Prof. Jan Fransoo, PhD

Professor for Operations Management and Logistics

Dean of Research

Publications

Journal Articles (Peer-Reviewed)

Copy reference link   DOI: 10.1007/s10696-017-9301-y

Abstract: Today, climate change is the greatest challenge for future generations. In particular, logistics is perceived as a key sector to contribute to sustainable development meeting the future generations’ needs in terms of low greenhouse gas emissions in a socially and economically responsible way. Green logistics involves all attempts to reduce the ecological impact of peoples’ mobility, traffic systems and of transport in regional and global supply chains including the reverse flow of products and materials.The primary objective of this special issue is to reflect the sustainable development of logistics from various perspectives preferably in an integrated and holistic approach and to examine research issues concerned with quantitative analysis and decision support for supply network design, freight transport and logistics infrastructure. For this special issue eight papers from 36 submissions have been selected for publication after a thorough peer-review according to the standards of the FSM journal.

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Copy reference link   DOI: 10.1016/j.ejor.2017.11.030

Abstract: We model a periodic review inventory system with non-stationary stochastic demand, in which a manufacturer is procuring a component from two available supply sources. The faster supply source is modeled as stochastic capacitated with immediate delivery, while the slower supply source is modeled as uncapacitated with a longer fixed lead time. The manufacturer’s objective is to choose how the order should be split between the two supply sources in each period, where the slower supply source is used to compensate for the supply capacity unavailability of the faster supply source. This is different from the conventional dual-sourcing problem, and motivated by the new reality of near-shoring options. We derive the optimal dynamic programming formulation that minimizes the total expected inventory holding and backorder costs over a finite planning horizon and show that the optimal policy is relatively complex. We extend our study by developing an extended myopic two-level base-stock policy and we show numerically that it provides a very close estimate of the optimal costs. Numerical results reveal the benefits of dual-sourcing under near-shoring, where we point out that in most cases the manufacturer should develop a hybrid procurement strategy, taking advantage of both supply sources to minimize its expected total cost.

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Copy reference link   DOI: 10.1007/s10111-017-0443-1

Abstract: Objective: To characterize how schedulers spend their time interacting with external parties.Background: Time is the most critical resource at the disposal of schedulers; however its usage has been overlooked by prior empirical studies. Methods: Seven schedulers for a total of nineteen 8-hour shifts where observed. Detailed time data about their activities and how these where interrupted was collected. Results: Schedulers interrupt themselves significantly and most of their activities are triggered externally. Despite this, schedulers are able to decide in most situations which activity to perform next. Schedulers spend more time on their informational role than on their decisional role; mostly at the requests of others, suggesting insufficient information system support to others in the organization.Conclusion: Schedulers other main role, besides making scheduling related decisions is to relay information. This implies that schedulers are subject to several external requests for activities. However, due to asynchronous communication that e-mails provide, they are still able to decide on their own schedule to do tasks.Application: The methodology used can be used to evaluate an individual use of time, in particular for time-critical such as scheduling. The analysis may provide insights as to how to improve the efficiency of such jobs.

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Copy reference link   DOI: 10.1016/j.cor.2017.06.015

Abstract: Tempelmeier and Hilger (2015) study the stochastic dynamic lot sizing problem with multiple items and limited capacity. They propose a linear optimization formulation for the problem based on a piece-wise linear approximation of the non-linear functions for the expected backorders and the expected inventory on hand. Building on the work of Tempelmeier and Hilger (2015), we correct an erroneous derivation of the linear optimization problem and propose an improved model.

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Copy reference link   DOI: 10.1016/j.trb.2018.02.007

Abstract: In this paper, we study a hinterland empty container transportation system<br/>which consists of a sea container terminal and an inland container terminal. There are a hinterland container operator who is in charge of the hinterland container transportation and an ocean carrier who has an empty container depot at the sea container terminal. We utilize a two-stage game model to describe the ocean carrier’s decision about the container’s free detention time and the hinterland container operator’s decision about the time when should an arrived empty container at the inland terminal be dispatched to the sea terminal. Optimal delivery policy of the empty container and the ocean carrier’s optimal free detention time are derived. It is shown that the decentralized system does not guarantee system coordination all the time. The ocean carrier has incentive to integrate the hinterland transportation operation only if the hinterland area is not very short of empty containers.

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Copy reference link   DOI: 10.1016/j.ejor.2017.09.014

Abstract: In large cities in emerging economies, traditional retail is present in a very high density, with multiple independently owned small stores in each city block. Consequently, when faced with a stockout, consumers may not only substitute with a different product in the same store, but also switch to a neighboring store. Suppliers may take advantage of this behavior by strategically supplying these stores in a coherent manner. We study this problem using consumer choice models. We build two consumer choice models for this consumer behavior. First, we build a Nested Logit model for the consumer choice process, where the consumer chooses the store on the first level and selects the product on the second level. Then, we consider an Exogenous Substitution model. In both models, a consumer may substitute at either the store level or the product level. Furthermore, we estimate the parameters of the two models using Markov chain Monte Carlo algorithm in a Bayesian manner. We numerically find that the Nested Logit model outperforms the Exogenous Substitution model in estimating substitution probabilities. Further, the information on consumers’ purchase records helps improve the estimation accuracies of both the first-choice probabilities and the substitution probabilities when the beginning inventory level is low. Finally, we show that explicitly including such substitution behavior in the inventory optimization process can significantly increase the expected profit.

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Copy reference link   DOI: 10.1016/j.trd.2017.08.016

Abstract: This article studies the allocation of CO2 emissions to a specific shipment in routing transportation. The authors show that this problem differs from a cost allocation problem specifically because the concavity condition does not hold necessarily in the CO2 allocation problem. This implies that a traditional cost allocation method cannot be straightforwardly translated into a CO2 allocation problem, and thus, new methods need to be developed. This study proposes four allocation mechanisms that are extensions from the literature and the common practice in industries. In doing so, the authors introduce the concept of carbon efficiency to assess if a particular allocation rule drives companies to carbon emissions reduction. They present analytical properties that show that the current practice of allocating CO2 emissions based on the greenhouse gas protocol, fails to be sensitive to drive companies to the sustainable practice of placing consolidated orders. The authors also conduct an experimental analysis using data of a logistics service provider that operates in Europe. Using the results of the experiments, they show that simple allocation methods can lead to a fair and carbon efficient allocation. In addition, the study provides insights by conducting a sensitivity analysis, and it shows that the CO2 allocations are not substantially susceptible to shipment size estimation errors.

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Copy reference link   DOI: 10.1287/opre.2017.1616

Abstract: Many seasonal products are transported via ocean carriers from origin to destination markets. The shipments arriving earlier in the market may sell at higher prices, but faster shipping services can be costly. In this paper, we study a newsvendor-type shipper who transports and sells seasonal products to an overseas market, where the selling price declines over time. A set of vessels with different schedules and freight rates are available to choose from. Our analysis demonstrates that a portfolio of vessels has two distinct effects on mitigating uncertainties in both demand and vessels’ arrival schedules, while these two portfolio effects have been previously understood as separate issues in the literature. To find the optimal portfolio in our problem,we first show that when vessels arrive in a deterministic sequence, the optimal portfolio can either be derived in closed form (in the single-demand setting) or computed efficiently with a variation of the shortest-path algorithm (in the multi-demand setting). Then, based on these results, we propose an approximation procedure to address the general problem with an uncertain arrival sequence. In each iteration of the procedure, we only need to minimize a cost function approximated by a deterministic arrival schedule and the portfolio generated can converge to the optimal one under mild conditions. Finally, we present a real-world case studyto demonstrate several practical implications of managing a carrier portfolio.

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Copy reference link   DOI: 10.1080/24725854.2017.1325026

Abstract: It has long been recognized that the bullwhip effect in real life depends on a behavioral component. However, non-experimental research typically considers only structural causes in its analysis. In this paper, we study the impact of behavioral biases on the performance of inventory/production systems modeled through an APVIOBPCS (Automatic Pipeline, Variable Inventory, Order Based Production Control System) design using linear control theory. To explicitly model managerial behavior, we allow independent adjustments to inventory and pipeline feedback loops. We consider the biases of smoothing/over-reaction to inventory and pipeline mismatches, and the under/over-estimation of the pipeline. To quantify the performance of the system, we first develop a new procedure to determine the exact stability region of the system and we derive an asymptotic stability region that is independent of the lead time. Afterwards, we analyze the effect of different demand signals on order and inventory variations. Our findings suggest that normative policy recommendations must take demand structure explicitly into account. Finally, through extensive numerical experiments, we find that the performance of the system depends on the combination of the behavioral biases and the structure of the demand stream.

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Copy reference link   DOI: 10.1016/j.compchemeng.2016.08.011

Abstract: In this work, we develop a mixed integer linear optimization model that can be used to select appropriate sources, capture technologies, transportation network and CO2 storage sites and optimize for a minimum overall cost for a nationwide CO2 emission reduction in the Netherlands. Five different scenarios are formulated by varying the location of source and storage sites available in the Netherlands. The results show that the minimum overall cost of all scenarios is €47.8 billion for 25 years of operation and 54 Mtpa capture of CO2. Based on the investigated technologies, this work identifies Pressure Swing Adsorption (PSA) as the most efficient for post-combustion CO2 capture in the Netherlands. The foremost outcome of this study is that the capture and compression is the dominant force contributing to a majority of the cost.KeywordsCarbon capture; CO2 reduction; Supply chain; Optimization; CCS; Mathematical model

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Copy reference link   DOI: 10.1007/s00291-016-0471-x

Abstract: We consider an original equipment manufacturer (OEM) who has outsourced the production activities to a contract manufacturer (CM). The CM produces for multiple OEMs on the same capacitated production line. The CM requires that all OEMs reserve capacity slots before ordering and responds to these reservations by acceptance or partial rejection, based on allocation rules that are unknown to the OEM. Therefore, the allocated capacity for the OEM is not known in advance, also because the OEM has no information about the reservations of the other OEMs. Based on a real-life situation, we study this problem from the OEM’s perspective who faces stochastic demand and stochastic capacity allocation from the contract manufacturer. We model this problem as a single-item, periodic review inventory system, and we assume linear inventory holding, backorder, and reservation costs. We develop a stochastic dynamic programming model, and we characterize the optimal policy. We conduct a numerical study where we also consider the case that the capacity allocation is dependent on the demand distribution. The results show that the optimal reservation policy is little sensitive to the uncertainty of capacity allocation. In that case, the optimal reservation quantities hardly increase, but the optimal policy suggests increasing the utilization of the allocated capacity. Further, in comparison with a static policy, we show that a dynamic reservation policy is particularly useful when backorder cost and uncertainty are low. Moreover, we show that for the contract manufacturer, to achieve the desired behavior, charging little reservation costs is sufficient.

