国外冷链物流的参考文献
物流与供应链管理参考文献目录
物流与供应链管理参考文献目录《物流与供应链管理》参考文献目录英文参考文献:[1] (美)鲍尔索克斯(Bowersox，D.J)，克劳斯(Closs，D.J)，库珀(Cooper，M.B.)著(马士华译注(供应链物流管理(英文版?原书第2版)[M]. 北京:机械工业出版社，2007.01[2] 姜阵剑，卢山，荆海鸥(Logistics and Supply Chain Management /现代物流与供应链管理概论(双语)[M](武汉:武汉理工大学出版社，2006.8[3] (美)Long D(国际物流:全球供应链管理[M](北京:电子工业出版社，2006.06[4] Jack Brimley and Robert Love，A New Distance Function for Modeling Travel Distancesin a Transportation Network[J]，Transportation Science 26[5] John L(Gattorna Strategic Supply Chain Alignment [M](MPG Books Ltd，Bodmin，Cornwall，1998[6] Silver, E.A., Pyke, D.F., Petersen, R(Inventory Management And Production Planning andScheduling [M], New York: John Wiley & Sons, 1998[7] Martin Christopher(Logistics and Supply Chain Management-Strategies for ReducingCosts and Improving Services [M](Financial Times/Pitman Publishing，1994[8] Benjamin S Blanchard(Logistics Engineering and Management (4th Edition) [M].Rentice Hall, 1992[9] James C. Johnson, Donald F. Wood(Contemporary Logistics(4th Edition) [M], MacmillanPublishing Company,1990[10] Donald Waters(Global Logistics and Distribution Planning[M]Boca Raton:CRC Press，1999[11] Igor H Ansoff(The New Corporate Strategy [M]. New York: John Wiley & Sons, 1998 [12] B Joseph Pine?(Mass Customization: The new Frontier in Business Competition [M].Boston: Harvard Business School Press, 1993.14,15[13] John L.Gattorna(Strategic Supply Chain Alignment [M]. MPG Books Ltd, Bodmin,Cornwall, 1998[14] Frank H. Mossman, Paul Bankit，and Omar K. Hfeltrich，Logistics Systems Analysis，reviewed[M].Washington , D.C.: University Press of America, 1979 [15] V. Daniel Hunt(Reengineering: Leveraging the Integrated Product Development[M],Oliver Wight Publication,Inc.1992[16] Martin Christopher(Logistics & Supply Chain Management: creating value-addingnetworks (3rd Edition) [M]. FT Press, February, 2005[17] David H. Taylor(Global Cases in Logistics and Supply Chain Management [M].1International Thomson Publishing Services, March 1997[18] Donald J. Bowersox, David J. Closs, M.Bixby Cooper(Supply Chain LogisticsManagement (2Rev Ed edition) [M]. McGraw Hill Higher Education, February 2006 [19] Ronald H. Ballou(Business Logistics/Supply Chain Management and Logware CDPackage (5th edition) [M]. Prentice Hall, September 2003 [20] Donald Waters(Logistics: An Introduction to Supply Chain Management [M]. PalgraveMacmillan, January 2003[21] Ann Brewer, Kenneth J Button, David A Hensher(Handbook of Logistics andSupply-Chain Management [M]. Pergamon, July 2001[22] Ronald H. Ballou(Business Logistics: Supply Chain Management (5th edition) [M].Prentice Hall, August 2003[23] John Mangan, Chandra Lalwani, Tim Butcher(Global Logistics and Supply ChainManagement [M]. Publisher: Wiley, June 2008[24] Andreas Klose, M. Gracia Speranza, Luk N. VanWassenhove(Quantitative Approaches toDistribution Logistics and Supply Chain Management (Lecture Notes in Economics andMathematical Systems) [M]. Springer, August 2002[25] Jonsson(Logistics and Supply Chain Management [M]. McGraw Hill Higher Education ,April 2008[26] John J. Coyle, C. John Langley, Brian Gibson, Robert A(Novack, Edward J. Bardi. SupplyChain Management: A Logistics Perspective (8th edition) [M]. South-Western College Pub,March 2008中文参考文献:[1] 唐纳德?鲍尔索克斯，戴维?克劳斯著(林国龙等译(物流管理:供应链过程的一体化[M](北京:机械工业出版社，1999[2] (美)兰伯特，斯托克，埃拉姆著(张文杰，叶龙，刘秉镰译(物流管理——物流与供应链管理系列[M](北京:电子工业出版社，2006.02[3] 何明珂等(中华人民共和国标准?物流术语[S](北京:中国标准出版社，国家技术监督局发布，2001[4] (美)科伊尔，(美)巴蒂，(美)兰利著(文武等译(企业物流管理:供应链视角(第7版)[M]. 北京:电子工业出版社，2003.07[5] [英]泰勒，胡克等译(全球物流与供应链管理案例[M](北京:中信出版社，2003.11[6] (美)森尼尔?乔普瑞，彼得?梅因德尔(供应链管理—战略、规划与运营[M].北京:社会科学文献出版社，2003[7] 赵林度(供应链与物流管理:理论与实务[M](北京:机械工业出版社，2003[8] 沈文，云俊，邓爱民编著(物流与供应链管理[M](北京:人民交通出版社，20022[9] 彭志忠(现代物流与供应链管理[M](济南:山东大学出版社，2002 [10] 朱道立，龚国华，罗齐(物流和供应链管理[M](上海:复旦大学出版社，2001 [11] 马士华，林勇，陈志祥(供应链管理[M](北京:机械工业出版社，2000 [12] 马士华(新编供应链管理(21世纪工商管理系列教材)(北京:人民大学出版社. 