Long considered backoffice support tools, information systems have become strategic competitive weapons. In the airline, travel services financial services, and distribution industries, for example, information systems have become strategic competitive weapons. Information systems have been used to produce new productsorto substantiallymodifyold one. Frequently, these systems increase the customer's "switching costs," and thereby increase dependence on the supplier This phenomenon has been discussed by several researchers, and disparate descriptive models proposed. A new model the Customer

Researchers have long studied the causes and prevention strategies of poor household water quality and early childhood diarrhea using intervention-control trials. Although the results of such trails can lead to useful information, they do not capture the complexity of this natural/engineered/social system. We report on the development of an agent-based model (ABM) to study such a system in Limpopo, South Africa. The study is based on four years of field data collection to accurately capture essential elements of the communities and their water contamination chain. An extensive analysis of those elements explored behaviors including water collection and treatment frequency as well as biofilm buildup in water storage containers, source water quality, and water container types. Results indicate that interventions must be optimally implemented in order to see significant reductions in early childhood diarrhea (ECD). Household boiling frequency, source water quality, water container type and the biofilm layer contribution were deemed to have significant impacts on ECD. Furthermore, concurrently implemented highly effective interventions were shown to reduce diarrhea rates to very low levels even when other, less important practices were sub-optimal. This technique can be used by a variety of stakeholders when designing interventions to reduce ECD incidences in similar settings.

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Diarrhea, the second leading cause of child morbidity and mortality, can have detrimental effects in the physical and cognitive development of children in developing countries. Health interventions (e.g., increased access to health services and safe water) designed to address this problem are difficult to implement in resource-limited settings. In this paper, we present a tool for understanding the complex relationship between water and public health in rural areas of a developing country. A spatial and temporal agent-based model (ABM) was developed to simulate the current water, sanitation, and health status in two villages in Limpopo Province, South Africa. The model was calibrated using empirical data and published sources. It was used to simulate the effects of poor water quality on the frequency of diarrheal episodes in children, and consequently on child development. Preliminary simulation results show that at the current total coliform levels in the water sources of the studied villages, children are expected to experience stunting by as much as −1.0 standard deviations from the World Health Organization height norms. With minor modifications, the calibrated ABM can be used to design and evaluate intervention strategies for improving child health in these villages. The model can also be applied to other regions worldwide that face the same environmental challenges and conditions as the studied villages.

Police patrol district design presents a multi-objective optimization problem with two goals: minimizing workload variation between patrol districts and minimizing the response time for officers responding to calls for service. We evaluate three different methods for scoring district designs: a closed form probability based approach, a discrete-event simulation based on hypercube models for spatial queuing systems, and an agent-based simulation model. We find that all methods provide similar evaluations when service demand is low enough that cross-boundary support is infrequent. However, when the demand for service routinely exceeds the supply available within districts, only the agent-based simulation model accurately represents the resulting complexities and significantly changes the evaluation scores to reflect the behavior of the system.

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