Business Commons^™

Hospital-Physician Integration And Physician Collaboration: Implications For Care Efficiency And Outcomes, Hui Jia

Doctoral Dissertations

This thesis focuses on healthcare operations management and consists of two essays that investigate empirically how the relationship between physicians and hospitals and the relationship between peer physicians, respectively, affect clinical care outcomes and care efficiency.

In the first essay, I study hospital-physician integration as a type of organization-service provider relationship. Many prior studies have provided insights into the benefits of a tight collaboration between hospitals and physicians. However, neutral and even negative effects of this relationship on healthcare performance have been observed and discussed in the literature. This mixed evidence points to a need for further study to elucidate …

Sparse Model Selection Using Information Complexity, Yaojin Sun

Doctoral Dissertations

This dissertation studies and uses the application of information complexity to statistical model selection through three different projects. Specifically, we design statistical models that incorporate sparsity features to make the models more explanatory and computationally efficient.

In the first project, we propose a Sparse Bridge Regression model for variable selection when the number of variables is much greater than the number of observations if model misspecification occurs. The model is demonstrated to have excellent explanatory power in high-dimensional data analysis through numerical simulations and real-world data analysis.

The second project proposes a novel hybrid modeling method that utilizes a mixture …

Effects Of Economic Development Status And Eco-Product On Consumption Values: From The Perspective Of Us Consumers, Mostafa Zaman

Doctoral Dissertations

Consumers select a product based on numerous product characteristics. Numerous studies conducted earlier revealed that consumers in developing countries preferred products made in western or developed countries because their product quality is better than the quality of local products (Lee & Nguyen, 2017; Dao & Heidt, 2018; Rodrigo et al., 2019). Moreover, consumers are increasingly concerned about manufacturers’ environmental issues. Although ethical consumers believe that eco-products could save the environment, some consumers are not concerned about the eco-products and thus select products based on other product attributes (Joshi & Rahman, 2015). Hence, it becomes very challenging for retailers to select …

Determining The Location Of A Milk Condensing Plant In Tennessee, David Frederick Mendez

Masters Theses

Given the increasing popularity of local foods and the desire to reduce shipping costs and carbon footprint, Tennessee-based dairy product producers are showing interest in sourcing fluid milk locally. Based on dairy farmer surveys, discussions with industry leaders, shipping distances, and transportation costs estimates, a mixed integer linear programming model is used to determine the optimal location of an in-state milk condensing plant. The objective is to minimize the total transportation costs of shipments of fluid milk from farms to the condensing plant plus the transportation cost of shipments of condensing plant products to further in-state processing. Twelve scenarios of …

Economic Forecasting With Many Predictors, Fanning Meng

Doctoral Dissertations

The dissertation is focused on the analysis of economic forecasting with a large number of predictors.

The first chapter develops a novel forecasting method that minimizes the effects of weak predictors and estimation errors on the accuracy of equity premium forecasts. The proposed method is based on an averaging scheme applied to quantiles conditional on predictors selected by LASSO. The resulting forecasts outperform the historical average, and other existing models, by statistically and economically meaningful margins.

In the second chapter, we find that incorporating distributional and high-frequency information into a forecasting model can produce substantial accuracy gains. Distributional information is …

Cell Phone Ethnography: Mixed Methods And The Brand Consumer Relationship, Robert Nathaniel Dove

Masters Theses

Overall, the goal of this study is to identify and differentiate the various motivations and cultural influences that can be used to explain consumer behavior. In doing so, this study hopes to facilitate the development of new and innovative marketing strategies, providing a new research design for the ethnographer’s toolkit. More importantly, this model can give shape to new constructs and new variables for further empirical testing in the field through quantitative and qualitative methods. By blending the two approaches, using qualitative interpretive anthropological analysis by field study with quantitative sentiment analysis adapted from market researcher Jeffery Breen’s (2012) methodology, …

Joint Optimization Of Allocation And Release Policy Decisions For Surgical Block Time Under Uncertainty, Mina Loghavi

Doctoral Dissertations

The research presented in this dissertation contributes to the growing literature on applications of operations research methodology to healthcare problems through the development and analysis of mathematical models and simulation techniques to find practical solutions to fundamental problems facing nearly all hospitals.

