Supply Chain Finance: research challenges ahead

Supply Chain Finance: research challenges ahead Kasper van der Vliet, Matthew J. Reindorp, Jan C. Beta Working Paper series 418 BETA publicatie ISBN ISSN NUR 804 Eindhoven WP 418 (working paper) Update November 2013

Supply Chain Finance: research challenges ahead Received: date / Accepted: date Abstract As intermediaries of capital and related services expand their offerings, Supply Chain Finance (SCF) has enjoyed considerable attention from industry. Trade literature and scientific studies posit the aim of SCF to be the reduction of capital costs through a reconfiguration of financial flows. The latest developments in industry and research suggest, however, that the dimensions of SCF are more complex. We highlight trends that widen the range of trade-offs to be considered in an SCF initiative, and exemplify the relevance of these trends through a case study of two European firms. While both firms aim to generate value from their SCF initiative, their approaches show different attitudes towards supply chain risk and the opportunity to customise supplier relations. We present a conceptual framework that positions SCF practices and shows the need for further research on strategic and tactical considerations. Keywords Finance Reverse Factoring Framework Case Study K. van der Vliet Eindhoven University of Technology, School of Industrial Engineering & Innovation Sciences Den Dolech 2, 5600MB Eindhoven, The Netherlands Tel.: +31-40-247-2028 E-mail: k.v.d.vliet@tue.nl M.J. Reindorp Den Dolech 2, 5600MB Eindhoven E-mail: m.j.reindorp@tue.nl J.C. Den Dolech 2, 5600MB Eindhoven E-mail: j.c.fransoo@tue.nl

2 1 Introduction Interest for Supply Chain Finance (SCF) has grown significantly since the financial crisis of 2008 [24, 26, 34, 41]. According executives surveyed by Aberdeen Group [26], the impact of demand volatility on available cash is a key factor behind these developments. As demand volatility calls on one hand for investment in safety stocks but on the other hand induces a desire to hold precautionary cash, balancing these concerns may become a challenge. While multidisciplinary research promises a remedy to such problems [32], the supply chain management discipline itself is in practice often surprisingly little involved in SCF initiatives. According to an executive of a transaction services provider, there is nothing very supply chain about finance right now [24]. Aberdeen [26] indicates that the supply chain management discipline is not involved in almost 50% of the SCF initiatives 1 surveyed. In this article, we argue that a more holistic approach to SCF is appropriate. In particular, we extend current perspectives by exploring the operational dimensions of an SCF arrangement. Our insights result from consideration of key trends in the concepts and practices of credit intermediation and a small case study of SCF initiatives. We summarize our view of SCF in terms of a framework that can orientate dialogue and research on best practices. Research on SCF fits with the growing body of literature at the interface of finance and operations. Works in this area address situations where firms can create value or improve risk management by jointly considering physical and financial flows [4, 5, 6, 9, 12, 18, 28]. While some have explored such problems in a supply chain setting [9, 19, 18], important challenges that can result from the inter-firm nature of an SCF arrangement remain largely unexplored. The potential complexity of these arrangements is evident from the general definition of SCF proposed by Pfohl and Gomm [27]: [SCF] is the inter-company optimization of financing as well as the integration of financing processes with customers, suppliers, and service providers in order to increase the value of all participating companies. As an optimization problem, implementation of SCF involves a choice of criteria to represent the interests of supply chain stakeholders, then the making trade-offs such that the best outcome is realized. Pfohl and Gomm [27] explore such trade-offs when the relevant criteria are cheaper financing versus the cost of information transfer needed to realize it. Firms may obtain financing at a lower price than what would normally be offered by financial intermediaries (cf. [11, 23, 25, 35]), but the cost of the required information revelation should marginally equal the resulting savings. Several other studies also see reduction of capital costs as the objective of SCF [14, 41, 29]. Our work complements this perspective by bringing supply chain competencies and implementation 1 We use the term SCF arrangement generally in this article in order to denote a specific instance of SCF between firms. Nonetheless, we may refer to SCF initiatives when the emphasis is on firms intentions or actions to realize an SCF arrangement. There is otherwise no substantive difference between the two referents.

Supply Chain Finance: 3 5. Advance cash minus interest Factor 6. Pay in full at maturity 4. Request to sell entitlement to payment Web platform 3. Confirm vendor s entitlement to payment 1. Place order Vendor Buyer 2. Send goods Fig. 1 Successive actions in a reverse factoring transaction tactics into the range of trade-offs that firms may consider when implementing an SCF arrangement. In practice, most SCF initiatives concern the implementation of an arrangement also known as reverse factoring [15, 24, 26, 34, 41]. Empirical and theoretical consideration of reverse factoring consequently provides considerable basis for our study. Formally, reverse factoring is an arrangement where a buyer facilitates early financing options for its suppliers by confirming future payment obligations to a factor, i.e., a financial intermediary [17]. Figure 1 gives a schematic representation of the process. Based on the confirmations provided by the buyer, the factor can fully reconcile the risk and pricing of any collateral transaction, and thus offer credit to the supplier at the same price it would to the buyer. Investment grade firms can thus generally use reverse factoring to improve the cost of capital of their suppliers. Prominent manufacturing firms such as Volvo, Scania, Nestle, Rolls Royce, Caterpillar, and Boeing, and major retailers, such as Sainsbury and Metro, are using reverse factoring [2, 7, 22, 24]. A study initiated by the Bank of England concluded that the scheme offers significant opportunities to expand lending to SMEs [1]. Some empirical research has analysed the use of the scheme [17, 34, 41] and proposes general managerial advice for successful implementation. As noted earlier, this literature primarily highlights the financial motives for SCF. Nevertheless, close examination of theory and practice suggests that the potential dimensions of SCF are diversifying and expanding away from a single focus. For instance, some firms are aware that reverse factoring may relax financial constraints that have a negative impact on suppliers operational performance [2]. While such insights fit perfectly with the perspective we advance here, we argue for an even broader view of the dimensions of SCF. The rest of this article is organized as follows. In Section 2, we offer a more detailed consideration of three important trends in the intermediation of credit within supply chains. These trends entail choices and accompanying