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Copy reference link   DOI: 10.1016/j.trb.2016.10.005

Abstract: We study the strategic problem of a logistics service provider managing a (possibly heterogeneous) fleet of vehicles to serve a city in the presence of access restrictions. We model the problem as an area partitioning problem in which a rectangular service area has to be divided into sectors, each served by a single vehicle. The length of the routes, which depends on the dimension of the sectors and on customer density in the area, is calculated using a continuous approximation. The aim is to partition the area and to determine the type of vehicles to use in order to minimize the sum of ownership or leasing, transportation and labor costs. We formulate the problem as a mixed integer linear problem and as a dynamic program. We develop efficient algorithms to obtain an optimal solution and present some structural properties regarding the optimal partition of the service area and the set of vehicle types to use. We also derive some interesting insights, namely we show that in some cases traffic restrictions may actually increase the number of vehicles on the streets, and we study the benefits of operating a heterogeneous fleet of vehicles.

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Copy reference link   DOI: 10.1007/s10696-016-9240-z

Abstract: This article applies multiobjective optimization to show how the tradeoffs between cost and carbon emissions may be obtained in the context of sustainable operations. We formulate a model where transportation mode selection and order quantity decisions are considered jointly. We derive structural properties of the model and develop several insights. First, we show that switching to a greener mode of transportation while continuing to optimize the total logistics costs function may lead to a dominated solution. Second, we prove that the modal shift occurs only under strong carbon emissions reduction requirements. Third, we show that the efficient frontier is non-convex and we analyze some implications. Finally, we analyze the impacts of an increase in truck capacity. The results are illustrated through an example of a French retailer.

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Copy reference link   DOI: 10.1186/s41072-016-0008-0

Abstract: In recent years, there has been significant interest in the development of connectivity indicators for ports. For short sea shipping, especially in Europe, Roll-on Roll-off (RoRo) shipping is almost equally important as container shipping. In contrast with container shipping, RoRo shipments are primarily direct, thus the measurement of its connectivity requires a different methodology. In this paper, we present a methodology for measuring the RoRo connectivity of ports and illustrate its use through an application to European RoRo shipping. We apply the methodology on data collected from 23 different RoRo shipping service providers concerning 620 unique routes connecting 148 ports. We characterize the connectivity of the ports in our sample and analyze the results. We show that in terms of RoRo connectivity, neither the number of links nor the link quality (frequency, number of competing providers, minimum number of indirect stops) strictly dominate the results of our proposed indicator. The highest ranking ports combine link quality and number. Finally, we highlight promising areas for future research based on the insights obtained.

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Copy reference link   DOI: 10.1111/tesg.12152

Abstract: Although anecdotal evidence suggests that co-location can bring about several benefits for co-located logistics companies, implying the need to incorporate such considerations in location decisions, these benefits have hardly been analysed empirically. This paper provides detailed insights for decision making by precisely analysing the synergies attained through the co-location of logistics firms in specialised and diverse logistics concentration areas. The paper analyses whether co-location in logistics concentration areas that specialise in fresh produce provides additional benefits over co-location in diverse logistics concentration areas that do not specialise in any particular type of products. A survey of managers of 127 logistics firms located in logistics concentration areas tested for differences in synergies through co-location in specialised versus diverse logistics concentration areas. Logistics firms co-located in fresh produce logistics parks share knowledge, combine transport and storage capacities, and trade products more than logistics firms co-located in diverse logistics concentration areas.

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Copy reference link   DOI: 10.1016/j.trd.2015.12.009

Abstract: Transportation CO2 emissions are expected to increase in the following decades, and thus, new and better alternatives to reduce emissions are needed. Road transport emissions are explained by different factors, such as the type of vehicle, delivery operation and driving style. Because different cities may have conditions that are characterized by diversity in landforms, congestion, driving styles, etc., the importance of assigning the proper vehicle to serve a particular region within the city provides alternatives to reduce CO2 emissions. In this article, we propose a new methodology that results in assigning trucks to deliver in areas such that the CO2 emissions are minimized. Our methodology clusters the delivery areas based on the performance of the vehicle fleet by using the k-means algorithm and Tukey’s method. The output is then used to define the optimal CO2 truck-area assignment. We illustrate the proposed approach for a parcel company that operates in Mexico City and demonstrate that it is a practical alternative to reduce transportation CO2 emissions by matching vehicle type with delivery areas.

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Copy reference link   DOI: 10.1016/j.ijpe.2014.09.015

Abstract: We study the inventory control problem of a retailer working under stochastic demand and stochastic limited supply. We assume that the unfilled part of the retailer¿s order is fully backordered at the supplier and replenished with certainty in the following period. As it may not always be optimal for the retailer to replenish the backordered supply, we also consider the setting in which the retailer has a right to either partially or fully cancel these backorders, if desired. We show the optimality of the base-stock policy and characterize the threshold inventory position above which it is optimal to fully cancel the replenishment of the backordered supply. We carry out a numerical analysis to quantify the benefits of supply backordering and the value of the cancelation option, and reveal several managerial insights.

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Copy reference link   DOI: 10.1016/j.ejor.2014.10.052

Abstract: Reverse factoring –a financial arrangement where a corporation facilitates early payment of its trade credit obligations to suppliers– is increasingly popular in industry. Many firms use the scheme to induce their suppliers to grant them more lenient payment terms. By means of a periodic review base stock model that includes alternative sources of financing, we explore the following question: what extensions of payment terms allow the supplier to benefit from reverse factoring? We obtain solutions by means of simulation optimization. We find that an extension of payment terms induces a non-linear financing cost for the supplier, beyond the opportunity cost of carrying additional receivables. Furthermore, we find that the size of the payment term extension that a supplier can accommodate depends on demand uncertainty and the cost structure of the supplier. Overall, our results show that the financial implications of an extension of payment terms needs careful assessment in stochastic settings.

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Copy reference link   DOI: 10.1016/j.ijpe.2014.11.017

Abstract: Intermodal transportation is often presented as an efficient solution for reducing carbon emissions without compromising economic growth. In this article, we present a new intermodal network design model in which both the terminal location and the allocation between direct truck transportation and intermodal transportation are optimized. This model allows for studying the dynamics of intermodal transportation solutions in the context of hinterland networks from a cost, carbon emissions and modal shift perspective. We show that maximizing the modal shift is harmful for both cost and carbon emissions and that there is a carbon optimal level of modal shift. We also show that even if transportation cost and carbon emissions share the same structure, these two objectives lead to different solutions and that the terminal is located closer to the port when optimizing cost and further away when optimizing carbon emissions. The model also allows for studying the tradeoff between distance and volume, the impact of using aggregated models for estimating train transportation cost and carbon emissions as well as the potential policy measures that enable aligning cost and carbon emissions.

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Copy reference link   DOI: 10.1016/j.jtrangeo.2015.05.007

Abstract: We analyse the opinions of shippers, logistic service providers (LSPs) and carriers related to regulations and issues faced by these companies regarding freight distribution in megacities, and the logistical performance measures likely affected by those regulations and issues. We present a review of the freight distribution literature focusing on a large number of freight distribution aspects, such as regulatory, collaborative, environmental, logistical and risk. We also investigate some logistical performance indicators adopted by the companies. Subsequently, we conduct a survey with 147 companies working in the São Paulo Metropolitan Region (SPMR). We use multivariate analysis of variance to assess the logistical performance indicators and non-linear canonical correlation analysis to identify the most relevant freight distribution attributes. The results that the majority of carriers are located inside the SPMR and efficiently handle these issues better than others actors. The lack of collaboration, cargo theft, traffic congestion and some regulations affect the LSP’s logistical performance. Moreover, the actors perceive regulatory aspects, mainly traffic congestion, and a lack of security for deliveries in unsafe areas as the significant issues for deliveries in megacities.

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Copy reference link   DOI: 10.1016/j.dss.2015.08.001

Abstract: In this paper, we present a DSS that generates schedules for the transportation of containers by barge in the hinterland, in particular from sea terminals to an inland terminal. As a case study, we propose the transportation from the Ports of Rotterdam and Antwerp to a terminal in the south of the Netherlands, where the problem is typical. This problem is modeled as a heterogeneous fleet vehicle routing problem. The main decision is based on the trade-off of either consolidating containers to generate economies of scale with barges or alternatively dispatch, expensively and quickly, single containers by truck. The DSS is flexible as it can be applied to different settings by properly tuning the several parameters in the model. With numerical experiments, based on real world data, we evaluate the effectiveness of this system and its applicability.

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Copy reference link   DOI: 10.1016/j.tranpol.2015.06.007

Abstract: This article is to shed light on the interactions among the various freight distribution constructs such as regulations, collaboration, detour, load/unload interfaces and logistical performance. The proposed model is empirically tested using Partial Least Squares with 119 freight operators. The findings reveal the moderating effect of regulations (negative effect) on the positive relationship between collaboration and load/unload interfaces regarding receivers and freight operators. According to the effects shown by our model, regulation, along with lack of collaboration, appear to be the Achilles’ heel of freight distributors, in that both factors contribute (directly and indirectly) to detour, which results in less efficient logistical performance.

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Copy reference link   DOI: 10.1016/j.ijpe.2014.09.008

Abstract: In this paper we analyze the strong sales dip observed in the manufacturing industry at the end of 2008, following the bankruptcy of Lehman Brothers and the subsequent collapse of the financial world. We suggest that firms¿ desire to retain liquidity during these times prompted a reaction characterized by the reduction of working capital, which materialized as a synchronized reduction in target inventory levels across industries. We hypothesize that such a reaction effectively acted as an endogenous shock to supply chains, ultimately resulting in the bullwhip-effect kind of demand dynamics observed. To test this proposition we develop a system dynamics model that explicitly takes into account structural, operational, and behavioral parameters of supply chains aggregated at an echelon level. We calibrate the model for use in 4 different business units of a major chemical company in the Netherlands, all situated 4–5 levels upstream from consumer demands in their respective supply chains. We show that the model gives a very good historical fit of the sales developments during the period following the Lehman collapse. We test the model¿s robustness to behavioral parameter estimation errors through sensitivity analysis, and the de-stocking hypothesis against an alternative model. Finally, we observe that the empirical data is aligned with experimental observations regarding human behavioral mechanisms concerning target adjustment times.

