Research On Operational Efficiency Models Of Logistics Providers And Logistics Industry In Big Data Environment

In the background of information and digitalization,big data is increasingly becoming an important resource for firms’ operation and industrial development,big data and big data analytics(BDA)have an important impact on the firms’ operational performance as well as the operation and optimization of supply chain and industrial chain.This dissertation focuses on the evaluation and optimization of the operational efficiency for logistics providers and regional logistics industry in the big data environment and the explortion of their impact mechanisms respectively,aiming to provide theoretical support for the firms and government to make decisions on the investment and operation concerning logistics providers and logistics industry in the big data environment.Therefore,this dissertation integrates and constructs the SBM model with undesirable outputs,two-stage DEA model with shared inputs,hierarchical regression analysis and structural equation model,using the primary data from 100 logistics providers and their customer firms(216)collected and the secondary data(industrial data)from data platform and statistical yearbooks to conduct empirical analysis.First,focusing on the dimension of logistics providers and their customer firms,based on the integration of DEA model and regression analysis,this dissertation constructs the model of assessing firms’ operational efficiency under the perspective of investment in big data analytics and supply chain management,and uses the collected sample data of logistics providers and their customer firms for empirical analysis to measure,analyze and compare the operational efficiency of logistics providers and their customer firms.Furthermore,this dissertation explores the effect of the investment in big data analytics and investment in supply chain management,as well as the interaction term on the operational efficiency of logistics providers and customer firms.Secondly,this dissertation further divides the firms’ internal operation mechanism driven by big data analytics into the stage of big data business analytics and supply chain operation,as well as the stage of the transformation of supply chain performance and firms’ competitive advantage,and constructs the two-stage DEA model with shared inputs to measure and analyze the overall operational efficiency and the efficiency of two sub-stages for logistics providers and customer firms.In addition,by constructing the hierarchical regression model,this dissertation explores the main effects and interaction effects of resource investment factors,such as investment in big data analytics and investment in supply chain management,as well as capability factors,such as big data analytics capability and supply chain agility,on the overall operational efficiency of firms driven by big data analytics.Then,based on the research perspective of big data analytics capability and supply chain operation,this dissertation constructs the model of organizational performance improvement driven by big data analytics capability with supply chain integration as the moderator and supply chain agility as the mediator.This dissertation further explores how the big data analytics capability of firms affects supply chain agility and organizational performance,what the role of supply chain agility plays in the effect mechanism of big data analytics capability on the organizational performance,and how supply chain integration moderates big data analytics capability,so as to improve supply chain agility and organizational performance.Finally,focusing on the exploratory perspective of logistics industry efficiency,this dissertation constructs the mathematical model of evaluating regional logistics efficiency and performance(economic performance and environmental performance)in the big data environment,to measure and analyze the regional logistics efficiency,and further provides the benchmarks and suggestions for efficiency improvement for the relatively inefficient regions through benchmark analysis.In addition,this dissertation explores the effect of internal and external factors of logistics industry on the regional logistics efficiency,economic performance and environmental performance for different regions and periods.