4 trade-offs for SCF that are not addressed in the existing literature. In Section 3, we report corroborative findings from a case study on reverse factoring. In Section 4, we synthesize our observations and present a view of research opportunities by means of a conceptual framework. In Section 5, we summarize and conclude our work. 2 Trends changing the SCF landscape At the core of SCF we find the concept of credit intermediation between supply chain members, i.e., intra-supply chain credit, in contrast to credit intermediation only by specialised financial institutions. Intra-supply chain credit is in fact is a well-established and well-researched phenomenon (see [33] for an extensive review). It is customary for vendors to give trade credit to customers: in the short term, they provide goods or services in return for a promise of payment. Vendors may even offer long-term financing through so-called captive financing vehicles [8]. Such practices are popular with manufacturers selling capital-intensive goods, for instance, producers of agriculture equipment [20]. Scientific literature indicates the following four main motives for intra-supply chain credit [23, 25]: (Motive 1) better information/control than intermediaries; (Motive 2) price discrimination; (Motive 3) transactional savings; (Motive 4) quality control and assurance. Nonetheless, recent developments in research on intra-supply chain credit and also in industry suggest an evolution of standard theory and practice. In the following paragraphs, we describe three emerging trends that are especially relevant for SCF. Trend 1: greater involvement of financial and/or technological intermediaries in intra-supply chain credit. Close to 85% of global trade is transacted on open account, yet the Society for Worldwide Interbank Financial Telecommunication (SWIFT) believes that a significant of share of it will migrate towards bank-intermediated services in the coming years [37]. This migration suggests that the ability of firms to exploit relative advantages over financial intermediaries (motive 1) is stagnating. Indeed, banks and technology providers have significantly invested in platforms to mitigate informational asymmetries and automate the process of making funds available, based on events in the supply chain [15, 38]. Most current services, including reverse factoring, can be classified as post-shipment solutions: financing is offered after completion of the physical transaction. Some pre-shipment services are also available, such as purchase-order financing or inventory financing, and the introduction of industry standards to better facilitate pre-shipment financing promises growth in this area [38]. Currently, discriminatory practices (motive 2) sometimes remain because marginal costs for intermediaries are too high: for instance,

Supply Chain Finance: 5 smaller suppliers have been excluded from reverse factoring arrangements because their inclusion was thought not to offer significant benefits [24, 41]. Increasing technological maturity will yield more opportunities for value creation, i.e., beyond purely transactional savings (motive 3), and thus more involvement of intermediaries. Trend 2: supply chain risk management as a motive for intra-supply chain credit. Recent research reveals that intra-supply chain credit creates value through mitigation and/or control of supply chain risk. This development may be seen as an extension of (motive 4). Yang and Birge [42] show how trade credit serves as a risk-sharing mechanism in the supply chain. Kim and Shin [16] show how trade credit mitigates incentive problems by building inter-firm credit relationships. Babich [3] analyses the joint decision to reserve capacity and grant financial aid to a supplier to control supply disruptions. In addition, industry practices are emerging in which risk management is the motive for offering credit in the supply chain. Caterpillar introduced reverse factoring as part of its program to gear its supply base after the credit crisis of 2008 [2]. Similarly, Rolls Royce introduced reverse factoring to strengthen the resilience of its supply chain [31]. Boeing implemented reverse factoring as part of a larger campaign to help SME suppliers sustain highly skilled export-related jobs [7]. While the use intra-supply chain credit for mitigation of supply chain risk may entail costs and/or risks for the facilitating company, these examples suggest that the net value of the engagement can be positive. Trend 3: multi-echelon perspective on the configuration of intra-supply chain credit. Traditionally, intra-supply chain credit is arranged between two parties. A supply chain thus consists of multiple financial arrangements that are in principle independent. Theoretical and empirical evidence suggests that the two trends already identified - greater involvement of intermediaries and supply chain risk management motives - may be further developed by the implementation of more integrated perspectives on the financial dimensions of the supply chain. Some studies analyse the potential working capital savings from adjustments in payment schemes across multiple tiers of the supply chain [14, 29]. Song and Tong [36] provide a new accounting framework that allows for evaluating key financial metrics under payment schemes in serial supply chains. Luo and Shang [21] illustrate the value of cash pooling in multi-divisional supply chains. Unilever provides financial aid to suppliers in multiple tiers of the tea supply chain, in order to mitigate uncooperative working capital practices among them [30]. Hewlett Packard makes use of a so-called Buy/Sell -scheme that they also offer as a service to firms [13]. This scheme offers firms that have outsourced manufacturing operations the opportunity to retain control of supply from second-tier firms. The three trends described suggest that a firm initiating an SCF arrangement may face important strategic and tactical considerations. For instance, to what extent should a firm involve financial or technological intermediaries, strive to realize risk management objectives, or pursue a multi-level perspective? In order to provide further evidence for the relevance of these trends,