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Copy reference link   DOI: 10.1287/trsc.2013.0481

Abstract: The transport sector is the second largest carbon emissions contributor in Europe and its emissions continue to increase. Many producers are committing themselves to reducing transport emissions voluntarily, possibly in anticipation of increasing transport prices. In this paper we study a producer that has outsourced transport and has decided to cap its carbon emissions from outbound logistics for a group of customers. Setting an emission constraint for a group of customers allows for taking advantage of the portfolio effect. We focus on reducing emissions by switching transport modes within an existing network, since this has a large impact on emissions. In addition, the company sets the sales prices, which influence demand. The problem is solved by decomposing the multi-product problem into several single-product problems, which we then analyze separately. Using the single-product solutions we create an efficient frontier which reflects the trade-off between total carbon emissions and the total prot. It is observed that a diminishing rate of return applies in reducing emissions by switching transport modes. In a case study we apply our method to a producer of bulk liquids and find that emissions can be reduced by 10% at only a 0.7% increase in total logistics cost.

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Copy reference link   DOI: 10.1007/s10696-012-9170-3

Abstract: A variety of activity-based methods exist for estimating the carbon footprint in transportation. For instance, the greenhouse gas protocol suggests a more aggregate estimation method than the Network for Transport and Environment (NTM) method. In this study, we implement a detailed estimation method based on NTM and different aggregate approaches for transportation carbon emissions in the dynamic lot sizing model. Analytical results show the limitations of aggregate models for both accurate estimation of real emissions and risks of compliance with carbon constraints (e.g., carbon caps). Extensive numerical experimentation shows that the magnitude of errors can be substantial. We provide insights under which limited conditions aggregate estimations can be used safely and when more detailed estimates are appropriate.

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Copy reference link   DOI: 10.1007/s10696-013-9189-0

Abstract: In almost all industries companies are confronted with the sustainability challenge induced by climate change, end of fossil fuel and scarcity of natural resources, just to name a few. In general, sustainability management—the so-called triple bottom line—seeks to balance the economic, social and environmental performance (e.g. CO2, waste, or resource consumption). Traditionally, the development of supply chains is driven by measures like costs and customer service. More recently, in view of the sustainability challenge environmental issues are increasingly taken into consideration, for instance, by adding environmental constraints to supply chain models or by considering carbon taxes and emission trading schemes or by including the effect of green house gas emissions in the choice of the transportation mode. This naturally leads to multi-objective considerations in order to analyze the trade-off between economic and environmental performance measures. The primary objective of this special issue is to reflect the recent developments in sustainability management in supply chains and related transport systems and to examine research issues concerned with quantitative and other modeling techniques to improve the environmental performance of supply chains in industry. For this special issue twelve papers have been selected for publication after a thorough peerreview according to the standards of the FSM journal.

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Copy reference link   DOI: 10.1080/13675567.2013.870141

Abstract: Although anecdotal evidence suggests that co-location of logistics establishments can bring about several benefits for the co-located logistics firms. These benefits have not been widely researched. This article seeks to contribute to an understanding of the spatial concentration of logistics establishments by empirically analysing the synergies they achieve through co-location. A survey of managers of 507 logistics establishments in the south of the Netherlands tested for differences in behaviour and circumstances between co-located and non-co-located establishments. The results show that synergies arise through co-location of logistics establishments: co-located logistics establishments more often combine transport capacity, have better availability of truck drivers, are better accessible, have better availability of repair and maintenance facilities, and have better expansion opportunities than do non-co-located logistics establishments. This means that regional aspects can be important variables in the location decisions of logistics firms.

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Copy reference link   DOI: 10.1080/09654313.2012.741573

Abstract: This article presents a method to identify "Absolute and Relative Employment Concentration (AREC) areas" for a particular industry. Two novel characteristics of the method are that it simultaneously analyses AREC, and that it combines spatial concentration per area with the spatial concentration in neighbouring areas. The method is easy to understand and apply. It is developed to assist regional policy makers and corporate decision-makers with their investment decisions related to new infrastructure or plants. The identification of concentration areas also allows for analysing the performance of these areas in relation to characteristics such as infrastructure availability and the housing and labour market. This can yield new academic insights that are relevant for regional planners. An application of the newly developed method to five industries in a Dutch province subdivided into 502 areas illustrates the value of the method in comparison to other methods.

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Copy reference link   DOI: 10.1007/s10696-012-9151-6

Abstract: More and more companies are paying attention to their carbon footprint beyond production emissions. In this work we consider a ‘carbon-aware’ company (either by choice or enforced by regulation) that is reconsidering the transport mode selection decision. Traditionally the trade-off has been between lead time (and corresponding inventory costs) and transportation costs but now emission costs come into the equation. We use a carbon emission measurement methodology based on real-life data and incorporate it into an inventory model. We consider the results for different types of emission regulation (including voluntary targets). We find that even though large emission reductions can be obtained by switching to a different mode, the actual decision depends on the regulation and non-monetary considerations, such as lead time variability.

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

Abstract: This paper analyzes the relationship between freight accessibility and logistics employment in the US. It develops an accessibility measure relevant for logistics companies based on a gravity model. This allows for an analysis of the accessibility of US counties focusing on four different modes of transportation: road, rail, air, and maritime. Using a Partial Least Squares model, these four different freight accessibility measures are combined into two constructs, continental and intercontinental freight accessibility, and related to logistics employment. Results show that highly accessible counties attract more logistics employment than other counties. The analyses show that it is very important to control for the effect of the county population on both freight accessibility and logistics employment. While county population explains the most variation in the logistics employment per county, there is a significant relationship between freight accessibility and logistics employment, when controlling for this effect. Keywords: Accessibility, Freight transport, Logistics employment

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Copy reference link   DOI: 10.1016/j.cor.2012.08.016

Abstract: In recent years, supply chains have become increasingly globalized. As a consequence, the world’s supply of all types of parts has become more susceptible to disruptions. Some of these disruptions are extreme and may have global implications. Our research is based on the supply risk management problem faced by a manufacturer. We model the problem as a dynamic program, design and implement approximate dynamic programming (ADP) algorithms to solve it, to overcome the well-known curses of dimensionality. Using numerical experiments, we compare the performance of different ADP algorithms. We then design a series of numerical experiments to study the performance of different sourcing strategies (single, dual, multiple, and contingent sourcing) under various settings, and to discover insights for supply risk management practice. The results show that, under a wide variety of settings, the addition of a third or more suppliers brings much less marginal benefits. Thus, managers can limit their options to a backup supplier (contingent sourcing) or an additional regular supplier (dual sourcing). Our results also show that, unless the backup supplier can supply with zero lead time, using dual sourcing appears to be preferable. Lastly, we demonstrate the capability of the proposed method in analyzing more complicated realistic supply chains.

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Abstract: While relationship learning has been addressed in marketing theory, it has not yet been explored as a possible dimension of the second-order construct of relationship quality (RQ). This construct has so far been mostly conceptualized to consist of trust and commitment, sometimes also satisfaction; however, some see the latter more as a consequence of the former two. Additionally, while RQ and its multidimensionality have been researched in the marketing literature, this area has remained virtually unexplored in the supply and operations management literature. The purpose of this paper is to analyze the multidimensional nature of the second-order construct of RQ in a particular setting of transnational corporation (TNC) buyer-supplier relationships. Our paper aims to determine if relationship learning can be considered an important dimension of RQ, alongside trust and commitment. In our study of relationship learning, we follow Jean, Sinkovics and Kim (2010) and Jean and Sinkovics (2010), who have focused on the governance aspect of relationship learning in managing supply performance outcomes. We employ an indirect testing approach by testing RQ as a second-order reflective construct comprised of trust, commitment and relationship within a simple variance-based Structural Equation Modeling (SEM). Our results confi rm that relationship learning is an important dimension of the second-order construct of RQ. This was done on a tentative sample of 11 TNC purchasing managers and 55 evaluated suppliers, albeit with some research limitations which we acknowledge. Our research calls for additional cross-validation of our tentative results.

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Copy reference link   DOI: 10.1016/j.tranpol.2013.09.022

Abstract: Although spatial concentration of logistics firms in logistics concentration areas can be beneficial for society at large, there is not much research on the relationship between land allocation policies and logistics concentration areas. This paper analyzes land allocation policies by means of a survey conducted in the south of the Netherlands. Results show that municipalities do not actively stimulate spatial concentration of logistics firms, although both aldermen and public administration employees acknowledge that co-location of logistics firms can lead to benefits. There is a need for cooperation between municipalities, such that a regional policy can be developed, to attain the regional benefits of logistics concentration areas, while local disadvantages (like congestion and CO2 emissions) can be reduced. Respondents acknowledge the positive effects of cooperation with respect to logistics land allocation, but recognize some impediments. Municipalities that already cooperate with others are positive about the results. Hence, municipalities are advised to build partnerships, such that land allocation policies can be better aligned with the stimulation of logistics concentration areas.

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Copy reference link   DOI: 10.1007/s00291-011-0267-y

Abstract: Linear programming (LP) models for Supply Chain Operations Planning are widely used in Advanced Planning Systems. The solution to the LP model is a proposal for order releases to the various production units (PU) in the supply network. There is a non-linear relationship between the work-in-process in the PU and the lead time that is difficult to capture in the LP model formulation. We propose a two-step lead time anticipation (LTA) procedure where the LP model is first solved irrespective of the available production capacity and is subsequently updated with aggregate order release targets. The order release targets are generated by a local smoothing algorithm that accounts for the evolution of the stochastic workload in the PU. A solution that is both feasible with respect to the planned lead time and meets the material requirements may not exist. By means of discrete event simulation, we compare a conservative strategy where the production quantities are reduced to an optimistic strategy where the planned lead time constraint is allowed to be violated.