In practice, surgical block schedule allocation is usually determined regardless of the stochastic nature of case demand and duration. Once allocated, associated block time release policies, if utilized, are often simple rules that may be far from optimal. Although previous research has examined these decisions individually, our model considers them jointly. A multi-objective model that characterizes financial, temporal, …

Monte Carlo Methods In Finance, Je Guk Kim

Doctoral Dissertations

Monte Carlo method has received significant consideration from the context of quantitative finance mainly due to its ease of implementation for complex problems in the field. Among topics of its application to finance, we address two topics: (1) optimal importance sampling for the Laplace transform of exponential Brownian functionals and (2) analysis on the convergence of quasi-regression method for pricing American option. In the first part of this dissertation, we present an asymptotically optimal importance sampling method for Monte Carlo simulation of the Laplace transform of exponential Brownian functionals via Large deviations principle and calculus of variations the closed form …

State Space Modelling Of Dynamic Choice Behavior With Habit Persistence, Kang Bok Lee

Doctoral Dissertations

In this dissertation, I present a new approach to capturing dependence across time in dynamic choice data. To achieve this, I develop a state space dynamic choice model and a novel algorithm to fit the data. Instead of capturing dependence in outcomes through lagged response variables, referred to as state dependence, I introduce a lagged utility term through the latent state equation. The lagged utility term captures habit persistence, which has not been explored directly in earlier models (Heckman, 1981b). The autoregressive nature of the lagged utility provides a significantly richer summary of prior utility than a lagged outcome variable. …

Indefinite Knapsack Separable Quadratic Programming: Methods And Applications, Jaehwan Jeong

Doctoral Dissertations

Quadratic programming (QP) has received significant consideration due to an extensive list of applications. Although polynomial time algorithms for the convex case have been developed, the solution of large scale QPs is challenging due to the computer memory and speed limitations. Moreover, if the QP is nonconvex or includes integer variables, the problem is NP-hard. Therefore, no known algorithm can solve such QPs efficiently. Alternatively, row-aggregation and diagonalization techniques have been developed to solve QP by a sub-problem, knapsack separable QP (KSQP), which has a separable objective function and is constrained by a single knapsack linear constraint and box constraints. …

A Simple, Practical Prioritization Scheme For A Job Shop Processing Multiple Job Types, Shuping Zhang

Doctoral Dissertations

The maintenance, repair, and overhaul (MRO) process is used to recondition equipment in the railroad, off-shore drilling, aircraft, and shipping industries. In the typical MRO process, the equipment is disassembled into component parts and these parts are routed to back-shops for repair. Repaired parts are returned for reassembling the equipment. Scheduling the back-shop for smooth flow often requires prioritizing the repair of component parts from different original assemblies at different machines. To enable such prioritization, we model the back-shop as a multi-class queueing network with a ConWIP execution system and introduce a new priority scheme to maximize the system performance. …

Real-Time Order Tracking For Supply Systems With Multiple Transportation Stages, Nana Bryan

Doctoral Dissertations

This dissertation studies a supply system consisting of a retailer, a manufacturer, and multiple transportation stages. The manufacturer fulfills the demand from the retailer for a single product. The replenishment process is not instantaneous. Orders may take more than one time period to be shipped from the manufacturer’s location, and shipped orders pass through multiple transportation stages until they reach the retailer. Each stage may represent a physical location or a step in the delivery process. Shipments are not allowed to cross over in time. The movement of each shipment depends on the congestion and movements of shipments ahead of …

Financial Services Innovation: Local Strategy, Management, And Change – A Field Investigation, Ann-Catherine Nave

Pursuit - The Journal of Undergraduate Research at The University of Tennessee

This study examines the innovation sources and processes of regional financial services firms through inductive field research. Innovation in these firms, and presumably other financial services firms and other smaller organizations, originate primarily out of three sources, the drive for efficiency, the external environment, and strategic, ambidextrous management. Successfully innovative firms balance the short-term need for efficiency improvements with the long-term desire to grow primarily through visionary, yet adaptive, leadership.