6 we examined the implementation of reverse factoring at two large European corporations. 3 SCF in practice: divergent approaches to reverse factoring Firms A and B are publicly listed multinational firms with large, complex, global supply networks consisting of thousands of entities. Both firms operate in the technology sector. At the time of our case study, firm A had operated reverse factoring arrangements for over a year, while firm B had just begun. We were interested to place each firm s strategy and implementation tactics in light of the three trends discussed above. We conducted semi-structured interviews with executives involved in the implementation process. The main results are displayed in Table 1. The perspective of risk management (trend 2) provides the main contrast between each firm s approach to reverse factoring. Firm A is not concerned with risk management in this context, and sees reverse factoring primarily as a means to improve its working capital position and cost of procurement. In contrast, firm B has an explicit risk-related goal: improve suppliers ability to respond to demand variability. More specifically, firm A uses reverse factoring to make standardized extensions to its payment terms, while still allowing suppliers to realize some reduction in total financing cost (with respect to the situation that existed before the use of reverse factoring). Longer payment terms entail that firm A realizes a reduction in working capital, and standardization of payment dates reduces transaction costs. Firm B is not motivated by potential savings in working capital or transaction costs from implementation. The responsiveness of its suppliers - of which many are critical - is a significant factor for revenues, market share, and profit. Reverse factoring improves suppliers liquidity and lowers their short-term financing costs, at least partially removing financial obstacles to operational agility. For firm B, the value of improved supply chain performance - better matching of supply with demand - appeared unquestionably greater than the foregone savings from a decrease of working capital. The different objectives of the two firms are further reflected in the role of the financial intermediary and the tactics used in the reverse factoring implementation (trend 1). At both firms the intermediary provides the technology and funding and explains the scheme to suppliers, but firm A allows the intermediary a deeper role in determining how financing is offered. The intermediary here is a tactical partner in the supply chain, providing estimations of each supplier s cost of capital and working capital position. Firm A consequently sets a threshold level on the annual value of transactions, in order to determine which suppliers are eligible for implementation. The return from implementations at a lower volume is thought not to justify the direct costs. Firm A thus first targets suppliers with the highest transactional volume and/or cost of capital, as these provide the greatest potential return in reduction of working capital and other costs. The terms offered to each sup-

Supply Chain Finance: 7 Table 1 Two firms with different approaches towards reverse factoring Trend firm A firm B (Trend 1) role of financial intermediary (Trend 2) risk management (Trend 3) multilevel perspective Provides strategic guidance and supports implementation by providing credit assessments; suppliers segmented based on their transactional volume and capital cost. No clear focus on risk management; decrease working capital through extension of payment terms and/or reduce costs of goods sold through reduction of prices and standardization of payment terms. New terms contractually agreed in amendments. Promote reselling of working capital benefits to firms upstream in supply chain. Has a passive role in supplier offering; scheme is offered to all suppliers on the same terms. Clear focus on risk management; increase the ability of the supply network to cope with demand volatility and support the realisation of its growth ambitions concerning the customer base. No terms changed to the existing contracts. Enable financial flexibility for firms upstream in the supply chain. plier are tailored to the size of the potential benefits, and all agreements are ultimately contractual. Firm B employs no such criteria and makes the scheme available to all suppliers. Small but critical suppliers can have big impact on the ability of firm B to meet final market demand, so there is no reason to discriminate based on size. In addition, in contrast to firm A, firm B does not amend the terms (e.g., with respect to logistics performance) of its contracts with suppliers, which suggests that it sees interests to be naturally aligned in its supply chain. Concerning the relevance of reverse factoring for their extended supply chain (trend 3), the firms again provide different but cogent views. Firm A notes that some suppliers - in particular, larger firms already have relatively good access to capital - initially saw little benefit from participating in the reverse factoring program. The possibility that such suppliers could in turn rearrange payment terms with their suppliers nevertheless became a decisive argument for participation. In contrast, firm B promotes propagation of cheap liquidity upstream in its supply chain, in order to stimulate further investment in supplier resilience. 4 A typology for future research on SCF The trends discussed above already suggest specific opportunities for further research, but the factors that influence intra-supply chain credit arrangements are likely to become only more diverse with time. In order to encourage di-

8 obj ecti ives Uniform Firm B Competence oriented Custom Str rate egic Transaction oriented Firm A Implementation tactics Fig. 2 A typology for SCF practices alogue and inspire research on SCF best practices, we propose more basic dimensions as the basis for an SCF typology: strategic objectives and implementation tactics. See Figure 2 for a visualization of these dimensions. Along the strategic dimension we distinguish transaction-oriented SCF at one extreme from competence-oriented SCF at the other. The contrast is inspired by our case study: an SCF arrangement may improve transactional efficiency through working capital or price benefits, while it can also be employed to enhance a supply chain competence, such as supply base agility. Along the tactical dimension we distinguish uniform implementations from customized implementations. In a uniform implementation, the initiating firm follows more or less a single specification for SCF arrangements, while in a customized implementation the firms adjusts the type and terms the agreement to fit the nature their supply relationship(s). For instance, firm A employs a higher level of customization than firm B, since the terms offered are tailored to the size of the transactional benefits. While these dimensions provide initial direction, they need further study to achieve managerial relevance. Are the choices of firm A and firm B indeed optimal for them (see approximate placements in Figure 2)? Under what circumstances would uniform, transaction-oriented SCF or customized, competenceoriented SCF be advisable? As financial intermediaries further proliferate their offerings, and pre-shipment or multi-level intra-supply chain credit gains more momentum, theoretical studies can help determine what competences can be enhanced by SCF and what type and degree of customization is advisable in each case. With respect to supply chain competencies, the range of objectives that might be realized by efficient financing is as varied as the investment opportunities present in the supply chain. Many supply chain variables that depend

