The Use of Big Data Analytics to Improve the Supply Chain Performance in Logistics Industry

Xiang, Lai Yin; Hwang, Ha Jin; Kim, Haeng Kon; Mahmood, Monowar; Dawi, Norazryana Mat

doi:10.1007/978-3-030-64773-5_2

Cited by 5 publications

(5 citation statements)

References 6 publications

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“…In the empirical results of our study, all direct hypotheses (H1, H2 and H3) were accepted, which confirmed the positive role of all exogenous constructs. We found that BDAC positively affected SCP in the Jordanian manufacturing sector, a result consistent with several studies in the SCM literature (Dubey et al ., 2018; Kalaitzi and Tsolakis, 2022; Mandal, 2018; Seyedan and Mafakheri, 2020; Xiang et al ., 2021). These studies emphasized that BDA enhance operational excellence through using processed BD in decision-making (Chae et al ., 2014).…”

Section: Discussionmentioning

confidence: 99%

“…Dubey et al . (2018), Mandal (2018), Seyedan and Mafakheri (2020) and Xiang et al . (2021) have confirmed that BDA provide many unique advantages in the SC by developing predictive models that accurately predict supply and demand, enhance the efficiency of production processes and deliver products to end customers.…”

Section: Literature and Hypothesis Developmentmentioning

confidence: 95%

“…In the SCM setting, BDAC is a firm's ability to collect and organise data related to the SC from heterogeneous systems and to analyse this data to make accurate decisions and build a superior and proactive SCM system (Arunachalam et al, 2018). Dubey et al (2018), Mandal (2018), Seyedan and Mafakheri (2020) and Xiang et al (2021) have confirmed that BDA provide many unique advantages in the SC by developing predictive models that accurately predict supply and demand, enhance the efficiency of production processes and deliver products to end customers. These in turn create value in the SC and lead to higher performance levels.…”

Section: Bdac and Scpmentioning

confidence: 99%

“…First, we provided a greater understanding of how firms can exploit BDA in the SC. They can use their organisational data-oriented capabilities to improve SCP by improving their operational efficiency, reducing potential risks (Seyedan and Mafakheri, 2020; Xiang et al ., 2021) and adding new value to increase customer satisfaction with products (Kalaitzi and Tsolakis, 2022).…”

Section: Implications and Conclusionmentioning

confidence: 99%

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Big data analytics capabilities and supply chain performance: testing a moderated mediation model using partial least squares approach

Al-Khatib

Ramayah²

2023

BPMJ

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PurposeIn this study, the authors investigate the effect of big data analytics capability (BDAC) on supply chain performance (SCP) to assess the mediating effect of supply chain innovation (SCI) and the moderating effect of a data-driven culture (DDC).Design/methodology/approachThe authors collected the primary data through an online questionnaire survey from the manufacturing sector operating in Jordan. The authors used 420 samples for the final data analysis, which the authors performed via partial least squares structural equation modelling using SmartPLS 3.3.9 software.FindingsThe results indicate that BDAC has a strong relationship with SCI and SCP. SCI shows a positive relationship with SCP as well as a mediating effect on SCI. The authors confirmed that DDC moderated the relationship between SCI and SCP.Originality/valueThe authors developed a conceptual and empirical model to investigate the relationship between BDAC, SCI, DDC and SCP. The authors contributed new theoretical and managerial insights that add value to the supply chain management literature through testing the moderated-mediated model of these constructs in Jordan’s manufacturing sector.

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Section: Discussionmentioning

confidence: 99%

Section: Literature and Hypothesis Developmentmentioning

confidence: 95%

Section: Bdac and Scpmentioning

confidence: 99%

Section: Implications and Conclusionmentioning

confidence: 99%

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Big data analytics capabilities and supply chain performance: testing a moderated mediation model using partial least squares approach

Al-Khatib

Ramayah²

2023

BPMJ

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“…Automated location-sensing creates such a system and is generally achieved by a combination of triangulation, scene analysis and proximity (Hightower and Borriello, 2001). This conjecture has been borne out by recent developments in mobile computing power to drive new modes of logistics tracking and supply chain performance improvements (Xiang et al , 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

Construction tracking: implications of logistics data

Maxwell

Couper

2022

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Purpose Construction suffers from “peculiarities” that concern the temporary natures of the construction site, project teams and unique product design. Considering the digital transformation of construction, new solutions are being investigated that can provide consistent data between changing projects. One such source of data manifests in the tracking of logistics activities across the supply chain. Construction logistics is traditionally considered a site management activity focused solely on the “back end” of projects, but an expanded logistics focus can unlock new avenues of improvement. This study aims to understand the requirements and benefits of such a consistent thread of data. Design/methodology/approach From a research project with one of Australia’s largest contracting companies, this paper details a series of construction tracking tests as an empirical case study in using Bluetooth low energy aware tracking technology to capture data across the manufacture, delivery and assembly of a cross-laminated timber structural prototyping project. Findings The findings affirm the tracking of expanded logistics data can improve back-end performance in subsequent projects while also demonstrating the opportunity to inform a project’s unique front-end design phase. The case study demonstrates that as the reliability, range and battery life of tracking technologies improve, their incorporation into a broader range of construction activities provides invaluable data for improvement across projects. Originality/value As a live case study, this research offers unique insights into the potential of construction tracking to close the data loop from final site assembly back to the early project design phase, thus driving continual improvement from a holistic perspective.

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Agile supply chain analytic approach: a case study combining agile and CRISP-DM in an end-to-end supply chain

Hamdani

Quintero

Enjolras

et al. 2022

Supply Chain Forum: An International Journal

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The Use of Big Data Analytics to Improve the Supply Chain Performance in Logistics Industry

Cited by 5 publications

References 6 publications

Big data analytics capabilities and supply chain performance: testing a moderated mediation model using partial least squares approach

Big data analytics capabilities and supply chain performance: testing a moderated mediation model using partial least squares approach

Construction tracking: implications of logistics data

Agile supply chain analytic approach: a case study combining agile and CRISP-DM in an end-to-end supply chain

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