Doctor of Philosophy, University of Toledo, 2023, Manufacturing and Technology Management

Blockchain technology (BCT) is a novel technology that can significantly change the business operations and models that we have today. It offers various advantages such as automation, improved efficiency, faster processing, cost savings, enhanced trust, and the elimination of intermediaries. BCT has many applications across diverse industries, including finance, commerce, food and agriculture, healthcare, education, and supply chain management. Despite its promising potential, the adoption of BCT remains relatively low due to a lack of understanding of the technology and uncertainties regarding its value proposition for businesses. This dissertation topic examines two research questions. First, the topic examines the determinants of blockchain adoption in supply chain management from beyond the dominant perspective. Second, the topic examines how blockchain adoption can create value for firms improving supply chain resilience in order to survive and sustain in a dynamic environment. The dissertation draws on dynamic capabilities theory to conceptualize the BCT adoption as a unique information processing capability that builds supply chain operational capabilities to improve supply chain resilience. Furthermore, the dissertation employs the technology–organization–environment (TOE) framework, diffusion of innovation (DOI) theory, institutional theory, and management fashion theory to identify and theorize paths via which factors influence blockchain adoption. This dissertation employs a survey method to collect data. The unit of analysis is firms that has adopted BCT or have the intention to adopt BCT in supply chain in the United States. The unit of observation is information systems or supply chain professionals who are familiar with blockchain applications in supply chain management (SCM) in different industries. These participants must have at least three years of experience with blockchain-related projects in the SCM. The study collected 320 responses from (open full item for complete abstract)

Committee: Benjamin George (Committee Co-Chair); Bassam Hasan (Committee Co-Chair); Mai Dao (Committee Member); Kishwar Ahmed (Committee Member) Subjects: Business Administration; Information Systems

Doctor of Philosophy (PhD), Ohio University, 2020, Industrial and Systems Engineering (Engineering and Technology)

A supply chain is a network of suppliers, production, or manufacturing facilities, retailers, and transportation channels which are structured to acquire supplies, produce new products, and distribute the finished products to retailers and customers. Closed Loop Supply Chain (CLSC) networks incorporate the flow of the returned, used, or recycled products from the customers through the retailers to the manufacturing, recycling, or refurbishing facilities to support managing the full lifecycle of the products. Social Network Analysis (SNA) has been developed to identify and analyze the patterns in social networks. SNA is used as a theoretical framework for better understanding of social networks by characterizing the structure of a network in terms of nodes and links. SNA is applied to various types of networks including telecommunication networks, protein interaction networks, animal disease epidemics, and customer interaction and analysis. Although SNA is a powerful method to study networks in many areas, it has not been comprehensively applied to supply chain networks. Likewise, there is no application and interpretation of SNA metrics in CLSCs. In this study, SNA metrics are introduced and interpreted for components in CLSC networks and forward and reverse logistic activities. Correspondingly, a decision making tool is developed based on selected SNA metrics for comparing alternative network designs in terms of network reliability and balance of the flows.

Committee: Saeed Ghanbartehrani (Advisor); Gary Weckman (Committee Member); Tao Yuan (Committee Member); Vardges Melkonian (Committee Member); Benjamin Sperry (Committee Member) Subjects: Industrial Engineering; Information Technology; Management