Supply Chain Finance: 9 on investment, such as inventory levels, lot sizes, capacity, and lead-times, are greatly influenced by the cost of financing at the respective tier of the chain. As these decisions frequently impact the rest of the chain, potential adjustments through SCF can be of great value. As often appears in standard investment theory, however, an opportunity with high expected value may entail significant risk. For instance, a pre-shipment financing program that helps vendors with raw materials purchases may expose the supply chain to higher obsolescence risks, which can lead to a great reduction in the risk-adjusted value. While the current literature on supply chain coordination of incentives through contracting is well developed (see, e.g., [10]), the potential of SCF as a rectifying mechanism for investment in supply chains remains largely unexplored. Since the potential benefit and risk of a particular type SCF engagement is likely to change under different conditions, appropriate consideration should be given to trade-offs. For instance, Tanrisever et al. [39] show that reverse factoring may promote operational improvement in the supply chain, but this improvement is highly sensitive to the terms proposed by the buyer. Customization measures may increase the return of an SCF arrangement, but they will usually require greater investment in technology and/or administration. As shown by the case of firm A, customization may also entail a more prominent role for the relevant financial intermediary due to its specialisation in financial analysis. There are thus numerous dimensions along which marginal cost must be balanced with marginal reward, generalizing the informational transfer setting discussed by Pfohl and Gomm [27]. For a competence-oriented SCF arrangement, a tactic of customization may face even more complexities. Besides operational and/or financial risks, firms may also be exposed to agency or moral hazard problems. Funding from SCF may be diverted to personal interests or used to serve other investment than what has been agreed between the parties involved. These problems of moral hazard are recognized in the literature of corporate finance and (contractual) remedies are generally prescribed [40]. Literature on SCF customization measures for ensuring effective supply chain investment is so far limited. In order to provide adequate answers, with appropriate consideration for the trade-offs and risks, multi-disciplinary and multi-method approaches may need to be applied or new approaches developed in SCF research [32]. 5 Conclusion New services to facilitate credit more efficiently between members of the supply chain will continue to evolve in industry. These applications may reduce the costs of financing the supply chain, but they can also indirectly enhance the supply chain by improving its ability to mitigate supply disruptions or invest sufficiently to achieve maximum operational efficiency. While there is empirical evidence of both approaches, conceptual and practical guidance on the conduct of competence-oriented SCF is scant, let alone how to customize SCF to maximize competence-oriented returns. Studies that consider the dy-

10 namics between physical and financial flows on the single firm-level show that measures to improve financial performance may eventually degrade operational performance [12, 28]. The same principle seems to hold for inter-firm financing concepts [39]. We propose a conceptual framework to inspire potentially fruitful research directions for forging SCF best practices. Further study is needed. Explanatory research can help to identify the antecedents for a particular type of SCF arrangement. Normative research can help to identify the SCF configurations that do meet multiobjective criteria, i.e., financial efficiency and supply chain operational performance. Such research can entail significant opportunities for industrial users, financial intermediaries and providers to develop better SCF technologies. References 1. ACT (2010) Supply chain finance: report of the supply chain finance working group URL http://www.treasurers.org/scf, [last accessed 6 March 2013] 2. Aeppel T (2010) bullwhip hits firms as growth snaps back. Wall Street Journal [last accessed 6 March 2013] 3. Babich V (2010) Independence of capacity ordering and financial subsidies to risky suppliers. Manufacturing & Service Operations Management 12(4):583 607 4. Babich V, Sobel MJ (2004) Pre-ipo operational and financial decisions. Management Science 50(7):935 948 5. Birge J, Kouvelis P, Seppi D (2007) Call for papers special issue of management science: Interfaces of operations and finance. Management Science 53(2):355 355 6. Birge JR (2000) Option methods for incorporating risk into linear capacity planning models. Manufacturing & Service Operations Management 2(1):19 31 7. Boeing (2012) Boeing, citi start export-import bank supplier financing program. Boeing Mediaroom [last accessed 6 March 2013] 8. Brennan M, Miksimovic V, Zechner J (1988) Vendor financing. The Journal of Finance 43(5):1127 1141 9. Buzacott J, Zhang R (2004) Inventory management with asset-based financing. Management Science 50(9):1274 1292 10. Cachon G (2003) Supply chain coordination with contracts. In: Graves, S.C. and de Kok, A.T. (ed) Handbooks in Operations Research and Management Science, Supply Chain Management: Design, Coordination, and Operation, vol 11, Elsevier, Boston, pp 227 339 11. Emery GW (1984) A pure financial explanation for trade credit. Journal of Financial and Quantitative Analysis 19(3):271 85 12. Gupta D, Wang L (2009) A stochastic inventory model with trade credit. Manufacturing & Service Operations Management 11(1):4 18