Shopper Value: A Framework And Examination Of The Impact Of Importance, Shopping Context And Shopping Social Situation, Robert Paul Jones

Doctoral Dissertations

This dissertation is exploratory, examining a little studied part of retail, the shopper. Shoppers are defined as: actively engaged in the pursuit of a target purchase driven by a specific need requiring a solution. The objectives of this research are to clarify the differences between consumers and shoppers, justifying the need for further study. This research also seeks to develop a values based framework of shopper behavior in order to facilitate future research. An extensive review of the literature provides a foundation for the differences between shoppers and consumers. The theory of reasoned action provides the foundation for the shopper …

Exploring The Effectiveness Of Environmentally Sustainable Practices In Municipal Government: A Case Study Of The City Of Knoxville’S Department Of Parks And Recreation, Anthony Michael Brown

Masters Theses

Sustainability practices produce programs and services that meet current needs while preserving the environment and natural resources for the future. City parks and recreation departments are facing budget shortfalls and increasing expectations from customers. Governments are now embracing sustainability practices to create financial savings while also fostering relations with customers.

The purpose of this single case study was twofold: (1) to examine the effectiveness of one city department’s strategies in outsourcing its environmental sustainability program through a performance contract with Ameresco; and (2) to examine the perceptions of key department employees about the effectiveness of the sustainability initiative. A …

Data Mining With Multivariate Kernel Regression Using Information Complexity And The Genetic Algorithm, Dennis Jack Beal

Doctoral Dissertations

Kernel density estimation is a data smoothing technique that depends heavily on the bandwidth selection. The current literature has focused on optimal selectors for the univariate case that are primarily data driven. Plug-in and cross validation selectors have recently been extended to the general multivariate case.

This dissertation will introduce and develop new and novel techniques for data mining with multivariate kernel density regression using information complexity and the genetic algorithm as a heuristic optimizer to choose the optimal bandwidth and the best predictors in kernel regression models. Simulated and real data will be used to cross validate the optimal …

The Generalized Dea Model Of Fundamental Analysis Of Public Firms, With Application To Portfolio Selection, Xin Zhang

Doctoral Dissertations

Fundamental analysis is an approach for evaluating a public firm for its investmentworthiness by looking at its business at the basic or fundamental financial level. The focus of this thesis is on utilizing financial statement data and a new generalization of the Data Envelopment Analysis, termed the GDEA model, to determine a relative financial strength (RFS) indicator that represents the underlying business strength of a firm. This approach is based on maximizing a correlation metric between GDEA-based score of financial strength and stock price performance. The correlation maximization problem is a difficult binary nonlinear optimization that requires iterative re-configuration of …

Algorithms For Multi-Sample Cluster Analysis, Fahad Almutairi

Doctoral Dissertations

In this study, we develop algorithms to solve the Multi-Sample Cluster Analysis (MSCA) problem. This problem arises when we have multiple samples and we need to find the statistical model that best fits the cluster structure of these samples. One important area among others in which our algorithms can be used is international market segmentation. In this area, samples about customers’preferences and characteristics are collected from di¤erent regions in the market. The goal in this case is to join the regions with similar customers’characteristics in clusters (segments).

We develop branch and bound algorithms and a genetic algorithm. In these algorithms, …

Approximation Methods For The Standard Deviation Of Flow Times In The G/G/S Queue, Xiaofeng Zhao

Doctoral Dissertations

We provide approximation methods for the standard deviation of flow time in system for a general multi-server queue with infinite waiting capacity (G / G / s ). The approximations require only the mean and standard deviation or the coefficient of variation of the inter-arrival and service time distributions, and the number of servers.

These approximations are simple enough to be implemented in manual or spreadsheet calculations, but in comparisons to Monte Carlo simulations have proven to give good approximations (within ±10%) for cases in which the coefficients of variation for the interarrival and service times are between 0 …

Multivariate Nonnormal Regression Models, Information Complexity, And Genetic Algorithms: A Three Way Hybrid For Intelligent Data Mining, Minhui Liu

Doctoral Dissertations

This dissertation develops a novel computationally feasible intelligent data mining and knowledge discovery technique to select the best subset of predictors in multivariate re- gression (MR) models under the assumption that the random error terms of the model follow a general nonnormal family of distributions. Our approach builds an easy-to-use three way hybrid approach by integrating clever statistical modeling procedures based on the information-theoretic measure of complexity (ICOMP) criterion with genetic algorithm (GA) and multivariate nonnormal regression models with Power Exponential (PE) and fam- ily of elliptically contoured (EC) error distributions. This dissertation is composed of four major parts.

