Inventory systems in the presence of an electronic market place

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Inventory systems in the presence of an electronic market place

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INVENTORY SYSTEMS IN THE PRESENCE OF AN ELECTRONIC MARKETPLACE BAO JIE NATIONAL UNIVERSITY OF SINGAPORE 2005 INVENTORY SYSTEMS IN THE PRESENCE OF AN ELECTRONIC MARKETPLACE BAO JIE (B.Eng. TSINGHUA UNIVERSITY) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF INDUSTRIAL AND SYSTEMS ENGINEERING NATIONAL UNIVERSITY OF SINGAPORE 2005 Acknowledgement I would like to express my profound gratitude to my supervisors Dr. Lee Loo Hay and Dr. Lee Chulung for their advice and guidance throughout my whole research work. I have learnt from their experience and expertise. I would also give my thanks to Associate Professor Ong Hoon Liong and Dr. Jaruphongsa Wikrom for their helpful suggestion on my research topic. My sincere thanks are conveyed to the National University of Singapore for providing financial aid for my research work. I also wish to thank the Department of Industrial & Systems Engineering for using its facilities, without which it would be impossible for me to complete the work reported in this dissertation. Specially, I wish to thank the ISE Systems Modeling and Analysis Laboratory technician Ms. Tan Swee -i- Lan for her kind assistance. And to members of the ISE Department, who have provided their help and contributed in one way or another towards the fulfillment of my research work. I am grateful for the hearty support from my family and Miss Liu Rujing. Their understanding, patience, confidence and encouragement have been a great source of power and motivation for me to pursue my Ph.D. Last but not the least, I thank all my friends in the ISE Department: Li Dong, Liu Shubin, Tang Yong, Yang Guiyu, to name a few, for the joy they have brought to me. Specially, I will thank my colleagues in this SMAL Lab: Cao Yi, Chen Gang, Dai Yuanshun, Han Yongbin, Liu Guoquan, Liu Na, Pan Xiajun, Wang Yang, Wang Wei, Wu Xue, Xiang Yanping, Xu Songsong, Yao Qiong, Zeng Yifeng and Zhou Runrun, for the happy hours spent with them. - ii - Content ACKNOWLEDGEMENT . I CONTENT III SUMMARY VII LIST OF TABLES . IX LIST OF FIGURES .X NOMENCLATURE XII CHAPTER INTRODUCTION 1.1 BACKGROUND 1.2 SUPPLY CHAIN MANAGEMENT AND E-BUSINESS 1.2.1 Supply chain management in E-Business . 1.2.2 Electronic marketplace 1.3 SCOPE OF THIS STUDY . 1.3.1 Motivation of this study 1.3.2 Inventory control in the presence of electronic marketplace . 1.3.3 Flow of the dissertation . 10 CHAPTER 2.1 LITERATURE REVIEW . 12 E-BUSINESS AND SUPPLY CHAIN MANAGEMENT . 12 2.1.1 E-Business and supply chain management 13 2.1.2 Electronic marketplaces and supply chain management . 14 2.2 ELECTRONIC MARKETPLACE . 15 2.2.1 Classification of different electronic marketplaces 16 2.2.2 Advantages of electronic marketplaces over traditional marketplaces . 17 2.2.3 Pricing mechanism in electronic marketplaces . 18 2.3 INVENTORY CONTROL 19 - iii - 2.3.1 Inventory control and electronic marketplaces 20 2.3.2 Two supply modes inventory systems . 22 2.3.3 Inventory systems for perishable products . 24 2.3.4 Dynamic pricing in the consideration of inventory control . 25 CHAPTER AN INVENTORY SYSTEM IN THE PRESENCE OF AN ELECTRONIC MARKETPLACE . 28 3.1 INTRODUCTION . 29 3.2 DYNAMIC PROGRAMMING MODEL FOR THE INVENTORY SYSTEM IN THE PRESENCE OF AN ELECTRONIC MARKETPLACE . 3.3 3.4 32 OPTIMAL INVENTORY CONTROL POLICY FOR ONE PERIOD LEAD TIME . 37 3.3.1 When S N* +1 ≤ Z N* 41 3.3.2 When S N* +1 > Z N* 47 INVENTORY CONTROL POLICIES FOR MULTIPLE PERIODS LEAD TIME 53 3.4.1 EM policy . 54 3.4.2 Order-up-to policy . 55 3.4.3 Standing order (SO) policy 56 3.4.4 Time dependent (TD) policy . 60 3.5 NUMERICAL EXPERIMENT . 64 3.5.1 Experiment design 65 3.5.2 Cost savings from the electronic marketplace . 66 3.5.3 Cost under the proposed policies and that under the optimal policy . 70 3.5.4 Impacts of system parameters on the cost of the proposed policies . 71 3.6 SUMMARY 75 CHAPTER IMPACTS OF AN ELECTRONIC MARKETPLACE ON AN INVENTORY SYSTEM WITH MULTIPLE INDEPENDENT RETAILERS 77 4.1 INTRODUCTION . 