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Nr. Year Title Author(s) 418 2013 Supply Chain Finance: research challenges ahead Kasper van der Vliet, Matthew J. Reindorp, Jan C. 417 2013 Improving the Performance of Sorter Systems by Scheduling Inbound Containers S.W.A. Haneyah, J.M.J. Schutten, K. Fikse 416 2013 Regional logistics land allocation policies: Stimulating spatial concentration of logistics firms Frank P. van den Heuvel, Peter W. de Langen, Karel H. van Donselaar, Jan C. 415 2013 The development of measures of process harmonization Heidi L. Romero, Remco M. Dijkman, Paul W.P.J. Grefen, Arjan van Weele 414 2013 BASE/X. Business Agility through Cross-Organizational Service Engineering. The Business and Service Design Approach developed in the CoProFind Project Paul Grefen, Egon Lüftenegger, Eric van der Linden, Caren Weisleder 413 2013 The Time-Dependent Vehicle Routing Problem with Soft Time Duygu Tas, Nico Dellaert, Tom van Windows and Stochastic Travel Times Woensel, Ton de Kok 412 2013 Clearing the Sky - Understanding SLA Elements in Cloud Computing Marco Comuzzi, Guus Jacobs, Paul Grefen 411 2013 Approximations for the waiting time distribution in an M/G/c A. Al Hanbali, E.M. Alvarez, M.C. van der priority queue Heijden 410 2013 To co-locate or not? Location decisions and logistics concentration areas Frank P. van den Heuvel, Karel H. van Donselaar, Rob A.C.M. Broekmeulen, Jan C., Peter W. de Langen 409 2013 The Time-Dependent Pollution-Routing Problem Anna Franceschetti, Dorothée Honhon, Tom van Woensel, Tolga Bektas, Gilbert Laporte 408 2013 Scheduling the scheduling task: A time management J.A. Larco, V. Wiers, J. perspective on scheduling 407 2013 Clustering Clinical Departments for Wards to Achieve a Prespecified Blocking Probability J. Theresia van Essen, Mark van Houdenhoven, Johann L. Hurink 406 2013 MyPHRMachines: Personal Health Desktops in the Cloud Pieter Van Gorp, Marco Comuzzi 405 2013 Maximising the Value of Supply Chain Finance Kasper van der Vliet, Matthew J. Reindorp, Jan C. 404 2013 Reaching 50 million nanostores: retail distribution in Edgar E. Blanco, Jan C. emerging megacities 403 2013 A Vehicle Routing Problem with Flexible Time Windows Duygu Tas, Ola Jabali, Tom van Woensel 402 2013 The Service Dominant Business Model: A Service Focused Conceptualization 401 2013 Relationship between freight accessibility and logistics employment in US counties 400 2012 A Condition-Based Maintenance Policy for Multi-Component Systems with a High Maintenance Setup Cost Egon Lüftenegger, Marco Comuzzi, Paul Grefen, Caren Weisleder Frank P. van den Heuvel, Liliana Rivera, Karel H. van Donselaar, Ad de Jong, Yossi Sheffi, Peter W. de Langen, Jan C. Qiushi Zhu, Hao Peng, Geert-Jan van Houtum 399 2012 A flexible iterative improvement heuristic to support creation E. van der Veen, J.L. Hurink, J.M.J. of feasible shift rosters in self-rostering Schutten, S.T. Uijland 398 2012 Scheduled Service Network Design with Synchronization and Transshipment Constraints for Intermodal Container K. Sharypova, T.G. Crainic, T. van Woensel, J.C. Transportation Networks 397 2012 Destocking, the bullwhip effect, and the credit crisis: empirical modeling of supply chain dynamics Maximiliano Udenio, Jan C., Robert Peels 396 2012 Vehicle routing with restricted loading capacities J. Gromicho, J.J. van Hoorn, A.L. Kok, J.M.J. Schutten

Nr. Year Title Author(s) 395 2012 Service differentiation through selective lateral transshipments E.M. Alvarez, M.C. van der Heijden, I.M.H. Vliegen, W.H.M. Zijm 394 2012 A Generalized Simulation Model of an Integrated Emergency Martijn Mes, Manon Bruens Post 393 2012 Business Process Technology and the Cloud: defining a Vassil Stoitsev, Paul Grefen Business Process Cloud Platform 392 2012 Vehicle Routing with Soft Time Windows and Stochastic Travel Times: A Column Generation and Branch-and-Price D. Tas, M. Gendreau, N. Dellaert, T. van Woensel, A.G. de Kok Solution Approach 391 2012 Improve OR-Schedule to Reduce Number of Required Beds J. Theresia van Essen, Joël M. Bosch, Erwin W. Hans, Mark van Houdenhoven, Johann L. Hurink 390 2012 How does development lead time affect performance over the ramp-up lifecycle? Evidence from the consumer electronics industry Andreas Pufall, Jan C., Ad de Jong, A.G. (Ton) de Kok 389 2012 The Impact of Product Complexity on Ramp-Up Performance Andreas Pufall, Jan C., Ad de Jong, A.G. (Ton) de Kok 388 2012 Co-location synergies: specialized versus diverse logistics concentration areas Frank P. van den Heuvel, Peter W. de Langen, Karel H. van Donselaar, Jan C. 387 2012 Proximity matters: Synergies through co-location of logistics establishments 386 2012 Spatial concentration and location dynamics in logistics: the case of a Dutch province Frank P. van den Heuvel, Peter W. de Langen, Karel H. van Donselaar, Jan C. Frank P. van den Heuvel, Peter W. de Langen, Karel H. van Donselaar, Jan C. 385 2012 FNet: An Index for Advanced Business Process Querying Zhiqiang Yan, Remco Dijkman, Paul Grefen 384 2012 Defining Various Pathway Terms W.R. Dalinghaus, P.M.E. Van Gorp 383 2012 The Service Dominant Strategy Canvas: Defining and Visualizing a Service Dominant Strategy through the Traditional Strategic Lens 382 2012 A Stochastic Variable Size Bin Packing Problem with Time Constraints 381 2012 Coordination and Analysis of Barge Container Hinterland Networks 380 2012 Proximity matters: Synergies through co-location of logistics establishments Egon Lüftenegger, Paul Grefen, Caren Weisleder Stefano Fazi, Tom van Woensel, Jan C. K. Sharypova, T. van Woensel, J.C. Frank P. van den Heuvel, Peter W. de Langen, Karel H. van Donselaar, Jan C. 379 2012 A literature review in process harmonization: a conceptual Heidi Romero, Remco Dijkman, Paul framework Grefen, Arjan van Weele 378 2012 A Generic Material Flow Control Model for Two Different S.W.A. Haneyah, J.M.J. Schutten, P.C. Industries Schuur, W.H.M. Zijm 377 2012 Dynamic demand fulfillment in spare parts networks with H.G.H. Tiemessen, M. Fleischmann, G.J. multiple customer classes van Houtum, J.A.E.E. van Nunen, E. Pratsini 376 2012 Paper has been replaced by wp 417 K. Fikse, S.W.A. Haneyah, J.M.J. Schutten 375 2012 Strategies for dynamic appointment making by container Albert Douma, Martijn Mes terminals 374 2012 MyPHRMachines: Lifelong Personal Health Records in the Pieter van Gorp, Marco Comuzzi Cloud 373 2012 Service differentiation in spare parts supply through dedicated stocks E.M. Alvarez, M.C. van der Heijden, W.H.M. Zijm 372 2012 Spare parts inventory pooling: how to share the benefits? Frank Karsten, Rob Basten

