Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience

By Rameshwar Dubey, Angappa Gunasekaran, Stephen J. Childe, Samuel Fosso Wamba, David Roubaud, Cyril R. H. Foropon. International Journal of Production Research, 2019

822 citations recorded by the source corpus.

Supply chain resilience and data analytics capability have generated increased interest in academia and among practitioners. However, existing studies often treat these two streams of literature independently. Our study model reconciles two different streams of literature: data analytics capability as a means to improve information-processing capacity and supply chain resilience as a means to reduce a ripple effect in supply chain or quickly recover after disruptions in the supply chain. We have grounded our theoretical model in the organisational information processing theory (OIPT). Four research hypotheses are tested using responses from 213 Indian manufacturing organisations collected via a pre-tested survey-based instrument. We further test our model using variance-based structural equation modelling, popularly known as PLS-SEM. All of the hypotheses were supported. The findings of our study offer a unique contribution to information systems (IS) and operations management (OM) literature. The findings further provide numerous directions to the supply chain managers. Finally, we note our study limitations and provide further research directions.

Subfields: Artificial Intelligence, Management Information Systems, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/c8f3f3341c1222fa8141fedeef353aa58f51161d

How researchers see this paper

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

In Artificial Intelligence

In Management Information Systems

In Strategy and Management

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, positive): “…(C) refers to the combination of tools, techniques, and processes for integrating structured, semi-structured, and unstructured data from different sources into processable information as a basis for decisionmaking (Biswas & Sen, 2016; Dubey et al., 2021; Er Kara et al., 2020; Ivanov et al., 2019).”
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).”
A supervised machine learning approach to data-driven simulation of resilient supplier selection in digital manufacturing (2019, background): “Digital technologies enable ﬂexible decision-making by providing real-time data for all parts of the SC [20, 70, 71].”
Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case (2020, neutral): “The understanding and progressing the research of how all these technologies can be used to operate the SCs in a resilient way in cases of epidemic outbreaks is an important future research area (Choi et al., 2017 (Choi et al., , 2019 Choi and Lambert, 2017b , Dubey et al., 2019a , Ganasegeran and A”
Disruption risks in supply chain management: a literature review based on bibliometric analysis (2020, methodology): “…to combine different methodologies, such as quantitative modelling (Fahimnia et al. 2015), simulations (Ivanov 2018, 2019), and empirical studies (Dubey et al. 2019a, 2019b; Ambulkar, Blackhurst, and Grawe 2015; Mishra et al. 2016), to mutually justify the correctness of the proposed managerial…”
Supply Chain Viability and the COVID-19 pandemic: a conceptual and formal generalisation of four major adaptation strategies (2021, background): “…for SC adaptation Technology adoption in SCs has reached an unprecedented scale, entailing inherent adaptability inside the SCs themselves (Blackhurst, Das, and Ivanov 2021; Dubey et al. 2021; Frazzon, Freitag, and Ivanov 2021; Ivanov and Dolgui 2020a; Ivanov, Dolgui, and Sokolov 2019).”
Internet of Things and Big Data as enablers for business digitalization strategies (2020, background): “Velocity indicates the speediness of data generation (Dubey et al., 2019) due to real-time and continuous connections.”
Blockchain adoption in operations and supply chain management: empirical evidence from an emerging economy (2020, methodology): “When a single respondent is used, a common method bias (CMB), also known as common method variance (CMV), can appear (Chua et al. 2018; Dubey et al. 2019).”
Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic (2020, methodology): “Altay et al. (2018); Dubey et al. (2019b), and Ivanov et al. (2018a) organized a debate around the intersections of flexibility, agility and uncertainty and developed the discussion towards the roles of agility and flexibility in achieving SC resilience.”
Blockchain-oriented dynamic modelling of smart contract design and execution in the supply chain (2019, background): “…time, recent production and supply chain literature calls for new methodical approaches to real-time capabilities in the SC (Cavalcantea et al. 2019; Queiroz and Wamba 2018; Oliveira and Handﬁeld 2019; Dubey, Gunasekaran, Childe, Blome, et al. 2019; Dubey, Gunasekaran, Childe, Wamba, et al. 2019).”
Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review (2022, background): “For example, it has been found that insights stemming from the processing of large datasets using BDA techniques can improve operation performance especially when such data come from multiple sources (Dubey, Gunasekaran, et al., 2021).”