78 4.2 MODELING ASSUMPTIONS AND NOTATIONS 79 4.3 STATIC PRICING MODEL 82 - iv - 4.3.1 Retailers’ expected one period cost and the MM’s profit 84 4.3.2 Retailers’ inventory control policy and the MM’s optimal commission charge 85 4.4 DYNAMIC PRICING MODEL 86 4.5 NUMERICAL EXPERIMENT . 89 4.5.1 Experiment design 89 4.5.2 Inventory cost saving of the aggregated supply chain and retailers’ cost savings from the electronic marketplace under the static pricing mechanism 90 4.5.3 Static and dynamic pricing mechanisms in the electronic marketplace . 93 4.6 NON-IDENTICAL RETAILERS AND IRRATIONAL BIDDING IN STATIC PRICING MECHANISM ELECTRONIC MARKETPLACE . 95 4.6.1 Non-identical retailers . 96 4.6.2 Over bidding and irrational bidding 98 4.7 SUMMARY 102 CHAPTER THE VALUE OF AN ELECTRONIC MARKETPLACE IN A PERISHABLE PRODUCT INVENTORY SYSTEM WITH AUTO-CORRELATED DEMAND . 104 5.1 INTRODUCTION . 105 5.2 MATHEMATICAL MODEL FOR THE ELECTRONIC MARKETPLACE AND ORDER QUANTITY . 106 5.3 OPTIMAL BIDDING DECISION IN THE ELECTRONIC MARKETPLACE AND ORDER QUANTITY FROM THE SUPPLIER 110 5.3.1 Optimal bidding decision in the electronic marketplace 111 5.3.2 Optimal Order quantity from the supplier . 114 5.4 NUMERICAL EXPERIMENT . 117 5.4.1 Experiment design 117 5.4.2 Impact of the demand process on cost savings from the electronic marketplace . 119 5.5 SUMMARY 126 CHAPTER SUMMARY AND CONCLUSION . 127 6.1 MAIN CONTRIBUTIONS . 128 6.2 FUTURE RESEARCH . 130 -v- REFERENCE . 133 APPENDIX A. RETAILER’S OPTIMAL ORDER QUANTITY WITHOUT EM 145 - vi - Summary Inventory control is one of the most important problems within the filed of supply chain management. This study investigates inventory systems in the presence of an electronic marketplace (EM), which represent a new distribution channel created by the fast development of E-Business. A periodic review inventory system in the presence of an EM is investigated first. In this system, regular orders can be issued to the supplier and emergency orders can be sourced from the EM at additional cost. Furthermore, excess inventory can be sold to the EM. When the order lead time from the supplier is one period, the optimal inventory control policy is developed from a dynamic programming model, which is characterized by three threshold inventory levels. When the order lead time from the supplier is longer than one period, three heuristic ordering policies are proposed to compute the order quantity from the supplier because of the computational difficulty of developing the optimal policy from the dynamic programming model. The first policy is a simple order-up-to policy. The second policy employs a constant order quantity in all periods, and the third policy solves a cost minimizing problem in each period to determine the order quantity. The second model investigated in this study considers an inventory system comprising multiple independent retailers and one EM. Retailers replenish products from their suppliers and can also purchase and sell products in the EM, which is operated by an independent market maker. Through extensive numerical studies, it is found that the inventory cost of the aggregated supply chain, which comprises all vii retailers decreases substantially from the EM and so does each retailer’s cost. These cost savings become greater when the retailers’ order lead time, demand variability and the number of retailers in the EM increase. These trends also apply to the market maker’s profit. Retailers’ total cost saving is important because this will attract them to participate into the EM, which in turn leads to the inventory cost savings of the aggregated supply chain. Finally, this study also investigates a periodic review inventory system for a perishable product in the presence of an EM. In this system, the retailer receives a fixed quantity of order from the supplier in each period. The retailer can also bid in the EM for the quantity she wants to purchase and/or sell as well as the price to offer. The supply and demand quantities in the EM depend on the prices offered. Demand from customers in different periods is assumed to be auto-correlated. The optimal bidding decision in the EM and order quantity from the supplier are obtained. It is found that when demands fluctuate greatly in different periods and there are strong correlations among demands in different