Doctor of Philosophy, University of Toledo, 2016, Industrial Engineering

The main goal of this research is to present new efficient methods and optimization models to enhance the Green Supply Chain Planning (GSCP). As a first objective, we focus on developing a novel optimization planning model in a green supply chain network consisting of suppliers, assemblers, distribution centers, and retailers. This model is subjected to various constraints which are related to the inventory and forward logistics management. We applied the proposed model for a vacuum and floor machines manufacturer case study located in the Midwestern, U.S. The main objective functions include: minimizing the costs of assembling, transporting, holding inventory at assembling sites and distribution centers, and shortage at retailers under carbon dioxide (CO2) emissions constraints throughout the logistic network; maximizing service levels and determining the acceptable service levels to meet final customers' demands. We applied three different solution methods including a gradient-based algorithm in MATLAB “Find Minimum of Constrained nonlinear multivariable function (FminCon)”, a novel metaheuristic algorithm “Grey Wolf”, and the “Branch and Bound (B&B)” algorithm in Lingo to find optimal solutions for the proposed optimization model, which has a specific complexity. We compared the achieved optimal solutions by these methods. The case study and expanded numerical example verify whenever the parameter of the minimum service level at retailers' sites increases or decreases, the amount of produced CO2 emissions and the total costs of the supply chain will directly correlate. It also demonstrates the trade-offs among the total costs of the supply chain network, CO2 emissions, and service levels. The achieved results reflect the efficiency of the proposed model for GSCP. As a second objective, we concentrate on revealing more information about optimal points in which performance measures of various adaptive (X ) ¯quality control charts hold their optimal minimum values. (open full item for complete abstract)

Committee: Matthew Franchetti Dr. (Committee Chair); Efstratios Nikolaidis Dr. (Committee Member); Kumar Ashok Dr. (Committee Member); Zhang Yue Dr. (Committee Member); Spivak Alex Dr. (Committee Member) Subjects: Applied Mathematics; Artificial Intelligence; Automotive Engineering; Business Costs; Computer Science; Engineering; Environmental Engineering; Environmental Management; Health Care; Health Care Management; Operations Research; Sustainability; Systems Design; Transportation Planning

Doctor of Philosophy in Manufacturing and Technology Management, University of Toledo, 2011, College of Business and Innovation

Supply chain risk management (SCRM) has become an emerging research issue during recent years (Christopher & Peck, 2004; Sheffi, 2005; Tang, 2006). Defining supply chain risk and identifying its sources have been essential tasks in determining how to manage supply chain risk. As firms face uncertain demands and supplier failures, they should be able to manage supply chain risks adequately, not only in order to maintain normal levels of operation but also to gain sustainable competitive advantages in the current business environment. By examining existing theories and conducting an extensive literature review, the researcher has identified two research gaps. One gap consists of a lack of available research on firm-level practices that make supply chains resilient in responding appropriately to supply chain disruptions and factors that lead firms to adopt and implement these practices. A second gap is the lack of a comprehensive and integrated resilient supply chain framework and methods to measure its development. Having identified research gaps, this study addresses three research questions: (1) What are the antecedents of resilient supply chain management practices? (2) What are the dimensions of resilient supply chain management practices, and how can each component be measured? (3) How do resilient supply chain management practices result in resilient supply chain capabilities? Drawing upon contingency theory (CT), this study identifies four types of risk and risk propensity as antecedents, or enablers, which result in firms implementing risk-related activities. A resource-based view (RBV) provides this study with the theoretical rationale to explain how firms' resources and routines not only reduce the detrimental effects of supply chain disruptions but also formulate external-facing capabilities that lead to a competitive advantage. The large-scale survey data was collected from the U.S. and South Korea, and analyzed by Structural Equation Modeling using AMOS (open full item for complete abstract)

Committee: Dale Dwyer (Committee Chair); Paul Hong (Committee Member); Hokey Min (Committee Member); Gene Chang (Committee Member); Sachin Modi (Committee Member) Subjects: Management

