考虑行为因素的周期性盘点库存系统运作研究
|
摘要
本论文研究考虑行为因素的周期性盘点库存系统,包括s形效用单节点库存系统和单分销商多零售商库存系统。作为预备知识,还研究了连续需求库存系统最优策略的计算。
对连续需求单节点库存系统,在离散网格的基础上建立基于数值积分和线性插值的算法以计算近似最优策略,分别构造近似最优策略成本上界和最优策略成本下界的误差估计,并证明当离散网格格点间距趋于零时近似最优策略收敛至最优策略。
对S形效用单节点库存系统,分别考察指数型S形效用和一般S形效用两种情形。单峰性在对这两种情形进行理论分析时都具有重要作用。对指数型S形效用单期问题,可证明最优策略为基于初始库存水平的订达策略,其最优订达库存水平可通过搜索得到,且最优效用为单峰函数。对指数型S形效用多期问题,若需求服从对数凹分布,则可建立动态规划算法求解最优策略。对一般S形效用单期问题,若需求服从指数分布,则可证明最优策略为基于初始库存水平的订达策略,最优订达库存水平可通过搜索得到,且最优效用为单峰函数；若需求服从一般分布,则在数值算例基础上为后续研究提出若干猜想。数值算例表明,在S形效用库存系统的运作管理中,收益预期和由收益预期带来的规避风险倾向占据主导地位,而损失预期和由损失预期带来的追逐风险倾向居于次要地位。
对单分销商多零售商库存系统,本论文将各种企业运作实例归纳为六种运作模式逐一建模,分别建立近似动态规划算法计算系统成本,并以数值算例比较不同运作模式下的系统绩效。计算结果表明,系统各节点只关注自身利益时的无序竞争行为严重损害库存系统整体利益,寄希望于单纯的信息共享来改善系统绩效并不现实,还需要通过合理的分配规则等多种方式来协调节点的行为。
本论文所获结果有助于洞见管理者行为因素对库存系统运作管理的影响,为进一步设计应对机制以减弱甚至消除这种影响、最终达到改善库存系统运作管理绩效的目的奠定基础。
This thesis investigates operations management of periodical inventory systems with considering impact of decision behaviors. Inventory system with S-shaped util-ity and single distributor multi-retailer inventory system are considered, respectively. Besides, computing optimal policy for inventory system with continuous demand is considered as a preliminary.
For inventory system with continuous demand, an algorithm, in which numerical integral and linear interpolation are used, is constructed on discretized grid for com-puting near optimal policy. Upper bound of cost of the near optimal policy as well as lower bound of optimal cost are estimated then. The near optimal policy is proved to converge to the optimal policy as scale of the grid tends to zero.
For inventory system with S-shaped utility, exponential-type S-shaped utility is first considered and then general S-shaped utility. Unimodality plays an important role in analysis. For a single period problem with exponential-type S-shaped utility, a state-dependent order-up-to policy with order-up-to levels found by searching is op-timal, and the optimal expected utility is unimodal. For a multi-period problem with exponential-type S-shaped utility, if demand follows log-concave distribution, a dy-namic programming algorithm can be constructed to obtain optimal policy. For a single period problem with general S-shaped utility, if demand follows exponential distribu-tion, a state-dependent order-up-to policy with order-up-to levels found by searching is optimal, and the optimal expected utility is unimodal, while if demand follows a general distribution, some conjectures on optimal policy are proposed. Numerical ex-amples reveal that expectation on gains and risk-aversion due to gains dominate the operations management of inventory system with S-shaped utility.
For single distributor multi-retailer inventory system, six operations scenarios are categorized, and approximation dynamic programming algorithms for all scenar-ios each are developed to obtain system cost. Numerical examples show that irregu- lar competition among retailers due to self-interesting reduces whole system interest sharply, and that one can hardly improve system performance only by sharing informa-tion without coordinating system members by some means such as, e.g., an appropriate allocating rule.
Results from this thesis provide insights on impact of managers'behaviors on operations management of inventory system, which help the managers design mech-anisms for reducing disadvantage of bounded rationality and improve performance of inventory system.
对连续需求单节点库存系统,在离散网格的基础上建立基于数值积分和线性插值的算法以计算近似最优策略,分别构造近似最优策略成本上界和最优策略成本下界的误差估计,并证明当离散网格格点间距趋于零时近似最优策略收敛至最优策略。
对S形效用单节点库存系统,分别考察指数型S形效用和一般S形效用两种情形。单峰性在对这两种情形进行理论分析时都具有重要作用。对指数型S形效用单期问题,可证明最优策略为基于初始库存水平的订达策略,其最优订达库存水平可通过搜索得到,且最优效用为单峰函数。对指数型S形效用多期问题,若需求服从对数凹分布,则可建立动态规划算法求解最优策略。对一般S形效用单期问题,若需求服从指数分布,则可证明最优策略为基于初始库存水平的订达策略,最优订达库存水平可通过搜索得到,且最优效用为单峰函数；若需求服从一般分布,则在数值算例基础上为后续研究提出若干猜想。数值算例表明,在S形效用库存系统的运作管理中,收益预期和由收益预期带来的规避风险倾向占据主导地位,而损失预期和由损失预期带来的追逐风险倾向居于次要地位。
对单分销商多零售商库存系统,本论文将各种企业运作实例归纳为六种运作模式逐一建模,分别建立近似动态规划算法计算系统成本,并以数值算例比较不同运作模式下的系统绩效。计算结果表明,系统各节点只关注自身利益时的无序竞争行为严重损害库存系统整体利益,寄希望于单纯的信息共享来改善系统绩效并不现实,还需要通过合理的分配规则等多种方式来协调节点的行为。
本论文所获结果有助于洞见管理者行为因素对库存系统运作管理的影响,为进一步设计应对机制以减弱甚至消除这种影响、最终达到改善库存系统运作管理绩效的目的奠定基础。
This thesis investigates operations management of periodical inventory systems with considering impact of decision behaviors. Inventory system with S-shaped util-ity and single distributor multi-retailer inventory system are considered, respectively. Besides, computing optimal policy for inventory system with continuous demand is considered as a preliminary.
