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面向供应链物流绩效的供需协调问题研究
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摘要
物流绩效是供应链整体绩效和竞争力的主要组成部分,而供需协调是供应链运作的核心内容和重要机制,对供应链物流绩效有重要影响。本文从面向供应链物流绩效的供需协调问题着手,结合实际问题进行了建模、分析,论证了供需协调策略对企业营运及物流绩效的影响,提出了物流能力约束下的供需协调策略,以及从供应链优化出发的节点物流能力规划、扩张协调策略。本文取得了预期的研究成果,主要创新性研究工作及其研究结论总结如下。
     建立了基于收货时间约束的供应链节点物流能力与客户服务水平之间的定量关系。基于对决定节点物流量的瓶颈因素的分析,提出了在延迟作业数最少时,延迟作业量最小的瓶颈工序作业排序的启发式方法,通过对启发式方法的扩展,提出了计算保证所有订单能够按时配装的瓶颈设施最小必需额定能力的定量方法。
     提出了运输能力柔性约束下的供应链批量协调策略。在运输能力柔性约束下,建立了供应链中供需双方在分散决策和集中决策情形下的最佳批量模型,研究表明:当生产商负责产品运输时,运输能力柔性越强,生产商的最佳生产批量越小,与批发商要求的短周期、多批次、小批量的订货越接近;并提出了在供应链分散决策情形下,改让批发商负责产品运输的批量协调策略;算例分析显示,当运输能力柔性较强时,数量折扣优于改由批发商负责产品运输的供需协调策略,但当运输能力柔性缺乏柔性时,后者优于前者。
     分析了Hockey-stick现象对企业营运及物流绩效的影响,论证了造成这种现象的根源是企业广泛使用的总量折扣(Volume discounts)政策。通过对某国际著名食品公司在大陆某生产厂的深入调研、数据收集和分析,研究后发现Hockey-stick现象是造成公司需求波动的主要原因,该现象对公司的仓储、运输等方面的物流绩效有显著不利的影响。通过建立数学模型和案例分析,论证了造成Hockey-stick现象的根源是公司普遍对其经销商提供的基于一定期间累计总订货量的价格折扣(Volume discounts)政策,公司可以通过多产品组合定价、延长或缩短考核周期、对经销商采用不同的考核周期、降低提供返利的最低数量、按经销商的实际销量提供返利等方法缓和或消除这种现象。
     提出了从供应链整体优化出发的下游物流能力扩张(或建设)协调策略。从供应链的角度,研究了服务或MTO制造企业向客户承诺的交货提前期、定价和能力扩张联合决策问题。研究表明,供应商可以运用降低产品转让价格、对零售商物流能力的建设投资实行补贴或与零售商共享增量利润等策略,激励零售商扩张物流能力,从而使供应链整体绩效更优。
The logistics performance is the main component of supply chain performance which has decisive influence upon supply chain competitiveness. The buyer-vendor coordination is the key mechanism of supply chain management, which can affect logistics performance. Thus, the problem of vender-buyer coordination for supply chain logistics performance is researched in this dissertation. The main contents could be summarized as follows.
     The quantization relationship between logistics capacity of supply chain node and level of customer service has constructed. In the case of constraint of due date of delivery, the maximum circulation quantity of node which has key influence upon the level of customer service is generally restricted to the capacity of bottleneck facility. A sequencing algorithm for both minimizing the number of late jobs and reducing tardiness quantity to the greatest extent is put forward. Finally, a method is extended to calculate the required capacity of bottleneck facility to achieve the perfect full rate of order.
     Based on constraint of transport capacity, the buyer-vendor coordination tactic is presented. Considering the freight cost of unit product is sensitive to order quantity and the manufacturer undertakes products transportation, the optimal lot size models in decentralized decision and centralized decision are presented. The analytical result shows that the more flexible the transport capacity is, the smaller the optimal production lot size is, which is consistent with short order lead time and small order quantity that claimed by the wholesaler. Then, the tactic of order lot size coordination based on other party in the supply chain for undertaking products transportation is put forward. Finally, the numerical analysis shows that under decentralized decision situation, when the transport capacity is more rigid, the quantity discount policy is superior to the tactic of replacing the manufacturer by the wholesaler to undertake products transportation. However, when the transport capacity is more flexible, the case is the opposition.
