Essays in Operations Management: Applications in Health Care and the Operations-Finance Interface

I present three essays pertaining to the management of supply chain risks in this dissertation. The first essay and the second essay analyze supply chain risks from a financial perspective, while the third essay analyzes supply chain risk with the objective of maximizing societal benefits in health care. In my first essay, I consider a firm facing inventory decisions under the influence of the financial market. With stochastic analytical methods, the purpose of this essay is to examine the optimal inventory decisions under a variety of conditions. I have identified the relevant factors impacting such decisions and the firm's value. Moreover, I have studied the benefits brought by efforts to improve the random capacity of the firm. I conclude that the financial market can significantly impact both a firm's inventory decisions and process improvement incentives. In my second essay, I model a stylized supply chain managed by a base-stock inventory policy where the decision maker holds concerns about the down-side risk of the supply chain cost. With stochastic analytical methods, the purpose of this essay is to obtain solutions of the problem of minimizing Conditional Value-at-Risk under various supply chain scenarios. I find that various supply chain parameters may influence the optimal solution and the optimality of a stock-less operation. I conclude that operating characteristics of a supply chain can shape its inventory policy when down-side risks are taken into account. For my third essay, the purpose of this essay is to investigate the operational decisions of a medical center specializing in bone marrow transplants. Using the queuing system method, I formulate the medical center as a queuing system with random patient arrivals and departures. I find optimal decisions and efficient frontiers regarding waiting room size and the number of transplant rooms with the objective of maximizing patient health benefits. I conclude that the design of a health care delivery system is crucial for health care institutions to sustain and improve their social impacts. In each of the three essays, I use analytical and numerical approaches to optimize managers' decisions with respect to various sources of risk

Financial Market Imperfections and Business Cycles

This paper develops a simple model of macroeconomic behavior which incorporates the impact of financial market "imperfections," such as those generated by asymmetric information in financial markets. These information asymmetries may lead to breakdowns in markets, like that for equity, in which risks arm shared. In particular, we analyze firm behavior in the presence of equity rationing and imperfect futures markets, in which there are lags in production. Aft a consequence, firms act in a risk-averse manner. We trace out the macroeconomic consequences, and show that they are able to account for many of the widely observed aspects of actual business cycles.

Modeling Overstock

Two main problems have been emerging in supply chain management: the increasing pressure to reduce working capital and the growing variety of products. Most of the popular indicators have been developed based on a controlled environment. A new indicator is now proposed, based on the uncertainty of the demand, the flexibility of the supply chains, the evolution of the products lifecycle and the fulfillment of a required service level. The model to support the indicator will be developed within the real options approach.overstock, stock management, real options

Scor Quality Model Affecting Manufacturing Firm’s Supply Chain Quality Performance And The Moderating Effect Of Qms

The main objective of this study is hypothesis testing to explain the nature of the relationship between the independent variables (The SCOR quality model) and the dependent variable (Supply Chain Quality Performance) and moderated by (QMS). Objektif utama kajian ini adalah untuk menerangkan hubungan antara model SCOR kualiti dengan prestasi kualiti rantaian bekalan sesebuah firma dan QMS memoderasikan huungan model SCOR kualiti dengan prestasi kuality rantaian bekalan

