Jessica L. Heier Stamm

Opinion: Endogenizing culture in sustainability science research and policy

Integrating the analysis of natural and social systems to achieve sustainability has been an international scientific goal for years (1, 2). However, full integration has proven challenging, especially in regard to the role of culture (3), which is often missing from the complex sustainability equation. To enact policies and practices that can achieve sustainability, researchers and policymakers must do a better job of accounting for culture, difficult though this task may be.

Game theory applications in humanitarian operations: a review

Purpose – The purpose of this paper is to summarize ways in which game theory has been or could be utilized within the humanitarian sector and to identify future research opportunities in this field. Game theory is a tool for modeling systems in which multiple decision makers act according to their own objectives and where individual choices affect system outcomes. Humanitarian logistics systems are often characterized by the presence of many such decision makers. Design/methodology/approach – The authors synthesize literature from operations research, humanitarian logistics, and the political and management sciences that describes either game theory models or settings in which game theory has the potential to contribute practical insights. Papers are categorized based on the types of decision makers highlighted and the facets of humanitarian operations described. Findings – The review of literature indicates that applications of game theory to humanitarian supply chain systems are limited to date but tha...

Bringing the “social” into sociohydrology: Conservation policy support in the Central Great Plains of Kansas, USA

Identifying means of empirically modeling the human component of a coupled, human-water system becomes critically important to further advances in socio-hydrology. We develop a social-psychological model of environmental decision-making that addresses four key challenges of incorporating social science into integrated models. We use the model to explain preferences for three conservation policies designed to conserve and protect water resources and aquatic ecosystems in the Smoky Hill River Basin, a semi-arid agricultural region in the Central U.S. Great Plains. Further, we compare the models capacity to explain policy preferences among members of two groups in the River Basin: agricultural producers and members of non-farming communities. We find that financial obligation is the strongest and most consistent explanation of support for conservation policies among members of both groups. We also find that policy support is grounded in cultural values- deeply-held ideas about right and wrong. Environmental values are particularly important explanations of policy support. The constellations of values invoked to make decisions about policies, and the social-psychological pathways linking values to policy support, can vary across policies and types of agents (farmers and non-farmers). We discuss the implications of the results for future research in socio-hydrology.

Quantifying and explaining accessibility with application to the 2009 H1N1 vaccination campaign.

Accessibility and equity across populations are important measures in public health. This paper is specifically concerned with potential spatial accessibility, or the opportunity to receive care as moderated by geographic factors, and with horizontal equity, or fairness across populations regardless of need. Both accessibility and equity were goals of the 2009 vaccination campaign for the novel H1N1a influenza virus, including during the period when demand for vaccine exceeded supply. Distribution system design can influence equity and accessibility at the local level. We develop a general methodology that integrates optimization, game theory, and spatial statistics to measure potential spatial accessibility across a network, where we quantify spatial accessibility by travel distance and scarcity. We estimate and make inference on local (census-tract level) associations between accessibility and geographic, socioeconomic, and health care infrastructure factors to identify potential inequities in vaccine accessibility during the 2009 H1N1 vaccination campaign in the U.S. We find that there were inequities in access to vaccine at the local level and that these were associated with factors including population density and health care infrastructure. Our methodology for measuring and explaining accessibility leads to policy recommendations for federal, state, and local public health officials. The spatial-specific results inform the development of equitable distribution plans for future public health efforts.

An agent-based modeling approach to improve coordination between humanitarian relief providers

Logistical coordination between humanitarian organizations is crucial during the response effort to a disaster, as coordinating aid improves efficiency, reduces duplication of effort, and ultimately leads to better outcomes for beneficiaries. One challenge in particular is making facility location decisions, where makeshift homes, medical tents, or other aid-related facilities need to be placed in a way that provides fair service to all in need. This research aims to improve upon the current practices of facility placement coordination by drawing on data from the 2015 earthquake in Nepal. We develop an agent-based simulation model with data from this event, and extend our findings to provide new insights about humanitarian decision making and coordination in regard to the facility location problem.

Decision-making tools: stochastic simulation model accounting for the impacts of biological variation on success of bovine embryo transfer programs

Abstract The objective of the project was to create an economic risk analysis tool for user-defined embryo transfer (ET) programs as an aid in decision-making. Distributions defining the biological uncertainty for many reproductive outcomes are estimated through extensive literature review and limited industry sources. Applying the Latin hypercube variation of Monte Carlo simulation, a sample value from the descriptive distribution associated with each stochastic variable is included in each iteration of the simulation. Through large numbers of iterations with dynamic combinations of variable values, the process culminates in a distribution of possible values for the net present value, annuity equivalent net present value, and return on investment associated with the modeled embryo production scenario. Two options for embryo production, multiple ovulation embryo transfer (MOET) and in vitro embryo production (IVP) from aspirated oocytes, are modeled. Within both MOET and IVP, the use of unsorted or sex-sorted semen is considered, as well as the exception or inclusion of follicular synchronization and/or stimulation before ovum pick-up in IVP procedures. Pretransfer embryo selection through embryo biopsy can also be accounted for when considering in vivo derived embryos. Ample opportunity exists for the commercial application of in-depth, alternative ET scenario assessment afforded through stochastic simulation methodology that the ET industry has not yet fully exploited.

Using Spatial Data Analytics to Identify Associations between Home Healthcare Services Accessibility and Socioeconomic Factors

Abstract Home healthcare can improve health outcomes and reduce healthcare costs. However, realizing its benefits is only possible if the service is accessible for patients who need it. Thus, evaluating and understanding the inequities in accessibility of home healthcare services are necessary to improve the healthcare system and overall population health. This article utilizes detailed healthcare system and socioeconomic data in a spatial statistical modeling framework, from which we make inference about spatially explicit relationships between home healthcare accessibility and socioeconomic factors, including rural/urban status, income, education, and race/ethnicity. This is accomplished via space-varying coefficient models that account for the spatial autocorrelation in both the response and predictor variables, as well as capture spatial heterogeneity in the relationships between accessibility and socioeconomic factors. We find statistically significant and spatially varying relationships between accessibility of home healthcare services and several socioeconomic variables at the zip code level. Our results have the potential to inform policies aimed at addressing disparities in spatial accessibility, promoting healthcare effectiveness, and improving outcomes. This work makes important contributions to improving healthcare outcomes using a spatial analytics framework that integrates healthcare systems data at a fine spatial scale with advanced statistical methods.