Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)

Legacy Department


Committee Chair/Advisor

Roth, Aleda V

Committee Member

Wang , Shouqiang

Committee Member

Wilson , Paul W

Committee Member

Miller , Daniel P


The primary objective of this dissertation is to provide insights for service providers in general, and retail bankers and hospital administrators in particular, that will help them improve their operational efficiency and effectiveness. In doing so, this dissertation consists of three essays that develop multiple service operations strategies, that identifies key elements affecting efficiency and effectiveness in two key critical industries: banking and healthcare. We contribute to service operations strategy research and practice by incorporating multi-disciplinary theories and approaches from marketing, economics, and quality management. Although operations researchers and practitioners alike realize the importance of productivity and effectiveness, they are largely unaware of more advanced techniques to achieve this goal. This dissertation fills, in part, this gap and leads one to understand research agendas in service strategy. In particular, this dissertation applies new theories and methods illustrating how bankers can improve efficiency. Moreover, it describes how hospital administrators can better understand the `hidden' costs of quality failures that associated with hospital readmission as well as the impact of the recent Medicare penalty plan on hospitals and patient welfare. We employ different methods (frontier efficiency estimation, econometrics, structural estimation, and principal-agent models) to critically analyze banking and healthcare industries.
The first essay deals with banking industry; the second and third essays are inter-related topics dealing with healthcare services. The first essay integrates diffusion theory from marketing literature and path dependency theory from economics into service operations management to estimate and compare efficiency of banks operating in the U.S. and in India. We develop and empirically test two hypotheses based on diffusion theory and path dependency theory. The hypotheses are tested using data from banks operating in the U.S. and India and estimate efficiency using free disposal hull (FDH) estimator instead of the widely used data envelopment analysis (DEA) estimator. We note that the DEA estimator imposes convexity of production frontier whereas FDH estimator does not. Our empirical analysis, rejected the assumption of convexity of production frontier; and we are the first in the operations management literature to employ these empirics to test assumptions that are typically held to be true, but not validated, when employing DEA analyses.
The second essay develops a theory-based econometric model to investigate the effect of readmission rate on marginal cost incurred by a hospital. We use secondary data derived from multiple sources, including Center for Medicare and Medicaid Services. We apply an inversion method and structural estimation procedure developed in the empirical Industrial Organization and econometrics literature to estimate marginal cost of a hospital associated with readmissions using data on all Arizona hospitals. This essay also demonstrates the effect of the recent Medicare penalty on average readmission rate of all hospitals in the state of Arizona by using counterfactual analysis with and without stochastic shocks in hospitals' investment to reduce readmission rates. The revised price charged by acute care hospitals after the elimination of critical access hospitals is also estimated as another counterfactual analysis. These analyses are very timely since patient protection and affordable care act (PPACA) was enacted recently, which penalizes hospitals with readmission rates higher than threshold readmission rates set by the government. Thus, in addition to research and practice, this essay offers strong policy insights.
The third essay formulates an analytical model to evaluate the potential impact of PPACA on hospitals (providers), the government, and patients. We build a model of 'readmission' with uncertainty for hospitals and use the principal-agent frame work to study the interaction between the government (principal) and the hospital (agent). The hospital can make effort to reduce the readmission rate (hidden action). The hospital side is modeled using queueing with feedback results. Finally, we evaluate the impact of hospital's efforts on the government's expense and patient welfare.



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