three extensions to the inventory theoretic approach- a transportation selection model, a discrete event simulation of the inventory theoretic approach, postponement from an inventory theoretic perspective

Three Extensions to the Inventory Theoretic Approach: A Transportation Selection Model A Discrete Event Simulation of the Inventory Theoretic Approach Postponement from an Inventory Theoretic Perspective Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Doral Edward Sandlin Graduate Program in Business Administration The Ohio State University 2010 Dissertation Committee: Professor Martha C. Cooper, Adviser Professor Keely L. Croxton, Professor Alan Johnson Professor John P. Saldanha Professor Walter Zinn Copyright by Doral E. Sandlin 2010 The views expressed in this article are those of the author and do not necessarily reflect the official policy or position of the Air Force, the Department of Defense, or the U.S. Government ii Abstract The objective of this research is to provide three extensions to the inventory theoretic approach which was developed to explain carrier/mode selection. One of the strengths of the approach is that it accounts for both demand and lead time uncertainty when calculating total logistics costs. As the world’s economies become more and more interconnected, supply chains are growing in length and complexity resulting in increased lead time uncertainty. To manage costs effectively, supply chain managers need to account for lead time uncertainty. This research attempts to extend the inventory theoretic approach in three stand-alone papers that examine issues such as product value, variation in demand of lead time, equipment shortages, overbooking, and currency fluctuations across multiple methodologies. The first chapter introduces the inventory theoretic approach and gives a brief overview of the remaining chapters. Chapter two develops an optimization model based on the inventory theoretic approach in an effort to aide managers in selecting the best carrier/mode for their product. Findings suggest that total logistics costs are minimized by selecting a faster mode of transportation as the value of the product and the coefficient of variation in demand increase. The model extends the existing state of the art in the inventory theoretic transportation selection literature by precluding the need for conducting multiple experiments among all available transportation options. Converting the inventory iii theoretic approach into an optimization problem provides a first step towards extending the inventory theoretic approach into the facility location literature stream. Chapter three uses the inventory theoretic approach in a discrete event simulation in an effort to investigate the accuracy of the numerical approach in estimating total logistics costs and rank-ordering the best to worst carriers. The inventory theoretic literature stream is replete with numerical examples and individual case studies, but has few examples of research that uses simulation. Empirical data for this study are gathered from a company. The case company uses a portfolio of carriers to ship product world- wide. Findings suggest that the numerical approach used in the inventory theoretic approach is robust for selecting the best carriers. In addition, carrier schedules were found to have an impact on which carrier provides the lowest total logistics cost. Finally, delays such as equipment shortages, ordering errors, and carrier overbooking were quantified. The results suggest that delays should be tracked by shippers, because an excessive number of delays by a carrier can impact the rank-ordering of carriers. Chapter four, the final chapter, extends the inventory theoretic approach to the postponement literature stream. A review of the postponement literature found that transportation uncertainty is largely ignored, lacks examples of an (s, Q) inventory model, and generally ignores the cost of in-transit stock, which is considered here. The fourth chapter also explores the concept of postponement as it relates to product life cycles. The literature supports the notion that postponement is more applicable to products with short product life cycles due to the risk of obsolescence. The second concept supported by the literature is the idea that products in the introduction/growth stage of a product life cycle should use a speculation strategy, while products in the iv mature/decline stages should use postponement. Empirical data for chapter four were gathered from a Global 500 Company. Results from this essay suggest that ignoring transportation uncertainty can underestimate the cost of using postponement and lead to the selection of a supply chain strategy that is more expensive. Other findings suggest that postponement strategies can be used for products with long product life cycles to reduce the total cost of a product. This is occurs for both products in the introduction/growth stage of the product life cycle as well as products at the mature/decline