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Cited by 118 publications
(62 citation statements)
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References 77 publications
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“… Reactive strategies Lifeline maintenance Transportation system and lifeline during disruption should be maintained, as loss of the lifeline and transport systems would affect the entire supply chain of the manufacturing sector Graveline and Grémont (2017) , HYPERLINK \l "bib37" Ivanov et al., (2016); Haraguchi and Lall (2015) BDA-driven and real-time information system Supply chain information systems use Big Data Analytics (BDA) capabilities to collect, process, and extract meaningful insights from real-time data across the overall supply chain to support suitable and timely decision-making. Kamble and Gunasekaran (2020) , Belhadi et al., (2019) Virtual marketplaces Refers to the development of digital marketplace for delivering the products and services. Sharifi et al., (2006) , Kamble et al., (2020 a) Supply chain simulation Simulation is a proven way to support multi-criteria decision making while tackling uncertainty and complexity related to supply chains Ivanov and Dolgui (2020) , HYPERLINK \l "bib23" Hofmann et al., (2019); Kamble et al., (2018) Supply chain collaboration Firms at every tier of the supply chain should work closely together to meet shared objectives of recovery and help each other to mitigate disruption impact Barrane et al., (2020) , Villena and Gioia (2018) ; Zhu et al., (2017) Inventories and reserve capacity Supply chains use inventory and reserve capacity to mitigate the negative effects caused by the disruption.…”
Section: Theoretical Background and Literature Reviewmentioning
confidence: 99%
“… Reactive strategies Lifeline maintenance Transportation system and lifeline during disruption should be maintained, as loss of the lifeline and transport systems would affect the entire supply chain of the manufacturing sector Graveline and Grémont (2017) , HYPERLINK \l "bib37" Ivanov et al., (2016); Haraguchi and Lall (2015) BDA-driven and real-time information system Supply chain information systems use Big Data Analytics (BDA) capabilities to collect, process, and extract meaningful insights from real-time data across the overall supply chain to support suitable and timely decision-making. Kamble and Gunasekaran (2020) , Belhadi et al., (2019) Virtual marketplaces Refers to the development of digital marketplace for delivering the products and services. Sharifi et al., (2006) , Kamble et al., (2020 a) Supply chain simulation Simulation is a proven way to support multi-criteria decision making while tackling uncertainty and complexity related to supply chains Ivanov and Dolgui (2020) , HYPERLINK \l "bib23" Hofmann et al., (2019); Kamble et al., (2018) Supply chain collaboration Firms at every tier of the supply chain should work closely together to meet shared objectives of recovery and help each other to mitigate disruption impact Barrane et al., (2020) , Villena and Gioia (2018) ; Zhu et al., (2017) Inventories and reserve capacity Supply chains use inventory and reserve capacity to mitigate the negative effects caused by the disruption.…”
Section: Theoretical Background and Literature Reviewmentioning
confidence: 99%
“…At present, most of the areas of business are linked to big data. It has significant influence on various perspectives of business such as business process management, human resources management, R&D management [8,63], business analytics [19,26,42,59,63], B2B business process, marketing, and sales [30,39,53,58], industrial manufacturing process [7,15,40], enterprise's operational performance measurement [20,69,81], policy making [2], supply chain management, decision, and performance [4,38,64], and so other business arenas.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Also, big data impact on industrial manufacturing process to gain competitive advantages. After analyzing a case study of two company, Belhadi et al [7] stated 'NAPC aims for a qualitative leap with digital and big-data analytics to enable industrial teams to develop or even duplicate models of turnkey factories in Africa' . This study also identified an Overall framework of BDA capabilities in manufacturing process, and mentioned some values of Big Data Analytics for manufacturing process, such as enhancing transparency, improving performance, supporting decision-making and increasing knowledge.…”
Section: Literature Reviewmentioning
confidence: 99%
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“…At present, most of the business areas are connected to big data. Big data has a critical effect on different dimensions of businesses, for example, in terms of human resources management, research, and development [27,28]; management processes [27,[29][30][31]; business to business processes, advertising, and marketing [32,33]; mechanical assembling measures [34][35][36]; enterprises' operational performance [36,37]; policy-making [38]; and supply chain management [38,39]. In particular, Rabhi, Falih [27] referenced big data as a noteworthy factor of business measure management and HR cycles to help in the decision-making process.…”
Section: Literature Reviewmentioning
confidence: 99%