For inventory system with continuous demand, an algorithm, in which numerical integral and linear interpolation are used, is constructed on discretized grid for com-puting near optimal policy. Upper bound of cost of the near optimal policy as well as lower bound of optimal cost are estimated then. The near optimal policy is proved to converge to the optimal policy as scale of the grid tends to zero.
For inventory system with S-shaped utility, exponential-type S-shaped utility is first considered and then general S-shaped utility. Unimodality plays an important role in analysis. For a single period problem with exponential-type S-shaped utility, a state-dependent order-up-to policy with order-up-to levels found by searching is op-timal, and the optimal expected utility is unimodal. For a multi-period problem with exponential-type S-shaped utility, if demand follows log-concave distribution, a dy-namic programming algorithm can be constructed to obtain optimal policy. For a single period problem with general S-shaped utility, if demand follows exponential distribu-tion, a state-dependent order-up-to policy with order-up-to levels found by searching is optimal, and the optimal expected utility is unimodal, while if demand follows a general distribution, some conjectures on optimal policy are proposed. Numerical ex-amples reveal that expectation on gains and risk-aversion due to gains dominate the operations management of inventory system with S-shaped utility.
For single distributor multi-retailer inventory system, six operations scenarios are categorized, and approximation dynamic programming algorithms for all scenar-ios each are developed to obtain system cost. Numerical examples show that irregu- lar competition among retailers due to self-interesting reduces whole system interest sharply, and that one can hardly improve system performance only by sharing informa-tion without coordinating system members by some means such as, e.g., an appropriate allocating rule.
Results from this thesis provide insights on impact of managers'behaviors on operations management of inventory system, which help the managers design mech-anisms for reducing disadvantage of bounded rationality and improve performance of inventory system.
引文
[1]中华人民共和国国家发展和改革委员会,中华人民共和国国家统计局,中国物流与采购联合会.2009年全国物流运行情况通报.北京,2010.
[2]中华人民共和国国家发展和改革委员会.物流业调整和振兴规划.北京,2009.
[3]中华人民共和国第十届全国人民代表大会第四次会议.中华人民共和国国民经济和社会发展第十一个五年规划纲要.北京,2006.
[4]宋则.降低我国物流成本的思路.中国社会科学院院报,2005-11-8：3.
[5]赵晓波,黄四明.库存管理.北京：清华大学出版社,2008.
[6]Zipkin P H. Foundations of Inventory Management. Boston:McGraw-Hill,2000.
[7]Harris F W. How Many Parts to Make at Once. Factory, The Magazine of Management, 1913,10:135-136,152.
[8]Arrow K J, Harris T, Marschak J. Optimal Inventory Policy. Econometrica,1951,19:250-272.
[9]Kimball G. General Principles of Inventory Control. Journal of Manufacturing and Opera-tions Management,1988,1:119-130.
[10]Scarf H. The Optimality of (s, S) Policies in the Dynamic Inventory Problem. In:Arrow K, Karlin S, Suppes P, (eds.). Proceedings of Mathematical Methods in the Social Sciences. Stanford:Stanford University Press,1960:196-202.
[11]Gans N, Croson R. Introduction to the Special Issue on Behavioral Operations. Manufac-turing and Service Operations Management,2008,10:563-565.
[12]赵晓波,谢金星,张汉勤,等.展望服务科学.工业工程与管理,2009,14：1-4.
[13]Federgruen A, Zipkin P. Computing Optimal (s, S) Policies in Inventory Models with Con-tinuous Demands. Advances in Applied Probability,1985,17:424-442.
[14]Tsitsiklis J. Periodic Review Inventory Systems with Continuous Demand and Discrete Order Sizes. Management Science,1984,30:1250-1254.
[15]Federgruen A, Zipkin P. Approximations of Dynamic, Multilocation Production and Inven-tory Problems. Management Science,1984,30:69-84.
[16]Veinott A F. On the Optimality of (s, S) Inventory Policies:New Conditions and a New Proof. SIAM Journal on Applied Mathematics,1966,14:1067-1083.
[17]Fox B L. Discretizing Dynamic Programs. Journal of Optimization Theory and Applica-tions,1973,11:228-234.
