CAREER: Service Distribution Equity using Spatio-Temporal Statistical Foundations

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The research objective of this Faculty Early Career Development (CAREER) project is to advance and develop methodology that addresses fundamental aspects of service distribution equity. Service distribution equity is the study of a population's access to services that are considered fundamental in fostering economic development, improving wellness and enhancing the general quality of life of a population within a given geographic area. This proposal focuses on rigorous methodology to address three important dimensions of service distribution equity: Measurement, Association and Catalysts of Change. To meet the needs of data modeling that scales to the dimensionality and dependencies intrinsic to the data used in addressing service distribution inequity, the research project includes a series of new modeling multivariate methods that rigorously account for data dependencies in a computationally efficient way. The statistical methods are theoretically-founded and generally apply to other studies in service industry research. This project focuses on financial services (deposit and lending) and healthcare services (primary, specialized and emergency care), but generally applies to other service activities which are distributed at multiple sites and by multiple providers.Identifying and addressing inequities in service distribution will create economic development opportunities as well as improve overall wellness of citizen without bias regarding demographic characteristics. Consequently, this research will ultimately impact population groups which historically have been deprived of access to fundamental services and eventually reduce the disparities associated with service distribution inequities. Moreover, this research will contribute with rigorous methodology to the field of service distribution equity, which will aid in the quantitative argumentation needed to influence policy, and with general spatio-temporal methodology to the field of statistics which can be applied to many other problems.