     Hockey-stick phenomenon prevails in supply chains and has many negative impacts on logistics and production operation of companies. Through statistic analysis of the data collected from the factory of an international notable food company which locates in mainland China, the effect of hockey-stick phenomenon on demand fluctuation and logistics performance of the factory is validated. A model is proposed to prove that the reason for the phenomenon is the price policy of volume discounts, which is popularly employed in industry. Then, the methods such as multiple products compounding pricing policy are proposed to mitigate the problem. Finally, our model and methods are validated by a case study.
     The coordination tactic of downstream logistics capacity expansion in supply chain is put forward. A mathematical framework is proposed to understand the interrelations among delivery time guarantee, pricing and order processing capacity of the retailer. The model and numerical analysis illustrate that the demand is higher and the retailer needs greater order processing capacity under the integrated decision situation than under the decentralized decision situation. The supplier could facilitate the retailer to add the order processing capacity and to achieve the best supply chain performance through reducing tranfer price, sharing in the investment cost of logistics capacity of the retailer or returning part profit increment of itself to the retailer.
引文
[1] Abad P L. Supplier pricing and lot sizing when demand is price sensitive. European Journal of Operational Research, 1994, 78 (3): 334~354
    [2] Aderohunmu R, Mobolurin A, Bryson N. Joint vendor buyer policy in JIT manufacturing. Journal of the Operational Research Society, 1995, 46 (3): 375~385
    [3] Alwan L C, Liu J J, Yao D Q. Stochastic characterization of upstream demand processes in a supply chain. IIE Transactions, 2003, 35(3): 207~219
    [4] Angerhofer B J, Angelides M C. A model and a performance measurement system for collaborative supply chains. Decision Support Systems, 2006, 42(1): 283~301
    [5] Anonymous. World-class logistics: Managing continuous change. Industrial Engineer, 1995, 27(12): 9~9
    [6] Anupindi R, Akella R. Diversification under supply uncertainty. Management Science, 1993,39 (8): 944~963
    [7] Arcelus F J, Srinivasan G. The single quantity discount problem under ROI maximization. Engineering Cost and Production Economics, 1989, 17(1–4): 263~269
    [8] Armitage H M. The use of management accounting techniques to improve productivity analysis in distribution operations. International Journal of Physical Distribution & Materials Management, 1984, 14(1): 41~51
    [9] Ballou Ronald H. Business logistics management. 4th Edition, Upper Saddle River, NJ: Prence Hall, 1999
    [10] Banker R D, Lee S-Y, Potter G, Srinivasan D. An empirical analysis of continuing improvements following the implementation of a performance-based compensation plan. Journal of Accounting and Economics, 2001, 30(3): 315~350
    [11] Bannerjee A. A joint economic lot size model for purchaser and vendor. Decision Science, 1986a, 17 (3): 292~311
    [12] Banerjee A. A quantity discount pricing model to increase vendor profits. Management Science, 1986b, 32 (8): 1513~1517
    [13] Banerjee A. A supplier’s pricing model under acustomer’s economic purchasing policy. International Journal of Management Science, 1986c, 14 (3): 409~414
    [14] Banerjee A, Burton J S. Coordinated vs. independent inventory replenishment policies for a vendor and multiple buyers. International Journal of Production Economics, 1994, 35(1-3): 215~222
    [15] Banerjee A, Burton J S, Banerjee S. A simulation study of lateral shipments in single suppliers, multiple buyers network. International Journal of Production Economics, 2003,81-82 (1): 103~114
    [16] Banerjee A, Kim L S. An integrated JIT inventory model. International Journal of Operations and Production Management, 1995,15 (9): 237~244
    [17] Barad M,Even Sapir D. Flexibility in logistics systems-modeling and performance evaluation. International Journal of Production Economics, 2003, 85(2): 155~170