stage. Finally, this research suggests that fluctuations in currency exchange rates can be mitigated by use of an assemble-to-order strategy which is a form of manufacturing postponement. v Dedication Soli Deo Gloria and in loving memory of my Dad, Doral R. Sandlin vi Acknowledgments A special thanks to my five committee members for their patience, wisdom and encouraging support. Completing this project was definitely a team effort that could not have been accomplished without their help. My dissertation chair, Dr. Martha Cooper, for guiding me through the dissertation process. Not only is Dr. Cooper a gifted scholar, she spends countless hours mentoring and guiding students in their individual endeavors. She is truly dedicated to helping people out. I have truly enjoyed working with Dr. Cooper throughout this process. The impetus for this research began in early 2007 during my search for dissertation research topics. When I first met with Dr. John Saldanha, we discovered that we had a mutual interest in transportation-related research due to our common backgrounds; he as a former First Officer on ocean carriers and myself as an Air Force pilot. This commonality in backgrounds eventually led to the selection of a transportation related research topic and also a friendship between our families. His insight and guidance on my research has been invaluable and I thank him for the time he has invested in my studies. The three other members of my committee also played pivotal roles to any degree of success that I have achieved in this program. Dr. Keely Croxton was my academic advisor during my course work at The Ohio State University and her knowledge of piece- wise linear optimization was a key part of the research done during the first article. Dr. Alan Johnson was my research advisor and my simulation professor at the Air Force vii Institute of Technology. I appreciate his insightful feedback during my research. Finally, Dr. Walter Zinn was instrumental in ensuring that my knowledge of inventory theory was sound and offering excellent advice on establishing validity for my simulations. The contributions made by all of my committee members were greatly appreciated and I thank them for all of the time and effort that they invested in guiding my research efforts. Two unnamed individuals from the case companies in Chapter three and Chapter four deserve special recognition. Without their assistance, which was a significant investment in time, I would not have been able to collect the data nor would I have had a proper understanding of their company’s supply chains. A special thanks to my fellow PhD students, past and present, to include Ping, Francois, Matias, Rudi, Tim and Chris. I appreciate your friendship and advice. You seven were a pleasure to work with and will make outstanding scholars. However, the most important contribution to this work came from my family for their unconditional support during my long, long hours researching, studying, and writing. Georgi, Maddie, and Chase you three are my pride and my joy. I look forward to seeing what life has in store for you. Thank you for your prayers, hugs, words of encouragement, and constant entertainment. Any tough day at the office was overcome by spending time with you three. Finally, to the person I owe the biggest debt of gratitude in supporting all of my academic endeavors is my beautiful wife. Shannon, thank you for patiently putting up with my schedule and carrying more than your fair share during my doctoral studies. I never would have made it through this program without you, nor would I have wanted to do so. I cherish your love, support, and friendship. You are a special gift from God. viii Vita 1992 Bachelor of Science, Civil Engineering The United States Air Force Academy, Colorado Springs, Colorado 2004 Masters of Business Administration Rutgers University, Camden, New Jersey 2006 Masters of Logistics Management Air Force Institute of Technology, Dayton, Ohio 2009 Masters of Arts in Logistics The Ohio State University, Columbus, Ohio Publications Bird, Donald M., Gregory E. Seely, Carolyn L. Miller, Doral E. Sandlin, Matthew R. Yakely, and Anthony C. Gomillion, and Peter J. Holland (1993), ―Harnessing the Resources of Space in the Recovery of Potable Water from Wastewater by Lyophilization (Freeze-Drying),‖ Proceedings of the 23 rd International Conference on Environmental Systems, July 12-15 1993, Colorado Springs, CO. Holland, Peter J., Carolyn L. Miller, Donald. M. Bird, Jenny E. Yung, and Doral E. Sandlin (1992), ―Recovering Potable Water from Wastewater in Space Platforms by Lyophilization,‖ Proceedings of the 22 nd International Conference on Environmental Systems, July 13-16 1992, Seattle, WA. Fields of Study Major Field: Business Administration Area of Specialization: Logistics Minor Field: Operations Management ix Table of Contents page Abstract ii Dedication v Acknowledgments vi Vita viii Table of Contents ix List of Tables xii List of Figures xiv Chapter 1: Introduction 1 References 6 Chapter 2: Optimizing Transportation Using a Total Logistics Cost Approach 8 Introduction 8 Literature Review 10 Research Setting 16 Model Framework 18 The Model 18 Experimental levels 23 Results 25 Sensitivity Analyses: Selecting a Sub-Optimal Transportation Option 26 Sensitivity Analyses: Freight Rates 30 [...]