Big data analytics in logistics and supply chain management: Certain investigations for research and applications

Abstract

The amount of data produced and communicated over the Internet is significantly increasing, thereby creating challenges for the organizations that would like to reap the benefits from analyzing this massive influx of big data. This is because big data can provide unique insights into, inter alia, market trends, customer buying patterns, and maintenance cycles, as well as into ways of lowering costs and enabling more targeted business decisions. Realizing the importance of big data business analytics (BDBA), we review and classify the literature on the application of BDBA on logistics and supply chain management (LSCM) -that we define as supply chain analytics (SCA), based on the nature of analytics (descriptive, predictive, prescriptive) and the focus of the LSCM (strategy and operations). To assess the extent to which SCA is applied within LSCM, we propose a maturity framework of SCA, based on four capability levels, that is, functional, process-based, collaborative, agile SCA, and sustainable SCA. We highlight the role of SCA in LSCM and denote the use of methodologies and techniques to collect, disseminate, analyze, and use big data driven information. Furthermore, we stress the need for managers to understand BDBA and SCA as strategic assets that should be integrated across business activities to enable integrated enterprise business analytics. Finally, we outline the limitations of our study and future research directions.

Managing Capabilities for Supply Chain Resilience Through it Integration

“…There are also other researches that amplified the collaboration benefits (Zhao et al, 2016;Bosona & Gebresenbet, 2011;Kim et al, 2015;Wang et al, 2016). The collaboration approach is based on a theoretical aspect of improvement of the efficiency of the chain, e. g., partial freight collection, information sharing, etc.…”

“…However, they did not consider collaboration and resilience aspects. Wang et al (2016) Goncalves & Chicareli (2014) identified capabilities that make the largest contribution to resilience flexibility (supplier, product, process, transportation), collaboration (information sharing, joined decision making, working together), structure of chain (physical, information), and agility (visibility, velocity). Goncalves and Chiricareli amplifies that empirical studies about most suitable management capabilities before, during a after a distribution in the supply chain is needed.…”

“…One of the most amplified capabilities is collaboration (Zhao, Liu, Zhang & Huang, 2016;Bosona & Gebresenbet, 2011;Kim et al, 2015;Wang, Gunasekaran, Ngai & Papadopoulos, 2016). Collaboration is based on certain computability, commitment, _______________________________________________________________ 2017 / 31 32 and capabilities.…”

“…The benefits and approaches to collaboration have been widely researched; however, the main research gap is that the most amplified resilience strategy is based on collaboration, which enables the supply chain members to share information and commitments and gain resilience. However, the strategy is based on unclear commitments and decreases the turnover rate of the working capital, because it recommends gaining flexibility by increasing redundancy (Zhao et al, 2016;Bosona & Gebresenbet, 2011;Kim et al, 2015;Wang et al, 2016). A large number of members in the collaboration process can provide better efficiency levels in terms of costs; however, it limits the ability of the collaboration to cope with disturbances by increasing the complexity and limiting the visibility.…”

Big data and the transformation of operations models: a framework and a new research agenda

“…The initial search for articles connecting Big Data with operations models was conducted using the Scopus database 1 , identifying 668 articles. As suggested by Wang et al, (2016) we then intuitively checked through all the titles and only included those articles in which: "big data technologies were not only considered as possible new tools for enterprise operation, but which were also triggering impacts in the management (operations and supply chain management) arena" (p. 98). This resulted in 200 articles which were retained for further analysis.…”