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Copy reference link   DOI: 10.1016/j.jtrangeo.2012.10.001

Abstract: This paper analyzes location dynamics of logistics establishments in relation to spatial clustering. Such an analysis is relevant for both decision makers within logistics firms and regional policy makers, as co-located logistics establishments as well as society as a whole can benefit from co-location of logistics establishments. For this analysis, longitudinal empirical data on logistics establishments in a Dutch province are used. Six general conclusions are drawn on spatial concentration and location decisions of logistic firms. First, logistics employment spatially concentrates in particular areas, called Absolute and Relative Concentration areas (AREC areas). Second, larger logistics establishments locate relatively often in AREC areas. Third, logistics establishments that relocate within the province locate relatively more in AREC areas than in other areas, while new logistics establishments do not. Fourth, logistics establishments from AREC areas are more likely to relocate in AREC areas than establishments from non-AREC areas. Hence, experience matters in location decisions of logistics firms. Fifth, transport establishments locate relatively often in emerging AREC areas. Finally, data on employment growth show that intermodal container terminals attract logistics employment, in their direct vicinity as well as on a municipal level.

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Copy reference link   DOI: 10.1111/j.1937-5956.2011.01310.x

Abstract: With supply chains distributed across global markets, ocean container transport now is a critical element of any such supply chain. We identify key characteristics of ocean container transport from a supply chain perspective. We find that unlike continental (road) transport, service offerings tend to be consolidated in few service providers, and a strong focus exists on maximization of capital intensive resources. Based on the characteristics of ocean container transport as part of global supply chains, we list a number of relevant and challenging research areas and associated questions.

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Copy reference link   DOI: 10.1080/0144929X.2010.535969

Abstract: Decision support systems (DSS) play an important role in supporting scheduling tasks in industrial settings. In this paper, a special aspect of DSS for scheduling, namely their development, implementation and usage in relation to user participation, is examined. The outlined research model proposes that different forms of user participation lead to different levels of model complexity. This complexity influences in turn such outcome variables like system performance and user satisfaction. The research model integrates several existing concepts from technology acceptance, planned behaviour, involvement, and participation research as well as control theory. These theories are expanded by the dynamics of the modelling process. For the empirical analysis, multiple case studies examining different cases of DSS development and implementation processes in different settings were conducted.

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Copy reference link   DOI: 10.1007/s10696-011-9104-5

Abstract: Due to rapid increases in the automotive markets in emerging economies, leading car manufacturers rapidly expand their manufacturing capacity in countries such as China. A certain portion of key performance components however continue to be sourced from developed countries. We study such a manufacturer that imports high-value components from a developed country. There are two available transportation modes: a slow mode with low cost and long and stochastic lead time, and a fast mode with high cost and short and deterministic lead time. Moreover, the manufacturer is subject to a credit constraint that bounds both the inwarehouse inventory and the number of outstanding orders (because it needs to pay for the components in advance). Consequently, the cheapest hedge against demand and supply uncertainty—inventory—is only available to a limited extent and the decision maker must turn to using the fast transportation mode for a much larger share of the orders. We model the manufacturer’s ordering policy and study its performance using simulation. Our study shows the adverse effects that the credit limit has on the growth opportunities of such companies in developing countries that import high-value components or other goods from developed countries. We show that especially the reduction in lead time variability can substantially reduce these adverse effects. Realizing that this variability is primarily caused by the import customs procedures, governments in developing economies have a means to assist their local manufacturers.

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Abstract: The paradigmatic shiftin marketing from the beginning of the 1990’s has transformed the study of economic exchange, towards addressing more the relational aspects of these exchanges, where relationship specificity has replaced transaction specificity. This is particularly true in transnational supply exchanges, where specialization and outsourcing have increased the importance of effective and efficient management of buyer-supplier relationships, and their corresponding networks in which they are embedded in. The purpose of this paper is to analyze the impact of selected dimensions of buyer-supplier relationships within a specific TNC business-to-business (B2B) setting on supply relationship performance from the suppliers’ perspective. The paper analyzes the impact of the functional aspect of the business network context on selected elements of buyer-supplier relationships, particular in terms of the impact on business performance. This is analyzed within a confirmatory testing of a reflective structural equation model. A unique feature of the model is its focus on the business network, which is operationalized through 2 dimensions, which are related to (a) network-based information and (b) network spillover effects, as key determinants of the "traditional" elements of buyer-supplier relationships (i.e. transaction-specific investments, trust, flexibility, and joint actions). The dataset includes a sample of 157 suppliers of the focal TNC world-wide (47.9 response rate on a web-based survey). In the end, the paper provides a series of managerial implications to be considered, focusing on the so called network management perspective and the role of a wider business network context.

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Abstract: End markets such as Construction in 2009 went down 15 percent compared to 2007. This article will provide an explanation why the sales volume of upstream suppliers to Construction markets first went down 30-50 percent, and then recovered to around original levels, and then went down again. Royal DSM together with a group of scientists from Eindhoven University of Technology have investigated this effect based on the hypothesis that de-stocking in the long value chains of the chemical industry is the cause of a significant part of the decline, and that de-stocking has been triggered by the collapse of Lehman Brothers mid September 2008. It is further based on the hypothesis that the supply chains act elastically to a strong impulse, thus creating wave-like effects.

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Copy reference link   DOI: 10.1002/nav.20450

Abstract: An important aspect of supply chain management is dealing with demand and supply uncertainty. The uncertainty of future supply can be reduced if a company is able to obtain advance capacity information (ACI) about future supply/production capacity availability from its supplier. We address a periodic-review inventory system under stochastic demand and stochastic limited supply, for which ACI is available. We show that the optimal ordering policy is a state-dependent base-stock policy characterized by a base-stock level that is a function of ACI. We establish a link with inventory models that use advance demand information (ADI) by developing a capacitated inventory system with ADI, and we show that equivalence can only be set under a very specific and restrictive assumption, implying that ADI insights will not necessarily hold in the ACI environment. Our numerical results reveal several managerial insights. In particular, we show that ACI is most beneficial when there is sufficient flexibility to react to anticipated demand and supply capacity mismatches. Further, most of the benefits can be achieved with only limited future visibility. We also show that the system parameters affecting the value of ACI interact in a complex way and therefore need to be considered in an integrated manner.

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Copy reference link   DOI: 10.1080/09537280903454172

Abstract: Abstract The aim of this article is to contribute empirically to the theory development on planning instabilities in industrial practice by studying in depth an industrial company which has difficulty in meeting its customer deadlines and faces a significant order backlog. Planners at the various levels of the hierarchical planning system and order chasers on the shop floor end up rescheduling open orders and updating (de facto) lead times very frequently when trying to meet deadlines, but eventually are not able to improve order fulfilment. Only after the introduction of an advanced planning system (APS) and centralisation of planning decisions in one single department, planning results could be improved significantly, accomplishing 97% of customer due dates and reducing order backlog drastically. These kinds of planning instabilities have received considerable attention due to their negative impact on planning performance; however, research has been limited to theoretical (e.g. simulation) settings and has focused on specific ways to overcome instabilities. Our main contribution is an empirical investigation of the underlying mechanism of such planning instabilities, with a particular focus on the impact on stability of human and organisational factors. Our findings clearly suggest that structure and frequency significantly influence stability, but that the underlying mechanisms are more subtle and differentiated than assumed in the modelling literature. A further contribution of the article to theory development is the introduction of the general term ’planning bullwhip’ for such kind of planning instabilities, by integrating in an aggregate manner the different terminologies that have been coined in extant research.

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Copy reference link   DOI: 10.1016/j.ijpe.2010.09.010

Abstract: We consider a contract manufacturer that serves a limited number of outsourcers (customers) on a single capacitated production line. The outsourcers have different levels of demand uncertainty and the contract manufacturer faces the question how to allocate the contractual capacity flexibility in an optimal way. The contractual capacity flexibility is a contract parameter that sets the amount of demand the contract manufacturer is obliged to accept from the outsourcers. We develop a hierarchical model that consists of two decision levels. At the tactical level, the contract manufacturer allocates the capacity flexibility to the different outsourcers by maximizing the expected profit. Offering more flexibility to the more uncertain outsourcer generates higher expected revenue, but also increases the expected penalty costs. The allocated capacity flexibilities (determined at the tactical level) are input parameters to the lower decision level, where the operational planning decisions are made and actual demands are observed. We perform a numerical study by solving the two-level hierarchical planning problem iteratively. We first solve the higher level problem, which has been formulated as an integer program, and then perform a simulation study, where we solve a mathematical programming model in a rolling horizon setting to measure the operational performance of the system. The simulation results reveal that when the acceptance decision is made (given the allocated capacity flexibility decision), priority is given to the less uncertain outsourcer, whereas when the orders are placed, priority is given to the most uncertain outsourcer. Our insights are helpful for contract manufacturers when having contract negotiations with the outsourcers. Moreover, we show that hierarchical integration and anticipation are required, especially for cases with high penalty cost and tight capacities.

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Copy reference link   DOI: 10.1287/ited.1100.0059

Abstract: This paper describes the organization and teaching of retail operations at The Wharton School at the University of Pennsylvania and the School of Industrial Engineering at Eindhoven University of Technology. We present the course outlines and discuss how differences in the schools’ environments affect the way retail operations is taught at each school.

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Copy reference link   DOI: 10.1287/mnsc.1090.1141

Abstract: Retail store managers may not follow order advices generated by an automated inventory replenishment system if their incentives differ from the cost minimization objective of the system or if they perceive the system to be suboptimal. We study the ordering behavior of retail store managers in a supermarket chain to characterize such deviations in ordering behavior, investigate their potential drivers, and thereby devise a method to improve automated replenishment systems. Using orders, shipments, and point-of-sale data for 19,417 item–store combinations over five stores, we show that (i) store managers consistently modify automated order advices by advancing orders from peak to nonpeak days, and (ii) this behavior is explained significantly by product characteristics such as case pack size relative to average demand per item, net shelf space, product variety, demand uncertainty, and seasonality error. Our regression results suggest that store managers improve upon the automated replenishment system by incorporating two ignored factors: in-store handling costs and sales improvement potential through better in-stock. Based on these results, we construct a method to modify automated order advices by learning from the behavior of store managers. Motivated by the management coefficients theory, our method is efficient to implement and outperforms store managers by achieving a more balanced handling workload with similar average days of inventory.

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Copy reference link   DOI: 10.1108/01443571011082526

Abstract: Purpose – The purpose of this paper is to understand the implications of outsourcing at the operational planning level, i.e. how the operational planning function is complicated owing to the strategic outsourcing decisions that have been made in the past. Design/methodology/approach – First, a literature review on outsourcing is conducted. Second, two case studies at three pharmaceutical companies are conducted to gather insights into the planning of outsourced operations. Findings – The paper finds that nothing has been documented in the literature on outsourcing at the operational planning level. Moreover, a number of implications of outsourcing at the operational planning level are discussed. One of the main insights is that in an outsourcing relationship, the order process consists of different, hierarchically connected, decisions in time, hence requiring a richer and more developed communication and ordering pattern than is commonly assumed. Research limitations/implications – The results seem to be generalizable to the pharmaceutical industry. However, future research should determine whether these results replicate in other industries. Originality/value – The literature on outsourcing has mainly focused on the strategic outsourcing decision. The paper contributes to a better understanding of the implications of outsourcing at the operational planning function, which has not been studied before.