Inventory drivers in a pharmaceutical supply chain

In recent years, inventory reduction has been a key objective of pharmaceutical companies, especially within cost optimization initiatives. Pharmaceutical supply chains are characterized by volatile and unpredictable demands –especially in emergent markets-, high service levels, and complex, perishable finished-good portfolios, which makes keeping reasonable amounts of stock a true challenge. However, a one-way strategy towards zero-inventory is in reality inapplicable, due to the strategic nature and importance of the products being commercialised. Therefore, pharmaceutical supply chains are in need of new inventory strategies in order to remain competitive. Finished-goods inventory management in the pharmaceutical industry is closely related to the manufacturing systems and supply chain configurations that companies adopt. The factors considered in inventory management policies, however, do not always cover the full supply chain spectrum in which companies operate. This paper works under the pre-assumption that, in fact, there is a complex relationship between the inventory configurations that companies adopt and the factors behind them. The intention of this paper is to understand the factors driving high finished-goods inventory levels in pharmaceutical supply chains and assist supply chain managers in determining which of them can be influenced in order to reduce inventories to an optimal degree. Reasons for reducing inventory levels are found in high inventory holding and scrap related costs; in addition to lost sales for not being able to serve the customers with the adequate shelf life requirements. The thesis conducts a single case study research in a multi-national pharmaceutical company, which is used to examine typical inventory configurations and the factors affecting these configurations. This paper presents a framework that can assist supply chain managers in determining the most important inventory drivers in pharmaceutical supply chains. The findings in this study suggest that while external and downstream supply chain factors are recognized as being critical to pursue inventory optimization initiatives, pharmaceutical companies are oriented towards optimizing production processes and meeting regulatory requirements while still complying with high service levels, being internal factors the ones prevailing when making inventory management decisions. Furthermore, this paper investigates, through predictive modelling techniques, how various intrinsic and extrinsic factors influence the inventory configurations of the case study company. The study shows that inventory configurations are relatively unstable over time, especially in configurations that present high safety stock levels; and that production features and product characteristics are important explanatory factors behind high inventory levels. Regulatory requirements also play an important role in explaining the high strategic inventory levels that pharmaceutical companies hold

A Conceptual Framework of Reverse Logistics Impact on Firm Performance

This study aims to examine the reverse logistics factors that impact upon firm performance. We review reverse logistics factors under three research streams: (a) resource-based view of the firm, including: Firm strategy, Operations management, and Customer loyalty (b) relational theory, including: Supply chain efficiency, Supply chain collaboration, and institutional theory, including: Government support and Cultural alignment. We measured firm performance with 5 measures: profitability, cost, innovativeness, perceived competitive advantage, and perceived customer satisfaction. We discuss implications for research, policy and practice

Improving bankruptcy prediction in micro-entities by using nonlinear effects and non-financial variables

The use of non-parametric methodologies, the introduction of non-financial variables, and the development of models geared towards the homogeneous characteristics of corporate sub-populations have recently experienced a surge of interest in the bankruptcy literature. However, no research on default prediction has yet focused on micro-entities (MEs), despite such firms’ importance in the global economy. This paper builds the first bankruptcy model especially designed for MEs by using a wide set of accounts from 1999 to 2008 and applying artificial neural networks (ANNs). Our findings show that ANNs outperform the traditional logistic regression (LR) models. In addition, we also report that, thanks to the introduction of non-financial predictors related to age, the delay in filing accounts, legal action by creditors to recover unpaid debts, and the ownership features of the company, the improvement with respect to the use of solely financial information is 3.6%, which is even higher than the improvement that involves the use of the best ANN (2.6%)

The hidden potential of "managerial macroeconomics" for CEO decision making in MBA programs

Macroeconomics has profound strategic and tactical implications for CEO decision making, yet many top-ranked business schools do not offer this subject in its appropriately integrative and applied management context. I illustrate how the careful cultivation of "macroeconomic literacy" in the MBA classroom using four innovative instructional strategies can improve CEO decision making across all functional areas of the firm while helping to meet important AACSB learning goals, including curriculum integration, application of interactive teaching strategies, soft skills enhancement, and promoting a global perspective. © Academy of Management Learning & Education, 2006

A DECISION SUPPORT AID FOR BEEF CATTLE INVESTMENT USING EXPERT SYSTEMS

The beef cattle investment decision provides an excellent opportunity to increase the economic efficiency of beef cattle production. The investment questions that face beef cattle producers are of interest to beef cattle producers, educators, and financial institutions involved in lending to beef cattle producing firms. This study develops a decision support aid utilizing expert system technology to assist beef cattle producers in making well-founded investment decisions with respect to the firm's beef cattle herd.Beef cattle investment, Decision support, Export systems, Livestock Production/Industries,