[18]Bertsekas D P. Convergence of Discretization Procedures in Dynamic Programming. IEEE Transactions on Automatic Control,1975,20:415-419.
[19]Hernandez-Lerma O, Runggaldier W J. Monotone Approximations for Convex Stochastic Control Problems. Journal of Mathematical Systems, Estimation, and Control,1994,4:99-140.
[20]Hernandez-Lerma O, Piovesan C, Runggaldier W J. Numerical Aspects of Monotone Ap-proximations in Convex Stochastic Control Problems. Annals of Operations Research,1995, 56:135-156.
[21]Lovejoy W S. Stopped Myopic Policies in Some Inventory Models with Generalized De-mand Processes. Management Science,1992,38:688-707.
[22]Morton T E, Pentico D. The Finite Horizon Nonstationary Stochastic Inventory Problem: Near-Myopic Bounds, Heuristics, Testing. Management Science,1995,41:334-343.
[23]Levi R, Pal M, Roundy R O, et al. Approximation Algorithms for Stochastic Inventory Control Models. Mathematics of Operations Research,2007,32:284-302.
[24]金雪军,杨晓兰.行为经济学.北京：首都经济贸易大学出版社,2009.
[25]董志勇.行为经济学原理.北京：北京大学出版社,2006.
[26]Allais M. Le Comportement de l'Homme Rationnel devant le Risque:Critique des Postulats et Axiomes de l'Ecole Americaine. Econometrica,1953,21:503-546.
[27]Ellsberg D. Risk, Ambiguity, and the Savage Axioms. Quarterly Journal of Economics, 1961,75:643-669.
[28]Simon H,(黄涛译).西蒙选集.北京：首都经济贸易大学出版社,2002.
[29]Smith A,(杨敬年译).国富论.西安：陕西人民出版社,2001.
[30]Kahneman D. Maps of Bounded Rationality:Psychology for Behavioral Economics. Amer-ican Economic Review,2003,93:1449-1475.
[31]Tversky A, Kahneman D. Judgment under Uncertainty:Heuristics and Biases. Science, 1974,185:1124-1130.
[32]Kahneman D, Tversky A. Prospect Theory:An Analysis of Decision under Risk. Econo-metrica,1979,47:263-291.
[33]Tversky A, Kahneman D. Loss Aversion in Riskless Choice:A Reference-Dependent Model. Quarterly Journal of Economics,1991,106:1039-1061.
[34]Tversky A, Kahneman D. Advances in Prospect Theory:Cumulative Representation of Uncertainty. Journal of Risk and Uncertainty,1992,5:297-323.
[35]Tversky A, Kahneman D. The Framing of Decisions and the Psychology of Choice. Science, 1981,211:453-458.
[36]Tversky A, Kahneman D. Rational Choice and the Framing of Decisions. Journal of Busi-ness,1986,59:S251-S278.
[37]Thaler R. Some Empirical Evidence on Dynamic Inconsistency. Economic Letters,1981, 8:201-207.
[38]Thaler R. Mental Accounting and Consumer Choice. Marketing Science,1985,4:199-214.
[39]Thaler R. Mental Accounting Matters. Journal of Behavioral Decision Making,1999, 12:183-256.
[40]Rabin M. Incorporating Fairness into Game Theory and Economics. American Economic Review,1993,83:1281-1302.
[41]Fehr E, Schmidt K M. A Theory of Fairness, Competition, and Cooperation. Quarterly Journal of Economics,1999,114:817-868.
[42]Bendoly E, Donohue K, Schultz K L. Behavior in Operations Management:Assessing Re-cent Findings and Revisiting Old Assumptions. Journal of Operations Management,2006, 24:737-752.
[43]Loch C, Wu Y. Behavioral Operations Management. Hanover:Now Publishers Inc.,2007.
[44]Schweitzer M E, Cachon G P. Decision Bias in the Newsvendor Problem with a Known Demand Distribution:Experimental Evidence. Management Science,2000,46:404-420.
[45]Bostian A J, Holt C, Smith A. Newsvendor "Pull-to-Center" Effect:Adaptive Learning in a Laboratroy Experiment. Manufacturing and Service Operations Management,2008, 10:590-608.
[46]Bolton G E, Katok E. Learning by Doing in the Newsvendor Problem:A Laboratory In-vestigation of the Role of Experience and Feedback. Manufacturing and Service Operations Management,2008,10:519-538.
[47]Benzion U, Cohen Y, Peled R, et al. Decision-making and the Newsvendor Problem:An Experimental Study. Journal of the Operational Research Society,2008,59:1281-1287.
[48]Gavirneni S, Xia Y. Anchor Selection and Group Dynamics in Newsvendor Decisions-A Note. Decision Analysis,2009,6:87-97.
[49]Lurie N H, Swaminathan J M. Is Timely Information Always Better? The Effect of Feedback Frequency on Decision Making. Organizational Behavior and Human Decision Processes, 2009,108:315-329.
[50]Fiegenbaum A. Prospect Theory and the Risk-Return Association:An Empirical Examina-tion in 85 Industries. Journal of Economic Behavior and Organization,1990,14:187-203.
[51]Jegers M. Prospect Theory and the Risk-Return Relation:Some Belgian Evidence. Academy of Management Journal,1991,34:215-225.