    [18] Barney J. Firm resources and sustained competitive advantage. Journal of Management, 1991, 17 (l): 99~120
    [19] Beamon B M. Measuring supply chain performance. International Journal of Operations and Production Management, 1999,19 (3): 275~292
    [20] Bechtel C, Jayaram J. Supply chain management: A strategic perspective. International Journal of Logistics Management, 1997, 8 (1): 15~34
    [21] Ben Daya M, Raouf A. Inventory models involving lead time as a decision variable. Journal of the Operational Research Society,1994,45(5): 579~582
    [22] Brewer P C, Speh T W. Using the balanced scorecard to measure supply chain performance. Journal of Business Logistics, 2000, 21 (1): 74~93
    [23] Bowersox, Donald J, Daugherty P L, et al. Leading-edge logistics: Competitive positioning for the 1990s. Oad Brook, IL: Council of Logistics Mangement, 1989
    [24] Boyaci T, Gallego G. Coordinating pricing and inventory replenishment policies for one wholesaler and one or more geographically dispersed retailers. International Journal of Production Economics, 2002, 77 (2): 95~111
    [25] Burnetas A, Gilbert M, Smith C. Quantity discount in single period contracts with asymmetric demand information. Http://www. Mccombs.utexas.edu/faculty/man/gilberts/papers Qdisc.pdf, 20030412/20040314
    [26] Bylka S. A dynamic model for the single vendor multi buyer problem. International Journal of Production Economics,1999, 59 (1–3): 297~304
    [27] Bylka S. Competitive and cooperative policies for the vendor buyer system. International Journal of Production Economics, 2003, 81–82(1): 533~544
    [28] Cachon G, Fisher M. Campbell soup’s continuous replenishment program: evaluation and enhanced inventory decision rules. Production and Operations Management, 1997, 6(3): 266~276
    [29] Chakrabarty A K, Martin G E. An optimal joint buyer seller discount pricing model. Computers and Operations Research, 1988, 15 (3): 271~281
    [30] Chakravarty A K, Martin G E. Operational economies of a process positioning determinant. Computers and Operations Research, 1991, 18(6): 515~530
    [31] Chen F. Information sharing and supply chain coordination. de Kok A G , Graves S C. Supply chain management: Design, coordination, and operation. In: Handbooks in Operations Research and Management Science. Amsterdam: North-Holland (Elsevier Science Publishers B.V.), 2003, 11: 341~421
    [32] Chen F, Drezner Z, Ryan J K, Simchi-Levi D. Quantifying the bullwhip effect in a simple supply chain: The impact of forecasting, lead times, and information. Management Science, 2000, 46 (3): 436~443
    [33] Chen F, Federgruen A, Zheng Y. Coordination mechanisms for a distribution system with one supplier and multiple retailers. Management Science, 2001, 47 (5): 693~708
    [34] Chen F, Ryan J K, Simchi-Levi D. The impact of exponential smoothing forecasts on bullwhip effect. Naval Research Logistics, 2000, 47(4): 269~286
    [35] Chiang C W, Fitzsimmons J, Huang Z et al. A game theoretic approach to quantity discount problem. Decision Sciences, 1994, 25 (1): 153~168
    [36] Chirsty P D, Grout R J. Safeguarding supply chain relationships. International Journal of Production Economics, 1994, 36 (3): 233~242
    [37] Christopher, R M. Do the management components of SCM affect logistics performance?. The International Journal of Logistics Management, 2004,15(2): 15~30
    [38] Clinton S, Closs D. Logistics strategy: does it exist?. Journal of Business Logistics, 1997, 18(1): 19~44
    [39] Cooper M C, Lambert D M, Pagh J D. Supply chain management-more than a new name for logistics. International Journal of logistics Management, 1997, 8 (1): 1~14
    [40] Corbett C J, de Groote X. A supplier’s optimal quantity discount policy underasymmetric information. Management Science, 2000, 46 (3): 444~450
    [41] Crowther J F. Rationale for quantity discounts. Harvard Business Review, 1964, (March-April): 121~127
    [42] Dada M, Srikanth K N. Pricing policies for quantity discounts. Management Science, 1987, 33 (10): 1247~1253
    [43] Daughery P J, Pittman P H. Utilization of time-based strategies: creating distribution flexibility/responsiveness. International Journal of Operations & Production Management, 1995, 15(2): 54~60
