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http://dx.doi.org/10.3745/JIPS.01.0051

Offline-to-Online Service and Big Data Analysis for End-to-end Freight Management System  

Selvaraj, Suganya (Dept. of Financial Information Security, Kookmin University)
Kim, Hanjun (Dept. of Financial Information Security, Kookmin University)
Choi, Eunmi (Dept. of Financial Information Security, Kookmin University)
Publication Information
Journal of Information Processing Systems / v.16, no.2, 2020 , pp. 377-393 More about this Journal
Abstract
Freight management systems require a new business model for rapid decision making to improve their business processes by dynamically analyzing the previous experience data. Moreover, the amount of data generated by daily business activities to be analyzed for making better decisions is enormous. Online-to-offline or offline-to-online (O2O) is an electronic commerce (e-commerce) model used to combine the online and physical services. Data analysis is usually performed offline. In the present paper, to extend its benefits to online and to efficiently apply the big data analysis to the freight management system, we suggested a system architecture based on O2O services. We analyzed and extracted the useful knowledge from the real-time freight data for the period 2014-2017 aiming at further business development. The proposed system was deemed useful for truck management companies as it allowed dynamically obtaining the big data analysis results based on O2O services, 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.
Keywords
Big Data Analysis; Freight Management System; O2O Service; System Architecture;
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Times Cited By KSCI : 5  (Citation Analysis)
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