periods, great cost savings can be obtained by purchasing and selling products in the EM to adjust the inventory level. viii Chapter Conclusion and future work correlations among demands in different periods, great cost savings can be obtained from the EM. The assumption that the product is perishable with the lifetime of one period may cause some loss of generality for the theoretic results obtained in Section 5.3. For products with the lifetime of longer than one period, still the bidding decision proposed in this study can be employed as a heuristic solution. Moreover, the insights obtained from this numerical experiment can also apply to these products. 6.2 Future research Inventory control policy for a single retailer For the inventory system studied in Chapter 3, when the order lead time becomes long, the proposed TD policy will becomes computationally inefficient because it needs to solve a cost minimizing problem in every period to determine the order quantity. This makes the TD policy difficult to implement. Therefore, it is valuable to develop some policies that are both efficient and can lead to low cost. Another direction for future research is to develop the retailer’s inventory control policy when the EM lead time is non-zero. The transaction prices in EM are assumed to be constant in the inventory system studied in Chapter 3. This assumption can be released so that the system - 130 - Chapter Conclusion and future work becomes more realistic. To model the stochastic price in the EM, knowledge from economics and marketing researches may be necessary. Impacts of an EM on an inventory system with multiple retailer For the inventory system studied in Chapter 4, it is valuable to study: what kind of retailers can benefit more from the EM. For example, those retailers with longer order lead time from the supplier obtain more cost savings than those with shorter lead time from the supplier? Furthermore, in the system studied in Chapter 4, it is assumed that each retailer makes their bidding decisions only to minimize her own cost. However, the retailers may play bidding games in the EM with each other. Therefore, it remains to explore that: is there a Nash equilibrium of this bidding game and how will it affect the cost savings from the EM. Furthermore, when the MM determines the commission charges in the EM, she may also play a Stackelberg with the retailers, where the MM is the leader and all the retailers are the follower. To explore the effects of this Stackelberg game on the cost savings from the EM is valuable. Inventory system for perishable products For the perishable product inventory system studied in Chapter 5, it is assumed that the lifetime of the product is one period. For general perishable products, whose lifetime are longer than one period, the theoretic results obtain in Chapter may not be - 131 - Chapter Conclusion and future work applicable any more. Therefore, the inventory control policy for such products remains to be studied. - 132 - Reference Reference (The) Economist, 2000. Shopping Around the Web: A Survey of e-Commerce, 26 February, 2000. Anand, K.S., R. Aron, 2003. Group-buying on the Web: A comparison of price discovery mechanisms. Management Science, 49(11), 1547-1564. Ariba, 2000. B2B Marketplaces in the New Economy. Research Report, downloadable at http://www.ariba.com/pdf/B2B_Mkts_white_paper.pdf. Arrow, K.A., T.E. Harris and J. Marschak, 1951. Optimal Inventory Policy. Econometrica 19, 250-272. Bakos, J.Y., 1991. A strategic analysis of EM. MIS Quarterly 15 (4), 295-310. Bakos, J.Y., 1997. Reducing buyer search costs: implications for Electronic Marketplaces. Management Science, 43(12), 1676-1692. Bakos, J.Y., 1998. The emerging role of Electronic Marketplaces on the Internet. Communications of the ACM 41 (8), 35-42. Bao, J., C. Lee and L.H. Lee, 2005. The value of an electronic marketplace in a perishable product inventory system with auto-correlated demand. Working paper, - 133 - Reference submitted to OR Spectrum. Department of Industrial & Systems Engineering, National University of Singapore. Barankin, E.W., 1961. A delivery-lag inventory model with an emergency provision. Naval Research Logistics Quarterly, 8, 285-311. Beil, D.R. and L.M. Wein, 2003. An