2008.01 [13] (美)兰伯特，斯托克，埃拉姆著(物流管理——物流与供应链管理系列[M](北京:电子工业出版社，2006.02[14] 宋华，胡左浩(现代物流与供应链管理——21世纪市场营销新知与案例丛书[M](北京:经济管理出版社，2004.02[15] 齐二石，刘亮(物流与供应链管理[M](北京:电子工业出版社，2007.10[16] 宋华(物流成本与供应链绩效管理[M](北京:人民邮电出版社，2007.01 [17]徐琪(供应链管理:理论与实验[M](上海:上海人民出版社，2008.01 [18] 徐剑，周晓晔，李贵华(物流与供应链管理[M](北京:国防工业出版社，2006.08 [19] 霍桂震(物流与供应链管理[M](北京:高等教育出版社，2006.08 [20] 张理(现代物流案例分析——21世纪电子商务与现代物流管理系列教材[M](北京:水利水电出版社，2005.05[21] 胡继灵(供应链的合作与冲突管理[M](上海:上海财经大学出版社，2007.11 [22] 刘南，赵成锋，陈远高(现代物流与经济发展理论、方法与实证分析[M](北京:中国物资出版社，2007.08[23] 张良卫，朱强(国际物流实务[M](北京:电子工业出版社，2008.01 [24] 骆温平(第三方物流[M](北京:高等教育出版社，2007.08 [25] 王欣兰(现代物流管理概论[M](北京:清华大学出版社，2007.10 [26] 施先亮，李伊松(供应链管理原理及应用[M](北京:清华大学出版社，2006.09 [27] 吴隽(物流与供应链管理[M](哈尔滨:哈尔滨工业大学出版社，2007.01 [28] 蒋长兵，吴承健(现代物流理论与供应链管理实践[M](杭州:浙江大学出版社，2006.12 [29] 魏修建，姚峰(现代物流与供应链管理(十一五电子商务规划教材)[M](西安:西安交通大学出版社，2008.0434。
有关冷链物流的英文文献
冷链物流的重要性及发展趋势介绍冷链物流是指在产品运输、贮存和销售过程中，通过使用低温环境和相应的设备，确保产品在整个供应链中的质量和安全。
随着消费者对食品和制药品质量和安全的要求日益增加，冷链物流得到了广泛的关注。
本文将探讨冷链物流的重要性以及其未来的发展趋势。
重要性1.保持质量和安全：冷链物流通过控制温度、湿度和其他环境因素，确保产品在整个供应链中的质量和安全。
这对于食品和制药等易腐败商品尤为重要。
例如，适当的冷链管理可以延长食品的保质期，并减少细菌和其他微生物的生长。
2.扩大市场范围：冷链物流使得农产品和其他易腐败商品可以远距离运输。
这使得农民和制造商能够将产品销售到更远的市场，扩大销售范围，增加收入。
3.降低损失和浪费：适当的冷链管理可以减少货物在运输和贮存过程中的损失和浪费。
这不仅可以节约资源，还有助于减少对环境的不良影响。
4.国际贸易的推动：冷链物流在促进国际贸易中发挥着重要作用。
冷链技术可以使产品在长途运输过程中保持良好的质量和新鲜度，从而促进了跨国贸易的发展。
发展趋势1.新技术的应用：随着科技的进步，新的冷链技术不断涌现。
例如，物联网、传感器和人工智能的发展为冷链物流提供了更多的监测和管理方式。
这些技术可以帮助实时监测货物的温度、湿度和位置等信息，确保货物的安全和质量。
2.环境友好的解决方案：环境问题成为全球关注的焦点，冷链物流也在寻求更环保的解决方案。
例如，使用可再生能源供电的冷藏设备，以减少对化石燃料的依赖；采用可降解的包装材料，减少塑料污染。
3.数据驱动的决策：冷链物流借助大数据分析和预测模型，使运营更加高效。
通过分析大量的数据，可以提前预测供应链中的问题，及时采取措施，减少损失和浪费。
4.合作伙伴关系的建立：冷链物流需要各方的合作，才能实现良好的供应链管理。
从供应商到物流公司，再到零售商，合作伙伴之间的紧密合作是冷链物流成功的关键。
冷链物流的挑战1.高昂的成本：冷链物流的设备成本和运营成本较高。
医药公司冷链物流运营管理问题研究参考文献
制药厂内部冷链物流的管理是一个非常复杂和关键的过程。
这一复杂工作涉及对温度敏感的药品的运输和储存，并尽最大努力确保在整个供应链中，这些药品保持在必要的温度参数范围内。
近年来，制药业出现了显著增长，因此有必要增加对冷链物流有效管理的需求。
专门研究这一专门领域的挑战并提出解决办法的学术文献激增。
当管理制药厂的冷链物流时，一个重大挑战是实时密切注视事物。
你知道，像有一个个人GPS追踪器对于你珍贵的药品！想象一下用温度感应器和RFID标记来装配它们，这样你就可以不断地检查它们的位置和状况。
这就像给他们一个个性化的Fitbit，但更高科技！我们不要忘记GPS追踪系统，比如在你的产品通过供应链的过程中，拥有一个虚拟的导游。
有了这些很酷的装置，你可以冲进去，在第一次出现麻烦时省下一天，无论是温度打嗝还是麻风供应链中断。
这些狡猾的技术并不仅仅让事情变得更容易——它们在冷链物流中增加了全新水平的披萨和兴奋。
谁知道追踪药品会这么好玩？
除了实时监测外，制药实体冷链物流管理研究的另一个关键方面是评估风险因素和执行缓解战略。
考虑到药品供应链的复杂和全球性，存在着多种风险因素，可能危及温度敏感产品的完整性，包括但不限于运输延误、温度波动和储存设施不足。
为应对这些挑战，研究人员提出了各种风险评估框架和缓解战略，例如利用预测模型、应急规划和供应商资格方案。
通过查明和减轻潜在风险，制药商可以提高其冷链
物流业务的可靠性和复原力，最终确保药品对全世界病人的安全和效力。
冷链物流毕业论文分析
河北经贸大学经济管理学院毕业论文中美农产品冷链物流的比较研究和启示专业名称: 国际经济与贸易班级：C 国贸 11-5学生姓名：XXX指导教师：XXX完成时间：2015 年 3月摘要近年来，我国农产品的产量不断增长。
随着水果蔬菜、肉类等农产品的市场的需求日益增加，以及人们对于农产品的高质量的要求和对高品质生活的追求，农产品冷链物流体系的建设变得更加迫切。
农产品冷链物流在国外发达国家如加拿大、日本、美国等已经发展成熟，形成了较为完整的冷链物流体系，然而在我国起步晚，市场规模小。
我国农产品在物流过程中的损耗大、成本高，严重影响到了我国农产品的质量安全和农产品的品质。
本文分析了我国农产品冷链物流的发展现状，从我国和美国农产品冷链物流比较的视角出发，对美国和我国农产品冷链物流现状做了对比研究，探讨了我国农产品冷链物流发展中村子的问题----我国的农产品冷链物流基础设施不足，设备落后，第三方物流较少介入，政府在农产品冷链物流方面制定的相关法规与政策比较少等等，确定了我国农产品冷链物流发展中存在的具体差距，针对以上不足，总结美国农产品冷链物流对我国的经验教训，并借鉴美国的先进经验提出了适合我国国情的农产品冷链物流发展的对策，这对于建设和完善我国农产品冷链物流体系有着重大的意义。
关键词农产品；中美；冷链物流；现状；对比研究；对策AbstractIn recent years, our country agricultural product production increasing. As the fruits and vegetables, meat and other agricultural products market demand is increasing, and people to the requirement of agricultural products of high quality and the pursuit of high quality life, agricultural cold chain logistics system construction is becoming more urgent. Agricultural products cold chain logistics in foreign developed countries such as Canada, Japan, the United States has grown up, formed a relatively complete system of cold chain logistics, late in our country, however, the market is small. Big loss, in the process of agriculturalproducts in China logistics cost is high, the serious influence to our country agricultural product quality safety and quality of agricultural products.This paper analyzes the situation of agricultural products cold chain logistics in