[52]Genesove D, Mayer C. Loss Aversion and Seller Behavior:Evidence from the Housing Market. Quarterly Journal of Economics,2001,116:1233-1260.
[53]Eeckhoudt L, Gollier C, Schlesinger H. The Risk-Averse (and Prudent) Newsboy. Manage-ment Science,1995,41:786-794.
[54]Keren B, Pliskin J S. A Benchmark Solution for the Risk-Averse Newsvendor Problem. European Journal of Operational Research,2006,174:1643-1650.
[55]Chen X, Sim M, Simchi-Levi D, et al. Risk Aversion in Inventory Management. Operations Research,2007,55:828-842.
[56]Agrawal V, Seshadri S. Impact of Uncertainty and Risk Aversion on Price and Order Quan-tity in the Newsvendor Problem. Manufacturing and Service Operations Management,2000, 2:410-423.
[57]Chen F, Federgruen A. Mean-Variance Analysis of Basic Inventory Models. Working paper. Graduate School of Business, Columbia University, New York, NY,2000.
[58]Choi S, Ruszczynski A. A Risk-Averse Newsvendor with Law Invariant Coherent Measures of Risk. Operations Research Letters,2008,36:77-82.
[59]Wang C X, Webster S. The Loss-Averse Newsvendor Problem. Omega,2009,37:93-105.
[60]Cui T H, Raju J S, Zhang Z J. Fairness and Channel Coordination. Management Science, 2007,53:1303-1314.
[61]Loch C, Wu Y. Social Preferences and Supply Chain Performance:An Experimental Study. Management Science,2008,54:1835-1849.
[62]Katok E, Wu D Y Contracting in Supply Chains:A Laboratory Investigation. Management Science,2009,55.
[63]Mason-Jones R, Towill D R. Information Enrichment:Designing the Supply Chain for Competitive Advantage. Supply Chain Management:An International Journal,1997,2:137-148.
[64]Zhou H, Benton Jr W C. Supply Chain Practice and Information Sharing. Journal of Oper-ations Management,2007,25:1348-1365.
[65]Doyle M P, Snyder C M. Information Sharing and Competition in the Motor Vehicle Indus-try. Journal of Political Economy,1999,107:1326-1364.
[66]Vickery S K, Jayaram J, Droge C, et al. The Effects of an Integrative Supply Chain Strategy on Customer Service and Financial Performance:An Analysis of Direct Versus Indirect Relationships. Journal of Operations Management,2003,21:523-539.
[67]Narasimhan R, Jayaram J. Causal Linkages in Supply Chain Management:An Exploratory Study of North American Manufacturing Firms. Decision Sciences,2007,29:579-605.
[68]Lau J S K, Huang G Q, Mak K L. Impact of Information Sharing on Inventory Replen-ishment in Divergent Supply Chains. International Journal of Production Research,2004, 42:919-941.
[69]Disney S M, Lambrecht M, Towill D R, et al. The Value of Coordination in a Two-echelon Supply Chain. HE Transactions,2008,40:341-355.
[70]Qiu M, Zhao X. Decentralised and Centralised Control of a Two-Stage Distribution System. International Journal of Services Operations and Informatics,2006,1:67-77.
[71]Qiu M, Ding H, Dong J, et al. Impact of Business Service Modes on Distribution Systems: A Reinforcement Learning Approach. Proceedings of IEEE International Conference on Services Computing, Salt Lake City, UT,2007.294-299.
[72]Zhao X, Qiu M. Information Sharing in a Multi-Echelon Inventory System. Tsinghua Science and Technology,2007,12:466-474.
[73]Qiu M, Ding H, Dong J, et al. A Myopic Policy Based Simulation Optimization Framework in a General Decentralized Supply Chain. Proceedings of IEEE International Conference on Service Operations and Logistics, and Informatics, Beijing, China,2008.2228-2233.
[74]Lee H L, So K C, Tang C S. The Value of Information Sharing in a Two-level Supply Chain. Management Science,2000,46:626-643.
[75]Cachon G P, Fisher M. Supply Chain Inventory Management and the Value of Shared Information. Management Science,2000,46:1032.
[76]Cachon G P. Stock Wars:Inventory Competition in a Two-Echelon Supply Chain with Multiple Retailers. Operations Research,2001,49:658-674.
[77]Zhao X D, Xie J X. Forecasting Errors and the Value of Information Sharing in a Supply Chain. International Journal of Production Research,2002,40:311-335.
[78]Chen F, A Federgruen Y S Z. Coordination Mechanisms for a Distribution System with One Supplier and Multiple Retailers. Management Science,2001,47:693-708.
[79]Cachon G P. Supply Chain Coordination with Contracts. In:De Kok A G, Graves S C, (eds.). Proceedings of Supply Chain Management:Design, Coordination and Operation. 2003:229-339.
[80]Wang H W, Guo M, Efstathiou J. A Game-theoretical Cooperative Mechanism Design for a Two-echelon Decentralized Supply Chain. European Journal of Operational Research, 2004,157:372-388.
[81]Bernstein F, Federgruen A. Decentralized Supply Chains with Competing Retailers under Demand Uncertainty. Management Science,2005,51:18-29.