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Copy reference link   DOI: 10.1007/s00291-007-0086-3

Abstract: This paper considers the problem of determining safety stocks in multi-item multi-stage inventory systems that face demand uncertainties. Safety stocks are necessary to make the supply chain, which is driven by forecasts of customer orders, responsive to (demand) uncertainties and to achieve predefined target service levels. Although there exists a large body of literature on determining safety stock levels, this literature does not provide an effective methodology that can address complex multi-constrained supply chains. In this paper, the problem of determining safety stocks is addressed by a simulation based approach, where the simulation studies are based on solving the supply chain planning problem (formulated as a mathematical programming model) in a rolling horizon setting. To demonstrate the utility of the proposed approach, an application of the approach at Organon, a worldwide operating biopharmaceutical company, will be discussed.

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Copy reference link   DOI: 10.1108/01443570910971397

Abstract: Purpose – The purpose of this paper is to investigate the antecedents of close supply chain collaboration and to develop a multi-variable conceptual model of factors that drive the need for close supply chain collaboration. Design/methodology/approach – A multi-variable conceptual model is developed based on literature and on a series of dyadic mini-cases in the electronics, fashion and consumer-packaged goods industry. Findings – This paper confirms that close supply chain collaboration is influenced by a multitude of factors. It reveals a need to integrate findings from analytical and empirical disciplines that study supply chain collaboration. The results suggest that collaborative initiatives are predominantly initiated with suppliers and not with customers, and that close supply chain collaboration may lead to inertia in business relations. Research limitations/implications – This paper is based on dyadic case studies in three different make-to-stock industries; future research may include a large-scale survey in more industries, including both make-to-order and make-to-stock environments. Practical implications – Based on the findings, firms can make better choices in their collaborative initiatives; based on the conceptual model, firms can identify potential areas of close supply chain collaboration. Originality/value – Findings from analytical and empirical literature are combined and such a combined perspective is deployed for the first time into a conceptual model of drivers of close supply chain collaboration.

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Copy reference link   DOI: 10.1016/j.ijpe.2006.06.010

Abstract: In retail stores, handling of products typically forms the largest share of the operational costs. The handling activities are mainly driven by the shelf stacking process. While the impact of the handling costs on the profitability of a store is substantial, there are no models available of the different drivers influencing store handling. In this paper, a study of the shelf stacking process is presented. First, a conceptual model based on warehouse operations is derived. It is shown that stacking costs are non-linear with the number of consumer units stacked. Secondly, by means of a motion and time study, data has been collected for dry groceries in four stores of two different European retail companies. Using regression, the developed model clearly demonstrates the impact of the most important drivers for stacking efficiency: case pack (CP) size, number of CPs stacked simultaneously, the filling regime and the working place of the employees. Efficiency gains of 8–49% by changing the driver parameter value are identified. Based on the presented insights both retail companies have already decided to structurally change their current operations.

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Copy reference link   DOI: 10.1057/palgrave.jors.2602553

Abstract: Shelf stacking represents the daily process of manually refilling the shelves with products from new deliveries. For most retailers, handling operations are labour-intensive and often very costly. This paper presents an empirical study of the shelf-stacking process in grocery retail stores. We examine the complete process at the level of individual sub-activities and study the main factors that affect the execution time of this common operation. Based on the insights from different sub-activities, a prediction model is developed that allows estimating the total stacking time per order line, solely on the basis of the number of case packs and consumer units. The model is tested and validated using real-life data from two European grocery retailers and serves as a useful tool for evaluating the workload required for the usual shelf-stacking operations. Furthermore, we illustrate the benefits of the model by analytically quantifying the potential time savings in the stacking process, and present a lot-sizing analysis to demonstrate the opportunities for extending inventory control rules with a handling component.

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Copy reference link   DOI: 10.1016/j.ijpe.2009.02.001

Abstract: We consider an original equipment manufacturer (OEM) that outsources some of its production activities to a contract manufacturer that serves several customers on the same capacitated production line. The contract manufacturer is not willing to share all relevant information with the OEM, and therefore, a complex situation arises for the OEM to control the outsourced operations properly. In this paper, we discuss and compare the performance of three different order release strategies, which differ in the number of decision levels, such that the probabilistic behaviour of the contract manufacturer is (partly) incorporated and production plans are generated based on (deterministic) mathematical programming models. Simulation results show that an order release strategy with multiple decision levels performs significantly better than an order release strategy with only one decision level. We also discuss the conditions for a successful implementation of the more advanced order release strategy. Further, some ideas for future research are presented.

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Copy reference link   DOI: 10.1016/j.eswa.2009.04.052

Abstract: Promotions and shorter life cycles make grocery sales forecasting more difficult, requiring more complicated models. We identify methods of increasing complexity and data preparation cost yielding increasing improvements in forecasting accuracy, by varying the forecasting technique, the input features and model scope on an extensive SKU-store level sales and promotion time series from a European grocery retailer. At the high end of data and technique complexity, we propose using regression trees with explicit features constructed from sales and promotion time series of the focal and related SKU-store combinations. We observe that data pooling almost always improves model performance. The results indicate that simple time series techniques perform very well for periods without promotions. However, for periods with promotions, regression trees with explicit features improve accuracy substantially. More sophisticated input is only beneficial when advanced techniques are used. We believe that our approach and findings shed light into certain questions that arise while building a grocery sales forecasting system.

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Copy reference link   DOI: 10.1080/00207540701420552

Abstract: Updating planned lead times in response to changing workload levels leads to erratic ordering behaviour, resulting in even larger variability in the workload levels and flow times. This phenomenon is called lead time syndrome, and describes the cyclic interaction between adaptive planned lead times and order sizes. Although it has been conceptually defined and intuitively accepted, formal analysis with analytical evaluation of the phenomenon has not been conducted. The objective of this paper is to provide a stronger understanding of the lead time syndrome, and to give new insights into the effects of frequently updating planned lead times. We develop a two-dimensional Markov process to model a single-item production process with orders released sensitive to the planned lead time. Using matrix-geometric methods, analytical results on the utilization level and the variability in the system are presented in relation to the frequency of updating the planned lead time. Although the average utilization level is always retained, the lead time syndrome causes an increase in the average workload level and the actual flow times of the completed orders. The variability of the planned lead time increases with the update frequency except at the utilization boundaries, where the relative effect of the update frequency diminishes.

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Copy reference link   DOI: 10.1287/msom.1070.0164

Abstract: This study considers a supply chain that consists of n retailers, each facing a newsvendor problem, and m warehouses. The retailers are supplied with a single product via some warehouses. In these warehouses, the ordered amounts of goods of these retailers become available after some lead time. At the time that the goods arrive at the warehouses, demand realizations are known by the retailers. The retailers can increase their expected joint profits if they can coordinate their orders and make allocations after demand realization. For this setting, we consider an associated cooperative game between the retailers. We show that this associated cooperative game has a nonempty core. Finally, we introduce a noncooperative game, where the retailers decide on their order quantities individually, and show that the set of payoff vectors resulting from strong Nash equilibria corresponds to the core of the associated cooperative game.

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Copy reference link   DOI: 10.1080/09537280802568163

Abstract: Production planning decisions are usually made by human planners that are assisted by decision support systems. While it is widely argued in the literature that current decision support systems for production planning are generally inadequate, it is not clear to what extent human planners actually disregard the planning decisions proposed by the system. In this study, we investigate this question. In a setting in which the planning system’s model has an adequate representation of reality, we collect data on actual planning decisions and compare them to the planning decisions proposed by the system. We conclude that planners systematically and largely neglect the system’s recommendations and that the extent of neglect is larger if the planning problem is more complex.

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Copy reference link   DOI: 10.1080/07408170701487997

Abstract: In this study we provide insights into the effectiveness of the clearing function concept in a hierarchical planning context. The clearing function is a mathematical representation of the relation between the Work-In-Process (WIP) and the throughput of a production process. We use it in a deterministic order release planning model to anticipate the dynamics of the operational level, which is subject to uncertainties. A multi-period single-item order release and scheduling problem is considered in which the delivery schedule of the orders is determined through the planned lead times, and the capacity loading decisions are separated from the order release decisions in a way so as to plan for on-time deliveries. Early or late delivery of the orders, which are released and delivered in batches, has not been considered explicitly in previous studies on clearing functions, and it significantly affects the inventory costs. Both linear and non-linear clearing functions are tested using a simulation approach. The results indicate that modeling the clearing of WIP by a shop should be based on the short-term operational dynamics of the shop rather than on the long-term average shop behavior, since it improves the consistency between the operational planning and scheduling levels of the hierarchy. The presented methods and results provide valuable information on modeling production characteristics in aggregate production planning and scheduling models.

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Copy reference link   DOI: 10.1108/09600030710840822

Abstract: This paper aims to identify customer behavior with regard to out-of-stocks (OOS) of perishable products (focused on bakery bread) and the resulting inventory performance for these perishable products. Design/methodology/approach – Insights on how consumers behave when their preferred bread product is OOS are derived based on 3,800 customer interviews performed in three stores of a large Dutch grocery retail chain. Next to this, additional logistical information was measured on regular moments with respect to the shelf availability per stock-keeping unit during the day and to waste at the end of the day. Findings – The customer behavior with regard to perishables is observed to be different from that for the non-perishable items. The key observation is that customers have a high willingness to substitute. The incorporation of the obtained knowledge of the observed consumer buying behavior into the existing automated store ordering (ASO) systems is discussed. In the current ASO systems, no distinction is made between perishable and non-perishable products, as it is primarily designed and used for the non-perishables. The authors show that the current ASO can be enriched and extended by taking into account some extra crucial parameters which are based on the observed consumer behavior. Originality/value – One common factor in the research papers published so far is that they primarily looked into the customer behavior for non-perishable items. The current paper on-hand extends these works towards perishable items with a focus on bakery bread.