China, from the perspective of our country and the United States agricultural cold chain logistics is, to the United States and China's agricultural products cold chain logistics present situation made contrast research, discusses the problems of the village - developing agricultural cold chain logistics in our country agricultural products cold chain logistics in our country inadequate infrastructure, poor equipment, the third party logistics is less involved, the government in agricultural cold chain logistics less relevant laws and regulations and policy, etc., determine the specific gap existing in the development of agricultural products cold chain logistics in China, in view of the above shortcomings, summing up the experience of the American agricultural products cold chain logistics in our country, and put forward the suitable for our country draw lessons from the advanced experience of the United States the situation of agricultural products cold chain logistics development countermeasures, for the construction and improvement of our agricultural products cold chain logistics system is of great significance.Keywords Agricultural products；China and American;Cold chain logistics ；Status;The comparative study；Countermeasures目录一、我国农产品冷链物流发展现状................................................................... .. (1)（一）农产品冷链物流成本高、技术设施落后 (1)（二）农产品冷链物流供应链存在安全隐患、体系不健全 (1)（三）农产品物流环节多，效率低下 (2)二、美国农产品冷链物流的先进经验................................................................... (2)（一）农产品冷链物流基础设施先进 (2)（二）农产品冷链物流规模化、专业化、社会化程度高 (2)（三）农产品冷链物流组织化程度高 (2)（四）政府宏观调控与市场调节功能健全 (3)三、中美农产品冷链物流的比较和分析......................................................................3（一）冷链物流的设备因素比较 (3)1.冷链物流运输率远低于美国 (3)2.蔬菜水果冷链水平比较 (3)（二）冷链物流的政策环境比较 (4)1.物流标准 (4)2.法律法规 (5)3.政府扶持和监管 (5)（三）冷链物流的市场化程度比较 (5)1.农民专业合作社 (5)2.第三方物流 (5)四、美国农产品冷链物流的发展对我国的启示 (5)（一）加快冷藏运输设备的研发改进, 减少运输耗损 (5)（二）完善冷链物流体系，加大政府指导力度 (6)（三）改造传统物流模式，大力发展第三方物流 (6)（四）加快农产品冷链物流的人才培养和引进 (6)参考文献................................................................... (7)中美农产品冷链物流的比较研究和启示我国每年消费的易腐食品大约为10亿吨左右，其中，需要冷链运输的超过了55%，但是只有12%左右的食品能够实现冷链运输。
生鲜冷链物流模式的文献研究
生鲜冷链物流模式的文献研究作者：葛瑶科杨漪清张思光来源：《财讯》2018年第22期生鲜冷链物流是我国生鲜农产品未来发展的重要环节，近年来不同学者对生鲜冷链物流模式的研究层出不穷，因此本文对相关领域的的研究文献进行了系统亿的分析研究s概括，并提出了自己的见解。
生鲜冷链物流文献研究国内研究现状近年来，相关学者开始在借鉴国外研究的基础上针对我国实际现状对适合中国生鲜冷链物流模式进行了研究，其研究方向大概可分为生鲜冷链物流模式的电子商务模式研究；生鲜冷链物流模式的“农超对接”模式研究以及各地域生鲜冷链物流模式研究。
具体概括为以下几部分：（1）生鲜冷链模式中的“农超对接”模式研究“农超对接”是近年来兴起的一种适合大型连锁超市的新型农产品物流模式，随着各大超市的实践以及相关研究的不断完善，相关学者认为其是大型连锁超市未来发展的必然选择，是生鲜农产品物流中具有生命力的一种新型模式。
其中学者吴克象通过构建“目标一行为一方式一效果”的逻辑模型，并结合我国目前超市的现状，通过典型案例分析得出超市进军生鲜领域以成为必然；学者樊俊花通过对廊坊市生鲜农产品集中流通的实证研究，认为“农超对接”模式，是新形势下农村建设和农场发展的主要趋势。
学者蒋明琳、林晓伟和舒辉提出提升农超对接模式下农产品冷链物流协同绩效，要寻求政府支持，加强政企合作，降低运营成本，加强农产品冷链物流标准的完善与执行，加强农户、超市等销售终端和农产品冷链物流企业组织的协调性，完善农产品冷链信息系统，实现共赢。
（2）生鲜冷链物流模式的电子商务模式研究信息网络、电商平台自2012年开始迎来了快速高效的发展机会，各类生鲜平台相继呈现，这为生鲜农产品物流提供了又一发展契机，如何能提高电商的配送效率，使物流的信息共享成为可能，是未来生鲜物流必不可少的现代化工具之一。
相关的理论研究也随之兴起，其中学者罗蓉以现代物流理论和系统论为基础，通过对电子商务背景下的生鲜农产品物流现状进行深入分析，利用层次分析法建立了一个新型的冷链物流体系绩效评价系统；学者葛继红和王文吴以产业组织理论为基础，通过对阿里案例的实证分析，提出差异化发展是未来生鲜电商拥有竞争优势的首要选择。
冷链物流论文内容
食品冷链物流张洁摘要：冷链物流(Cold Chain Logistics) 泛指冷藏冷冻类食品在生产、贮藏运输、销售，到消费前的各个环节中始终处于规定的低温环境下，以保证食品质量，减少食品损耗的一项系统工程。
它是随着科学技术的进步、制冷技术的发展而建立起来的，是以冷冻工艺学为基础、以制冷技术为手段的低温物流过程。
中国农产品冷链物流业的快速发展，国家必须尽早制定和实施科学、有效的宏观政策。
冷链物流的要求比较高，相应的管理和资金方面的投入也比普通的常温物流要大。
Abstract: Cold Chain Logistics (Cold Chain Logistics) refers to refrigerated and frozen foods in the production, storage, transportation, sale and consumption prior to each link is always in the specified low temperature environment, in order to ensure food quality and reduce food losses a systems engineering. It is with the advancement of science and technology, refrigeration technology development and set up, based on freezing technology-based, low-temperature refrigeration technology as a means of logistic processes. Chinese agricultural products cold chain logistics industry's rapid development, the state must develop and implement as soon as possible scientific and effective macro policy. Cold chain logistics requirements are relatively high, the corresponding aspects of the investment management and capital than normal room temperature logistics to be big.关键词：冷链、物流、食品、发展状况1冷链物流的特点1）商品全程温度控制我们把冷链物流形容成一个由“线”连接起多个“节点”的链条，链条的未端是消费者。