inverse-optimization-based auction mechanism to support a multiattribute RFQ process. Management Science, 49(11), 1529-1546. Bitran, G. and S.V. Mondschein, 1997. Periodic pricing of seasonal products in retailing. Management Science, 43(1), 64-79. Bitran, G., R. Caldentey and S.V. Mondschein, 1998. Coordinating clearance markdown sales of seasonal products in retail chains. Operations Research, 46(5), 609624. Boyd, E.A. and I. Bilegan, 2003. Revenue management and ecommerce. Management Science, 49(10), 1363-1386. Bradley III, D.B. and D. Peters, 1997. Electronic Marketplaces: Collaborate If You Want To Compete. Proceedings of 1997 USASBE Annual National Conference Entrepreneurship: The Engine of Global Economic Development San Francisco, California 21-24 June 1997. Carr, S.M., 2003. Note on online auctions with costly bid evaluation. Management Science, 49(11), 1521-1528. - 134 - Reference Chiang, C., 2001. A note on optimal policies for a periodic inventory system with emergency orders, Computers and Operations Research, 28, 93-103. Chiang, C., 2003. Optimal replenishment for a periodic review inventory system with two supply modes, European Journal of Operational Research, 149, 229-244. Chiang, C. and G.J. Gutierrez, 1996. A periodic review inventory system with two supply modes. European Journal of Operational Research, 94, 527-547. Chiang, C. and G.J. Gutierrez, 1998. Optimal control policies for a periodic review inventory system with emergency orders. Naval Research Logistics, 45, 187-204. Dai, Q. and R.J. Kauffman, 2001. Business Models For Internet Based E-Procurement Systems and B2B EM: An Exploratory Assessment. Proceedings of the 34th Annual Hawaii International Conference on Systems Science, 3-6 Jan. 2001 Daniel, K.H., 1962. A delivery-lag inventory model with emergency. In Multistage Inventory Models and Techniques, Edited by H.E. Scarf, D.M. Gilford, M.W. Shelly. Stanford University Press, Stanford, CA. Diamond, P.A., 1971. A model of price adjustment. Journal of Economic Theory, 3, 156-168. Dong, L. and E. Durbin. 2001. Markets for surplus components with a strategic supplier. Working paper, Olin School of Business, Washington University, St. Louis, MO. - 135 - Reference Elmaghraby, W., A. Gulcu and P. Keskinocak, 2002. Optimal markdown mechanisms in the presence of rational customers with multi-unit demands. Georgia Institute of Technology, Working paper. Elmaghraby, W. and P. Keskinocak, 2003. Dynamic pricing in the presence of inventory considerations: Research overview, current practices and future directions. Management Science, 49(10), 1287-1309. Federgruen, A. and A. Heching, 1999. Combined pricing and inventory control under uncertainty. Operations Research, 47(3), 454-475. Feng, Y. and G. Gallego, 1995. Optimal starting times for end-of-season sales and optimal stopping times for promotional fares. Management Science, 41(8), 1371-1391. Fukuda, Y., 1964. Optimal policies for the inventory problem with negotiable leadtime. Management Science, 10(4), 690–708. Gallego, G. and G.J. van Ryzin, 1994. Optimal dynamic pricing of inventories with stochastic demand over finite horizon. Management Science, 40(8), 999–1020. Gastwirth, J.L., 1976. HTUOn Probabilistic Models of Consumer Search for InformationUTH. HTUThe Quarterly Journal of EconomicsUTH, 90 (1), 38-50. Geoffrion, A.M. and R. Krishnan, 2001. Prospects for operations research in the EBusiness era. Interfaces 31(2), 6–36. - 136 - Reference Geoffrion, A.M. and R. Krishnan, 2003a. E-Business and management science: mutual impacts (Part of 2). Management Science, 49(10), 1275-1286. Geoffrion, A.M. and R. Krishnan, 2003b. E-Business and management science: mutual impacts (Part of 2). Management Science, 49(11), 1445-1456. Goyal, S.K. and B.C. Giri, 2001. Recent trends in modelling of deteriorating inventory. European Journal of Operational Research, 134, 1-16. Graves, S.C., D.B. Kletter and W.B. Hetzel, 1998. A dynamic model for requirements planning with application to supply chain optimization. Operations Research, 46(S3), S35-S49. Graves, S.C., H.C. Meal, S. Dasu, and Y. Qiu, 1986. Two-stage production planning in a dynamic environment. In Multi-Stage Production Planning and Inventory Control, Edited by S. Axsa¨ter, C. Schneeweiss and E. Silver. Lecture