    [44] Daugherty P, Stank T, Ellinger A. Leveraging logistics/distribution capabilities: The effect of logistics service on market share. Journal of Business Logistics, 1998, 19(2): 35~51
    [45] de Groote X. The flexibility of production processes: A general framework. Management Science, 1994, 40(7): 933~945
    [46] Disney S M, Towill D R. The effect of vender managed inventory (VMI) dynamics on the bullwhip effect. International Journal of Production Economics, 2003, 85(2): 199~215
    [47] Dolan R J. A normative model of industrial buyer response to quantity discounts. In: Jain S C. (Ed.), Research Frontiers in Marketing: Dialogue and Directions. American Marketing Association, 1978 Education Series, 1978, 121~125
    [48] Dolan R J. Quantity discounts: Managerial issues and research opportunities. Marketing Science, 1987, 6(1): 1~22
    [49] Drezner Z, Wesolowsky G O. Multi-buyers discount pricing. European Journal of Operational Research, 1989, 40(1): 38~42
    [50] Elinger A E. Improving marketing/logistics cross-functional collaboration in the supply chain. Industrial Marketing Management, 2000, 29(1): 1~12
    [51] Ellinger A E, Daugherty P J, Keller S B. The relationship between marketing/logistics interdepartmental integration and performance in U.S. manufacturing Firms: An empirical study. Journal of Business Logistics, 2000, 21(1): 1~22
    [52] Eng T Y. An investigation into the mediating role of cross-functional coordination on the linkage between organizational norms and SCM performance. Industrial Marketing Management, 2006, 35(6): 762~ 773
    [53] Fawcett S, Clinton S. Enhancing logistics to improve the competitiveness of manufacturing organizations: A triad perspective. Transportation Journal, 1997, 37(1): 18~28
    [54] Fawcett S, Stanley L, Smith S. Developing logistics capability to improve the performance of international operations. Journal of Business Logistics, 1997, 18(2): 16~23
    [55] Ford D, Hakasson H, Johnsen J. How should companies interact in business net works?. Journal of Business Research, 2002, 55(2): 133~139
    [56] Forrester J. Industrial dynamics. New York: MIT Press, and John Wiley & Sons, Inc, 1961
    [57] Forrester J. Industrial dynamic, a major breakthough for decision makers. Harvard Business Review, 1958, (July-August): 67~96
    [58] Frohlich M T, Westbrook R. Arcs of integration: An international study of supply chain strategies. Journal of Operations Management, 2001, 19(2): 185~200
    [59] Garavelli A C. Flexibility configurations for the supply chain management. International Journal of Production Economics, 2003, 85(2): 141~153
    [60] Geary S. Top performers cut total supply-chain costs. In: Wood J A, Marien E J. (Eds.), The Supply Chain Year Book. New York: McGraw-Hill, 2001, 427~430
    [61] Gill P J, Abend. Wal-Mart: The supply chain heavyweight champ. Supply Chain Management, 1997, 1(1): 8~16
    [62] Global Logistics Research Team at Michigan State University. World class logistics: The challenge of managing continuous change. Oak Brook, IL: Council of Logistics Management, 1995
    [63] Gunasekaran A, Patel C, McGaughey R E. A framework for supply chain performance measurement. International Journal of Production Economics, 2004, 87(3): 333~347
    [64] Gunasekaran A, Patel C, Tirtiroglu E. Performance measures and metrics in a supply chain environment. International Journal of Operations and Production Management, 2001,21 (1-2): 71~87
    [65] Goyal S K. An integrated inventory model for a single supplier single customer problem. International Journal of Production Research, 1976, 15 (1): 107~111
    [66] Goyal S K. Comment on: A generalized quantity discount pricing model to increasesupplier’s profits. Management Science, 1987a, 33 (12): 1635~1636
    [67] Goyal S K. Determination of a supplier’s economic ordering policy. Journal of the Operational Research Society, 1987b, 38(9): 853~857
    [68] Goyal S K. A joint economic lot size model for purchaser and vendor: A comment. Decision Science, 1988, 19(1): 236~241
    [69] Goyal S K. A one vendor multi buyer integrated inventory model: A comment. European Journal of Operational Research, 1995,82 (1): 209~210
