Big Data Analytics in Operations Management

By Tsan-Ming (Jason) Choi, Stein W. Wallace, Yulan Wang. 2018

815 citations recorded by the source corpus.

Subfields: Information Systems and Management, Management Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/243d553f1fc5b7ee8cfb6f49629f3a0a32b2c5c5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems and Management

In Management Information Systems

In Management Science and Operations Research

Citations in the corpus

Improving supply chain resilience through industry 4.0: A systematic literature review under the impressions of the COVID-19 pandemic (2021, neutral): “Some scholars consider BDA part of AI and vice versa (Baryannis et al., 2019; Brintrup et al., 2020; Choi et al., 2018).”
Blockchain technology in supply chain operations: Applications, challenges and research opportunities (2020, neutral): “SCM has entered the big data era (Choi et al., 2018; Kuo and Kusiak, 2019), and blockchain technology has emerged as a disruptive technology.”
The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics (2018, background): “…al. (2016), Schrauf and Berttram (2016), Gunasekaran et al. (2016, 2017), Nguyen et al. (2017), Moghaddam and Nof (2017), Hofmann and Rüsch (2017), Choi, Wallace, and Wang (2018), Gunasekaran et al. (2018), Ben-Daya, Hassini, and Bahroun (2018) identi ﬁ ed classi ﬁ cations of different digital…”
A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0 (2020, background): “…uncertainty, structural dynamics and risk analytics (Blackhurst et al. 2005; Ivanov, Sokolov, and Kaeschel 2010; Flynn, Koufteros, and Lu 2016; Ivanov et al. 2018; Choi, Wallace, and Wang 2018; Dubey, Gunasekaran, Childe, Wamba, et al. 2019; Ivanov, Dolgui, and Sokolov 2019; Panetto et al. 2019).”
Big data analytics capability in supply chain agility (2019, background): “Insights derived via big data analysis can provide opportunities for operational improvements (Fosso Wamba et al. 2015; Papadopoulos et al. 2017; Lamba and Singh, 2017; Srinivasan and Swink, 2017; Choi et al. 2017).”
Linkages between big data analytics, circular economy, sustainable supply chain flexibility, and sustainable performance in manufacturing firms (2021, background): “The BDA capabilities enable executives and managers to control the company’s performance in real-time, provide a swift and low-cost investigation of abnormalities and propose adequate prescriptions and actions (Wamba et al. 2020; Choi, Wallace, and Wang 2018).”
Generative artificial intelligence in supply chain and operations management: a capability-based framework for analysis and implementation (2024, neutral): “The SCOM domain is complex and multifaceted, and while the framework captures a broad range of areas within SCOM, a more granular categorisation could provide deeper insights into specific operational and managerial challenges (Choi, Wallace, and Wang 2018).”
Blockchain-oriented dynamic modelling of smart contract design and execution in the supply chain (2019, background): “…the decision-making support in supply chain (SC) management can be considered as good as the digital technology behind it (Dubey, Gunasekaran, Childe, Papadopoulos, et al. 2019; Dubey et al. 2018; Jha et al. 2017; Koh et al. 2017; Ivanov, Dolgui, and Sokolov 2019; Choi, Wallace, and Wang 2018).”
Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic (2020, background): “…(i.e., agile, lean, sustainable, resilient, and digital SC) (Altay et al. 2018; Bier et al. 2020; Blackhurst et al. 2011; Brandenburg and Rebs 2015; Choi et al. 2018; Das et al. 2006; Dolgui et al. 2018; Dubey et al. 2015; Govindan et al. 2016; DuHadway et al. 2019; Hosseini et al. 2019a; Ivanov…”