Nr. Year Title Author(s) 371 2012 Condition based spare parts supply X. Lin, R.J.I. Basten, A.A. Kranenburg, G.J. van Houtum 370 2012 Using Simulation to Assess the Opportunities of Dynamic Martijn Mes Waste Collection 369 2012 Aggregate overhaul and supply chain planning for rotables J. Arts, S.D. Flapper, K. Vernooij 368 2012 Operating Room Rescheduling J.T. van Essen, J.L. Hurink, W. Hartholt, B.J. van den Akker 367 2011 Switching Transport Modes to Meet Voluntary Carbon Emission Targets Kristel M.R. Hoen, Tarkan Tan, Jan C., Geert-Jan van Houtum 366 2011 On two-echelon inventory systems with Poisson demand and Elisa Alvarez, Matthieu van der Heijden lost sales 365 2011 Minimizing the Waiting Time for Emergency Surgery J.T. van Essen, E.W. Hans, J.L. Hurink, A. Oversberg 364 2012 Vehicle Routing Problem with Stochastic Travel Times Including Soft Time Windows and Service Costs Duygu Tas, Nico Dellaert, Tom van Woensel, Ton de Kok 363 2011 A New Approximate Evaluation Method for Two-Echelon Inventory Systems with Emergency Shipments Erhun Özkan, Geert-Jan van Houtum, Yasemin Serin 362 2011 Approximating Multi-Objective Time-Dependent Optimization Problems Said Dabia, El-Ghazali Talbi, Tom Van Woensel, Ton de Kok 361 2011 Branch and Cut and Price for the Time Dependent Vehicle Routing Problem with Time Windows Said Dabia, Stefan Röpke, Tom Van Woensel, Ton de Kok 360 2011 Analysis of an Assemble-to-Order System with Different Review Periods A.G. Karaarslan, G.P. Kiesmüller, A.G. de Kok 359 2011 Interval Availability Analysis of a Two-Echelon, Multi-Item System Ahmad Al Hanbali, Matthieu van der Heijden 358 2011 Carbon-Optimal and Carbon-Neutral Supply Chains Felipe Caro, Charles J. Corbett, Tarkan Tan, Rob Zuidwijk 357 2011 Generic Planning and Control of Automated Material Handling Systems: Practical Requirements Versus Existing Sameh Haneyah, Henk Zijm, Marco Schutten, Peter Schuur Theory 356 2011 Last time buy decisions for products sold under warranty Matthieu van der Heijden, Bermawi Iskandar 355 2011 Spatial concentration and location dynamics in logistics: the case of a Dutch province Frank P. van den Heuvel, Peter W. de Langen, Karel H. van Donselaar, Jan C. 354 2011 Identification of Employment Concentration Areas Frank P. van den Heuvel, Peter W. de Langen, Karel H. van Donselaar, Jan C. 353 2011 BPMN 2.0 Execution Semantics Formalized as Graph Rewrite Pieter van Gorp, Remco Dijkman Rules: extended version 352 2011 Resource pooling and cost allocation among independent service providers Frank Karsten, Marco Slikker, Geert-Jan van Houtum 351 2011 A Framework for Business Innovation Directions E. Lüftenegger, S. Angelov, P. Grefen 350 2011 The Road to a Business Process Architecture: An Overview of Approaches and their Use 349 2011 Effect of carbon emission regulations on transport mode selection under stochastic demand 348 2011 An improved MIP-based combinatorial approach for a multiskill workforce scheduling problem 347 2011 An approximate approach for the joint problem of level of repair analysis and spare parts stocking 346 2011 Joint optimization of level of repair analysis and spare parts stocks Remco Dijkman, Irene Vanderfeesten, Hajo A. Reijers K.M.R. Hoen, T. Tan, J.C., G.J. van Houtum Murat Firat, Cor Hurkens R.J.I. Basten, M.C. van der Heijden, J.M.J. Schutten R.J.I. Basten, M.C. van der Heijden, J.M.J. Schutten