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Copy reference link   DOI: 10.1016/j.ijpe.2005.04.005

Abstract: In this study, our concern is to show the effect of updating lead times on the performance of a two-level hierarchical planning system. Lead times are updated by taking periodic feedbacks of the most recent information from the production environment and using this information in estimating lead times for planning the future production orders. A simulation model is used based on a multistage production planning and scheduling environment where the components are manufactured in a general job shop and final products are manufactured in a flow shop. Our results demonstrate that under certain conditions frequent updates of lead times will lead to uncontrolled production system with erratic and very long lead times. Keywords: Hierarchical planning; Scheduling; Lead time; Production planning

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Copy reference link   DOI: 10.1016/j.jom.2005.09.008

Abstract: The complexity of planning tasks have increased over the past decade. There is relatively poor understanding what the implications are of increased task complexity in planning and scheduling operations. Previous work in the behavioral sciences have investigated the concept of cognitive load, addressing both task complexity and task workload or stress, and have concluded that decision makers tend to resort to routine action and reduce the variety in their actions with increasing complexity and workload. Alternatively, control theory suggests that a higher variety of actions is needed to deal with more complex problems. In this paper, we investigate the effects of task complexity in a chemical plant on the variety of actions deployed by the planners. The single work center resource structure and the availability of actual planning data from an MRP-application database allows us to both use field data and study a situation which is simple enough to measure the main effect. Our results suggest that increased task complexity without time pressure does indeed lead to increased action variety deployed by the planners. Keywords: Cognitive load; Task complexity; Field study; Chemical industry; Requisite variety

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Copy reference link   DOI: 10.1057/palgrave.jors.2601966

Abstract: Batch process industries are characterized by complex precedence relationships among operations, which makes the estimation of an acceptable workload very difficult. Previous research indicated that a regression-based model that uses aggregate job set characteristics may be used to support order acceptance decisions. Applications of such models in real-life assume that sufficient historical data on job sets and the corresponding makespans are available. In practice, however, historical data maybe very limited and may not be sufficient to produce accurate regression estimates. This paper shows that such a lack of data significantly impacts the performance of regression-based order acceptance procedures. To resolve this problem, we devised a method that uses the bootstrap principle. A simulation study shows that performance improvements are obtained when using the parameters estimated from the bootstrapped data set, demonstrating that this bootstrapping procedure can indeed solve the limited data problem in production control.

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Copy reference link   DOI: 10.1016/j.ijpe.2004.10.019

Abstract: Abstract In the last decade large supermarket chains have started developing and implementing automated store ordering (ASO) systems in order to improve both the quality and efficiency of the inventory replenishment decisions in their stores. These ASO systems have been developed mainly for non-perishables. The aims of this paper are 1. to better understand the product, sales and supply characteristics of perishables in supermarkets, 2. to define and operationalise relevant concepts in controlling the inventories of perishables, 3. to investigate how the intelligence in ASO systems in supermarkets can be further improved, 4. to give academics empirically based insight in the relevance of the inventory models that are currently available in the literature, insight in relevant parameter settings and insight in which models are needed. The research is carried out in cooperation with two Dutch supermarket chains and focusses on perishable items. To further improve the intelligence in the ASO systems, we will classify the items in a supermarket, based on the notion that different items need different inventory control rules. For every class of items, we describe the main logistic characteristics; moreover, for the perishable items we describe the inventory control rules which are currently being applied and we discuss the desired inventory control strategy for these items. Keywords: Inventory management; Perishables; Empirical data; Classification; Retail; Model; Distribution

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Copy reference link   DOI: 10.1007/s00291-005-0015-2

Abstract: Abstract Customer order acceptance is an important process in make-to-order industries. Acceptance policies should operate such that a pre-specified delivery reliability is achieved, while maximizing resource utilization. By selecting orders with specific characteristics that maximize resource utilization, an important and often unforeseen effect occurs: the mix of orders changes such that the expected delivery reliability is no longer met. This paper investigates the selectivity of an aggregate and a detailed acceptance procedure, for batch process industries featuring complex job and resource structures. We found that the detailed policy maximizes resource utilization but underestimates the consequences on the realized makespan of significantly changing the job mix. The aggregate policy, while being selective, performs much better with respect to the delivery reliability, but achieves a lower capacity utilization. We propose a third procedure, the hybrid policy, which combines the strengths of both the detailed and aggregate acceptance procedures. Simulation experiments show that the hybrid policy successfully controls the delivery reliability, without loosing much of the beneficial effect of the selectivity on utilization.

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Copy reference link   DOI: 10.1016/j.jom.2005.01.001

Abstract: The operations management research in process industries, which cover a wide range of businesses are discussed. The first significant contribution that recognized the field of process industries within operations management was the documentation of the differences between discrete and process industries. The theoretical, analytical, and modeling work within operations management is also labeled as production planning and control (PPC) models. The relationship between reference models for production planning and control, empirical studies describing the field of process industries, and studies describing specific characteristics of process industries are also described.

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Copy reference link   DOI: 10.1016/j.tre.2005.07.003

Abstract: In this paper we present a dual supply model taking into account that in many industries the replenishment cycle does not only involve the physical distribution of goods, but also the manufacturing of products. Further, we suggest postponing the transportation mode decision until the products are available for shipping. We investigate a class of order-up-to policies and show how to compute the optimal policy parameters. Our model enables us to quantify the value of the postponement of the transportation decision and the value of using an additional slow mode instead of only using the existing fast mode. In a numerical study the influence of various model parameters is investigated and it is shown that the use of a slow mode can be economically beneficial, especially for low value items.

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Copy reference link   DOI: 10.1016/j.ejor.2004.03.014

Abstract: We study a situation with n retailers, each of them facing a news-vendor problem, i.e., selling to customers over a finite period of time (product with a short life cycle, such as fashion). Groups of retailers might improve their expected joint profit by coordinating their orders, followed by transshipments after demand realization is known. We analyze these situations by defining a cooperative game, called a general news-vendor game, for such a situation with n retailers. We concentrate on whether it makes sense to cooperate by studying properties of general news-vendor games. Our main result states that general news-vendor games have non-empty cores.

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Copy reference link   DOI: 10.1016/j.im.2003.06.005

Abstract: Whereas much of the modeling literature in supply chain planning addresses the analysis of decision models and presents solution techniques and much of the empirical literature on planning systems such as ERP and APS software addresses implementation challenges from an organizational perspective, research on the modeling process of capturing the planning process in planning software is very scarce. In this paper, we examine this modeling process. Our approach is based on a normative method for hierarchical planning and presents a case study where this modeling process was used. We analyze the process, relate it to the literature on modeling, and demonstrate the value of the theory in explaining major observations. We conclude that the hierarchical premise on which most planning processes are based is very difficult to capture in an advanced planning system, and find that users and organizations essentially circumvent this problem by creating their own workflows, independent of the system’s prescribed one.

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Copy reference link   DOI: 10.1080/09537280110061548

Abstract: For all kinds of reasons, rework, i.e. the transformation of products not fulfilling preset specifications into products that do, is an important issue in process industries. Despite a considerable amount of published research on planning and control of rework, and in addition many papers referring to the existence of rework in the process industries, hardly any attention has been paid to the consequences of many process industries specific characteristics for execution, planning and control of rework operations. Here are identified the characteristics of the process industries that influence the possibilities for rework in these industries, based on a framework provided by Flapper and Jensen ( International Journal of Production Research , 1999, to be published). How the available operations management literature assists in determining operational strategies for planning and control of rework in process industries is assessed. It is concluded that many relevant and interesting problems have not been addressed.

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Copy reference link   DOI: 10.1108/01443570210414338

Abstract: Gives an overview of quantitative model-based research in operations management, focusing on research methodology. Distinguishes between empirical and axiomatic research, and furthermore between descriptive and normative research. Presents guidelines for doing quantitative model-based research in operations management. In constructing arguments, builds on learnings from operations research and operations management research from the past decades and on research from a selected number of other academic disciplines. Concludes that the methodology of quantitative model-driven empirical research offers a great opportunity for operations management researchers to further advance theory.

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Copy reference link   DOI: 10.1007/s00291-002-0108-0

Abstract: Batch process industries are characterized by complex precedence relationships between operations, which renders the estimation of an acceptable workload very difficult. A detailed schedule based model can be used for this purpose, but for large problems this may require a prohibitive large amount of computation time. We propose a regression based model to estimate the makespan of a set of jobs. We extend earlier work based on deterministic processing times by considering Erlang-distributed processing times in our model. This regression-based model is used to support customer order acceptance. Three order acceptance policies are compared by means of simulation experiments: a scheduling policy, a workload policy and a regression policy. The results indicate that the performance of the regression policy can compete with the performance of the scheduling policy in situations with high variety in the job mix and high uncertainty in the processing times.

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Copy reference link   DOI: 10.1016/S0925-5273%2800%2900052-9

Abstract: To properly conduct aggregate control functions such as order acceptance and capacity loading, good estimates of the available production capacity need to be on hand. Capacity structures in batch process industries are generally so complex that it is not straightforward to estimate the capacity of a production department. In this paper, we assess the quality of estimation models that are based on regression. The paper builds on earlier results, which have demonstrated that a limited number of factors can explain a large share of the variance in makespan estimation based on regression models.

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Copy reference link   DOI: 10.1057/palgrave.jors.2601162

Abstract: Supply chain planning concepts from multi-echelon inventory theory are generally based on some form of centralised planning of supply chains. Those multi-echelon models that do consider decentralised planning, assume complete information and/or a specific single objective function. This paper investigates how multi-echelon inventory theory can accommodate a setting with decentralised decision makers (a supplier and a number of retail groups) without complete information. We present a coordination procedure that does not require the retail groups to exchange demand information, but does allow using opportunities for demand pooling between them. We illustrate our ideas by way of a quantitative analysis of a two-echelon divergent supply chain, with both cooperative and non cooperative retail groups. We conclude that coordination across a supply chain with decentralised control and limited centralised information is feasible by using available algorithms with satisfactory service level and cost performance.

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Abstract: In dit artikel wordt een methode beschreven voor het bepalen van de optimale seriegroottes, wanneer deze beslissing een langetermijnbeslissing is. Deze methode is ontwikkeld na een logistiek onderzoek in de Synthetische Fabriek van Solvay Pharmaceuticals, waar actieve stoffen van geneesmiddelen worden geproduceerd. Het overschakelen op een andere seriegrootte bleek hier een zeer ingrijpende beslissing met gevolgen voor de lange termijn. De bestaande methoden voor het bepalen van de optimale seriegroottes (zoals de formule van Camp) waren niet geschikt in deze situatie. De in dit artikel beschreven methode zal vooral zIjn toepassing kunnen vinden in de procesindustrie, zoals de farmaceutische, chemische, staal- en glasindustrie, omdat daar een seriegrootteverandering vaak een langetermijnbeslissing is.