Doctor of Philosophy, University of Toledo, 2005, Manufacturing Management

With advances in information technology (IT), information systems integration (ISI) and its role in an integrated supply chain have become important to executives and researchers. ISI represents the degree of cooperation in information system practices between business functions within a firm and between a firm and its trading partners. It has been documented that the introduction and utilization of ISI for supply chain management enhance the firms' competitiveness and growth. While many firms focus on achieving high levels of IT utilization, without high levels of ISI, supply chain members may not attain the full benefits of working within a supply chain. The concept of ISI can be captured using two main sub-constructs (e.g., internal ISI and external ISI) and can be conceptualized at three levels – (1) Strategic, (2) Operational, and (3) Infrastructural. Studying the effects of ISI in these levels can help researchers and executives understand how ISI practices at different levels contribute to overall supply chain effectiveness. The implications of such an understanding may bring significant benefits to both operations researchers and practitioners. Such benefits may include making better decisions about which IT to utilize, which information systems (IS) practices to emphasize, and what level of ISI to attain. From a practitioner's perspective, this research provides important guidelines so firms may better understand ISI issues and effectively implement IT. This study proposes three significant contributions to supply chain management research. First, this study applies an information system perspective to study both causes and effects of supply chain integration. It proposes a theoretical framework that considers the role of ISI as a mediator between IT utilization and supply chain integration. Second, this study provides the inferences made from an instrument that is valid and reliable for the current study's context, which are beneficial for both practitione (open full item for complete abstract)

Committee: T.S. Ragu-Nathan (Advisor) Subjects: Business Administration, Management

Doctor of Philosophy, The Ohio State University, 2023, Business Administration

Supply chain risk management and public policy are both complex and ever-changing fields that continually affect each other across many industries including the United States (US) pharmaceutical industry. There is a call for more overlap between public policy and SCM from supply chain scholars (Helper et al., 2021; Joglekar et al., 2016; Spring et al., 2017; Tokar and Swink, 2019) and from public-policy makers (The White House, 2021). This dissertation focuses on understanding the elements connecting public policy and supply chain risk management (SCRM) and how the decisions in one discipline can affect the decisions in the other. First, a conceptual model is created depicting the elements, sub-elements, and relationships between public policy and supply chain risk management. This model is created through a structured literature review of notable and influential supply chain management journals and leverages interpretive sensemaking to contextually understand the public policy, social welfare, supply chain risk, supply chain risk management, and supply chain performance elements in each paper. The relationships are also identified in context and support a feedback loop between the elements; showing that public policy can affect SCRM and so too can SCRM affect public policy by way of affecting social welfare. This model is generalizable, spanning industries and geographic regions. After establishing the conceptual model, a deeper study of the US pharmaceutical supply chain is executed in the second essay. Pharmacy benefit managers (PBMs) are a player in the support supply chain of US pharmaceutical distribution, working on behalf of health care sponsors (e.g., health insurance) to manage the business decisions surrounding pharmaceutical coverage. This study asks how one of the PBM's sourcing practices, removal of drugs from insurance coverage, affects adverse events to patients. Secondary data from the FDA adverse events reporting s (open full item for complete abstract)

Committee: Keely Croxton (Committee Co-Chair); A. Michael Knemeyer (Committee Co-Chair); Terry Esper (Committee Member); John Gray (Committee Member) Subjects: Business Administration

Doctor of Philosophy, The Ohio State University, 2022, Business Administration

Supply chains have grown increasingly global and interconnected over the past decades. Technological advancements have enabled organizations to pursue improved performance while simultaneously reducing costs; all in pursuit of increased profits. However, this same supply chain globalization has amplified companies' risk exposures. These risks lead to increased supply chain disruptions- interruptions in the flow of materials and products between entities in supply chains. At the same time, high-impact disasters- from various causes- are increasing in frequency. For example, evidence from the COVID-19 pandemic has revealed how discrete events cause ripples felt across industries and geographies. Therefore, it is essential to improve our understanding of resilience- an organization's ability to withstand, recover and grow from disruption- not only to further scientific knowledge, but also to provide actionable guidance to our practitioner community. This dissertation examines how organizations respond to disruptions and communicate those disruptions- to partner organizations and public stakeholders. In Chapter 2, we utilize semi-structured interviews to explore how an organization's capabilities of agility, adaptability, and alignment (AAA capabilities) connect to and enable its resilience. We find empirical evidence suggesting that alignment between and within organizations drives the ability to respond to short-term disruptions (agility) and make long-term adjustments (adaptability). In Chapter 3, we utilize an online scenario-based experiment to assess whether the timing and accuracy of shared disruption-related information influence the relationship between a buyer and supplier. Much of the literature on information sharing during supply chain disruptions assumes that the information transmitted is accurate, an assumption unlikely to be true given the uncertainty surrounding supply chain disruptions. We show that when a supplier shares information quickly, regard (open full item for complete abstract)