    [70] Goyal S K, Gupta Y P. Integrated inventory model: The buyer vendor co-ordination. European Journal of Operational Research, 1989, 41 (3): 261~269
    [71] Goyal S K, Nebebe F. Determination of economic production shipment policy for a single vendor single buyer system. European Journal of Operational Research, 2000, 121(1): 175~178
    [72] Graves S C. A single-item inventory model for a nonstationary demand process. Manufacturing and Service Operations Management, 1999, 1(1): 50~61
    [73] Gurnani H. A study of quantity discount pricing models with different ordering structures: Order coordination, order consolidation and multi-tier ordering hierarchy. International Journal of Production Economics, 2001, 72 (3): 203~225
    [74] Hariga M, Ben Daya M. Some stochastic inventory models deterministic variable lead time. European Journal of Operational Research, 1999,113(1): 42~52
    [75] Hill R M. The single vendor, single buyer integrated production inventory model with a generalized policy. European Journal of Operational Research, 1997, 97(3): 493~499
    [76] Hill R M. The optimal production and shipment policy for the single vendor single buyer integrated production inventory problem. International Journal of Production Research, 1999, 37(11): 2463~2475
    [77] Holmberg S. A systems perspective on supply chain measurment. International Journal of Physical Distribution and Logistics Management, 2000, 30(10): 847~868
    [78] Hoque M A, Goyal S K. An optimal policy for a single vendor single buyer integrated production inventory system with capacity constraint of the transport equipment. International Journal of Production Economics, 2000, 65(3): 305~315
    [79] Innis Daniel E, Lalonde Bernard. Customer service: The key to customersatisfaction, customer loyalty, and market share. Journal of Business Logistics, 1994, 15(1): 1~28
    [80] Jammernegg W, Reiner G. Performance improvement of supply chain processes by coordinated inventory and capacity management. International Journal of Production Economics, forthcoming
    [81] Joglekar P N. A quantity discount pricing model to increase vendor profits. Management Science, 1988, 34 (11): 1391~1398
    [82] Joglekar P, Tharthare S. The individually responsible and rationale decision approach to economic lot sizes for one vendor and many purchases. Decision Sciences, 1990, 21(3): 492~506
    [83] Joong C. Firm performance in the E-commance market: The role of logistics capabilities and logistics outsouring. Foyetteville, AR, USA: University of Arkansas, 2001, 20~40
    [84] Kelle P, Milne A. The effect of (s, S) ordering policy on the supply chain. International Journal of Production Economics, 1999, 59(1-3): 113~122
    [85] Khouja M. Optimizing inventory decisions in a multistage multi customer supply chain. Transportation Research Part E, 2003a, 39 (3): 193~208
    [86] Khouja M. Synchronization in supply chains: Implications for design and management. Journal of Operational Research Society, 2003b, 54 (9): 984~994
    [87] Khouja M J. Optimal ordering, discounting, and pricing in the single-period problem. International Journal of Production Economics, 2000, 65(2): 201~216
    [88] Kim K H, Hwang, Hark. An incremental discount pricing schedule with multiple customers and single price break. European Journal of Operational Research, 1988, 35(1): 71~79
    [89] Kim K H, Hwang H. Simultaneous improvement of supplier’s profit and buyer’s cost by utilizing quantity discounts. Journal of the Operational Research Society, 1989, 40(3): 255~256
    [90] Kim S W. Organizational structures and the performance of supply chain management. International Journal of Production Economics, 2007, 106(2): 323~345
    [91] Klastorin T D, Moinzadeh K, Son J. Coordinating orders in supply chains through price discounts. IIE Transactions, 2002, 34 (8): 663~677
    [92] Kohli R, Park H. A cooperative game theory model of quantity discounts. Management Science, 1989, 35(6): 693~707
    [93] Lai K H, Ngai E W T, Cheng T C E. An empirical study of supply chain performance in transport logistics. International Journal of Production Economics, 2004, 87(3): 321~331