国外冷链物流的转型分析与借鉴
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高、 规模 大 、 技术 新 的跨 区 域 １ 、作为经济 重建 与成长 的支 农产 品冷链物流配送 中心 撑， 构建完善 的冷链物流体 系 ２ 、农产 品冷链 物流 核心技 术 建立 安全 、 高效 、 充 足和可 靠 ２ 、国 内外 冷链实 现消 除 “ 浪 １ 、协助农特 产 品与加工 食品 得 到广泛推 广， 形成 一批具 有 的冷 链运输 系统 ，其 范 围是 费 、 非效率 、 非均等化 ” 业 者，建立城 市 ， 城际， 跨岸 较 强 资源 整 合能 力和 国际 竞 推 动 目标 国际性 的 ， 形式 是综合 性 的， ３ 、 在整体上 『 把建立 最优化 的 集运配体系 争 力 的核 心农 产 品冷 链 物 流 特点 是智能性 的 ，性质 是环 冷链体系Ｊ 作为发展 的 目标 ２ 、提供低温 品全程 保鲜 与调 企 业，初步建 成布局 合理 、 设 ４ 、 通 过提高政 策的综 合性 、 一 度 服务 ， 塑造 台湾优 良与 安全 施 先进 、 上下 游衔 接 、 功 能 完 境友善 的 体化程度来提高冷链效 率 的低温物流服务 品牌形象 善、 管理 规范 、 标 准健 全 的 农 ５ 。 产 品冷 链 物 流 服 务体 系 。 强化货主 与物流 业界 以及 ３ 相关者之 间的相互合作 肉类和水产 品农 产品冷 链 物流水 平显著 提高 ， 食 品安全 保 障能力显 著增强 ； 果蔬农 产 品冷 链 物 流 进 一 步加 快 发展 。
外文翻译农产品冷链物流发展现状及对策研究.doc
河北科技师范学院本科毕业论文（设计）外文翻译商业智能在打造无缝冷链物流中的应用院（系、部）名称：商务管理系专业名称：物流管理学生姓名：宋国栋学生学号：9116100407指导教师：李丽杰2013年12月15日河北科技师范学院教务处制Applications of business intelligence in making cold chains seamlessAzimuddin KhanAbstractDue to intense competition, it has become inevitable for business organisations world over to become efficient and cost effective. Seamless cold chain infrastructure is critical for the success of cold chain business. Concurrent growth in demand for products such as fresh agricultural produce, frozen food, photographic films, chemicals and pharmaceutical drugs has lead to the necessity of managing cold chains intelligently. The managers of cold chains at strategic and functional level need actionable information for making their organisations agile. In the recent times, the concept of business intelligence has gained momentum and found application in diverse areas. In this paper, authors have made an effort to develop a framework of BI system for cold chains and highlighted the application areas of business intelligence for cold chains including a case study of cold chain business.Keywords: cold chains; business intelligence; BI; analytics; supply chain;1.IntroductionIndia falls short of 10 million tons cold storage facilities for storing agriculture-based produce, it has nearly 21.7 million tons of such storage facilities against required 31 million tons, and as a result 40% of produce is lost in fields after post-harvesting(KPMG-ASSOCHAM, 2009). India is a populous country and resource utilisation is always a major concern, to meet the demand. The demand for perishable food stuff, i.e., farm produce like fruits, vegetables and milk products, meat, fish, frozen food, photographic films, chemicals, and pharmaceutical drugs is increasing world over. This has also increased concerns regarding food hygiene and safety during storage and transportation to end point.The cold chains are providing integration of farm, processing, warehousing, distribution and retail business. Discrepancies in cold chain management can render products unfit for use so much so that consumption of these can even pose a threat to life. According to Bourlakis and Weightman (2004),the cold chains are vital. Effective management of cold chains is crucial for maintaining the safety, sanctity of food, and profitability of business.Technology finds significant application in facilitating processes related to warehouse, inventory, transportation, and distribution. These processes generate huge volumes of data. Such large volumes of data need to be analysed, streamlined and channelised in an intelligent manner to make organisation agile (Khan and Saxena, 2010). The sensible extract of information aids