Committee: Keely Croxton (Committee Co-Chair); A. Michael Knemeyer (Committee Co-Chair); Xiang Wan (Committee Member); Mikaella Polyviou (Committee Member) Subjects: Business Administration

Master of Science (MS), Bowling Green State University, 2020, Applied Statistics (ASOR)

When studying relevant research in the emerging field of green supply chain optimization, it is currently difficult to find modeling that provides a realistic, multi-nodal distribution process concerned with large-scale freight manufacturing and transport. Seen even more rarely is a combined objective that is focused on minimizing both cost and environmental impact. This thesis aims to fill that gap, as it follows products sold by a major US retailer from its manufacturing in Southern China to arrival, processing, and distribution in the United States. A multi-objective, linear optimization model is used. Decision variables include manufacturer, transportation method, port selection, distribution center selection, and timing. The paper utilizes published methodology for carbon emissions calculation and carbon market prices, and provides sensitivity analyses to extrapolate findings into real-world solutions. Many global organizations and nations have taken steps aimed at becoming carbon neutral. As the transportation sector makes up nearly one-third of all greenhouse gas emissions, it is important to explore options related to freight that reduce these emissions prior to any government regulations being enforced. The formulated linear program provides a breadth of decisions that contribute to moving products and satisfying demand. These decisions not only include location sourcing and time period selection, but also carbon-focused aspects of freight movement, including vehicle choice. The model formulated in this thesis allows interested corporations to customize inputs and evaluate the model using organization-specific parameters, enabling a holistic view of current operations from both an economic and environmentally conscious angle.

Committee: Ibrahim Capar Dr. (Advisor); Zubair Mohamed Dr. (Committee Member); Christopher Rump Dr. (Committee Member); William Sawaya Dr. (Committee Member) Subjects: Industrial Engineering; Operations Research; Statistics

Doctor of Philosophy (PhD), Ohio University, 2019, Industrial and Systems Engineering (Engineering and Technology)

As a strategic decision in the supply chain design, the manufacturing system design impacts the quality, flexibility and the profitability of the entire supply chain. The global supply chain network confronts challenges such as the uncertain market demand and the global trade tariffs. The main goal of this dissertation is to design global supply chain under the stochastic demand considering manufacturing operations and the impact of tariffs. The methodology consists of eight steps. First, the local manufacturer, located in USA, groups the similar products into families to save time, effort and cost. Second, as a clustering approach, the p-median model is studied and then modified to identify families considering the minimum average family similarity. Third, the manufacturer decides the best design for the manufacturing operations, in this step, the classical-cellular manufacturing system is designed under the stochastic market demand. Fourth, the expected revenues generated by the cells open for product families, considering the expected sales and selling prices, are determined. Besides, the expected manufacturing costs including the labor, machine, material and shortage costs are determined as well. Eventually, the expected profits are calculated and the optimal number of cells is identified based on the highest profits generated. Although, the optimal design of the manufacturing system generates higher profits, the demand may not be fully covered.Fifth, based on the optimal design obtained in the third step, the optimal expected profits of the product, based on the scenarios of restrictions on their demand coverage probabilities, are determined by a proposed mathematical model. In this step, if there is no restriction, the maximum profits are made when only one product is produced and sold. This is due to that it has the lowest processing time among all products. When restrictions are applied on the demand coverage, other products are produced and sold; however, l (open full item for complete abstract)

Committee: Gürsel Süer (Advisor); Khurrum Bhutta (Committee Member); Gary Weckman (Committee Member); Tao Yuan (Committee Member); Ashley Metcalf (Committee Member) Subjects: Business Administration; Industrial Engineering; Management; Systems Science

Master of Science (MS), Ohio University, 2018, Industrial and Systems Engineering (Engineering and Technology)

Designing a resilient supply chain (SC) is imperative in today's uncertain world as SCs are in constant risk of disruptions. This thesis presents a linear mathematical model developed specifically to aid in the design of a resilient supply chain. The model minimizes the overall network costs while determining optimal demand assignment, location of facilities, and investment level in resilience. An experimental study included in this thesis analyzes the applications of the model, its benefits in terms of SC resilience, limitations, and opportunities for improvement through future research.

