their experiences. We develop a decision model for forest use under social learning to explore whether social learning is efficient to improve landowners’ decisions and can lead to effective forest management. We assume that a forest is composed of a number of land parcels that are individually managed; landowners choose whether or not to cut trees by comparing the expected utilities of forest conservation and deforestation; landowners learn utility values not only from their own experiences, but also by exchanging and sharing information with others in a society. By analyzing the equilibrium and stability of the landscape dynamics, we observed four possible outcomes: a stationary-forested landscape, a stationary-deforested landscape, an unstable landscape fluctuating near an equilibrium, and a cyclic-forested landscape induced by synchronized deforestation. Synchronized deforestation, which resulted in a resource shortage in a society, was likely to occur when landowners employed a stochastic decision and a short-term memory about past experiences. Social welfare under a cyclic-forested landscape can be significantly lower than that of a stationary-forested landscape. This implies that learning and remembering past experiences are crucial to prevent overexploitation of forest resources and degradation of social welfare.
Keywords: Decision-making; Expected utility; Slow regeneration; Memory; Markov chain; Stochastic decision
Abstract
Many marketing efforts focus on promotional activities that support the launch of new products. Promotional strategies may play a crucial role in the early stages of the product life cycle, and determine to a large extent the diffusion of a new product. This paper proposes an agent-based model to simulate the efficacy of different promotional strategies that support the launch of a product. The article in particular concentrates on the targeting and the timing of the promotions. The results of the simulation experiments indicate that promotional activities highly affect diffusion dynamics. The findings indicate that: (1) the absence of promotional support and/or a wrong timing of the promotions may lead to a failure of product diffusion; (2) the optimal targeting strategy is to address distant, small and cohesive groups of consumers; and (3) the optimal timing of a promotion differs between durable categories (white goods, such as kitchens and laundry machines, versus brown goods, such as TVs and CDs players). These results contribute to the planning and the management of promotional strategies supporting new product launches.
Keywords: Diffusion of innovations; Agent-based model; Targeting strategies; Promotions; Takeoff of diffusions; Word-of-mouth; Social influence
Abstract
The use of agent-based models (ABMs) for investigating land-use science questions has been increasing dramatically over the last decade. Modelers have moved from ‘proofs of existence’ toy models to case-specific, multi-scaled, multi-actor, and data-intensive models of land-use and land-cover change. An international workshop, titled ‘Multi-Agent Modeling and Collaborative Planning—Method2Method Workshop’, was held in Bonn in 2005 in order to bring together researchers using different data collection approaches to informing agent-based models. Participants identified a typology of five approaches to empirically inform ABMs for land use science: sample surveys, participant observation, field and laboratory experiments, companion modeling, and GIS and remotely sensed data. This paper reviews these five approaches to informing ABMs, provides a corresponding case study describing the model usage of these approaches, the types of data each approach produces, the types of questions those data can answer, and an evaluation of the strengths and weaknesses of those data for use in an ABM.
Keywords: agent-based model, empirical parameterization, human–environment interactions, household surveys, experiments, companion modeling, participant observation, spatial data
Abstract
Diffusions of new products and technologies through social networks can be formalized as spreading of infectious diseases. However, while epidemiological models describe infection in terms of transmissibility, we propose a diffusion model that explicitly includes consumer decision-making affected by social influences and word-of-mouth processes. In our agent-based model consumers’ probability of adoption depends on the external marketing effort and on the internal influence that each consumer perceives in his/her personal networks. Maintaining a given marketing effort and assuming its effect on the probability of adoption as linear, we can study how social processes affect diffusion dynamics and how the speed of the diffusion depends on the network structure and on consumer heterogeneity. First, we show that the speed of diffusion changes with the degree of randomness in the network. In markets with high social influence and in which consumers have a sufficiently large local network, the speed is low in regular networks, it increases in small-world networks and, contrarily to what epidemic models suggest, it becomes very low again in random networks. Second, we show that heterogeneity helps the diffusion. Ceteris paribus and varying the degree of heterogeneity in the population of agents simulation results show that the more heterogeneous the population, the faster the speed of the diffusion. These results can contribute to the development of marketing strategies for the launch and the dissemination of new products and technologies, especially in turbulent and fashionable markets.
Keywords: Innovation diffusion; Threshold models; Word-of-mouth; Social networks; Heterogeneous markets
Abstract
Some social-ecological systems (SESs) have persisted for hundreds of years, remaining in particular configurations that have withstood a variety of natural and social disturbances. Many of these long-lived SESs have adapted their institutions to the particular pattern of variability they have experienced over time as well as to the broader economic, political, and social system in which they are located. Such adaptations alter resource use patterns in time and/or space to maintain the configuration of the SESs. Even well-adapted SESs, however, can become vulnerable to new types of disturbances. Through the analysis of a series of case studies, we begin to characterize different types of adaptations to particular types of variability and explore vulnerabilities that may emerge as a result of this adaptive process. Understanding such vulnerabilities may be critical if our interest is to contribute to the future adaptations of SESs as the more rapid processes of globalization unfold.
Keywords: disturbances, institutions, resilience, robustness, social-ecological system, variability
Abstract
Farmers within irrigation systems, such as those in Bali, solve complex coordination problems to allocate water and control pests. Lansing and Kremer’s [Lansing, J.S., Kremer, J.N., 1993. Emergent properties of Balinese water temples. American Anthropologist 95(1), 97–114] study of Balinese water temples showed that this coordination problem can be solved by assuming simple local rules for how individual communities make their decisions. Using the original Lansing–Kremer model, the robustness of their insights was analyzed and the ability of agents to self-organize was found to be sensitive to pest dynamics and assumptions of agent decision making.
Keywords: Irrigation; Coordination; Networks; Synchronization; Agent-based model
Abstract
In this paper, we present the 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 use the model to explore possible rankings of food preferences for different types of hominids (Homo ergaster and Australopithecus boisei) in different types of semi-arid landscapes. We let the agents adjust their preferences to maximize their calorie intake and show that A. boisei could not meet its calorie requirements in different landscapes.
Abstract
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