[82]Svoronos A, Zipkin P. Estimating the Performance of Multi-Level Inventory Systems. Op-erations Research,1988,36:57-72.
[83]Axsater S. Evaluation of Installation Stock Based (R, Q)-policies for Two-level Inventory Systems with Poisson Demand. Operations Research,1998,46:S135-S145.
[84]Armony M, Plambeck E L. The Impact of Duplicate Orders on Demand Estimation and Capacity Investment. Management Science,2005,51:1505-1518.
[85]Byrne P J, Heavey C. The Impact of Information Sharing and Forecasting in Capacitated Industrial Supply Chains:A Case Study. International Journal of Production Economics, 2006,103:420-437.
[86]Axsater S, Rosling K. Notes:Installation vs. Echelon Stock Policies for Multilevel Inventory Control. Management Science,1993,39:1274-1280.
[87]Axsater S, Marklund J. Optimal Position-Based Warehouse Ordering in Divergent Two-Echelon Inventory Systems. Operations Research,2008,56:976-991.
[88]Lee H L, Padmanabhan V, Whang S. Information Distortion in a Supply Chain:The Bull-whip Effect. Management Science,1997,43:546-558.
[89]Gal-Or E. Information Sharing in Oligopoly. Econometrica,1985,53:329-343.
[90]Li L. Information Sharing in a Supply Chain with Horizontal Competition. Management Science,2002,48:1196-1212.
[91]Davenport T H, Brooks J D. Enterprise Systems and the Supply Chain. The Journal of Enterprise Information Management,2004,17:8-19.
[92]Chen F, Zheng Y S. One-warehouse Multiretailer Systems with Centralized Stock Informa-tion. Operations Research,1997,45:275-287.
[93]Kim C O, Jun J, Baek J K, et al. Adaptive Inventory Control Models for Supply Chain Man-agement. International Journal of Advanced Manufacturing Technology,2005,26:1184-1192.
[94]Choi K, J G Dai J S. On Measuring Supplier Performance Under Vendor-Managed-Inventory Programs in Capacitated Supply Chains. Manufacturing and Service Operations Management,2004,6:53-72.
[95]Bernstein F, Chen F, Federgruen A. Coordinating Supply Chains with Simple Pricing Schemes:The Role of Vendor-Managed Inventories. Management Science,2006,52:1483-1492.
[96]Powell W B. Approximate Dynamic Programming:Solving the Curses of Dimensionality. Hoboken, New Jersey:John Wiley & Sons,2007.
[97]Sobel M J, Zhang R Q. Inventory Policies for Systems with Stochastic and Deterministic Demand. Operations Research,2001,49:157-162.
[98]Veinott A F, Wagner H M. Computing Optimal (s, S) Inventory Policies. Management Science,1965,11:525-552.
[99]Bouakiz M, Sobel M J. Inventory Control with an Exponential Utility Criterion. Operations Research,1992,40:603-608.
[100]Sterman J D. Modeling Managerial Behavior:Misperceptions of Feedback in a Dynamic Decision Making Experiment. Management Science,1989,35:321-339.
[101]Sobel M J. Discounting and Risk Neutrality. Working paper. Department of Operations, Weatherhead School of Management, Case Western Reserve University, Cleveland, OH, 2006.
[102]Bagnoli M, Bergstrom T. Log-concave Probability and Its Applications. Economic Theory, 2005,26:445-469.
[103]Wakker P, Zank H. A Simple Preference Foundation of Cumulative Prospect Theory with Power Utility. European Economic Review,2002,46:1253-1271.
[104]Jackson P L. Stock Allocation in a Two-echelon Distribution System or "What to Do until Your Ship Comes in". Management Science,1988,34:880-895.
[105]De Vericourt F, Karaesmen F, Dallery Y. Optimal Stock Allocation for a Capacitated Supply System. Management Science,2002,48:1486-1501.
[106]Putterman M L. Markov Decision Process:Discrete Stochastic Dynamic Programming. New York:John Wiley & Sons,1994.
[2]中华人民共和国国家发展和改革委员会.物流业调整和振兴规划.北京,2009.
[3]中华人民共和国第十届全国人民代表大会第四次会议.中华人民共和国国民经济和社会发展第十一个五年规划纲要.北京,2006.
[4]宋则.降低我国物流成本的思路.中国社会科学院院报,2005-11-8：3.
[5]赵晓波,黄四明.库存管理.北京：清华大学出版社,2008.
[6]Zipkin P H. Foundations of Inventory Management. Boston:McGraw-Hill,2000.
[7]Harris F W. How Many Parts to Make at Once. Factory, The Magazine of Management, 1913,10:135-136,152.
[8]Arrow K J, Harris T, Marschak J. Optimal Inventory Policy. Econometrica,1951,19:250-272.
[9]Kimball G. General Principles of Inventory Control. Journal of Manufacturing and Opera-tions Management,1988,1:119-130.
[10]Scarf H. The Optimality of (s, S) Policies in the Dynamic Inventory Problem. In:Arrow K, Karlin S, Suppes P, (eds.). Proceedings of Mathematical Methods in the Social Sciences. Stanford:Stanford University Press,1960:196-202.