in prudent decision-making and contributes to value proposition for business by making them more competitive with proper utilisation of business intelligence (BI).In this backdrop, an attempt has been made to understand the concept of BI with reference to cold chains, development of framework for implementation of BI solution, identifying the application areas of BI for cold chains. To date, there have been few academic studies on the use of BI solutionsin cold chains, yet, ractitioners and researchers are interested in understanding the concept for improving performance and profits using BI. An attempt has also been made to understand the cold chain business through a case study of cold chain company.2. Concept of BITechnology has empowered cold chain business to access huge volume of data, which plays a critical role in planning and controlling of cold chain activities like warehousing management, transportation, distribution operation, freight management and of course the compliance management.In the year 1989, Howard Dresner, a research scholar at Garter Group (an IT research and advisory firm in Connecticut) popularised the term BI with a set of methods and concepts to improve business decision-making by using data resources. Simon and Shaffer (2001) stated that the period from 1990 to 1999 was a remarkable decade in which many core computing and communication technologies and developments from the prior decade came together and transformed the method of business. In 1990s, technology led to the birth and widespread acceptance of applications such as enterprise resource planning (ERP) and customer relationship management (CRM). Due to failure of distributed database management system, organisations pursued data warehousing, where data would be consolidated from many distributed and heterogeneous stores of data. Organisations that built and deployed data warehouses typically focused their usage on the informational/analytical side to generate reports, analyse trends, and so on.McDonald et al. (2002) stated that “once the data warehouse has been constructed, the stage is set for effective business intelligence”. A data warehouse provid es the supportinfrastructure for BI. BI is built on the foundation of data warehouse. Kalakota and Robinson (2001) define BI “as a group of applications that enable both the active and passive delivery of information or rather turn raw data into actionable intelligence. Data and information are collected from large databases to answer to mission-critical questions asked by its managers”. Gangadharan and Swami (2004) stated that BI is the result of in-depth analysis of detailed business data, including database and application technologies, as well as analysis practice. According to Moss and Hoberman (2004), the processes, technologies, and tools needed to turn data into information, information into knowledge and knowledge into plans, drive profitable business action. BI encompasses data warehousing, business analytics tools and content/knowledge management.Turban et al. (2007) infersthat “organizations are being compelled to capture, understand and harness their data to support decision making in order to improve business operations. Business cycle times are now extremely compressed; faster, more informed, and better decision-making is therefore a competitive imperative”. BI starts with day to day information that organisations need to run the business and assist to take correct decision based on facts at right time and at right place through out the life of business by doing analytics. This is a modern mantra for modern approaches to BI.As per Cody et al. (2002), BI and knowledge management technologies have been used in improving the quantitative and qualitative value of the knowledge available todecision-makers. BI has