基于作业流程的货运量—物流量折合系数研究
发布时间：2018-08-10 22:31
【摘要】：伴随着社会经济的快速发展，近几年物流业的发展也更多地受到了国家和政府部门的大力支持和倡导，物流园区的建设和规划也随之兴起。不管是地方政府、或者说是物流企业，都极其重视当代物流业的发展与规划。而物流量这一指标参数是进行物流系统规划的主要支撑，也是进行物流系统规模规划的重要参数之一，它对于物流节点中一些与物流相关的设施的设计布局和相应物流设备的选取等都有着重要的指导意义。但由于我国的物流统计工作尚处于初级阶段，统计指标中也没有物流量这一指标，还没有建立起比较完善的物流统计指标体系。就目前关于物流量的理论研究和实践活动的情况来看，对物流量内涵的界定还不是足够明晰，此外，统计口径也尚且没有统一衡量标准，暂时未能达到一致。在实际的物流规划与建设中，由于缺少全社会物流量的相关统计数据，人们往往采用近似或类推的方法，一般都是用货运量代替物流量来进行与物流相关的节点或园区等的需求分析，使用该方法获得结果分析普遍存在着不合理性，故而在它的基础上所开展的物流规划也就存有一定的片面和盲目性。由于物流量与货运量之间的密切联系，如何在现有货运量统计数据的基础上，得到物流量与货运量之间的折合系数，并由此进行物流量的定量分析就十分迫切和必要。文章希望通过对物流量的定量分析和研究，能够为将来物流节点的规划，提供较为准确可信的物流量数据作参考；同时为今后物流统计中关于物流量指标的统计研究提供一些思路和方向，以便更好地促进我国物流统计工作的发展。 本文在对国内外关于物流量及物流量预测等相关理论研究的基础上，针对物流量内涵的界定及其分类和计算等问题展开研究，进行了深入详细地阐述。分析和介绍了当前我国物流统计中存在的指标不完善及数据缺乏等问题，并提出以货物参与物流活动的作业流程环节为标准，进行物流量分析和计算的思路，通过分析不同货物参与物流活动的主要作业流程和环节，选择货运量指标作为主要研究对象，研究物流量和货运量的折合系数（Conversion Coefficient of Logistics volume and Freight volume，即CCLF），选取煤炭、粮食等几种典型货物作为代表，分别对其线路物流量和节点物流量的CCLF进行实例分析和计算得出结果。结果表明，以线路物流量为主要研究对象时，，煤炭、粮食和生鲜农产品这几种货物的线路物流量与货运量之间的折合系数，即线路物流量的粮食、生鲜农产品的节点物流量的CCLF分别为5.33644,6.6565。并提出了以全社会货运量的统计数据为准,对线路物流量进行修正和折合的CCLF计算模型。
[Abstract]:With the rapid development of social economy, the development of logistics industry in recent years has been more and more strongly supported and advocated by the state and government departments, and the construction and planning of logistics parks have arisen. Parameters are the main support of logistics system planning, and also one of the important parameters of logistics system scale planning. It has important guiding significance for the design and layout of some logistics-related facilities and the selection of corresponding logistics equipment in logistics nodes. There is no such index as logistics volume in the statistical index, and a comparatively perfect statistical index system of logistics has not been established. As far as the current theoretical research and practical activities on logistics volume are concerned, the definition of logistics volume connotation is not clear enough. In addition, there is no uniform measurement standard for statistical caliber, and it has not yet reached one. As a result, in the actual logistics planning and construction, due to the lack of relevant statistical data of the logistics volume of the whole society, people often adopt approximate or analogical methods, generally using freight volume instead of logistics volume to carry out the demand analysis of logistics-related nodes or parks, etc. The results obtained by this method are generally unreasonable. Because of the close relationship between the logistics volume and the freight volume, it is urgent and necessary to obtain the conversion coefficient between the logistics volume and the freight volume on the basis of the existing statistical data of the freight volume. The article hopes that through the quantitative analysis and research of logistics quantity, it can provide more accurate and credible logistics flow data for the future logistics node planning, and provide some ideas and directions for the future statistical research of logistics quantity index in logistics statistics, so as to better promote the development of logistics statistics in China.