[11]Gans N, Croson R. Introduction to the Special Issue on Behavioral Operations. Manufac-turing and Service Operations Management,2008,10:563-565.
[12]赵晓波,谢金星,张汉勤,等.展望服务科学.工业工程与管理,2009,14：1-4.
[13]Federgruen A, Zipkin P. Computing Optimal (s, S) Policies in Inventory Models with Con-tinuous Demands. Advances in Applied Probability,1985,17:424-442.
[14]Tsitsiklis J. Periodic Review Inventory Systems with Continuous Demand and Discrete Order Sizes. Management Science,1984,30:1250-1254.
[15]Federgruen A, Zipkin P. Approximations of Dynamic, Multilocation Production and Inven-tory Problems. Management Science,1984,30:69-84.
[16]Veinott A F. On the Optimality of (s, S) Inventory Policies:New Conditions and a New Proof. SIAM Journal on Applied Mathematics,1966,14:1067-1083.
[17]Fox B L. Discretizing Dynamic Programs. Journal of Optimization Theory and Applica-tions,1973,11:228-234.
[18]Bertsekas D P. Convergence of Discretization Procedures in Dynamic Programming. IEEE Transactions on Automatic Control,1975,20:415-419.
[19]Hernandez-Lerma O, Runggaldier W J. Monotone Approximations for Convex Stochastic Control Problems. Journal of Mathematical Systems, Estimation, and Control,1994,4:99-140.
[20]Hernandez-Lerma O, Piovesan C, Runggaldier W J. Numerical Aspects of Monotone Ap-proximations in Convex Stochastic Control Problems. Annals of Operations Research,1995, 56:135-156.
[21]Lovejoy W S. Stopped Myopic Policies in Some Inventory Models with Generalized De-mand Processes. Management Science,1992,38:688-707.
[22]Morton T E, Pentico D. The Finite Horizon Nonstationary Stochastic Inventory Problem: Near-Myopic Bounds, Heuristics, Testing. Management Science,1995,41:334-343.
[23]Levi R, Pal M, Roundy R O, et al. Approximation Algorithms for Stochastic Inventory Control Models. Mathematics of Operations Research,2007,32:284-302.
[24]金雪军,杨晓兰.行为经济学.北京：首都经济贸易大学出版社,2009.
[25]董志勇.行为经济学原理.北京：北京大学出版社,2006.
[26]Allais M. Le Comportement de l'Homme Rationnel devant le Risque:Critique des Postulats et Axiomes de l'Ecole Americaine. Econometrica,1953,21:503-546.
[27]Ellsberg D. Risk, Ambiguity, and the Savage Axioms. Quarterly Journal of Economics, 1961,75:643-669.
[28]Simon H,(黄涛译).西蒙选集.北京：首都经济贸易大学出版社,2002.
[29]Smith A,(杨敬年译).国富论.西安：陕西人民出版社,2001.
[30]Kahneman D. Maps of Bounded Rationality:Psychology for Behavioral Economics. Amer-ican Economic Review,2003,93:1449-1475.
[31]Tversky A, Kahneman D. Judgment under Uncertainty:Heuristics and Biases. Science, 1974,185:1124-1130.
[32]Kahneman D, Tversky A. Prospect Theory:An Analysis of Decision under Risk. Econo-metrica,1979,47:263-291.
[33]Tversky A, Kahneman D. Loss Aversion in Riskless Choice:A Reference-Dependent Model. Quarterly Journal of Economics,1991,106:1039-1061.
[34]Tversky A, Kahneman D. Advances in Prospect Theory:Cumulative Representation of Uncertainty. Journal of Risk and Uncertainty,1992,5:297-323.
[35]Tversky A, Kahneman D. The Framing of Decisions and the Psychology of Choice. Science, 1981,211:453-458.
[36]Tversky A, Kahneman D. Rational Choice and the Framing of Decisions. Journal of Busi-ness,1986,59:S251-S278.
[37]Thaler R. Some Empirical Evidence on Dynamic Inconsistency. Economic Letters,1981, 8:201-207.
[38]Thaler R. Mental Accounting and Consumer Choice. Marketing Science,1985,4:199-214.
[39]Thaler R. Mental Accounting Matters. Journal of Behavioral Decision Making,1999, 12:183-256.
[40]Rabin M. Incorporating Fairness into Game Theory and Economics. American Economic Review,1993,83:1281-1302.
[41]Fehr E, Schmidt K M. A Theory of Fairness, Competition, and Cooperation. Quarterly Journal of Economics,1999,114:817-868.
[42]Bendoly E, Donohue K, Schultz K L. Behavior in Operations Management:Assessing Re-cent Findings and Revisiting Old Assumptions. Journal of Operations Management,2006, 24:737-752.
[43]Loch C, Wu Y. Behavioral Operations Management. Hanover:Now Publishers Inc.,2007.
[44]Schweitzer M E, Cachon G P. Decision Bias in the Newsvendor Problem with a Known Demand Distribution:Experimental Evidence. Management Science,2000,46:404-420.
[45]Bostian A J, Holt C, Smith A. Newsvendor "Pull-to-Center" Effect:Adaptive Learning in a Laboratroy Experiment. Manufacturing and Service Operations Management,2008, 10:590-608.