applied the functionality, scalability, and reliability of modern database management systems to build ever-larger data warehouses, and to utilise BI tools to extract business analytics from the vast amount of available enterprise data. BI systems facilitate the decision-makers to correct their intuition by taking advantage of analytical tools, which can test and verify intuition before applying it to the decision-making process. Decision-maker can also use predictive models to improve their decision-making. The current state of decision-making is forcing companies, to reap the real benefits of BI. BI solution can turn dynamic, detail data into information, and make it available in real-time to thedecision-makers. Actionable information must be accessible on-demand when it is required. It provides trends and patterns that might otherwise go undetected and unseen bydecision-makers.3. Framework for implementation of BI in cold chainsThe BI can be built with the use of technology through BI system, refining the processes and BI tools for analytics. BI can be applied at all three levels in the cold chains, i.e., strategic, tactical and operational. A framework has been proposed in Figure 1. The framework includes four basic components which are existing IT setup, Transformation tools, data warehousing and various BI tools for analytics.3.1 Existing IT setup for data collectionIn an organisation, online transaction processing system and other enterprise application generate huge volume of data. These data are stored in databases. These databases along with application software, present the business information to the business user through IT infrastructure including PC, Notebook, Tablet, Smart Phone and networks. All the applications for running cold chain business including warehouse management, logistic management, network planning, RFID tracking and monitoring, CRM, inventory management, quality assurance, HR application, order management and data management generate huge volume of data with different database at different location. There are certain external information, and data about the financial and market information which are taken from research organisations, government, regulatory bodies and company’s websites, audio, video, spatial and supplier data. Data can also come from e-mail, voice application, images, spatial data taken from satellite and regulatory compliance (Hazard Analysis and Critical Control Points (HACCP)/ISO 22000 norms) (Keener, 2007). Cold chain business has to heavily rely on radio frequency identification (RFID) tags attached to items, cases or pallets, monitor and log the environment temperature at predefined intervals duringtransportation or product lifecycle. The recorded data can be read and analysedin real time for better analytics.3.2 Data transformation toolsThe objective of this stage is to define and design data management strategy to ensure that organisation has right information and uses it properly. The greatest challenge is to collect the clean data, that too from various sources so that BI solution delivers the correct actionable information to management at different levels. The organisation should concentrate on quality of data, and investment must be made to ensure high levels of data quality. The duplicate data should be unified as it comes from various sources. The data coming from transaction system is atomic level data and should be recorded in detailed form. It is necessary to first clean and validate it using business rules through data cleansing tools. Transformation procedure defines business logic which maps data from its source to destination. Extract, transfer and load (ETL)tools are very helpful to reduce the development time, manage the flow of data from source to destination and upload data to tables of