哈密市物流业与其相关产业的灰色关联研究
摘要
加入WTO给我国的物流业发展带来了前所未有的巨大机遇,哈密市的物流业也将从中得到新的发展机遇。一方面,进出口贸易的增长为物流业的发展提供了新的市场空间；另一方面,物流业的发展又将降低企业的仓储和运输成本,使得资源得到有效配置,效率提高,增强了市场竞争力,加速了企业经济的发展进程。
本文正是基于这样的背景,首先对物流的相关理论进行了介绍,包括物流的概念、分类、基本功能等,随后对哈密市物流业的基本情况、物流业的成本、现状以及特点进行了阐述,接着详细介绍了灰色关联分析方法,并以哈密市为例进行了实证分析。在进行实证分析时,以物流业的国民生产总值的增加额为灰灰色关联分析的参考序列,以农业、工业、建筑业、批发零售及餐饮业、交通运输及邮电业、社会服务业和文教卫生业为比较序列,通过灰色关联度分析,得出：工业、建筑业、批发和零售业、住宿和餐饮业、其他服务业、农业与物流业的关联度分别为：0.43,0.94,0.94,0.44,0.56,0.88。其中,建筑业、批发和零售业与物流业的关联度最高,农业次之,工业与物流业的关联度最低。针对求解的结果,提出了适合哈密发展的相应的政策及建议。
WTO has brought unprecedented opportunities on China's logistics industry. Hami will also benefit from new opportunities. On the one hand, the growth of import and export trade, the development of the logistics industry has provided a new market space; On the other hand, the logistics industry in turn reduce the cost of enterprise storage and transport.This makes the efficient allocation of resources,increased efficiency, enhanced market competitiveness, accelerating the process of economic development of the enterprise.
Based on the background, firstly,we introduce the related theories of logistics, including the logistics concept, classification, basic functions. Then we analysis the basic situation of the logistics industry, logistics costs, status and characteristics about Hami. Followed by details of the Grey relational analysis,we take Hami as a model to discuss. Conducting empirical analysis, we take the logistics industry's GDP growth as a value of grey relational analysis of the reference sequence, take agriculture, industry, construction, wholesale and retail and restaurants,transport and post and telecommunications, social services and cultural and educational industry to compare the sequences of grey correlation analysis. After that, we obtain that:all the index values are 0.43,0.94,0.94, 0.44,0.56,0.88. Construction, wholesale and retail trade and logistics industry has the highest correlation, followed by agriculture, industry and logistics industry has the lowest correlation. The results for the solution proposed corresponding policies and proposals for the development of Hami.
本文正是基于这样的背景,首先对物流的相关理论进行了介绍,包括物流的概念、分类、基本功能等,随后对哈密市物流业的基本情况、物流业的成本、现状以及特点进行了阐述,接着详细介绍了灰色关联分析方法,并以哈密市为例进行了实证分析。在进行实证分析时,以物流业的国民生产总值的增加额为灰灰色关联分析的参考序列,以农业、工业、建筑业、批发零售及餐饮业、交通运输及邮电业、社会服务业和文教卫生业为比较序列,通过灰色关联度分析,得出：工业、建筑业、批发和零售业、住宿和餐饮业、其他服务业、农业与物流业的关联度分别为：0.43,0.94,0.94,0.44,0.56,0.88。其中,建筑业、批发和零售业与物流业的关联度最高,农业次之,工业与物流业的关联度最低。针对求解的结果,提出了适合哈密发展的相应的政策及建议。
WTO has brought unprecedented opportunities on China's logistics industry. Hami will also benefit from new opportunities. On the one hand, the growth of import and export trade, the development of the logistics industry has provided a new market space; On the other hand, the logistics industry in turn reduce the cost of enterprise storage and transport.This makes the efficient allocation of resources,increased efficiency, enhanced market competitiveness, accelerating the process of economic development of the enterprise.
Based on the background, firstly,we introduce the related theories of logistics, including the logistics concept, classification, basic functions. Then we analysis the basic situation of the logistics industry, logistics costs, status and characteristics about Hami. Followed by details of the Grey relational analysis,we take Hami as a model to discuss. Conducting empirical analysis, we take the logistics industry's GDP growth as a value of grey relational analysis of the reference sequence, take agriculture, industry, construction, wholesale and retail and restaurants,transport and post and telecommunications, social services and cultural and educational industry to compare the sequences of grey correlation analysis. After that, we obtain that:all the index values are 0.43,0.94,0.94, 0.44,0.56,0.88. Construction, wholesale and retail trade and logistics industry has the highest correlation, followed by agriculture, industry and logistics industry has the lowest correlation. The results for the solution proposed corresponding policies and proposals for the development of Hami.
引文
1. 包晓,李素兰.淡析企业物流外包的风险管理[J].当代经济,2010,2：60—61.
2. 曹明霞.灰色关联分析模型及其应用的研究[硕士学位论文].南京：南京航空航天大学图书馆.
3. 哈密市“十一五”国民经济及社会发展规划纲要.
4. 华细玲,张凤玉.现代物流概论[M].北京：中国商业出版社,2006：10—24.
