Prof. Dr. Sandra Transchel

Associate Professor of Supply Chain and Operations Management

Publications

Journal Articles (Peer-Reviewed)

Copy reference link   DOI: doi:http://dx.doi.org/10.1016/j.ejor.2016.12.016

Abstract: Abstract Empirical research has shown that the degree of order variability in supply chains is significantly influenced by product- and industry-specific factors. This paper analyzes the impact of perishability on order variability and the bullwhip effect in supply chains. We decompose the ordering process of a retailer into a sales and an outdating process and quantify their short- and long-term variability and correlation. We find differences to non-perishable product supply chains driven by the impact of the inventory depletion policy, stock-out management, and retailers service level requirement. These three factors significantly affect the retailer’s order variability and thus the decision making process and the profitability of the upstream supply stage. For the majority of instances, the perishable nature of a product results in the ordering process having a lower variability than the demand process. Only when inventory depletion is dominated by last-in-first-out in high service level environments, variability amplification can be observed. We propose a dynamic ordering policy for the upstream supply stage, taking into account negative correlation of retailer orders between periods. This dynamic policy may lead to substantial performance improvements. In a sensitivity analysis, we investigate the impact of shelf life, lead time and demand correlation.

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Copy reference link   DOI: doi:http://dx.doi.org/10.1016/j.ejor.2015.08.003

Abstract: Abstract Practical experience and scientific research show that there is scope for improving the performance of inventory control systems by delaying a replenishment order that is otherwise triggered by generalised and all too often inappropriate assumptions. This paper presents the first analysis of the most commonly used continuous (s, S) policies with delayed ordering for inventory systems with compound demand. We analyse policies with a constant delay for all orders as well as more flexible policies where the delay depends on the order size. For both classes of policies and general demand processes, we derive optimality conditions for the corresponding delays. In a numerical study with Erlang distributed customer inter-arrival times, we compare the cost performance of the optimal policies with no delay, a constant delay and flexible delays. Sensitivity results provide insights into when the benefit of delaying orders is most pronounced, and when applying flexible delays is essential.

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Copy reference link   DOI: doi:10.1080/00207543.2015.1053579

Abstract: We consider production systems in technology industries where output quality of a single production run has a large variance. Firms operating such systems classify products into different quality bins and sell units in one bin at the same tagged quality level and the same price. Consumers have heterogeneous quality preferences and choose that quality that maximises their net utility. We examine firms’ assortment, production and pricing problem. We present a three-stage solution procedure that optimises the production quantity, quality specification and number of bins. In that regard, we show that for a manufacturing technology with known quality distribution and known distribution of customers’ quality preference, the optimal assortment and production quantity are set such that on average, the demand of each bin is exactly fulfilled. We examine the impact of an improved manufacturing technology, variation in consumer preferences and changing price premium on the optimal assortment, lot size, market share, yield loss and the overall profitability. We further show that when the quality distribution of the manufacturing process is unknown, downward substitution leads to product offering of higher quality and higher prices. Finally, we discuss practical considerations for pricing, technology and optimal product offerings, and explain the proliferation of bins witnessed in the last decade in the processor industry.

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Copy reference link   DOI: 10.1111/poms.12173

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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Copy reference link   DOI: 10.1016/j.bushor.2013.11.002

Abstract: Better-aligned operational and strategic plans and a better balance of supply and demand bring tangible benefits to firms. However, functional departments in firms often operate without vertical and horizontal alignment. The outcomes are delays and amplification of the information flow, suboptimal corporate plans, uncoordinated reactions within the business, insufficient operational flexibility, and discrepancies in supply and demand. Sales and operations planning (S&OP) can circumvent these negative consequences and align the organization. Our multi-method research develops a holistic S&OP maturity model that firms can use for the assessment of their internal S&OP processes and shows the pathway to an integrated S&OP approach for the achievement of a better-aligned organization. We present a case study of a medium-sized, Swiss-based pharmaceutical company that has recently implemented S&OP to highlight why companies implement S&OP, the prerequisites and roadblocks encountered during implementation, and the benefits envisioned and achieved. Finally, we reveal the great relevance of the topic by means of a questionnaire survey which shows that organizations’ current S&OP performance is underdeveloped and that many improvements are indispensable to enjoy all benefits associated with the alignment process.