[46]Bolton G E, Katok E. Learning by Doing in the Newsvendor Problem:A Laboratory In-vestigation of the Role of Experience and Feedback. Manufacturing and Service Operations Management,2008,10:519-538.
[47]Benzion U, Cohen Y, Peled R, et al. Decision-making and the Newsvendor Problem:An Experimental Study. Journal of the Operational Research Society,2008,59:1281-1287.
[48]Gavirneni S, Xia Y. Anchor Selection and Group Dynamics in Newsvendor Decisions-A Note. Decision Analysis,2009,6:87-97.
[49]Lurie N H, Swaminathan J M. Is Timely Information Always Better? The Effect of Feedback Frequency on Decision Making. Organizational Behavior and Human Decision Processes, 2009,108:315-329.
[50]Fiegenbaum A. Prospect Theory and the Risk-Return Association:An Empirical Examina-tion in 85 Industries. Journal of Economic Behavior and Organization,1990,14:187-203.
[51]Jegers M. Prospect Theory and the Risk-Return Relation:Some Belgian Evidence. Academy of Management Journal,1991,34:215-225.
[52]Genesove D, Mayer C. Loss Aversion and Seller Behavior:Evidence from the Housing Market. Quarterly Journal of Economics,2001,116:1233-1260.
[53]Eeckhoudt L, Gollier C, Schlesinger H. The Risk-Averse (and Prudent) Newsboy. Manage-ment Science,1995,41:786-794.
[54]Keren B, Pliskin J S. A Benchmark Solution for the Risk-Averse Newsvendor Problem. European Journal of Operational Research,2006,174:1643-1650.
[55]Chen X, Sim M, Simchi-Levi D, et al. Risk Aversion in Inventory Management. Operations Research,2007,55:828-842.
[56]Agrawal V, Seshadri S. Impact of Uncertainty and Risk Aversion on Price and Order Quan-tity in the Newsvendor Problem. Manufacturing and Service Operations Management,2000, 2:410-423.
[57]Chen F, Federgruen A. Mean-Variance Analysis of Basic Inventory Models. Working paper. Graduate School of Business, Columbia University, New York, NY,2000.
[58]Choi S, Ruszczynski A. A Risk-Averse Newsvendor with Law Invariant Coherent Measures of Risk. Operations Research Letters,2008,36:77-82.
[59]Wang C X, Webster S. The Loss-Averse Newsvendor Problem. Omega,2009,37:93-105.
[60]Cui T H, Raju J S, Zhang Z J. Fairness and Channel Coordination. Management Science, 2007,53:1303-1314.
[61]Loch C, Wu Y. Social Preferences and Supply Chain Performance:An Experimental Study. Management Science,2008,54:1835-1849.
[62]Katok E, Wu D Y Contracting in Supply Chains:A Laboratory Investigation. Management Science,2009,55.
[63]Mason-Jones R, Towill D R. Information Enrichment:Designing the Supply Chain for Competitive Advantage. Supply Chain Management:An International Journal,1997,2:137-148.
[64]Zhou H, Benton Jr W C. Supply Chain Practice and Information Sharing. Journal of Oper-ations Management,2007,25:1348-1365.
[65]Doyle M P, Snyder C M. Information Sharing and Competition in the Motor Vehicle Indus-try. Journal of Political Economy,1999,107:1326-1364.
[66]Vickery S K, Jayaram J, Droge C, et al. The Effects of an Integrative Supply Chain Strategy on Customer Service and Financial Performance:An Analysis of Direct Versus Indirect Relationships. Journal of Operations Management,2003,21:523-539.
[67]Narasimhan R, Jayaram J. Causal Linkages in Supply Chain Management:An Exploratory Study of North American Manufacturing Firms. Decision Sciences,2007,29:579-605.
[68]Lau J S K, Huang G Q, Mak K L. Impact of Information Sharing on Inventory Replen-ishment in Divergent Supply Chains. International Journal of Production Research,2004, 42:919-941.
[69]Disney S M, Lambrecht M, Towill D R, et al. The Value of Coordination in a Two-echelon Supply Chain. HE Transactions,2008,40:341-355.
[70]Qiu M, Zhao X. Decentralised and Centralised Control of a Two-Stage Distribution System. International Journal of Services Operations and Informatics,2006,1:67-77.
[71]Qiu M, Ding H, Dong J, et al. Impact of Business Service Modes on Distribution Systems: A Reinforcement Learning Approach. Proceedings of IEEE International Conference on Services Computing, Salt Lake City, UT,2007.294-299.
[72]Zhao X, Qiu M. Information Sharing in a Multi-Echelon Inventory System. Tsinghua Science and Technology,2007,12:466-474.
[73]Qiu M, Ding H, Dong J, et al. A Myopic Policy Based Simulation Optimization Framework in a General Decentralized Supply Chain. Proceedings of IEEE International Conference on Service Operations and Logistics, and Informatics, Beijing, China,2008.2228-2233.
[74]Lee H L, So K C, Tang C S. The Value of Information Sharing in a Two-level Supply Chain. Management Science,2000,46:626-643.