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Copy reference link   DOI: 10.1016/S0925-5273(99)00111-5

Abstract: We study multipurpose batch process industries with no-wait restrictions, overlapping processing steps, and parallel resources. To achieve high utilization and reliable lead times, the master planner needs to be able to accurately and quickly estimate the makespan of a job set. Because constructing a schedule is time consuming, and production plans may change frequently, estimates must be based on aggregate characteristics of the job set. To estimate the makespan of a complex set of jobs, we introduce the concept of job interaction. Using statistical analysis, we show that a limited number of characteristics of the job set and the available resources can explain most of the variability in the job interaction.

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Copy reference link   DOI: 10.1111/j.1937-5956.2000.tb00326.x

Abstract: In this article, we describe the Global Project Coordination Course, a course in which project teams composed of three students from each of two overseas universities execute company-sponsored projects dealing with global supply chain management issues. The 75,000 to 100,00 contributed in total by the three to four sponsoring companies funds all course expenses. We assess the benefits and challenges of the use of cross-cultural project teams with diverse educational backgrounds. We conclude that the course provides a unique and effective vehicle for furthering students’ knowledge of Supply Chain Management and Information Systems, improving understanding of "soft" issues, and training students to work in diverse, global, cross-cultural project teams.

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Copy reference link   DOI: 10.1108/13598540010319993

Abstract: Increased demand variability in supply chains (the bullwhip effect) has been discussed in the literature. The practical measurement of this effect, however, entails some problems that have not received much attention in the literature and that have to do with the aggregation of data, incompleteness of data, the isolation of demand data for defined supply chains that are part of a greater supply web. This paper discusses these conceptual measurement problems and discusses experiences in dealing with some of these problems in an industrial project. Also presents empirical results of measurements of the bullwhip effect in two supply chains.

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Copy reference link   DOI: 10.1023/A%3A1008999002145

Abstract: We investigate the performance of workload rules used to support customer order acceptance decisions in the hierarchical production control structure of a batch chemical plant. Customer order acceptance decisions need to be made at a point in time when no detailed information is available about the actual shop floor status during execution of the order. These decisions need therefore be based on aggregate models of the shop floor, which predict the feasibility of completing the customer order in time. In practice, workload rules are commonly used to estimate the availability of sufficient capacity to complete a set of orders in a given planning period. Actual observations in a batch chemical manufacturing plant show that the set of orders accepted needs to be reconsidered later, because the schedule turns out to be infeasible. Analysis of the planning processes used at the plant shows that workload rules can yields reliable results, however at the expense of a rather low capacity utilization. In practice this is often unacceptable. Since, solving a detailed scheduling problem is not feasible at this stage, this creates a dilemma that only can be solved if we can find more detailed aggregate models than workload rules can provide.

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Copy reference link   DOI: 10.1016/S0965-8564%2898%2900066-4

Abstract: The Netherlands Railways operates a double tracked intensively used network of railroads. To expand the transportation capacity, each year a number of infrastructure expansions are considered. The evaluation of these expansions is traditionally done by establishing a set of detailed timetables that serve the forecasted transportation demand and that can be executed with the proposed infrastructure expansion. However, the development of a detailed timetable is a very time consuming process, and therefore leaves little opportunity for comparing many alternatives. In this paper, we present and test an aggregate model that can be used to single out the most promising investment alternatives in the railroad infrastructure, specifically passing constructions. The aggregate model provides the user with insight into the ranking of the various alternatives and additionally gives a relative insight into the theoretical capacity of the proposed infrastructure change.

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Copy reference link   DOI: 10.1023/A%3A1007672800764

Abstract: Aggregate models of detailed scheduling problems are needed to support aggregate decision making such as customer order acceptance. In this paper, we explore the performance of various aggregate models in a decentralized control setting in batch chemical manufacturing (no-wait job shops). Using simulation experiments based on data extracted from an industry application, we conclude that a linear regression based model outperforms a workload based model with regard to capacity utilization and the need for replanning at the decentralized level, specifically in situations with increased capacity utilization and/or a high variety in the job mix.

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Copy reference link   DOI: 10.1016/0377-2217%2895%2900061-T

Abstract: We introduce a two-level hierarchical planning and scheduling approach for multi-item, single-machine production systems facing stochastic demand. The hierarchical approach extends the existing heuristics to handle situations where demand levels are high compared to the available production capacity. At the top level of the hierarchy the approach deploys a heuristic procedure for coordinating capacity in the medium term. The heuristic produces target production cycle times and target service levels for each of the products. It iteratively allocates capacity to individual products for maximizing the expected profit while meeting the individual product service level targets set by the management. The bottom level of the hierarchy focuses on the short term and aims to realize the target service level while keeping the production cycles stable. At this level, a fixed-sequence order up-to operational scheduling policy which permits a limited amount of flexibility for reacting to short-term demand variations is implemented. Demand which cannot be met from inventory gets lost. We also present and discuss the results of extensive simulation tests under a wide range of environments that serve to demonstrate the superiority of the approach, especially when the demand level is high.

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Copy reference link   DOI: 10.1108/01443579410072382

Abstract: Discusses the variety of production control situations within process industries. Following a literature review, a typology is introduced which discriminates between two extreme types of process industries: batch/mix and process/flow businesses. Reviews the research in production and inventory control in each of the extreme types. Identifies a control framework for operations management in process/flow businesses. Notes that although detailed scheduling approaches for batch/mix businesses exist, a control framework for the latter is missing. Concludes that operations management in batch process industries needs considerable research attention.

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Abstract: No abstract.

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Journal Articles (Professional)

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Abstract: El artículo explica los factores que pueden provocar que una empresa padezca el "efecto látigo" en la planificación de su producción. A partir de esto presenta medidas que pueden ayudar a mitigarlo. Aunque los autores avisan de que no hay soluciones generales, sino que cada empresa debe crear su propia solución, ofrecen diversos métodos de análisis para poder desarrollar y adaptar una solución a la medida de sus necesidades.

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Abstract: Innovative "project-based courses" are bringing the business and academic worlds together to advance global supply chain management. By collaborating with universities to solve specific supply chain problems, companies not only benefit from the infusion of new ideas, but also gain access to a pool of potential future employees. The universities, for their part, strengthen their relationships with—and relevance to—industry. It’s a classic win-win situation.

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Books

Copy reference link   DOI: 10.1007/978-3-319-29791-0

Abstract: This book is primarily intended to serve as a research-based textbook on sustainable supply chains for graduate programs in Business, Management, Industrial Engineering, and Industrial Ecology, but it should also be of interest for researchers in the broader sustainable supply chain space, whether from the operations management and industrial engineering side or more from the industrial ecology and life-cycle assessment side.

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Abstract: Millions of small, family operated nanostores are the main source of consumer packaged goods in many neighborhoods of large cities across the developing world. In many of these countries, well over half of consumer goods are sold via the nanostore channel. Understanding this channel is critical for anyone selling or intending to sell into these large and fast growing markets. Tackling the logistics complexities of serving millions of nanostores is a challenge that many face, yet few master. In this book, we discuss logistics distribution and commercial route-to-market concepts for this channel and present best practices from Latin America, Asia, and North Africa. The book serves to inspire managers in marketing, sales, supply chain, distribution, logistics, and general management to develop their understanding and their business success in these growing markets.This book includes a unique set of case studies focusing on companies that have successfully created forward-looking approaches to retail operations over the world. The case studies included provide readers with a range of best practices, useful insights, and commercial and logistics strategies for serving diverse distribution channels. The authors (with extensive experience within these markets) and editors (from premier research institutions in Europe and the US) have done extensive field research over multiple years to develop the insights that are shared in this book.With the growth of convenience stores in the developed world, the insights also serve as an inspiration for those in Europe and North America that are confronted with a rapid proliferation of retail outlets as proximity shopping is becoming the norm. In the final chapter, the editors reflect on recent developments, particularly in China, where electronic commerce and nanostores are partnering to become a strong rival for the organized retail channel.

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Abstract: Logistics – the services, knowledge, and infrastructure that allow for the free movement of goods and people – is now recognized as a key driver of competitiveness and economic development. Efficient logistics systems are a precondition for regions, countries, cities, and businesses to participate in the global economy, boost growth, and improve livelihoods. Policy making has turned its attention to sustainable growth paths, valuing scarce resources, minimizing environmental impacts, and allowing economies to prosper across generations. In this new integrated vision of development, sustainable logistics is a key nexus. To improve sustainable logistics practices in the developing world, private sector technologies and innovations, as well as governmental policies and academic knowledge, need to be brought together. The government of the Netherlands and the World Bank have taken a first step in this direction and established the first Multi-Donor Trust Fund for Sustainable Logistics (MDTF-SL) in September 2013.

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Book Chapters

Copy reference link   DOI: 10.1007/978-3-319-29791-0_3

Abstract: This chapter presents an overview of the methods and challenges behind carbon footprinting at the supply chain level. We start by providing some information about the scientific background on climate change. This information is necessary to clarify the overall methodology behind carbon footprinting measurement. We also briefly review the main motivations for carbon footprinting. Then we propose an overview of the main methods available to measure a carbon footprint at the supply chain level. We propose to organize these methods in function of the quantity of information required, and we highlight a trade-off between the scope of measurement chosen and the accuracy of the estimation made. We continue by emphasizing the importance of supply chain (Scope 3) emissions in many supply chains. Finally, the chapter also discusses some challenges related to supply chain carbon footprinting. We specifically consider how to get information in practice, what level of accuracy is needed and how to extend the horizons beyond carbon.

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Copy reference link   DOI: 10.1007/978-3-319-29791-0_9

Abstract: Transportation is one of the main contributing factors of global carbon emissions, and thus, when dealing with facility location models in a distribution context, transportation emissions may be substantially higher than the emissions due to production or storage. Because facility location models define the configuration of deliveries, green location models become an important alternative to reduce CO2 emissions in logistics.This chapter presents a variety of green location models that include the estimation of carbon emissions. It also provides basic guidelines in understanding these models in comparison with cost minimization models.