Notes in Economics and Mathematical Systems, Springer-Verlag, Berlin, 266, 9–43. Graves, S.C., R. Kan, and P.H. Zipkin, 1993. Logistics of Production and Inventory— Handbook of OR/MS. North-Holland, Amsterdam, The Netherlands. Grieger, M., 2003. Electronic marketplaces: A literature review and a call for supply chain management research. European Journal of Operational Research 144, 280-294. Gross, D. and A. Soriano, 1972. On the economic application of airlift to product distribution and its impact on inventory levels. Naval Research Logistics, 19, 501–507. - 137 - Reference Guttman, R.H., A.G. Moukas and P. Maes, 1998. Agent-mediated electronic commerce: A survey. Knowledge Engineering Review, 13(2), 147-159. Heath, D.C. and P.L. Jackson, 1994. Modeling the Evolution of Demand Forecasts with Application to Safety Stock Analysis in Production/Distribution Systems. IIE Transactions, 26(3), 17-30. Henderson, D.R., 1984. Electronic marketing in principle and practice. American Journal of Agricultural Economics 66 (5), 848–853. Johansen, S.G. and A. Thorstenson, 1998. An inventory model with Poisson demands and emergency orders. International Journal of Production Economics, 56–57, pp. 275289. Johnson, C., K. Delhagen and A. Dash, 2002. US e-commerce: The next five years. Forrester Report, August 27. Kafka, S.J., B.D. Temkin, M.R. Sanders, J. Sharrard and T.O. Brown, 2000. EMarketplaces boost B2B trade. Forrester Research Report, February 2000. Kahn, J.A., 1987. Inventories and the Volatility of Production. The American Economic Review, 77(4), 667-679. Kaplan, S. and M. Sawhney, 2000. E-hubs: The New B2B Marketplaces. Harvard Business Review (May/June), 97-104. - 138 - Reference Keenan, F. and S. Ante. 2002. The new teamwork. Business Week, February 18. Keskinnocak, P., R. Goodwin, F. Wu, R. Akkiraju and S. Murthy, 2001. Decision Support for Managing an Electronic Supply Chain. Electronic Commerce Research, 1, 15–31. Keskinocak, P. and S. Tayur, 2001. Quantitative analysis for Internet-Enabled Supply Chains. Interfaces 31(2), 70-89. Kleindorfer, P.R. and D.J. Wu, 2003. Integrating long-term and short-term contracting via business-to-business exchanges for capital-intensive industries. Managemet Science, 49(11), 1597-1615. Lazear, E.P., 1986. Retail pricing and clearance sales. The American Economic Review, 76(1), 14—32. Lee, C., L.H. Lee and J. Bao, 2003. An inventory model in the presence of electronic marketplace. 5PthP Euro/Informs Joint International Meeting, Istanbul, Turkey, July 2003. Lee, H.L., K.C. So and C.S. Tang, 2000. The Value of Information Sharing in a TwoLevel Supply Chain. Management Science, 46(5), 626–643. Lee, H.L. and S. Whang, 2002. The impact of the secondary market on the supply chain, Management Science, 48(6), 719-731. - 139 - Reference Lee, H.L., V. Padmanabhan, S. Whang, 1997a. Information distortion in a supply chain: The bullwhip effect. Management Science, 43(4), 546–558. Lee, H.L., V. Padmanabhan, S. Whang, 1997b. The bullwhip effect in a supply chain. Sloan Management Review, 38 (Spring), 93–102. Lee, L.H., C. Lee and J. Bao, 2005a. Inventory control in the presence of an electronic marketplace. To appear in European Journal of Operational Research. Lee, L.H., C. Lee and J. Bao, 2005b. The impacts of an electronic marketplace on an inventory system with multiple independent retailers. Working paper, submitted to European Journal of Operational Research. Department of Industrial & Systems Engineering, National University of Singapore. Lipis, L.J., R. Villars, D. Byron and V. Turner, 2000. Putting Markets into Place: An eMarketplace Definition and Forecast. (Downloadable from website http://www.idc.com). Magretta, J., 1998. The power of virtual integration: An interview with Dell Computer’s Michael Dell. Harvard Business Review, 16(2), 73-84. McCoy, J.H. and M.E. Sarhan, 1988. Livestock and Meat Marketing. AVI Book. Miller, B.L., 1986. Scarf's State Reduction Method, Flexibility, and a Dependent Demand Inventory Model. Operations Research, 34(1), 83-90. - 140 - Reference Moinzadeh, K. and C.P. Schmidt, 1991. An (S-1, S) inventory system with emergency orders. Operations Research, 39(2), 308–321. Moinzadeh, K. and S. Nahmias, 1998. A continuous review model for an inventory