[75]Cachon G P, Fisher M. Supply Chain Inventory Management and the Value of Shared Information. Management Science,2000,46:1032.
[76]Cachon G P. Stock Wars:Inventory Competition in a Two-Echelon Supply Chain with Multiple Retailers. Operations Research,2001,49:658-674.
[77]Zhao X D, Xie J X. Forecasting Errors and the Value of Information Sharing in a Supply Chain. International Journal of Production Research,2002,40:311-335.
[78]Chen F, A Federgruen Y S Z. Coordination Mechanisms for a Distribution System with One Supplier and Multiple Retailers. Management Science,2001,47:693-708.
[79]Cachon G P. Supply Chain Coordination with Contracts. In:De Kok A G, Graves S C, (eds.). Proceedings of Supply Chain Management:Design, Coordination and Operation. 2003:229-339.
[80]Wang H W, Guo M, Efstathiou J. A Game-theoretical Cooperative Mechanism Design for a Two-echelon Decentralized Supply Chain. European Journal of Operational Research, 2004,157:372-388.
[81]Bernstein F, Federgruen A. Decentralized Supply Chains with Competing Retailers under Demand Uncertainty. Management Science,2005,51:18-29.
[82]Svoronos A, Zipkin P. Estimating the Performance of Multi-Level Inventory Systems. Op-erations Research,1988,36:57-72.
[83]Axsater S. Evaluation of Installation Stock Based (R, Q)-policies for Two-level Inventory Systems with Poisson Demand. Operations Research,1998,46:S135-S145.
[84]Armony M, Plambeck E L. The Impact of Duplicate Orders on Demand Estimation and Capacity Investment. Management Science,2005,51:1505-1518.
[85]Byrne P J, Heavey C. The Impact of Information Sharing and Forecasting in Capacitated Industrial Supply Chains:A Case Study. International Journal of Production Economics, 2006,103:420-437.
[86]Axsater S, Rosling K. Notes:Installation vs. Echelon Stock Policies for Multilevel Inventory Control. Management Science,1993,39:1274-1280.
[87]Axsater S, Marklund J. Optimal Position-Based Warehouse Ordering in Divergent Two-Echelon Inventory Systems. Operations Research,2008,56:976-991.
[88]Lee H L, Padmanabhan V, Whang S. Information Distortion in a Supply Chain:The Bull-whip Effect. Management Science,1997,43:546-558.
[89]Gal-Or E. Information Sharing in Oligopoly. Econometrica,1985,53:329-343.
[90]Li L. Information Sharing in a Supply Chain with Horizontal Competition. Management Science,2002,48:1196-1212.
[91]Davenport T H, Brooks J D. Enterprise Systems and the Supply Chain. The Journal of Enterprise Information Management,2004,17:8-19.
[92]Chen F, Zheng Y S. One-warehouse Multiretailer Systems with Centralized Stock Informa-tion. Operations Research,1997,45:275-287.
[93]Kim C O, Jun J, Baek J K, et al. Adaptive Inventory Control Models for Supply Chain Man-agement. International Journal of Advanced Manufacturing Technology,2005,26:1184-1192.
[94]Choi K, J G Dai J S. On Measuring Supplier Performance Under Vendor-Managed-Inventory Programs in Capacitated Supply Chains. Manufacturing and Service Operations Management,2004,6:53-72.
[95]Bernstein F, Chen F, Federgruen A. Coordinating Supply Chains with Simple Pricing Schemes:The Role of Vendor-Managed Inventories. Management Science,2006,52:1483-1492.
[96]Powell W B. Approximate Dynamic Programming:Solving the Curses of Dimensionality. Hoboken, New Jersey:John Wiley & Sons,2007.
[97]Sobel M J, Zhang R Q. Inventory Policies for Systems with Stochastic and Deterministic Demand. Operations Research,2001,49:157-162.
[98]Veinott A F, Wagner H M. Computing Optimal (s, S) Inventory Policies. Management Science,1965,11:525-552.
[99]Bouakiz M, Sobel M J. Inventory Control with an Exponential Utility Criterion. Operations Research,1992,40:603-608.
[100]Sterman J D. Modeling Managerial Behavior:Misperceptions of Feedback in a Dynamic Decision Making Experiment. Management Science,1989,35:321-339.
[101]Sobel M J. Discounting and Risk Neutrality. Working paper. Department of Operations, Weatherhead School of Management, Case Western Reserve University, Cleveland, OH, 2006.
[102]Bagnoli M, Bergstrom T. Log-concave Probability and Its Applications. Economic Theory, 2005,26:445-469.
[103]Wakker P, Zank H. A Simple Preference Foundation of Cumulative Prospect Theory with Power Utility. European Economic Review,2002,46:1253-1271.
[104]Jackson P L. Stock Allocation in a Two-echelon Distribution System or "What to Do until Your Ship Comes in". Management Science,1988,34:880-895.
[105]De Vericourt F, Karaesmen F, Dallery Y. Optimal Stock Allocation for a Capacitated Supply System. Management Science,2002,48:1486-1501.
[106]Putterman M L. Markov Decision Process:Discrete Stochastic Dynamic Programming. New York:John Wiley & Sons,1994.