data warehouse.3.3 Data warehousing and data martInmon (1995) defined a “data warehouse as a centralized repository (collection of resources that can be accessed to retrieve information) of an organization’s electronically stored data, designed to facilitate reporting and analysis”. Kimball and Ross (2002) have given another approach where data marts are first created to provide reporting and analytical capabilities for specific business processes. Data marts contain, primarily, dimensions and facts. Facts cancontain either atomic data and, if necessary, summarised data. The single data mart can be build for specific business area such as sales or production. These data marts can eventually beintegrated to create a comprehensive data warehouse. The data warehouse is a play ground for analytics and it provides retrieval of data without slowing down operational systems.3.4 BI tools for analyticsThere are many categories of tools available in the BI market. BI vendors are now also consolidating tools in every category to provide complete BI solution to companies. However, some organisations still prefer to have best of breed strategy in which they select BI tools in each category from different vendors. The various categories are query and reporting, online analytical processing, dashboards and scorecards, performance management, predictive analytics and data mining and advanced visualisation.BI can derive better return on investment (ROI) from complex integrated cold chain management software and other operational systems implemented by unlocking the wealth of information stored in these systems.4.Application areas of BI for cold chainsThe cold chain business is constantly searching for cost effective methods to remain competitive in fast changing world where margins are thin, customer expectation is very high, regulatory compliances are mandatory, and product life is very short. Companies in cold chain are working hard to adopt the information technology to get the rich insight into the hidden trends through cold chain analytics. The BI system provides reports, analyses, and monitors the vast corporate data. It also helps companies to reduce supply chain production cost,improve efficiencies, accuracy, increase revenue and performance. The cold chain analytics also provides the details to reduce waste, produce fresher, higher quality products, and enhance the economic value generated from perishable food industry by giving 360-degree overview of financial and operational results. As per suggested framework, various BI tools can be utilised to generate various analytics in following areas of cold chain business.4.1 Supply chain intelligenceSupply chain intelligence allows cold chains to evaluate supplier performance to negotiate prices, ensure timely deliveries and maintain high standard of quality by analysing the demand patterns, supply networks, operations and customer service requirements.Wal-Mart has set the standard of supply chain analytics. With the analytics driven intelligence, supply chain disruption can be reduced to better manage suppliers. Commodity classification provides information regarding procurement data from various sources within or outside company and classify the spend information into meaningful categories to understand true volumes per commodity. This can be used to develop the sourcing strategies. Spend analysis provides a dynamic ranking system for identifying and prioritising the most valuable suppliers. Demand driven forecasting allows planning of future requirements and management of supply chain by using statistical models. Scenario planning and what if analysis reduces the finished goods inventory and stockouts. The complete process of optimisation of plans and procedures creates an everlasting and sustainable competitive advantage