system with two supply modes. Management Science, 34(6), 761–773. Mueller, R.A.E., 2000. Emergent E-Commerce in Agriculture. Agriculture Issues Center, AIC Issues Brief (14), December. Murthi, B.P.S. and S. Sarkar, 2003. The role of the management sciences in research on personalization. Management Science, 49(10), 1344–1362. Nahmias, S., 1982. Perishable inventory theory: A review. Operations Research, 30(4), 680-708. Neuts, M.F., 1964. An inventory model with optional lag time. Journal of SIAM, 12(1), 179–185. Padmanabhan, B. and A. Tuzhilin, 2003. On the use of optimization for data mining: Theoretical interactions and eCRM opportunities. Management Science, 49(10), 1327– 1343. Peleg, B., H.L. Lee and W.H. Hausman, 2002. Short-term e-procurement strategies versus long-term contract. Production and Operations Management, 11(4), 458-479. - 141 - Reference Pinker, E.J., A. Seidmann and Y. Vakrat, 2003. Managing online auctions: Current business and research issues. Management Science, 49(11), 1454–1484. Raafat, F., 1991. Survey of literature on continuously deteriorating inventory models. Journal of Operational Research Society, 42(1), 27-37. Rosenshine, M. and D. Obee, 1976 Analysis of a standing order inventory system with emergency orders. Operations Research, 24(6), 1143-1155. Rothschild, M., 1974. Searching for the lowest price when the distribution price is unknown. Journal of Political Economy, 82, 689-711. Salop, S. and J.E. Stiglitz, 1982. The theory of sales: a simple model of equilibrium price dispersion with identical agents. American Economic Review, December 1982, 1121-1130. Schmid, B., R. Grutter, S. Schmid-Isler, K. Stanoevska and P. Stahler, 1998. Ein Glossar fur die NetAcademy (1) Institute for Media and Communications Management, University of St. Gallen, March. Segev, A., J. Gebauer and F. Farber, 1999. Internet-based Electronic Markets. EM Electronic Markets, (3), 138-146. Smith, B.C., D.P. Gu¨nther, B.V. Rao and R.M. Ratliff, 2001. E-commerce and Operations Research in Airline Planning, Marketing, and Distribution. Interfaces, 31(2), 37-55. - 142 - Reference Snir, E.M. and L.M. Hitt, 2003. Costly bidding in online markets for IT services. Management Science, 49(11), 1504–1520. Spann, M. and B. Skiera, 2003. Internet-based virtual stock markets for business forecasting. Management Science, 49(10), 1310–1326. Stigler, G., 1961. The economics of information. Journal of Political Economy, 69, 213-225. Swaminathan, J.M. and S.R. Tayur, 2003. Models for Supply Chains in E-Business, Management Science, 49(10), 1387–1406. Tagaras, G. and D. Vlachos, 2001. A Periodic review inventory system with Emergency Replenishment. Management Science, 47(3), 415-429. Thomas, D.J. and P.M. Griffin, 1996. Coordinated Supply Chain Management. European Journal of Operational Research, 94(1), 1-15. Thowsen, G.T., 1975. A dynamic nonstationary inventory problem for a price/quantity setting firm. Naval Research Logistics Quarterly, 22, 461—476. Van Hoek, R., 2001. E-supply chain—virtually non-existing. Supply chain management: An International Journal, (1), 21-28. Veinott, A.F., Jr., 1966. The status of mathematical inventory theory, Management Science, 12(11), 745–777. - 143 - Reference Whittemore, A.S. and S.C. Saunders, 1977. Optimal inventory under stochastic demand with two supply options. SIAM Journal on Applied Mathematics, 32(2), 293– 305. Zabel, E., 1970. Monopoly and uncertainty. The Review of Economic Studies, 37(2), 205-219. - 144 - Appendix A Appendix A. Retailer’s optimal order quantity without EM The retailer’s problem of determining the order quantity is formulated as Pa.3. Pa.3. N Min : M ( I ) = ∑ E∧ [ Lk ( I )] I ≥0 k =1 Dk −1 ∧ Because Lk ( I ) is convex with respect to I for any Dk −1 , M (I ) is convex with respect to I . Thus, a simple search algorithm can be applied to obtain the optimal I . - 145 - [...]