On the basis of the research on the theories of logistics volume and logistics volume forecasting at home and abroad, this paper studies the definition, classification and calculation of logistics volume, and expounds in detail. It analyzes and introduces the problems of imperfect indexes and lack of data existing in logistics statistics in China, and puts forward the following suggestions: By analyzing the main processes and links of different goods participating in logistics activities, the freight volume index is selected as the main research object, and the Conversion Coefficient of Logistics volume is studied. And Freight volume, namely CCLF, chooses several typical goods such as coal, grain and so on as the representative, carries on the example analysis and the computation respectively to its route logistics quantity and the node logistics quantity CCLF to obtain the result. The CCLF coefficients between freight volume, i.e. the grain of line logistics volume and the node logistics volume of fresh agricultural products, are 5.33644 and 6.6565 respectively.
【学位授予单位】：长安大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F259.2
本文编号：2176409
[Abstract]:With the rapid development of social economy, the development of logistics industry in recent years has been more and more strongly supported and advocated by the state and government departments, and the construction and planning of logistics parks have arisen. Parameters are the main support of logistics system planning, and also one of the important parameters of logistics system scale planning. It has important guiding significance for the design and layout of some logistics-related facilities and the selection of corresponding logistics equipment in logistics nodes. There is no such index as logistics volume in the statistical index, and a comparatively perfect statistical index system of logistics has not been established. As far as the current theoretical research and practical activities on logistics volume are concerned, the definition of logistics volume connotation is not clear enough. In addition, there is no uniform measurement standard for statistical caliber, and it has not yet reached one. As a result, in the actual logistics planning and construction, due to the lack of relevant statistical data of the logistics volume of the whole society, people often adopt approximate or analogical methods, generally using freight volume instead of logistics volume to carry out the demand analysis of logistics-related nodes or parks, etc. The results obtained by this method are generally unreasonable. Because of the close relationship between the logistics volume and the freight volume, it is urgent and necessary to obtain the conversion coefficient between the logistics volume and the freight volume on the basis of the existing statistical data of the freight volume. The article hopes that through the quantitative analysis and research of logistics quantity, it can provide more accurate and credible logistics flow data for the future logistics node planning, and provide some ideas and directions for the future statistical research of logistics quantity index in logistics statistics, so as to better promote the development of logistics statistics in China.
On the basis of the research on the theories of logistics volume and logistics volume forecasting at home and abroad, this paper studies the definition, classification and calculation of logistics volume, and expounds in detail. It analyzes and introduces the problems of imperfect indexes and lack of data existing in logistics statistics in China, and puts forward the following suggestions: By analyzing the main processes and links of different goods participating in logistics activities, the freight volume index is selected as the main research object, and the Conversion Coefficient of Logistics volume is studied. And Freight volume, namely CCLF, chooses several typical goods such as coal, grain and so on as the representative, carries on the example analysis and the computation respectively to its route logistics quantity and the node logistics quantity CCLF to obtain the result. The CCLF coefficients between freight volume, i.e. the grain of line logistics volume and the node logistics volume of fresh agricultural products, are 5.33644 and 6.6565 respectively.
【学位授予单位】：长安大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F259.2
【参考文献】
相关期刊论文 前10条
1 赵晓卓;苏德勤;韩增林;;现代物流综合统计指标体系构建探讨[J];商业研究;2006年02期
2 初良勇,田质广,谢新连;组合预测模型在物流需求预测中的应用[J];大连海事大学学报;2004年04期
3 张宝X;张宝一;;基于BP神经网络的非线性函数拟合[J];电脑知识与技术;2012年27期
4 曲昭仲;毛禹忠;;对物流业核算指标与指标体系完善的探讨[J];经济师;2007年07期
5 董艳;叶怀珍;;物流量概念界定及其内涵分析[J];交通运输工程与信息学报;2006年03期
6 沈国华;;区域物流规划预测中物流量内涵探讨[J];武汉交通职业学院学报;2006年02期
7 施学良;戴晓震;;区域物流量预测的灰色GM(1,1)模型应用[J];交通与运输(学术版);2006年02期
8 刘晓叙;;灰色预测与一元线性回归预测的比较[J];四川理工学院学报(自然科学版);2009年01期
9 蒋良奎;组合预测权系数的一种计算方法[J];上海海运学院学报;1996年02期
10 廖伟;贺政纲;;物流量的界定及分类[J];物流工程与管理;2009年08期
相关博士学位论文 前2条
1 管小俊;煤炭物流运输网络风险评价及均衡保持关键问题研究[D];北京交通大学;2010年
2 沈欣;粮食物流园区规划与建设研究[D];东北农业大学;2010年
本文编号：2176409
本文链接：https://www.wllwen.com/jingjilunwen/jingjiguanlilunwen/2176409.html
