Cloud enabled big data business platform for logistics services: A research and development agenda

被引：0

作者：

Graduate School of Management, Plymouth University, Plymouth, United Kingdom ^{[1
]}

不详 ^{[2
]}

不详 ^{[3
]}

机构：

[1] Graduate School of Management, Plymouth University, Plymouth

[2] Bournemouth University, Bournemouth

[3] University of Vaasa, Vaasa

来源：

Lect. Notes Bus. Inf. Process. | / 22-33期

关键词：

3/4PL; Big data; Big data analytics; Big data logistics business platform (BDLBP); Business intelligence; Cloud computing;

D O I：

10.1007/978-3-319-18533-0_3

中图分类号：

学科分类号：

摘要：

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. © Springer International Publishing Switzerland 2015.

引用

页码：22 / 33

页数：11

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