一种基于智慧物流发展水平的区域物流量预测方法  

A Regional Logistics Volume Prediction Method Based on the Development Level of Smart Logistics

作　　者：刘伟华[1] 高永正 侯家和 LIU Weihua;GAO Yongzheng;HOU Jiahe(College of Management and Economics,Tianjin University,Tianjin 300072,China)

机构地区：[1]天津大学管理与经济学部,天津300072

出　　处：《工程管理科技前沿》2024年第4期37-45,共9页Frontiers of Science and Technology of Engineering Management

基　　金：天津市科技计划资助项目(22ZLGCGX00060)。

摘　　要：随着智慧物流的不断发展,全社会物流资源得以更加高效的整合与优化,智慧物流发展水平将会影响区域物流运作方式与效率,进而影响物流量。然而,当前缺乏基于智慧物流发展的区域物流量的有效预测方法。本文构建了一种考虑区域智慧物流发展水平的物流量预测模型。从物流业的经济环境、发展规模、创新活动、智慧技术四个方面构建区域智慧物流发展水平的评价指标体系,并运用因子分析和ARIMA(自回归差分移动平均)模型对智慧物流发展水平进行历史测度和未来预测。在此基础上,构建了基于智慧物流发展水平和历史物流量的区域物流量预测模型,并以T市的实际数据进行实证分析。结果表明,该方法能够充分考虑智慧物流发展的影响,从而更加科学、全面地进行物流量预测。The prediction of regional logistics volume serves as a crucial basis for resource allocation,planning and design of logistics system.With the continuous development of smart logistics,the logistics resources of the whole society have been integrated and optimized more efficiently,and tiers between logistics and commercial circulation have become closer.Consequently,the development level of smart logistics will affect the regional logistics operation mode and efficiency,and thus affect the region logistics volume.However,there is currently a lack of effective prediction methods for regional logistics volume based on the development of smart logistics.Thus,it is necessary to predict regional logistics volume considering the development of smart logistics.This paper constructs a logistics volume prediction model considering the development level of regional smart logistics.First,this paper builds the evaluation index system of the development level of regional smart logistics from the four aspects of the economic environment,development scale,innovative activities,and smart technology of the logistics industry.Second,this paper uses factor analysis and auto-regressive moving average(ARIMA)model to measure the development level of regional smart logistics historically and predict the future.On this basis,this study constructs a regression model to predict regional logistics volume based on the development level of smart logistics and historical logistics volume.Specifically,the factor analysis is applied to eliminate redundant or insignificant information in the evaluation indicators and avoid subjective bias in setting the weights of evaluation indicators.The ARIMA model is utilized to depict the temporal trends of evaluation indicators and estimate the predicted values for the development level of smart logistics.The multivariate regression is employed to capture the correlation between regional logistics volume and smart logistics.This paper also makes an empirical analysis with the actual data of T city in China

关 键 词：智慧物流 发展水平 物流量 因子分析 ARIMA模型 

分 类 号：F273[经济管理—企业管理]