Nr. Year Title Author(s) 345 2011 Inventory control with manufacturing lead time flexibility Ton G. de Kok 344 2011 Analysis of resource pooling games via a new extension of the Erlang loss function Frank Karsten, Marco Slikker, Geert-Jan van Houtum 343 2011 Vehicle refueling with limited resources Murat Firat, C.A.J. Hurkens, Gerhard J. Woeginger 342 2011 Optimal Inventory Policies with Non-stationary Supply Bilge Atasoy, Refik Güllü, Tarkan Tan Disruptions and Advance Supply Information 341 2011 Redundancy Optimization for Critical Components in High- Availability Capital Goods Kurtulus Baris Öner, Alan Scheller-Wolf, Geert-Jan van Houtum 340 2011 Making Decision Process Knowledge Explicit Using the Product Data Model Razvan Petrusel, Irene Vanderfeesten, Cristina Claudia Dolean, Daniel Mican 339 2010 Analysis of a two-echelon inventory system with two supply Joachim Arts, Gudrun Kiesmüller modes 338 2010 Analysis of the dial-a-ride problem of Hunsaker and Murat Firat, Gerhard J. Woeginger Savelsbergh 335 2010 Attaining stability in multi-skill workforce scheduling Murat Firat, Cor Hurkens 334 2010 Flexible Heuristics Miner (FHM) A.J.M.M. Weijters, J.T.S. Ribeiro 333 2010 An exact approach for relating recovering surgical patient workload to the master surgical schedule P.T. Vanberkel, R.J. Boucherie, E.W. Hans, J.L. Hurink, W.A.M. van Lent, W.H. van Harten 332 2010 Efficiency evaluation for pooling resources in health care Peter T. Vanberkel, Richard J. Boucherie, Erwin W. Hans, Johann L. Hurink, Nelly Litvak 331 2010 The Effect of Workload Constraints in Mathematical M.M. Jansen, A.G. de Kok, I.J.B.F. Adan Programming Models for Production Planning 330 2010 Using pipeline information in a multi-echelon spare parts inventory system Christian Howard, Ingrid Reijnen, Johan Marklund, Tarkan Tan 329 2010 Reducing costs of repairable spare parts supply systems via dynamic scheduling H.G.H. Tiemessen, G.J. van Houtum 328 2010 Identification of Employment Concentration and Specialization Areas: Theory and Application Frank P. van den Heuvel, Peter W. de Langen, Karel H. van Donselaar, Jan C. 327 2010 A combinatorial approach to multi-skill workforce scheduling M. Firat, C. Hurkens 326 2010 Stability in multi-skill workforce scheduling M. Firat, C. Hurkens, A. Laugier 325 2010 Maintenance spare parts planning and control: A framework M.A. Driessen, J.J. Arts, G.J. van for control and agenda for future research Houtum, W.D. Rustenburg, B. Huisman 324 2010 Near-optimal heuristics to set base stock levels in a twoechelon R.J.I. Basten, G.J. van Houtum distribution network 323 2010 Inventory reduction in spare part networks by selective throughput time reduction M.C. van der Heijden, E.M. Alvarez, J.M.J. Schutten 322 2010 The selective use of emergency shipments for servicecontract differentiation E.M. Alvarez, M.C. van der Heijden, W.H.M. Zijm 321 2010 Heuristics for Multi-Item Two-Echelon Spare Parts Inventory Control Problem with Batch Ordering in the Central Engin Topan, Z. Pelin Bayindir, Tarkan Tan Warehouse 320 2010 Preventing or escaping the suppression mechanism: intervention conditions Bob Walrave, Kim E. van Oorschot, A. Georges L. Romme 319 2010 Hospital admission planning to optimize major resources Nico Dellaert, Jully Jeunet utilization under uncertainty 318 2010 Minimal Protocol Adaptors for Interacting Services R. Seguel, R. Eshuis, P. Grefen 317 2010 Teaching Retail Operations in Business and Engineering Schools Tom Van Woensel, Marshall L. Fisher, Jan C.

