Abstract
This paper explores the support provided by big data systems developed in the cloud for empowering modern logistics services through fostering synergies among 3/4PL (third /fourth party logistics) in order to establish interoperable or highly integrated and sustainable logistics supply chain services. However, big data applications could have limited capabilities of providing performant logistics services without addressing the quality and accuracy of data. The main outcome of the paper is the definition of an architectural framework and associated research and development agenda for the application of cloud computing for the development and deployment of a Big Data Logistics Business Platform (BDLBP) for supply chain network management services. The capabilities embedded in the BDLBP can provide powerful decision support to logistics networking and stakeholders. Two of the three strategic and operational capabilities as operational capacity planning, and real-time route optimisation are built upon literature based on operational research, and are extended to the scope of dynamic and uncertain situations. The third capability, strategic logistics network planning is currently under researched and this approach aims at covering this capability supported by big data analytics in the cloud.
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Neaga, I., Liu, S., Xu, L., Chen, H., Hao, Y. (2015). Cloud Enabled Big Data Business Platform for Logistics Services: A Research and Development Agenda. In: Delibašić, B., et al. Decision Support Systems V – Big Data Analytics for Decision Making. ICDSST 2015. Lecture Notes in Business Information Processing, vol 216. Springer, Cham. https://doi.org/10.1007/978-3-319-18533-0_3
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