Adaptive Cloud-Based Big Data Analytics Model for Sustainable Supply Chain Management

被引:1
作者
Stefanovic, Nenad [1 ]
Radenkovic, Milos [2 ]
Bogdanovic, Zorica [3 ]
Plasic, Jelena [1 ]
Gaborovic, Andrijana [1 ]
机构
[1] Univ Kragujevac, Fac Tech Sci Cacak, Cacak 32000, Serbia
[2] Union Univ, Sch Comp, Belgrade 11000, Serbia
[3] Univ Belgrade, Fac Org Sci, Belgrade 11010, Serbia
关键词
big data; sustainable supply chain; business intelligence; analytics; machine learning; model; cloud computing; PREDICTIVE ANALYTICS;
D O I
10.3390/su17010354
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Due to uncertain business climate, fierce competition, environmental challenges, regulatory requirements, and the need for responsible business operations, organizations are forced to implement sustainable supply chains. This necessitates the use of proper data analytics methods and tools to monitor economic, environmental, and social performance, as well as to manage and optimize supply chain operations. This paper discusses issues, challenges, and the state of the art approaches in supply chain analytics and gives a systematic literature review of big data developments associated with supply chain management (SCM). Even though big data technologies promise many benefits and advantages, the prospective applications of big data technologies in sustainable SCM are still not achieved to a full extent. This necessitates work on several segments like research, the design of new models, architectures, services, and tools for big data analytics. The goal of the paper is to introduce a methodology covering the whole Business Intelligence (BI) lifecycle and a unified model for advanced supply chain big data analytics (BDA). The model is multi-layered, cloud-based, and adaptive in terms of specific big data scenarios. It comprises business process modeling, data ingestion, storage, processing, machine learning, and end-user intelligence and visualization. It enables the creation of next-generation BDA systems that improve supply chain performance and enable sustainable SCM. The proposed supply chain BDA methodology and the model have been successfully applied in practice for the purpose of supplier quality management. The solution based on the real-world dataset and the illustrative supply chain case are presented and discussed. The results demonstrate the effectiveness and applicability of the big data model for intelligent and insight-driven decision making and sustainable supply chain management.
引用
收藏
页数:26
相关论文
共 44 条
  • [1] Accenture, Big Data Analytics in Supply Chain: Hype or Here to Stay?
  • [2] Adewusi AO., 2024, Comput Sci IT Res J, V5, P415, DOI [10.51594/csitrj.v5i2.791, DOI 10.51594/CSITRJ.V5I2.791]
  • [3] Artificial Intelligence Approach to Predict Supply Chain Performance: Implications for Sustainability
    Ali, Syed Mithun
    Rahman, Amanat Ur
    Kabir, Golam
    Paul, Sanjoy Kumar
    [J]. SUSTAINABILITY, 2024, 16 (06)
  • [4] [Anonymous], 2010, Supply Chain Sustainability
  • [5] [Anonymous], 2015, ObviEnce Supplier Quality Dataset
  • [6] Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges and implications for practice
    Arunachalam, Deepak
    Kumar, Niraj
    Kawalek, John Paul
    [J]. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2018, 114 : 416 - 436
  • [7] Using Big Data for Sustainability in Supply Chain Management
    Chalmeta, Ricardo
    Barqueros-Munoz, Jose-Eduardo
    [J]. SUSTAINABILITY, 2021, 13 (13)
  • [8] How the Use of Big Data Analytics Affects Value Creation in Supply Chain Management
    Chen, Daniel Q.
    Preston, David S.
    Swink, Morgan
    [J]. JOURNAL OF MANAGEMENT INFORMATION SYSTEMS, 2015, 32 (04) : 4 - 39
  • [9] Cohen A.M., 2015, Harv. Bus. Rev, V94, P1
  • [10] Columbus L., Ten Ways Big Data Is Revolutionizing Supply Chain Management