Committee: Felipe Aros-Vera (Advisor) Subjects: Engineering; Operations Research

Master of Science (MS), Ohio University, 2017, Industrial and Systems Engineering (Engineering and Technology)

In this research, inventory management and production planning are applied in a global supply chain system. Data set comes from a pharmaceutical company that produces blood sugar strips. There is a manufacturing plants located in Puerto Rico with its own warehouse. Based on the customer demand, distribution centers and regional retailer centers are established in the continents and several countries, respectively. In order to choose the best locations for the distribution centers a facility-planning model is used. When inventory levels in the regional retailer centers drop to reorder points, items are ordered from a continental distribution center. The main distribution centers order the items from the manufacturing plants when their reorder points are violated. It is important to note that manufacturing plants are assumed to have limited capacity. In this problem, transportation leadtimes and demand quantities are defined as stochastic variables following normal distribution. The objective is to cover the demand with the minimum total cost. In the first step, a mathematical model is applied to choose the distribution centers. Then, continuous inventory policy is considered for retailers, distribution centers, and Puerto Rico warehouse. In the final step, simulation model is used to evaluate the entire approach.

Committee: Gursel Suer (Advisor) Subjects: Industrial Engineering

Master of Science (MS), Ohio University, 2017, Industrial and Systems Engineering (Engineering and Technology)

In a hospital, there are many factors that must be considered when determining inventory levels and frequency of ordering. Many supplies in a hospital are perishable, so they must be disposed of if they are not used before their expiration date. In addition, multiple hospitals in an area are often owned by the same organization, so they could potentially benefit from joint purchasing in larger quantities and redistributing to the individual hospitals. This inventory model determines the inventory level and reorder point for supplies to minimize total cost. The total cost includes holding cost, distribution cost, purchasing cost, stockout cost and discarding expired product cost. To reflect the fact that hospitals can jointly take advantage of bulk purchasing, a discount cost structure is utilized. To validate the model small-sized numerical examples are solved using the CPLEX solver within GAMS software. And for large-sized problems a Genetic Algorithm is presented. The model is also tested on a case based on data from the catheterization laboratory of a large hospital. Also, a sensitivity analysis of optimal solution is conducted and some important observations are drawn.

Committee: Dale Masel (Advisor); Diana Schwerha (Committee Member); Felipe Aros-Vera (Committee Member); Ashley Metcalf (Committee Member) Subjects: Industrial Engineering

PHD, Kent State University, 2016, College of Business and Entrepreneurship, Ambassador Crawford / Department of Management and Information Systems

As competition in the global market continues to grow and customers are becoming more environmentally as well as cost conscious, recent trends in retail practices attest to the attention and resources devoted to the returns in supply chains. Topping the list is the economic incentive to reap as much value as possible from returns. With the growth of an internet consumer base, vigorous competition and the advance of online sales regardless of product type, size and locations, many firms provide generous return policies. This has caused a significant increase in the volume of reverse flows and therefore great potential for value recovery from returns. According to the National Retail Federation, the value of merchandise returned amounted to $260.5 billion in 2015. Hence, ways of improving the performance of a supply chain through effectively and efficiently closing the loop have received considerable attention both from academic researchers and industry practitioners over the past two decades. One way to recoup returns value as quickly as possible is to decentralize reverse logistics functions to third party reverse logistics providers (3PRLP). Outsourcing to a 3PRLP allows a firm to gain a state-of-the-art reverse logistics program immediately thereby avoiding the capital investment and start up delay required to implement an in-house RL program. This dissertation proposes two models of a Closed-Loop Supply Chain (CLSC) with independent 3PRLP for returns processing. The first model presents a CLSC where demand is generated by a stochastic process. A fraction of the units that are initially sold are returned by the consumers for a full refund in every period. We model the forward flow interaction between the supplier, the retailer and 3PRLP by a widely accepted control policy that is lot size-reorder point inventory policy, which is detailed by the Markov process. We further propose a queuing network to capture reverse flow activities of the 3PRLP, which consists o (open full item for complete abstract)