... revealing the impacts of E-Business on supply chain management and explore how companies can make use of the opportunities provided by E-Business to improve their supply chain management In the next section, an introduction to supply chain management in EBusiness is provided 1.2 Supply chain management and E-Business Supply chain management spans from product design, material procurement, production, inventory, ... -8- Chapter 1 Introduction failures and so on The main difficulty in inventory control is to tradeoff between the costs of maintaining high and low inventory levels Maintaining high inventory level could effectively buffer variability and provide high customer service level but will lead to high inventory holding costs On the other hand, maintaining insufficient inventories will harm customer service... use of EMs to improve inventory control 1.3.2 Inventory control in the presence of electronic marketplace EMs provide companies more procurement and distribution options by providing abundant supply and demand information Keskinocak and Tayur (2001) classified information gathered from EMs into three categories: • E-orders: demand posted online by new customers; • E -inventory: other companies’ inventory. .. review supply chain management in the presence of EMs because this study investigates inventory control problems in the presence of an EM 2.1.1 E-Business and supply chain management Geoffrion and Krishnan (2003a) classified the impacts of E-Business on supply chain management to be two levels At the lower level, E-Businesses provide enriched information, based on which companies can improve their current... market The authors obtained the equilibrium price in the secondary market and the optimal inventory levels to choose for each reseller in both periods The authors found that the introduction of the secondary market may not always increase sales of the supplier, however, resellers can always obtain cost savings from the secondary market Dong and Durbin (2001) extended the model of Lee and Whang (2002)... supply and demand queries and recommend trades for its participants It also offers auction services to finish final transactions This agent-based decision support system is currently implemented in an EM of an European paper trading company 2.3 Inventory control Inventory control is one of the most classical problems within the area of supply chain management Researches of inventory control can be dated... advantages of their current supply chains and new channels so that they can manage the material and information flows in both channels properly Supply chain management in E-Business is a vast topic Thus, this study does not intend to be a comprehensive one Instead, this study focuses on one of the supply chain problems, inventory control, in the presence of an EM, which is a new distribution channel created... system, the retailer receives a fixed quantity of order from the supplier in each period The retailer can also bid in the EM for the quantity she wants to purchase and/or sell as well as the price to offer The supply and demand quantities in the EM depend on the prices offered Demand from customers in different periods is assumed to be auto-correlated The impacts of different demand processes on the cost... posted online; • E-capacity: other companies’ capacity posted on the web The information gathered from EMs can help companies make more informed decisions to improve their inventory control For example, when the demand from customers is low, companies may choose to sell some of their excess inventories through an EM to satisfy E-orders instead of carrying them and bear high inventory holding cost Similarly,... of this study 1.3.3 Flow of the dissertation This dissertation contains 6 chapters In Chapter 2, literatures related to this study will be reviewed The topics covered in the literature review include: supply chain management and E-Business, electronic marketplaces, inventory systems, etc In Chapter 3, a single level periodic review inventory system in the presence of an EM is investigated, where a retailer . INVENTORY SYSTEMS IN THE PRESENCE OF AN ELECTRONIC MARKETPLACE BAO JIE NATIONAL UNIVERSITY OF SINGAPORE 2005 INVENTORY SYSTEMS IN THE PRESENCE OF AN ELECTRONIC MARKETPLACE. of inventory control 25 CHAPTER 3 AN INVENTORY SYSTEM IN THE PRESENCE OF AN ELECTRONIC MARKETPLACE 28 3.1 INTRODUCTION 29 3.2 DYNAMIC PROGRAMMING MODEL FOR THE INVENTORY SYSTEM IN THE PRESENCE. Classification of different electronic marketplaces 16 2.2.2 Advantages of electronic marketplaces over traditional marketplaces 17 2.2.3 Pricing mechanism in electronic marketplaces 18 2.3 INVENTORY