for the organisation throughout a supply chain despite the risks associatedso commonly with unbounded challenges.4.2 Transportation analyticsIncreasing fuel costs, international expansion, and global competition has forced to useBI to streamline operations, distribution, and fleet management. BI optimises service and ensures consistent on-time performance for cold chains. Customers are demanding more services at lower prices, making operational efficiency improvements a requirement for maintaining acceptable profitability. The process of getting products delivered from one place to another on time, efficiently, and at the lowest costwithout losing life are main objectives of cold chains. The temperature conditions at origin and destination, seasonal temperature, load configurations, transport routes and modes, total duration of transit, duration and location of handling and stopover points are very important factors for temperature sensitive transportation. In thisextremely competitive business, one late delivery or losing quality of products can miss revenue opportunities and a lost customerforever. BI tools can help gain insight into the complex process of transportation by providing carrier performance evaluation, mode-cost analysis, supplier compliance analysis, carrier relationship management, capacity planning, cycle time analysis, routing and scheduling, truck and driver performance analysis, and root cause and claims analysis.4.3 Warehouse analyticsWarehouse management provides the ability to know the location of stock, time of requirement, and transporting it correctly in the shortest time. BI provides inventory analysis, warehouse performance analysis based on picking accuracy, shipping accuracy, lines per hour, overtime hours and on time shipments, picking analysis to improve warehouse efficiency and layout design, and warehouse space utilisation analysis for getting cost per unit of space over a period of time.4.4 Inventory analysisInventory optimisation analysis enables to reduce the over capacity and ensure sufficient supplies, monitor carrying cost for obsolete and slow moving items and usage across location and time. These analyses provides inventory carrying costs, inventory turns, order fulfilment lead time, percentage of backorders, average item inventory, finished goods on hands, etc. The intelligent analytics provides improved quality, reduces spoilage, and lowers rejections to make the customer or retailer more satisfied.4.5 Quality life cycle analysis4.6 Asset maintenance analytics4.7 Customer intelligence4.8 Financial analytics4.9 Customer profitability analysis6 Conclusions5.ConclusionsLike every other business, cold chain business has also become fiercely competitive. In order to stay ahead, and remain competitive, the cold chains should implement BI solution. Huge volume of data generation from existing applications like warehouse management, logistics management, inventory management, RFID tracking and monitoring, order management, quality assurance, CRM, and supply chain management has given an opportunity to manager to take smart decision based on analytics rather than intuition. The suggested framework will guide cold chains to streamline their operation. BI solution implementation requires basic operational system in place. With rapid development of information technology, communication system and reduction of cost of smart phones has opened the new doors for cold chains to provide the mobile BI to their executives. There are some new trends like BI search, BI gadgets, and query as web service will make a lot of difference in future BI and those who implement BI solutions intelligently will definite have an edge over others.摘要随着全球竞争的加剧，企业如何控制成本，使企业运营变得更加高效越来越成为世界上所有企业不得不面对的课题。
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