Committee: Alfred Guiffrida (Committee Chair); Butje Eddy Patuwo (Committee Co-Chair); Emmanuel Dechenaux (Committee Member) Subjects: Business Administration

PHD, Kent State University, 2016, College of Business and Entrepreneurship, Ambassador Crawford / Department of Management and Information Systems

As competition in the global market continues to grow and customers are becoming more environmentally as well as cost conscious, recent trends in retail practices attest to the attention and resources devoted to the returns in supply chains. Topping the list is the economic incentive to reap as much value as possible from returns. With the growth of an internet consumer base, vigorous competition and the advance of online sales regardless of product type, size and locations, many firms provide generous return policies. This has caused a significant increase in the volume of reverse flows and therefore great potential for value recovery from returns. According to the National Retail Federation, the value of merchandise returned amounted to $260.5 billion in 2015. Hence, ways of improving the performance of a supply chain through effectively and efficiently closing the loop have received considerable attention both from academic researchers and industry practitioners over the past two decades. One way to recoup returns value as quickly as possible is to decentralize reverse logistics functions to third party reverse logistics providers (3PRLP). Outsourcing to a 3PRLP allows a firm to gain a state-of-the-art reverse logistics program immediately thereby avoiding the capital investment and start up delay required to implement an in-house RL program. This dissertation proposes two models of a Closed-Loop Supply Chain (CLSC) with independent 3PRLP for returns processing. The first model presents a CLSC where demand is generated by a stochastic process. A fraction of the units that are initially sold are returned by the consumers for a full refund in every period. We model the forward flow interaction between the supplier, the retailer and 3PRLP by a widely accepted control policy that is lot size-reorder point inventory policy, which is detailed by the Markov process. We further propose a queuing network to capture reverse flow activities of the 3PRLP, which consists o (open full item for complete abstract)

Committee: Alfred Guiffrida (Committee Chair); Butje Patuwo (Committee Co-Chair); Emmanuel Dechenaux (Committee Member) Subjects: Business Administration

Doctor of Philosophy (PhD), Ohio University, 2016, Mechanical and Systems Engineering (Engineering and Technology)

Global supply chain decisions, such as facility location, manufacturing system design, resource allocation, and distribution center location are long-term strategic decisions in nature and involve many uncertainties. Traditionally, a hierarchical approach is used design supply chain networks and manufacturing systems. First, the location of the facilities are determined, and then the manufacturing systems are designed at the selected locations. In this dissertation, a multi-stage supply chain network model is developed where locations of the plants and inner manufacturing system design are determined simultaneously for labor-intensive manufacturing companies. This dissertation aims to develop a decision making framework to integrate manufacturing systems and supply chain network design decisions considering optimal operator assignment and layered cellular manufacturing in mind. The industry studied is fashion jewelry manufacturing where labor cost is one of the major cost factors. Hence, optimizing the number of workers required for each operation, cell, and plant is critical for the cost efficiency of the entire supply chain. The optimal number of operators are determined for each manufacturing process, and then the optimal cell sizes are found for each manpower level using a heuristic procedure. The optimal number of manufacturing cells required to cover the uncertain demand is determined with mathematical modeling, and the designed layered cellular manufacturing systems for manufacturing stages are evaluated using Arena simulation models. The results of these models and methods are used as inputs while finding the optimal locations of the plants and allocating the optimal number of cells, workers, and machines for each selected plant. Different supply chain design alternatives considering various factors such as the shortest lead times, minimum capacity allocations, and multiple shifts are also studied.