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  • Acknowledgement

  • Chapter 1 Introduction

    • 1.1 Background

    • 1.2 Supply chain management and E-Business

      • 1.2.1 Supply chain management in E-Business

      • 1.2.2 Electronic marketplace

      • 1.3 Scope of this study

        • 1.3.1 Motivation of this study

        • 1.3.2 Inventory control in the presence of electronic market

        • 1.3.3 Flow of the dissertation

        • Chapter 2 Literature review

          • 2.1 E-Business and supply chain management

            • 2.1.1 E-Business and supply chain management

            • 2.1.2 Electronic marketplaces and supply chain management

            • 2.2 Electronic marketplace

              • 2.2.1 Classification of different electronic marketplaces

              • 2.2.2 Advantages of electronic marketplaces over traditional

              • 2.2.3 Pricing mechanism in electronic marketplaces

              • 2.3 Inventory control

                • 2.3.1 Inventory control and electronic marketplaces

                • 2.3.2 Two supply modes inventory systems

                • 2.3.3 Inventory systems for perishable products

                • 2.3.4 Dynamic pricing in the consideration of inventory cont

                • Chapter 3 An inventory system in the presence of an electron

                  • 3.1 Introduction

                  • 3.2 Dynamic programming model for the inventory system in th

                  • 3.3 Optimal inventory control policy for one period lead tim

                    • 3.3.1 When

                    • 3.3.2 When

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