5. 黄祖庆,达庆利.一个允许退货的库存控制策略模型[J].东南大学学报(自然科学版),2003,33(6)：792-795.
6. 霍红,杨艳玲,张玉斌.基于灰关联熵的物流服务体系准优势比较分析[J].学术交流,2010,191(2)：111—115.卢锐,许彩国.中外物流理论的演变[J].财贸经济,2006,3：91—94.
7. 季葆苓.物流业务外包的战略及交易成本分析[J].大众科技,2008(10)：219-220.
8. 江玮璠.基于定期处理的多品种逆向物流库存控制研究[J].数学的实践与认识,2010,40(6)：46—52.
9. 敬春菊.现代物流业与其相关产业灰色关联度研究—基于山西省的实证分析[J].数学的实践与认识,2010,40(4)：47—51.
10.李电生,夏国建.基于灰色关联熵的水产品贸易与物流耦合性研究[J].统计与决策,2010,2：55-57.
11.李桂艳.物流外包的潜在风险及其防范[J].中国高新技术企业,2007(8)：73-74.
12.李智彬,胡琳.企业物流外包的风险及防范对策[J].消费导刊,2008(18)：108.
13.潘瑞玉.物流相关概念的综述[J].物流科技,2009,6：11—13.
14.商娟.企业物流业务外包的优势与风险[J].财经与管理,2009,20：203.
15.宋杰珍.物流涵义辨析[J].经营与管理,2009：49—50.
16.孙玉刚.灰色关联分析及其应用的研究[硕士学位论文].南京：南京航空航天大学图书馆.
17.陶承德.可持续发展论[M].北京：九洲图书出版社,1998：23—67.
18.田肇云.逆向物流网络中选址—路径问题的研究[J].北京机械工业学院学报,2006,21(4)：73-76.
19.王艳珍.物流学概论[M].哈尔滨：哈尔滨工业大学出版社,2009：7—39.
20.吴蓓.生产企业与第三方物流[J].湘潮,2008(10)：33-34.
21.武慧硕.基于相对熵—灰色关联的上市中小企业信用评价[硕士学位论文].大连：大连理工大学图书馆.
22.夏春玉,李健生.绿色物流[M].北京：中国物资出版社,2005：15—65.
23.谢家平,陈荣秋.产品回收处理策略优化的0-1型目标规划模型[J].系统工程理论与实践,2004,(3)：52-57.
24.徐莹,钱海良.供需网环境下的逆向物流网络结构[J].经营与管理,2010,3：67—68.
25.严智渊.灰色关联分析与应用[M].江苏：江苏科学技术出版社,1989：1—23.
26.杨杰等.包含逆向物流的供应链库存控制问题研究[J].北京交通大学学报(社会科学版),2006,5(2)：15—18.
27.叶宗裕.关于多指标综合评价中指标正向化和无量纲化方法的选择[J].浙江统计,2003,4：24—25.
28.于江.企业外包物流的选择与合作[J].财经问题研究,2003,5：61—63.
29.张建升.物流发展与城乡收入差异—基于中国省级而板数据的实证分析[J].经济与管理,2010,24(4)：31—35.
30.赵榕,赵礼强,刘彬.企业逆向物流外包的合作伙伴选择研究[J].沈阳航空工业学院学报,2009,26(6)：14—17.
31.朱道立.逆向物流系统和技术[J].复旦学报,2003,5：673-679.
32. A.Hoecht, P. Trott.. Innovation risks of strategicoutsourcing[J]. Technovation,2006,26(5):672-681.
33. Anu H Bask. Relationships among TPL providers and members of supply chains-a strategic perspective[J].The Journal of Business & Industrial Marketing,2001(6):470-486.
34. Fleischmann M, Bloemhof-Ruwward J M, Dekker R, etal. Quantitative models for reverse logistics:a review[J]. European Journal of Opertional Research,1997,103(1):1-17.
35. Guide Jr D R, Kraus M E, Srivastava R.Scheduling Policies for Remanufacturing.International Journal of Production Economics,1997,48:187-204.
36. Johson M R. Wang M H.Planning Product Disassembly for Material Recovery Opportunities[J].International Journal of Production Research.1995,33(11):3119-3142.
37. Kiesmueller G P,van der Laan E A.An inventory model with dependent product demands and returns[J].International Journal of Production Economics,2001,72(1):73-87.
38. Minner S,Kleber R.Optimal control of production and remanufacturing in a simple ecovery model with linear cost functions[J]. OR Spektrum,2001,23(1):3-24.
39. Minner S.Strategic safety stocks in reverse logistics supply chains[J]. International Journal of Production Economics,2001,71 (3):417-428.
40. Skjoett-Larsen T..Third party logistics-from an interior ganilizational point of view[J].International Journal of Physical Distribution & Logistics management,2000,30(2):112-127.
41. Toktay L B,Wein M,Zenions S A. Inventory management of remanufacturable products[J]. Management Science,2000,46(11):1412-1426.
2. 曹明霞.灰色关联分析模型及其应用的研究[硕士学位论文].南京：南京航空航天大学图书馆.
