Sandra Transchel is Associate Professor for Supply Chain and Operations Management. From 2008 to 2011 Transchel was Assistant Professor for Supply Chain Management at the Pennsylvania State University, USA. In 2011 she was Visiting Assistant Professor at Tuck School of Business at Dartmouth, USA. In 2008 Dr. Transchel received her PhD from the University of Mannheim, Germany and graduated in March 2004 with a Diploma degree in Business Mathematics from the Otto-von-Guericke University in Magdeburg, Germany.
Transchel’s research interests are in the areas of supply chain management, inventory control, revenue management, and production scheduling. Her current research focuses on retail operations and supply chain management with the special interest in the integration of supply and demand management. Her research conducts theoretical research in inventories to study the relationship between replenishment policies, inventory levels, price strategies, perishability, and customers’ substitution behavior. She also studies optimal price and capacity management in Airline Alliances. Dr. Transchel’s research has appeared in numerous academic journals including Operations Research, European Journal of Operational Research, International Journal of Production Research, International Journal of Production Economics, and Business Research.
Bansal, Saurabh and Sandra Transchel (2014): Managing Supply Risk for Vertically Differentiated Co-Products, Production and Operations Management, 23 (9): 1577-1598.
Abstract: The manufacturing complexity of many high-tech products results in a substantial variation in the quality of the units produced. After manufacturing, the units are classified into vertically differentiated products. These products are typically obtained in uncontrollable fractions, leading to mismatches between their demand and supply. We focus on product stockouts due to the supply–demand mismatches. Existing literature suggests that when faced with product stockouts, firms should satisfy all unmet demand of a low-end product by downgrading excess units of a high-end product (downward substitution). However, this policy may be suboptimal if it is likely that low-end customers will substitute with a higher quality product and pay the higher price (upward substitution). In this study, we investigate whether and how much downward substitution firms should perform. We also investigate whether and how much low-end inventory firms should withhold to strategically divert some low-end demand to the high-end product. We first establish the existence of regions of co-production technology and willingness of customers to substitute upward where firms adopt different substitution/withholding strategies. Then, we develop a managerial framework to determine the optimal selling strategy during the life cycle of technology products as profit margins shrink, manufacturing technology improves, and more capacity becomes available. Consistent trends exist for exogenous and endogenous prices.
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Associate Professor of Logistics and Supply Chain Management at Kühne Logistics University, Hamburg, Germany
Dean of Programs at Kühne Logistics University, Hamburg, Germany
|07/2011 - 12/2011|
Visiting Assistant Professor of Business Administration at Tuck School of Business at Dartmouth, Hanover, NH, USA
|11/2008 - 06/2011|
Assistant Professor of Supply Chain Management at the Department of Supply Chain and Information Systems, Smeal College of Business at The Pennsylvania State University, State College, PA, USA
|10/2006 - 02/2007|
Visiting Researcher at the Tuck School of Business, Department of Operations Management & Management Science (Prof. David F. Pyke) at Tuck School of Business at Dartmouth, Hanover, NH, USA
Doctoral Degree (Dr. rer. pol. equivalent to Ph.D.) in Business Administration at the University of Mannheim; Doctoral Thesis: Integrated supply and demand management in operations
Diploma in Business Mathematics at the Otto-von-Guericke University, Magdeburg; Diploma Thesis: “On the performance of linear replenishment policies of a production-inventory problem under random demand and yield”