First, …

Stochastic Optimization Models For Contingency Allocation In Project Management, Barbara Maria Thibadeau

Doctoral Dissertations

In many cases, risks that threaten successful project completion can be mitigated (or eliminated) with a proper contingency allocation strategy and exacerbated by an improper one. Yet, despite this importance, there is a dearth of research on the cost contingency allocation problem in academic literature. This thesis looks at the cost contingency allocation problem from two different perspectives and two distinct solutions are introduced: a stochastic linear programming model that addresses a short term strategy and convex-concave utility model that provides a long-term planning solution.

The project manager’s ability to approve random requests for contingency is dependent on several constraints, …

Essays On Quantitative Analysis Of Supply Chain Structures, Contracts And Coordination, Xinjie Shi

Doctoral Dissertations

This thesis consists of three separate, but related, essays that deal with the topic of how supply chain structure as well as the use of contracts impact performance of a supply chain. The main focus is the analysis of behavior of indirect-sale supply chains in terms of relative bargaining power and decision rights of the participants. Modeling as Stackelberg games, this thesis explores the existence of Nash equilibriums and the issues surrounding supply chain coordination.

In Essay one, “The Role of Decision Structure in Supply Chain Coordination with Stochastic Demand”, the analysis focuses on how different supply chain structures affect …

New Approaches To Risk Management And Scenario Approximation In Financial Optimization, Maksym Bychkov

Doctoral Dissertations

The first part of the thesis addresses the problem of risk management in financial optimization modeling. Motivation for constructing a new concept of risk measurement is given through the history of development: utility theory, risk/return tradeoff, and coherent risk measures. The process of describing investor's preferences is presented through the proposed collection of Rational Level Sets (RLS). Based on RLS, a new concept termed Rational Risk Measures (RRM) for nancial optimization models is defined. The advantages of RRM over coherent risk measures are discussed. Approximation of a given set of scenarios using tail information is addressed in the second part …

Intelligent Data Mining Using Kernel Functions And Information Criteria, Zhenqiu Liu

Doctoral Dissertations

Radial Basis Function (RBF) Neural Networks and Support Vector Machines (SVM) are two powerful kernel related intelligent data mining techniques. The current major problems with these methods are over-fitting and the existence of too many free parameters. The way to select the parameters can directly affect the generalization performance(test error) of theses models. Current practice in how to choose the model parameters is an art, rather than a science in this research area. Often, some parameters are predetermined, or randomly chosen. Other parameters are selected through repeated experiments that are time consuming, costly, and computationally very intensive. In this dissertation, …

A Genetic Algorithm For The Vehicle Routing Problem, Vickie Dawn Wester

Masters Theses

The purpose of this research was to develop a version of a genetic algorithm (GA ) which would provide near optimal solutions for Vehicle Routing Problems (VRP) with both time and weight constraints. The genetic algorithm used for the experimentation was adapted from a GA which had been developed by James Bean at the University of Michigan to solve machine scheduling problems. The VRP data sets used in this research were obtained from the literature. Various aspects of the GA were experimented with in order to develop a version which would perform consistently well for all the data sets. The …

Marketing As A Science, Harlan D. Mills

The Harlan D. Mills Collection

No abstract provided.

The Effect Of The 'Tendency To Report Injuries' On Minor Accident Statistics, James A. Barker

Masters Theses

This study is concerned with the effect of the "tendency to report injuries" on minor accident statistics. Assuming that individuals with the largest number of voluntary visits for nonoccupational illnesses to the Dispensary would be those who most readily report to the Dispensary in the event of minor injuries, the individuals may be defined as those who have a tendency to report injuries. The hypothesis to be tested in this thesis is: The tendency to report injuries has no significant effect on the systematic variance in reported injuries between two successive one-year exposure intervals.