Committee: Gursel A. Suer Ph.D. (Advisor) Subjects: Industrial Engineering; Operations Research

Doctor of Business Administration, Cleveland State University, 2014, Monte Ahuja College of Business

I investigate the effect of supply-chain disruption on a firm's decisions on investment in quality, and on ordering decisions, when there is a choice between suppliers, and a variable rate of knowledge transfer. I find that supply-chain disruption has a negative effect on profit, which can be mitigated by appropriate policies for order allocation and supplier development. When the probability of disruption is high, the firm should seek alternative sources of supply (even if they have lower levels of quality). Under certain conditions, the firm can improve its profit by investing in quality improvement efforts at the alternative supplier. I consider three different policies for supply-chain management and quality investment, and find that investment in supplier development is warranted when the initial quality level of the new supplier is relatively low; when the expected rate of improvement from such investment is relatively high; when the effectiveness of inspection is relatively low; and when the cost of inspection is relatively high.

Committee: Susan Slotnick PhD (Advisor); Raymond Henry PhD (Committee Member); Birsen Karpak PhD (Committee Member); Walter Rom PhD (Committee Member) Subjects: Business Costs; Management; Operations Research

PhD, University of Cincinnati, 2014, Business: Business Administration

A supply chain describes the entire process of providing a product or service from suppliers to customers through various manufacturers, distributors, retailers or other intermediaries. As the goal of supply chain management is to maximize overall supply chain surplus, operations management researchers systematically study inventory management, sourcing strategy and supply-network design from a supply chain perspective. Such an approach can capture the connections and influences of decisions made by individual agents in the supply chain. Understanding the optimal supply chain decisions under various scenarios ultimately helps to design better supply chain strategies to increase overall supply chain profitability. This dissertation proposes three essays using both analytical models and behavioral experiments to explore supply chain strategies in the presence of supply-capacity uncertainty, consumer trade-in services, or human fairness concerns. Specifically, the three essays study the following: 1) The first essay studies how uncertainty in supply capacity affects optimal ordering and pricing decisions, supplier and retailer profits, and incentives to reduce such uncertainty. Surprisingly, if two suppliers sell their identical products indirectly to the market through a retailer, then capacity risk reduction does not necessarily translate into increased profits for the supplier that reduces its risk. 2) The second essay studies the structure of the supply chain facilitating used-product return from, and resale to, end consumers and the impact of structure and key parameters on the effectiveness and efficiency of consumer trade-in programs. We model the typical supply chain structure of the trade-in program and study how the return quality will affect the program efficiency and agent incentives towards individual structures. 3) The third essay is a behavioral study on how private manufacturing cost information may affect channel interactions in the presence of hu (open full item for complete abstract)

Committee: Michael Fry Ph.D. (Committee Chair); Uday Rao Ph.D. (Committee Chair); Haresh Gurnani Ph.D. (Committee Member); Debashis Pal Ph.D. (Committee Member); Amitabh Raturi Ph.D. (Committee Member) Subjects: Business Education

Doctor of Philosophy, University of Toledo, 2014, College of Business and Innovation

Over the years, we have seen that products manufactured and the supply base of many manufacturers have become more complex. The reasons for the increase in complexity are many. Prominent ones are (a) advances in manufacturing technology; (b) customers' demand for new and improved product functionality; and (c) manufacturers' need to differentiate themselves from their competitors. The resulting increase in complexity can however have negative implications on the performance of the supply chain. As products and supply bases become more complex, the task of managing these complexities and achieving the desired results becomes more challenging. Inability to manage these complexities results in lower performance throughout the supply chain. Thus, we can say that product complexity and supply base complexity are both "necessary evils". Manufacturing literature has recognized that product complexity can have negative effects on plant performance. Emerging studies have explored the negative impacts of product complexity and supply base complexity. However, most of these studies are either conceptual or address narrow aspects of performance, such as delivery performance. In order to bridge this gap, the first aim of this study is to examine the impact of product complexity and supply base complexity on efficiency and responsiveness of the supply chain. Secondly, the study examines the mediating impact of coordination mechanism on the relationship between product complexity / supply base complexity on supply chain performance. Operational coordination and strategic coordination are proposed to be the mediating variables. Thirdly, recognizing the fact that complexity is unavoidable and inevitable in certain circumstances, the study proposes a set of mechanisms that help supply chains improve coordination and thus reduce the negative effects of complexity on supply chain performance. The proposed research model was tested using data collected by a large scale survey of m (open full item for complete abstract)