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Copy reference link   DOI: 10.1080/00207543.2010.532910

Abstract: Tailored for a complex application in the process industry, this article examines a multi-product production planning and scheduling problem with sequence-dependent setup cost and times. The manufacturing process is characterised by a two-stage structure where the sequencing problem occurs on the first level and contribution margin, holding cost, penalty cost are accounted on the second level. We present a hybrid mixed-binary optimisation model based on the general lot-sizing and scheduling problem [Fleischmann, B. and Meyr, H. 1997. The general lotsizing and scheduling problem. OR Spectrum, 19 (1), 11–21], which combines discrete and continuous-time elements within a standard inventory and lot-size (I&L) formulation. Since the I&L formulation does not provide sharp linear programming-relaxation bounds, we present two alternative reformulations based on a transportation problem. In a numerical study inspired by real industry data, we show that on average, both reformulations yield significant improvements in computation time and integrality gap.

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Copy reference link   DOI: 10.1016/j.ijpe.2010.06.018

Abstract: We study a problem of dynamic quantity competition in continuous time with two competing retailers facing different replenishment cost structures. Retailer 1 faces fixed ordering costs and variable procurement costs and all inventory kept in stock is subject to holding costs. Retailer 2 only faces variable procurement costs. Both retailers are allowed to change their sales quantities dynamically over time. Following the structure of the economic order quantity (EOQ) model, retailer 1 places replenishment orders in batches and retailer 2 follows a just-in-time (JIT) policy. The objective of both retailers is to maximize their individual average profit anticipating the competitor's replenishment and output decisions. The problem is solved by a two-stage hierarchical optimization approach using backwards induction. The second-stage model is a differential game in output quantities between the two retailers for a given cycle length. At the first stage, the replenishment policy is determined. We prove the existence of a unique optimal solution and derive an open-loop Nash equilibrium. We show that both retailers follow contrary output strategies over the order cycle. The EOQ retailer, driven by inventory holding costs, decreases his market share whereas the output of the JIT retailer increases. Moreover, depending on the cost structure, the EOQ retailer might partially be a monopolist. At the first stage, the EOQ retailer determines the cycle length, anticipating the optimal output trajectories at the second stage.

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Abstract: We consider an economic order quantity model where the supplier offers an all-units quantity discount and a price sensitive customer demand. We compare a decentralized decision framework where selling price and replenishment policy are determined independently to simultaneous decision making. Constant and dynamic pricing are distinguished. We derive structural properties and developalgorithms that determine the optimal pricing and replenishment policy and show how quantity discounts not only influence the purchasing strategy but also the pricing policy. A sensitivity analysis indicates the impact of the fixed-holding cost ratio, the discount policy, and the customers' price sensitivity on the optimal decisions.

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Books

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Abstract: The goal matching supply with demand, which is the fundament of supply chain management, has changed the role of operations management from pure cost control to value creation. The recent developments of integrating revenue management with supply chain management activities and the resulting successes have indicated the tremendous potential to improve the supply chain performance in the same way that revenue management has revolutionized the airline industry. This thesis investigates how an integration of revenue management and supply chain management influences decision making and the overall profitability. In particular, simultaneous decision making of selling price, inventory control strategy and capacity acquisition is analyzed.

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Conference Proceedings

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Abstract: In disassemble-to-order (DTO) systems randomness of recoverable parts gained from used products creates a major challenge for appropriate planning. Typically, it is assumed that yields from disassembly are either stochastically proportional (SP) or follow a binomial (BI) process. In the case of yield misspecification, it can be shown that the BI yield assumption usually results in a lower penalty than the SP yield assumption. For BI yield, however, a suitable, powerful heuristic is needed in order to facilitate DTO problems olving for complex realworld product structures. We present a heuristic approach that is based on a ecomposition procedure for the underlying non-linear stochastic optimization problem and that can be applied to problems of arbitrary size. A numerical performance study reveals that this heuristic yields close - to - optimal results.

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