Nr. Year Title Author(s) 316 2010 Design for Availability: Creating Value for Manufacturers and Customers Lydie P.M. Smets, Geert-Jan van Houtum, Fred Langerak 315 2010 Transforming Process Models: executable rewrite rules Pieter van Gorp, Rik Eshuis versus a formalized Java program 314 2010 Working paper 314 is no longer available ---- 313 2010 A Dynamic Programming Approach to Multi-Objective Time- S. Dabia, T. van Woensel, A.G. de Kok Dependent Capacitated Single Vehicle Routing Problems with Time Windows 312 2010 Tales of a So(u)rcerer: Optimal Sourcing Decisions Under Osman Alp, Tarkan Tan Alternative Capacitated Suppliers and General Cost Structures 311 2010 In-store replenishment procedures for perishable inventory R.A.C.M. Broekmeulen, C.H.M. Bakx in a retail environment with handling costs and storage constraints 310 2010 The state of the art of innovation-driven business models in the financial services industry E. Lüftenegger, S. Angelov, E. van der Linden, P. Grefen 309 2010 Design of Complex Architectures Using a Three Dimension R. Seguel, P. Grefen, R. Eshuis Approach: the CrossWork Case 308 2010 Effect of carbon emission regulations on transport mode selection in supply chains K.M.R. Hoen, T. Tan, J.C., G.J. van Houtum 307 2010 Interaction between intelligent agent strategies for real-time transportation planning Martijn Mes, Matthieu van der Heijden, Peter Schuur 306 2010 Internal Slackening Scoring Methods Marco Slikker, Peter Borm, René van den Brink 305 2010 Vehicle Routing with Traffic Congestion and Drivers' Driving and Working Rules A.L. Kok, E.W. Hans, J.M.J. Schutten, W.H.M. Zijm 304 2010 Practical extensions to the level of repair analysis R.J.I. Basten, M.C. van der Heijden, J.M.J. Schutten 303 2010 Ocean Container Transport: An Underestimated and Critical Jan C., Chung-Yee Lee Link in Global Supply Chain Performance 302 2010 Capacity reservation and utilization for a manufacturer with Y. Boulaksil; J.C. ; T. Tan uncertain capacity and demand 300 2009 Spare parts inventory pooling games F.J.P. Karsten; M. Slikker; G.J. van Houtum 299 2009 Capacity flexibility allocation in an outsourced supply chain Y. Boulaksil, M. Grunow, J.C. with reservation 298 2010 An optimal approach for the joint problem of level of repair analysis and spare parts stocking R.J.I. Basten, M.C. van der Heijden, J.M.J. Schutten 297 2009 Responding to the Lehman Wave: Sales Forecasting and Supply Management during the Credit Crisis Robert Peels, Maximiliano Udenio, Jan C., Marcel Wolfs, Tom Hendrikx 296 2009 An exact approach for relating recovering surgical patient workload to the master surgical schedule 295 2009 An iterative method for the simultaneous optimization of repair decisions and spare parts stocks Peter T. Vanberkel, Richard J. Boucherie, Erwin W. Hans, Johann L. Hurink, Wineke A.M. van Lent, Wim H. van Harten R.J.I. Basten, M.C. van der Heijden, J.M.J. Schutten 294 2009 Fujaba hits the Wall(-e) Pieter van Gorp, Ruben Jubeh, Bernhard Grusie, Anne Keller 293 2009 Implementation of a Healthcare Process in Four Different Workflow Systems R.S. Mans, W.M.P. van der Aalst, N.C. Russell, P.J.M. Bakker 292 2009 Business Process Model Repositories - Framework and Survey Zhiqiang Yan, Remco Dijkman, Paul Grefen 291 2009 Efficient Optimization of the Dual-Index Policy Using Markov Chains Joachim Arts, Marcel van Vuuren, Gudrun Kiesmuller

Nr. Year Title Author(s) 290 2009 Hierarchical Knowledge-Gradient for Sequential Sampling Martijn R.K. Mes; Warren B. Powell; Peter I. Frazier 289 2009 Analyzing combined vehicle routing and break scheduling from a distributed decision making perspective C.M. Meyer; A.L. Kok; H. Kopfer; J.M.J. Schutten 288 2010 Lead time anticipation in Supply Chain Operations Planning Michiel Jansen; Ton G. de Kok; Jan C. 287 2009 Inventory Models with Lateral Transshipments: A Review Colin Paterson; Gudrun Kiesmuller; Ruud Teunter; Kevin Glazebrook 286 2009 Efficiency evaluation for pooling resources in health care P.T. Vanberkel; R.J. Boucherie; E.W. Hans; J.L. Hurink; N. Litvak 285 2009 A Survey of Health Care Models that Encompass Multiple Departments P.T. Vanberkel; R.J. Boucherie; E.W. Hans; J.L. Hurink; N. Litvak 284 2009 Supporting Process Control in Business Collaborations S. Angelov; K. Vidyasankar; J. Vonk; P. Grefen 283 2009 Inventory Control with Partial Batch Ordering O. Alp; W.T. Huh; T. Tan 282 2009 Translating Safe Petri Nets to Statecharts in a Structure- R. Eshuis Preserving Way 281 2009 The link between product data model and process model J.J.C.L. Vogelaar; H.A. Reijers 280 2009 Inventory planning for spare parts networks with delivery I.C. Reijnen; T. Tan; G.J. van Houtum time requirements 279 2009 Co-Evolution of Demand and Supply under Competition B. Vermeulen; A.G. de Kok 278 2010 Toward Meso-level Product-Market Network Indices for B. Vermeulen, A.G. de Kok Strategic Product Selection and (Re)Design Guidelines over the Product Life-Cycle 277 2009 An Efficient Method to Construct Minimal Protocol Adaptors R. Seguel, R. Eshuis, P. Grefen 276 2009 Coordinating Supply Chains: a Bilevel Programming Approach Ton G. de Kok, Gabriella Muratore 275 2009 Inventory redistribution for fashion products under demand G.P. Kiesmuller, S. Minner parameter update 274 2009 Comparing Markov chains: Combining aggregation and A. Busic, I.M.H. Vliegen, A. Scheller-Wolf precedence relations applied to sets of states 273 2009 Separate tools or tool kits: an exploratory study of engineers' I.M.H. Vliegen, P.A.M. Kleingeld, G.J. van preferences Houtum 272 2009 An Exact Solution Procedure for Multi-Item Two-Echelon Spare Parts Inventory Control Problem with Batch Ordering 271 2009 Distributed Decision Making in Combined Vehicle Routing and Break Scheduling 270 2009 Dynamic Programming Algorithm for the Vehicle Routing Problem with Time Windows and EC Social Legislation C.M. Meyer, H. Kopfer, A.L. Kok, M. Schutten A.L. Kok, C.M. Meyer, H. Kopfer, J.M.J. Schutten 269 2009 Similarity of Business Process Models: Metics and Evaluation Remco Dijkman, Marlon Dumas, Boudewijn van Dongen, Reina Kaarik, Jan Mendling 267 2009 Vehicle routing under time-dependent travel times: the impact of congestion avoidance A.L. Kok, E.W. Hans, J.M.J. Schutten 266 2009 Restricted dynamic programming: a flexible framework for solving realistic VRPs Working Papers published before 2009 see: http://beta.ieis.tue.nl J. Gromicho; J.J. van Hoorn; A.L. Kok; J.M.J. Schutten;