Committee: Monideepa Tarafdar (Committee Co-Chair); Ragu-Nathan T.S. (Committee Co-Chair); Thuong Le (Committee Member); Abdollah Afjeh (Committee Member) Subjects: Business Administration; Management

MS, University of Cincinnati, 2004, Engineering : Industrial Engineering

To respond to increasing competition, decreasing life cycle of products and manage the business in an effective manner more firms are now embracing the concept of Supply Chain to increase their overall rofitability. Reduced Life Cycle has increased the rate of products returns and product disposals. Companies have realized the value they could recover by remanufacturing or recycling the returned or disposed products. The tool to streamline and optimize this task of collecting the used products, refurbish them and finally sell it is Reverse Supply Chain. The paper starts by giving a background and definition of the Reverse Supply Chain. It enumerates the major issues involved in designing the reverse chain and the cost concentrations for implementing it. A comparison of the reverse chain with traditional forward chain points out their differences. A linear model has been formulated for a hypothetical case of reverse chain, which attempts to minimize the cost by considering the maximum number of collection and refurbishing sites, which should be open, and the cost of transporting the used products throughout the chain. As we are concerned with End of Life products, the concept of Greening the Supply Chain for creating environmentally safe chain has been introduced. A mass balance model has been formulated and used to compare two scenarios for used lead acid batteries viz. Refurbishing and Disposal. This mass balance equation could be used for comparing the feasibility of these two options with real time data.

Committee: Dr. RICHARD SHELL (Advisor) Subjects: Engineering, Industrial

Doctor of Philosophy, University of Toledo, 2010, Manufacturing Management

Over the past decade, an important focus of researchers has been on supply chain management (SCM), as many organizations believe that effective SCM is the key to building and sustaining competitive advantage for their products/services. To manage the supply chain, companies need to adopt an SCM strategy (SCMS) and implement appropriate SCM practices. However, different SCM strategies and practices require support from appropriate information technology (IT) applications and their usage. To effectively manage the supply chain, there is therefore a need for aligning these applications and their usage with the supply chain strategy and practices of the firm. While the literature on IT-business alignment has mainly focused on various aspects of the alignment between information systems (IS) strategy (ISS) and business strategy, it is largely deficient in offering an understanding of how specific supply chain strategies should be aligned with relevant IS strategies. Similarly, prior studies on SCM have developed considerable detail on supply chain strategies, without enunciating the implications of these strategies for the use of IT. Additionally, many studies have examined the importance of implementing SCM practices and their impact on supply chain and firm performance without identifying the corresponding IS usage that might be required for executing those practices in a more effective manner. Thus, there are no studies that explore the alignment between SCMS and ISS and between SCM practices and the usage of IT. This study contributes to the literature of SCM and IT by examining the alignment between the supply chain and information systems (SC-IS) at two levels. First, it looks at different SCM strategies and assesses appropriately- aligned information strategies that would enhance their effectiveness vis-a-vis their effect on the supply chain and firm performance; this is what this study refers to as alignment at the planning/strategic level. Second, the study look (open full item for complete abstract)

Committee: Monideepa Tarafdar PhD (Committee Co-Chair); T.S. Ragu-Nathan PhD (Committee Co-Chair); Thuong Le PhD (Committee Member); Hokey Min PhD (Committee Member) Subjects: Information Systems; Management