3. 哈密市“十一五”国民经济及社会发展规划纲要.
4. 华细玲,张凤玉.现代物流概论[M].北京：中国商业出版社,2006：10—24.
5. 黄祖庆,达庆利.一个允许退货的库存控制策略模型[J].东南大学学报(自然科学版),2003,33(6)：792-795.
6. 霍红,杨艳玲,张玉斌.基于灰关联熵的物流服务体系准优势比较分析[J].学术交流,2010,191(2)：111—115.卢锐,许彩国.中外物流理论的演变[J].财贸经济,2006,3：91—94.
7. 季葆苓.物流业务外包的战略及交易成本分析[J].大众科技,2008(10)：219-220.
8. 江玮璠.基于定期处理的多品种逆向物流库存控制研究[J].数学的实践与认识,2010,40(6)：46—52.
9. 敬春菊.现代物流业与其相关产业灰色关联度研究—基于山西省的实证分析[J].数学的实践与认识,2010,40(4)：47—51.
10.李电生,夏国建.基于灰色关联熵的水产品贸易与物流耦合性研究[J].统计与决策,2010,2：55-57.
11.李桂艳.物流外包的潜在风险及其防范[J].中国高新技术企业,2007(8)：73-74.
12.李智彬,胡琳.企业物流外包的风险及防范对策[J].消费导刊,2008(18)：108.
13.潘瑞玉.物流相关概念的综述[J].物流科技,2009,6：11—13.
14.商娟.企业物流业务外包的优势与风险[J].财经与管理,2009,20：203.
15.宋杰珍.物流涵义辨析[J].经营与管理,2009：49—50.
16.孙玉刚.灰色关联分析及其应用的研究[硕士学位论文].南京：南京航空航天大学图书馆.
17.陶承德.可持续发展论[M].北京：九洲图书出版社,1998：23—67.
18.田肇云.逆向物流网络中选址—路径问题的研究[J].北京机械工业学院学报,2006,21(4)：73-76.
19.王艳珍.物流学概论[M].哈尔滨：哈尔滨工业大学出版社,2009：7—39.
20.吴蓓.生产企业与第三方物流[J].湘潮,2008(10)：33-34.
21.武慧硕.基于相对熵—灰色关联的上市中小企业信用评价[硕士学位论文].大连：大连理工大学图书馆.
22.夏春玉,李健生.绿色物流[M].北京：中国物资出版社,2005：15—65.
23.谢家平,陈荣秋.产品回收处理策略优化的0-1型目标规划模型[J].系统工程理论与实践,2004,(3)：52-57.
24.徐莹,钱海良.供需网环境下的逆向物流网络结构[J].经营与管理,2010,3：67—68.
25.严智渊.灰色关联分析与应用[M].江苏：江苏科学技术出版社,1989：1—23.
26.杨杰等.包含逆向物流的供应链库存控制问题研究[J].北京交通大学学报(社会科学版),2006,5(2)：15—18.
27.叶宗裕.关于多指标综合评价中指标正向化和无量纲化方法的选择[J].浙江统计,2003,4：24—25.
28.于江.企业外包物流的选择与合作[J].财经问题研究,2003,5：61—63.
29.张建升.物流发展与城乡收入差异—基于中国省级而板数据的实证分析[J].经济与管理,2010,24(4)：31—35.
30.赵榕,赵礼强,刘彬.企业逆向物流外包的合作伙伴选择研究[J].沈阳航空工业学院学报,2009,26(6)：14—17.
31.朱道立.逆向物流系统和技术[J].复旦学报,2003,5：673-679.
32. A.Hoecht, P. Trott.. Innovation risks of strategicoutsourcing[J]. Technovation,2006,26(5):672-681.
33. Anu H Bask. Relationships among TPL providers and members of supply chains-a strategic perspective[J].The Journal of Business & Industrial Marketing,2001(6):470-486.
34. Fleischmann M, Bloemhof-Ruwward J M, Dekker R, etal. Quantitative models for reverse logistics:a review[J]. European Journal of Opertional Research,1997,103(1):1-17.
35. Guide Jr D R, Kraus M E, Srivastava R.Scheduling Policies for Remanufacturing.International Journal of Production Economics,1997,48:187-204.
36. Johson M R. Wang M H.Planning Product Disassembly for Material Recovery Opportunities[J].International Journal of Production Research.1995,33(11):3119-3142.
37. Kiesmueller G P,van der Laan E A.An inventory model with dependent product demands and returns[J].International Journal of Production Economics,2001,72(1):73-87.
38. Minner S,Kleber R.Optimal control of production and remanufacturing in a simple ecovery model with linear cost functions[J]. OR Spektrum,2001,23(1):3-24.
39. Minner S.Strategic safety stocks in reverse logistics supply chains[J]. International Journal of Production Economics,2001,71 (3):417-428.
40. Skjoett-Larsen T..Third party logistics-from an interior ganilizational point of view[J].International Journal of Physical Distribution & Logistics management,2000,30(2):112-127.
41. Toktay L B,Wein M,Zenions S A. Inventory management of remanufacturable products[J]. Management Science,2000,46(11):1412-1426.