... out the advantages of using optimization models include the handling of all kinds of costs (fixed, variable, and nonlinear) In addition, they efficiently handle a wide variety of variables, constraints are easily added or changed, and they guarantee the optimal answer given valid assumptions and accurate data Hence, additional constraints and other considerations can be added to the MILP formulation... Door -to- Door Transit Time (Days) Figure 2.1: Speed and Reliability Profiles of International Door -to- Door Transportation Options 16 Each transportation option represents a combination of transportation modes and carriers Freight rates for the transportation options are generally inversely related to the mean and standard deviation of door -to- door transit times Integrated air and ocean guaranteed moves are... constitute the largest proportion of the total logistics cost (Ballou 2004, pg 14) Therefore, the challenge is to find the right balance of inventory and transportation costs that achieve customer service goals at the minimum total logistics 8 cost Transportation carrier and mode selection is critical to achieving this balance This paper presents a model that balances transportation and relevant inventory. .. variation in demand By examining carriers and products as a bundle of attributes, Baumol and Vinod’s (1970) model enables researchers to determine the impact of a change in the value of an attribute, which gives their model a great deal of flexibility They found that the optimal choice of transportation requires a trade-off among the cost of transportation and the cost of inventory Transportation speed... Russell, and Tyworth (2006) and Leachman (2008) and parameters for port dwell times and inland modes provided by Leachman (2008) were used to set the range of means (22-50 days) and standard deviations (0.5-5.5 days) of total door -to- door transit times for direct and indirect ocean The myriad of carriers along with their corresponding modes of transportation and implications for inventory make this a complex... requirements of the inventory theoretic approach This gap in the inventory theoretic literature stream needs to be addressed if the usefulness of the inventory theoretic approach is to be expanded to other literature streams such as the facility location problem This paper attempts to contribute to the inventory theoretic literature by modifying the classic inventory theoretic transportation selection model to. .. time parameters are changed They extended the literature stream by allowing for non-normal distributions of lead time and demand during lead time and by relaxing the assumption of linear transportation costs Swan and Tyworth (2001) applied the inventory theoretic approach to railroad shipping to show that improving the transit time and increasing reliability is central to the profitability of both the. .. exposition of inventory theoretic transportation selection models These models trade off inventory and transportation costs at a fixed customer service level, to select the optimum transportation for a single product on a single lane This research extends the classic inventory theoretic transportation selection model to a global supply chain setting To do this, a new approach for modeling the nonlinear safety... models can handle a wide variety of variables, easily accommodate additional constraints, and guarantee the optimal answer given valid assumptions and accurate data In contrast to the matrix approach, which explicitly enumerates through the options, a MILP uses implicit enumeration Powers (1989) points out that some of the advantages of using optimization models include the handling of all kinds of costs... margins increase the pressure managers feel to reduce transportation costs If transportation costs are reduced at the expense of selecting a slower, less reliable transportation option, this would increase inventory costs, assuming constant customer service goals This is due to the speed and reliability of transportation influencing the level of inventory in the supply chain Transportation and inventory costs . Three Extensions to the Inventory Theoretic Approach: A Transportation Selection Model A Discrete Event Simulation of the Inventory Theoretic Approach Postponement from an Inventory Theoretic. handle a wide variety of variables, easily accommodate additional constraints, and guarantee the optimal answer given valid assumptions and accurate data. In contrast to the matrix approach,. the inventory theoretic approach in a discrete event simulation in an effort to investigate the accuracy of the numerical approach in estimating total logistics costs and rank-ordering the