Offline-to-Online Service and Big Data Analysis for End-to-end Freight Management System
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초록
Freight management systems require a new business model for rapid decision making to improve their businessprocesses by dynamically analyzing the previous experience data. Moreover, the amount of data generated bydaily business activities to be analyzed for making better decisions is enormous. Onlinetooffline or offlinetoonline (O2O) is an electronic commerce (ecommerce) model used to combine the online and physicalservices. Data analysis is usually performed offline. In the present paper, to extend its benefits to online and toefficiently apply the big data analysis to the freight management system, we suggested a system architecturebased on O2O services. We analyzed and extracted the useful knowledge from the realtime freight data for theperiod 2014–2017 aiming at further business development. The proposed system was deemed useful for truckmanagement companies as it allowed dynamically obtaining the big data analysis results based on O2Oservices, which were used to optimize logistic freight, improve customer services, predict customer expectation,reduce costs and overhead by improving profit margins, and perform load balancing.
Abstract
Freight management systems require a new business model for rapid decision making to improve their businessprocesses by dynamically analyzing the previous experience data. Moreover, the amount of data generated bydaily business activities to be analyzed for making better decisions is enormous. Onlinetooffline or offlinetoonline (O2O) is an electronic commerce (ecommerce) model used to combine the online and physicalservices. Data analysis is usually performed offline. In the present paper, to extend its benefits to online and toefficiently apply the big data analysis to the freight management system, we suggested a system architecturebased on O2O services. We analyzed and extracted the useful knowledge from the realtime freight data for theperiod 2014–2017 aiming at further business development. The proposed system was deemed useful for truckmanagement companies as it allowed dynamically obtaining the big data analysis results based on O2Oservices, which were used to optimize logistic freight, improve customer services, predict customer expectation,reduce costs and overhead by improving profit margins, and perform load balancing.
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