Big data optimisation and management in supply chain management: a systematic literature review

被引:0
作者
Idrees Alsolbi
Fahimeh Hosseinnia Shavaki
Renu Agarwal
Gnana K Bharathy
Shiv Prakash
Mukesh Prasad
机构
[1] Umm Al- Qura University,Department of Information Systems, College of Computer Science and Information Systems
[2] University of Technology Sydney,School of Computer Science
[3] University of Technology Sydney,Business School
[4] University of Technology Sydney,ARDC Research Data Specialist, Faculty of Engineering & Information Technology
[5] University of Allahabad (A Central University),Department of Electronics and Communication
来源
Artificial Intelligence Review | 2023年 / 56卷
关键词
Big data; Big data optimization; Big data management; Supply chain management; Performance measurement; Systematic review;
D O I
暂无
中图分类号
学科分类号
摘要
The increasing interest from technology enthusiasts and organisational practitioners in big data applications in the supply chain has encouraged us to review recent research development. This paper proposes a systematic literature review to explore the available peer-reviewed literature on how big data is widely optimised and managed within the supply chain management context. Although big data applications in supply chain management appear to be often studied and reported in the literature, different angles of big data optimisation and management technologies in the supply chain are not clearly identified. This paper adopts the explanatory literature review involving bibliometric analysis as the primary research method to answer two research questions, namely: (1) How to optimise big data in supply chain management? and (2) What tools are most used to manage big data in supply chain management? A total of thirty-seven related papers are reviewed to answer the two research questions using the content analysis method. The paper also reveals some research gaps that lead to prospective future research directions.
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页码:253 / 284
页数:31
相关论文
共 220 条
[1]  
Addo-Tenkorang R(2016)Big data applications in operations/supply-chain management: a literature review Computers and Industrial Engineering 101 528-543
[2]  
Helo PT(2022)Different approaches of bibliometric analysis for data analytics applications in non-profit organisations J Smart Environ Green Comput 2 90-104
[3]  
Alsolbi I(2018)A review on Data Analytics for Supply Chain Management: a Case study Int J Inform Eng Electron Bus 11 30-975
[4]  
Wu M(2020)A hybrid Artificial neural network, genetic algorithm and Column Generation Heuristic for minimizing Makespan in Manual Order picking Operations Expert Syst Appl vol 113566-156
[5]  
Zhang Y(2017)bibliometrix: an R-tool for comprehensive science mapping analysis J Informetrics 11 959-84
[6]  
Joshi S(2018)The emerging big data analytics and IoT in supply chain management: a systematic review Supply Chain Management 25 141-200
[7]  
Sharma M(2020)Predictors of firm performance and supply chain: evidence from indonesian Pharmaceuticals Industry Int J Supply Chain Manage 9 1080-135
[8]  
Tafavogh S(2017)Big Data and Predictive Analysis is key to Superior Supply Chain performance: a south african experience Int J Inform Syst Supply Chain Manage 10 66-33
[9]  
Sinha A(2018)Managing supply chain resources with Big Data Analytics: a systematic review Int J Logistics 21 177-180
[10]  
Prasad M(2013)Holistically evaluating agent-based social systems models: a case study Simulation 89 102-1614