    [94] Lai K H, Ngai E W T, Cheng T C E. Measures for evaluating supply chain performance in transport logistics. Transportation Research Part E, 2002, 38(6): 439~456
    [95] La Londe, Bernard J, Cooper M C. Partnerships in providing customer service: A third party perspective. Oak Brook, IL: Council of Logistics Mangement, 1989
    [96] Lal R, Staelin R. An approach for developing an optimal discount pricing policy. Management Science, 1984, 30(12): 1524~1539
    [97] Lambert D M. The supply chain management and logistics controversy. In: Brewer A M, Button K J, Hensher D A. (Eds.), Handbook of Logistics and Supply Chain Management. Pergamon, Oxford, 2001, 99~126
    [98] Lee H L, Billington C. Managing supply chain inventory: Pitfalls and opportunities. Sloan Management Review, 1992, 33 (3): 65~73
    [99] Lee H L, Padmanabhan P, Whang S. The bullwhip effect in supply chains. Sloan Management Review, 1997a, 38(3): 93~102
    [100] Lee H L, Padmanabhan P, Whang S. Information distortion in a supply chain: The bullwhip effect. Management Science, 1997b, 43(4): 546~558
    [101] Lee H L, Rosenblatt M J. A generalized quantity discount pricing model to increase supplier’s profits. Management Science, 1986, 32(9): 1177~1185
    [102] Lee H L, So K C, Tang C S. The value of information sharing in a two-level supply chain. Management Science, 2000, 46(5): 626~643
    [103] Li D, O’Brien C. Integrated decision modelling of supply chain efficiency. International Journal of Production Economics, 1999, 59 (1–3): 147~157
    [104] Lee L, Lee Y S. Pricing and delivery-time performance in a competitive environment. Management Science, 1994, 40(5): 633~646
    [105] Li S, Huang Z, Ashley A. Seller buyer system cooperation in a monopolistic market. Journal of the Operational Research Society, 1995, 46 (12): 1456~1470
    [106] Li S, Huang Z, Ashley A. Improving buyer seller system cooperation throughinventory control. International Journal of Production Economics, 1996, 43(1): 37~46
    [107] Lu L. Theory and methodology: A one vendor multi buyer integrated inventory model. European Journal of Operational Research, 1995, 81(2): 312~323
    [108] Lynch D, Keller S, Ozment J. The effects of logistics capabilities and strategy on firm performance. Journal of Business Logistics, 2000, 21(2): 47~ 67
    [109] Mattessich P W, Muray-Close M, Monsey B R. Collaboration: What makes it works. Wilder Foundation, 2001
    [110] McCarthy T M, Golicic S L. Implementing collaborative forecasting to improve supply chain performance. International Journal of Physical Distribution and Logistics Management, 2002, 32 (6): 431~454
    [111] McCullen P, Towill D R. Practical ways of reducing bullwhip: The case of the glosuch supply chain. Control, 2000, 26(10): 24~30
    [112] Mentzer J T, Konrad B P. An efficiency/effectiveness approach to logistics performance analysis. Journal of Business Logistics, 1991, 21(1): 33~62
    [113] Merriam-Webster. Merriam-Webster Collegiate Dictionary. Merriam-Webster, 2003, 11
    [114] Metters R. Quantifying the bullwhip effect in supply chains. Journal of Operations Management, 1997, 15(2): 89~100
    [115] Michael Moore J. An n job, one mochine sequencing algorothm for minimizing the number of late jobs. Management Science, 1968, 15(1): 102~110
    [116] Misra A K. Selective discount for supplier buyer coordination using common replenishment epochs. European Journal of Operational Research, 2004, 153(3): 751~756
    [117] Monahan J P. A quantity pricing model to increase vendor profits. Management Science, 1984, 30(6): 720~726
    [118] Morash Edward A, Droge Cornelia L M, Vickery Shawnee K. Strategic logistics capabilities for competitive advantage and firm success. Journal of Business Logistics, 1996, 17(1): 1~22
    [119] Munson L C, Rosenblatt J M. Theories and realities of quantity discounts: An exploratory study. Production and Operations Management, 1998, 7(1): 352~369
    [120] Munson L C, Rosenblatt J M. Coordinating a three level supply chain with quantitydiscounts. IIE Transactions, 2001, 33 (4): 371~384
    [121] Munson L C, Rosenblatt J M, Rosenblatt Z. The use and abuse of power in supply chains. Business Horizons, 1999, 42 (1): 55~65