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Copy reference link   DOI: 10.7148/2016-0439

Abstract: A major challenge for the industrial deployment of a CO2 emission reduction methodology is to reduce the overall cost and the integration of all the nodes in the supply chain for CO2 emission reduction. In this work, we develop a mixed integer linear optimization model that selects appropriate sources, capture process, transportation network and CO2 storage sites and optimize for a minimum overall cost. Initially, we screen the sources and storage options available in the Netherlands at different levels of detail (locations and industrial activities) and present the network of major sources and storage sites at the more detailed level. Results for a case study estimate the overall optimized cost to be €47.8 billion for 25 years of operation and 54 Mtpa reduction of CO2 emissions (30% of the 2013 levels). This work also identifies the preferred technologies for the CO2 capture and we discuss the reasons behind it. The foremost outcome of this case study is that capture and compression consumes the majority of the costs and that further optimization or introduction of new efficient technologies for capture can cause a major reduction in the overall costs.

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Copy reference link   DOI: 10.1007/978-3-319-11891-8_17

Abstract: The increase in traded container volumes worldwide puts pressure on the hinterland road network, leading congestion and emission problems. This leads to a requirement to develop intermodal transportation systems. In this chapter, we analyze the most important features of such container transportation systems for the hinterland supply chain. At the network design level, we review the current state of the art and we identify avenues for future research. Among others, we highlight that the coordination of container shipments across the container supply chain is a particularly relevant issue as hinterland networks involve several actors. At the operational level, we characterize the most important factors influencing the trade-off between intermodal transportation and truck-only deliveries. In addition, we provide a case study of coordination at an intermodal barge terminal in the Netherlands. We highlight that the exchange of information is the key enabler for efficient hinterland intermodal transportation and we show that a better information system can be of crucial importance.

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Copy reference link   DOI: 10.1016/B978-0-444-63456-6.50074-0

Abstract: Decisions in an oil refinery are made at three levels: planning, scheduling and control. Existing facilities have to be operated close to their maximum capacity, while continuously responding to cost fluctuations. In many of the currently reported planning models each decision level has its own model and is used separately. Integration of these models will lead to solutions closer to the optimum than modeling the decision levels separately. However, simply combining the levels into one model would lead to very large models that yet cannot be solved within reasonable time. To overcome the computational time issue a rolling horizon approach is proposed in this work.

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Copy reference link   DOI: 10.1007/978-1-4419-6132-7_15

Abstract: International Series in Operations Research & Management ScienceInternational container transport is the backbone of global supply chains. Hinterland transport, the transport from the port to the final destination and vice versa, is an important component of international container transport. However, academic attention to hinterland transport has emerged only recently. This chapter discusses business models and network design in hinterland transport. Understanding business models is relevant, as many different types of companies (e.g., shipping lines, terminal operating companies and forwarders) play a role in hinterland transport. Their business models influence how they position themselves in the market, their stance concerning cooperation and coordination in hinterland transport, and their scope in network design. Network design is a core issue in hinterland transport. New services need to be designed—and in such a way that they are expected to be profitable. Furthermore, current service patterns only change through deliberate redesign. So competition through the (re)design of transport services is a very important—perhaps the most important—form of competition in intermodal freight transport. One potentially promising innovation in this respect is the extended gate concept, where an inland hub becomes the ‘virtual gate’ of the deep sea terminal.

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Copy reference link   DOI: 10.1016/B978-0-444-53711-9.50185-1

Abstract: In earlier work we have developed and tested a scheduling model [1] in the AIMMS software. In this follow-up contribution we will develop a planning model. Next we will identify the information flow between scheduling model and the planning model. Lastly we will integrate the two models in a straight-forward fashion using run-modes and rolling-horizon methodology. With a case study we prove that the overall strategy aids systematic integration of the two levels, which allows fast optimization of the short-term as well as the long-term decisions without significantly affecting the quality of the solution.

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Copy reference link   DOI: 10.1007/978-3-642-13382-4_8

Abstract: Instabilities in production planning and control have received considerable attention due to their negative impact on planning performance. However, extant research has been limited to theoretical (e.g. simulation) settings and has focused on specific methodologies (e.g. mathematical) to overcome instabilities. The objective of this chapter is to make two contributions to the theory development on production planning instabilities. First, it aims to make an empirical contribution through an in-depth case study, and second, it introduces a holistic framework that supports analysis of hierarchical planning systems and their potential instabilities. The in-depth case study is carried out on an industrial company that has difficulty to meet its customer deadlines and faces a significant order backlog. Planners of the company at different hierarchical levels and order chasers on the shop floor end up rescheduling open orders and updating lead times continuously when trying to meet deadlines, but eventually are not able to improve order fulfillment. Only after the introduction of an Advanced Planning System and centralization of planning decisions in a single department, on-time delivery was significantly improved and order back log drastically reduced. This case study allows studying of the underlying mechanism of such planning instabilities, with a particular focus on the impact on stability of human and organizational factors. On the basis of our findings and additional conceptual research we have then developed a framework constituted by six key planning systems attributes. By taking into consideration these factors, a firm can address the root causes of planning instabilities, rather than merely focus on its symptoms.

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Abstract: Historically, the scheduling of crude oil unloading, blending and charging in an oil refinery has been done manually by a scheduler. This is a very time consuming process and often the manual scheduler will not find the optimal schedule. Systematic optimization could dramatically improve the quality of the schedules.

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Copy reference link   DOI: doi:10.1007/978-3-642-13382-4_1

Abstract: Planning and scheduling play an important role in performance enhancement in any operation. This has probably been best recognized in industry, where a wide range of software applications have been developed to support decision makers with decisions such as machine scheduling, forecasting, inventory control, and sales & operations planning.

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Copy reference link   DOI: 10.1007/978-3-540-93775-3_8

Abstract: This paper considers the problem of determining safety stocks in multi-item multi-stage inventory systems that face demand uncertainties. Safety stocks are necessary to make the supply chain, which is driven by forecasts of customer orders, responsive to (demand) uncertainties and to achieve predefined target service levels. Although there exists a large body of literature on determining safety stock levels, this literature does not provide an effective methodology that can address complex multi-constrained supply chains. In this paper, the problem of determining safety stocks is addressed by a simulation based approach, where the simulation studies are based on solving the supply chain planning problem (formulated as a mathematical programming model) in a rolling horizon setting. To demonstrate the utility of the proposed approach, an application of the approach at Organon, a worldwide operating biopharmaceutical company, will be discussed.

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Abstract: Chapter Overview • Modelling and simulation using quantitative models: making causal relationships explicit • An historical overview of how modelling and simulation research has evolved out of scientific management, management consulting and military applications, and what are its strengths and weaknesses for understanding and solving OM problems • Modelling and simulation characterized as descriptive or prescriptive research, and as axiomatic or empirical research • How to perform research in OM using modelling and simulation in steps to be taken, and demonstrated in an example, both in descriptive and prescriptive scientific problem settings • The relevance of research using modelling and simulation for understanding and solving real—life OM problems

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Abstract: In hierarchical production planning structures, decisions by planning entities at the various levels may lead to a planning bullwhip, for example, because of an inappropriate updating frequency of plans. In this planning bullwhip, poor estimates of the lead time and poor actual performance reinforce each other. We study the planning bullwhip in relation to the mitigating role that human planners may play, as the effect very often is originated and amplified by the use of decision support systems. We use the case study methodology. Our findings suggest that especially the planning structure plays a crucial role in enabling humans to mitigate the planning bullwhip.

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Abstract: Decision support systems (DSS) play an important role in supporting scheduling tasks in industrial settings. In this paper, a special facet of DSS, respectively their development, implementation and usage in relation to user participation, is examined. The outlined research model proposes that different forms of user participation lead to different levels of model complexity. This complexity influences in turn such outcome variables like system performance, user satisfaction etc. The research model integrates several existing concepts from technology acceptance, planned behaviour, involvement and participation research as well as control theory. These theories are expanded by the dynamics of the modelling process. For the empirical analysis multiple case studies examining different cases of DSS development and implementation processes in different settings were conducted

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Copy reference link   DOI: 10.1007/3-540-27059-0_2

Abstract: In this chapter, we have shown that both customer service and the capacity utilization in retail chains can be increased by improving the logistic decisions taken by the retailer. New teclmologies allow the retailers to improve their logistic decisions by increasing either the level of differentiation, the level of sophistication and/or the level of integration in their decisionmaking. In many retail chains, different items need different logistic solutions. In this chapter, we distinguished five product categories: items that are phasing-inlout, items that are on promotion, items that are driving the utilization of capacities, and regular items. All these categories require a different way of controlling the operations. Most ASO systems currently applied are primarily developed for regular items. In this chapter, we describe how these ASO systems can be improved to also support other products. Al though the findings are based on observations at Dutch retailers, discussions with retailers in other countries indicate that most results also apply elsewhere. A final remark can be made on the importance of labor costs in retail chains, and its impact on the focus of Retail Logistics. In many retail chains, we noted that labor costs by far outweigh the inventory holding costs at the operational level (i.e. if the size of the store, the product as sortment and the planograms are fixed). This implies that a major focus of top management in retail chains should be on how to improve labor efficiency. Little scientific research has been done in this area, and so more research is needed to get a better understanding of the factors detennining labor efficiency in stores.

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Abstract: Batch process industries are characterized by complex precedence relationships between operations, which renders the estimation of an acceptable workload very difficult. A detailed schedule based model can be used for this purpose, but for large problems this may require a prohibitive large amount of computation time. We propose a regression based model to estimate the makespan of a set of jobs. We extend earlier work based on deterministic processing times by considering Erlang-distributed processing times in our model. This regression-based model is used to support customer order acceptance. Three order acceptance policies are compared by means of simulation experiments: a scheduling policy, a workload policy and a regression policy. The results indicate that the performance of the regression policy can compete with the performance of the scheduling policy in situations with high variety in the job mix and high uncertainty in the processing times.

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Abstract: In this article, we describe the Global Project Coordination Course, a course in which project teams composed of three students from each of two overseas universities execute company-sponsored projects dealing with global supply chain management issues. The 75,000 to 100,00 contributed in total by the three to four sponsoring companies funds all course expenses. We assess the benefits and challenges of the use of cross-cultural project teams with diverse educational backgrounds. We conclude that the course provides a unique and effective vehicle for furthering students’ knowledge of Supply Chain Management and Information Systems, improving understanding of "soft" issues, and training students to work in diverse, global, cross-cultural project teams.

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