    [122] Narasimhan R, Carter J R. Linking business unit and material sourcing strategies. Journal of Business Logistics, 1998, 19(2): 155~171
    [123] New S J. A framework for analyzing supply chain improvement. International Journal of Operations and Production Management, 1996, 16 (4): 19~34
    [124] Ouyang L Y, Yen N C, Wu K S. Mixture inventory model with backorders and lost sales for variable lead time. Journal of the Operational Research Society, 1996, 47(6): 829~832
    [125] Ozment John, Chard Douglas N. Effects of customer service variables on sales: An analysis of historical data. International Journal of Physical Distribution and Materials Management, 1986, 16(3): 5~14
    [126] Palaka K, Erlebacher S, Kropp D H. Lead time setting, capacity utilisation, and pricing decision under lead time dependent demand. IIE Transactions, 1998, 30(2) :151~163
    [127] Parlar M, Wang Q. Discounting decisions in a supplier-buyer relationship with a linear buyer’s demand. IIE Transactions, 1994, 26(2): 34~41
    [128] Porter Michael E. Competitive strategy: Techniques for analyzing industries and competitors. NY: The Free Press, 1980
    [129] Prafulla N J. Comments on“A quantity discount pricing model to increase vender profits”. Management Science, 1988, 34(11): 1391~1398
    [130] Rao U S, Swaminathan J M, Zhang J. Demand and production management with uniform guaranteed lead time. Production and Operations Management Society, 2005, 14(4): 400~412
    [131] Ray S, Jewkes E M. Customer lead time management when both demand and price are lead time sensitive. European Journal of Operational Research, 2004, 153(3): 769~781
    [132] Rhea M J, Shrock D L. Measuring the effectiveness of physical distribution customer service programs. Journal of Business Logistics, 1987, 8(1): 31~45
    [133] Robins J A. Organizational economics: Notes on the use if transaction-cost theory in the study of organizations. Administrative Science Quarterly, 1987, 32(1): 68~86
    [134] Sadrian A A, Yoon Y S. Business volume discount: A new perspective on discount pricing strategy. International Journal of Purchasing and Materials Management, 1992, 28(2): 43~46
    [135] Sadrian A A, Yoon Y S. A procurement decision support system in business volume discount environments. Operations Research, 1994, 42 (1): 14~23
    [136] Sarmah S P, Acharya D, Goyal S K. Buyer vendor coordination models in supply chain management. European Journal of Operational Research, 2006, 175(1): 1~15
    [137] Seaker R F. Decision environments, organizational structure, and logistics performance: An exploratory study. Philadelphia: Pennsylvania State University, 2000
    [138] Stewart G. Supply chain performance benchmarking study reveals keys to supply chain excellence. Logistics Information Management, 1995, 8 (2): 38~44
    [139] Shah J, Singh N. Benchmarking internal supply chain performance: Development of a framework. The Journal of Supply Chain Management, 2001, 37 (1): 37~47
    [140] Shang Kuo-chang, Marlow Peter B. Logistics capability and performance in Taiwan’s major manufacturing firms. Transportation Research Part E, 2005, 41(3): 217~234
    [141] So K C. Price and time competition for service delivery. Manufacturing and Service Operations Management, 2000, 2(4): 392~409
    [142] So K C, Song J-S. Price, delivery time guarantees and capacity selection. European Journal of Operational Research, 1998, 111(1): 28~49
    [143] So K C, Zheng X. Impact of supplier’s lead time and forecast demand updating on retailer’s order quantity variability in a two-level supply chain. International Journal of Production Economics, 2003, 86(2): 169~179
    [144] Stainer A. Logistics: A productivity and performance perspective. Supply Chain Management, 1997, 2(2): 53~62
    [145] Stalk G. Time: The next source of competitive advantage. Harvard Business Review, 1988, (July-August): 41~51
    [146] Stalk G, Hout T M. Competing against time: How time-based competition is reshaping global markets. New York: The Free Press, 1990
    [147] Stank T, Lackey C. Enhancing performance through logistical capabilities in Mexican maquiladora firms. Journal of Business Logistics, 1997, 18(2): 16~23
    [148] Stank T P, Goldsby T J, Vickery S K, Savitskie K. Logistics service performance: Estimating its influence on marketing share. Journal of business logistics, 2003, 24(1): 21~56
    [149] Sterman J D. Modeling managerial behavior: Misperceptions of feedback in a dynamic decision making experiment. Management Science, 1989, 35(3): 321~339
    [150] Tan K C, Kannan V R, Handfield R B, Ghosh S. Supply chain management: An empirical study of its impact on performance. International Journal of Operations and Production Management, 1999, 19 (10): 1034~1052
    [151] Taylor A T. Supply chain coordination under channel rebates with sales effort effects. Management Science, 2002, 48 (8): 992~1007
    [152] Thomas J. The quest continues. Logistics Management & Distribution Report, 1998, 37(8): 39~41
    [153] Thomas D J, Grifin P J. Coordinated supply chain management. European Journal of Operational Research, 1996, 94(1): 1~15
    [154] Towill D R, McCullen P. The impact of an agile manufacturing on supply chain dynamics. International Journal Logistics Management, 1999, 10(1): 83~96
    [155] Van de Ven A H V, Delbecq A L, Koeing R Jr. Determinants of coordination modes with organizations. American Sociological Review, 1976, 41(2): 322~338
    [156] Viswanathan S. Optimal strategy for the integrated vendor buyer inventory mode. European Journal of Operational Research, 1998, 105 (1): 38~42
    [157] Viswanathan S, Piplani R. Coordinating supply chain inventories through common replenishment epoch. European Journal of Operational Research, 2001, 129(2): 277~286
    [158] Viswanathan S, Wang Q. Discount pricing decisions in distribution channels with price-sensitive demand. European Journal of Operational Research, 2003, 149(3): 571~587
    [159] Wang Q. Determination of supplier’s optimal quantity discount schedules with heterogenous buyers. Naval Research Logistics, 2002, 49 (1): 46~59
    [160] Weng Z K. Channel coordination and quantity discounts. Management Science, 1995a, 41(9): 1509~1522
    [161] Weng Z K. Modeling quantity discounts under general price sensitive demand functions: Optimal policies and relationships. European Journal of OperationalResearch, 1995b, 86(2): 300~314
    [162] Weng Z k, Wong R T. General models for the supplier’s all unit quantity discount policy. Naval Research Logistics, 1993, 40(7): 971~991
    [163] Woo Y Y, Hsu S L, Wu S. An integrated inventory model for a single vendor and multiple buyers with ordering cost reduction. International Journal of Production Economics, 2001, 73 (3): 203~215
    [164] Yang C P, Wee M H. An arborescent inventory model in a supply chain system. Production Planning and Control, 2001, 12 (8): 728~735
    [165] Zhao Meng, Dr?ge C, Stank T. The effect of logistics capabilities on firm performance: Costomer-focused versus information-focused capabilities. Journal of Business Logistics, 2001, 22(2): 91~103
    [166]陈荣秋.生产计划与控制.武汉:华中理工大学出版社, 1995, 251~273
    [167]达庆利,张钦,沈厚才.供应链中牛鞭效应问题研究.管理科学学报, 2003, 6(3): 86~93
    [168]但斌,陈军,吴庆.基于多级折扣价格的易逝品订货策略研究.中国管理科学, 2006, 14(3): 38~44
    [169]高峻峻,王迎军,郭亚军,赵先得.弹性需求下供应链契约中的Pareto优化问题.系统工程理论方法应用, 2002, 11(1): 36~40
    [170]姬小利,王宁生.信息不对称情况下的VMI协调机制设计.系统工程, 2004, 22(1): 24~28
    [171]黄小原,郭海峰,卢震.供应链时滞系统模型及其牛鞭效应的H∞控制.系统工程学报, 2005, 20(6): 585~590
    [172]李刚,汪寿阳,于刚,阎洪.牛鞭效应与生产平滑模型有效性问题.管理科学学报, 2004, 7(1): 1 ~18
    [173]李华,李益强,徐国华.供应链配送中的提前期模型研究.管理工程学报, 2004, 18(3): 112~14
    [174]廖贵生.物流能力与组织绩效关系之研究.台北科技大学学报, 1999, 32(1): 299~312
    [175]刘斌,刘思峰,陈剑.不确定需求下供应链渠道协调的数量折扣研究.南京航空航天大学学报, 2005, 37(2): 256~261
    [176]刘春玲,黎继子,孟波.基于两单链合作下的集群式供应链牛鞭效应的H∞控制研究.中国管理科学, 2007, 15(1): 41~46
    [177]马士华,陈习勇.供应链环境下的物流能力构成及特性研究.管理学报, 2004, 19 (1): 107~111
    [178]马士华,孟庆鑫.供应链物流能力的研究现状及发展趋势.计算机集成制造系统-CIMS, 2005, 11(3): 301~307
    [179]常良峰,卢震,黄小原.供应链渠道协调中的Stackelberg主从对策.控制与决策, 2003, 18(6): 651~660
    [180]邵晓峰,黄培清,季建华.供应链中供需双方合作批量模型研究.管理工程学报, 2001, 15(2): 54~57
    [181]余玉刚,梁樑,王志强,侯定丕.订单生产方式下供应链买卖双方1:n协调订货批量模型.系统工程, 2004, 22(1): 33~38
    [182]万杰,李敏强,寇纪淞.供应链分配机制对牛鞭效应的影响研究.系统工程学报, 2002, 17(4): 340~348
    [183]汪传旭.基于ARMA(1,1)需求的供应链历史订单量信息价值的分析.管理工程学报, 2004, 20(4): 25~30
    [184]石小法,张丽清,杨东援.信息对供应链的影响研究.系统工程, 2002, 20(3): 37~40
    [185]张钦,达庆利,沈厚才.在ARIMA(0,1,1)需求下的牛鞭效应与信息共享的评价.中国管理科学, 2001, 9(6): 1~6

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