Predictive big data analytics for supply chain demand forecasting: methods, applications, and research opportunities

Seyedan, Seyedeh Mahya; Mafakheri, Fereshteh

doi:10.1186/s40537-020-00329-2

Cited by 230 publications

(116 citation statements)

References 122 publications

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“…Data analytics is used, for example, to predict customer behavior and future demands. This prediction possibility enables long-term, detailed planning and the early identification of increased uncertainties and risks (Seyedan and Mafakheri, 2020). The early identification of events increases the planning and preparation flexibility for companies.…”

Section: Discussionmentioning

confidence: 99%

Informal governance in the digital transformation

Keller

Burkhardt

Lasch

2021

IJOPM

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PurposeThe purpose of this study is to explore if and how informal governance mechanisms are used for coordinating actors of digitalized supply networks.Design/methodology/approachA multiple case study analysis of ten German firms in digitalized supply networks is conducted. Data are collected through semi-structured expert interviews with interviewees having notable years of professional experience in purchasing or sales.FindingsThis research shows that reduced personal contacts in digitalized supply networks decrease the ability to coordinate with informal governance mechanisms. However, the need for informal governance in digitalized supply networks remains when facing supply network disruptions or building new business relationships.Originality/valueThis is the first study examining the role of informal governance mechanisms in digitalized supply networks. Theoretical and practical insights on the changing abilities and needs to use informal governance after the digital transformation are given.

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Section: Discussionmentioning

confidence: 99%

Informal governance in the digital transformation

Keller

Burkhardt

Lasch

2021

IJOPM

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“…It also cuts down intermediaries and serves as a platform for stakeholders to share data in real-time. (7) Predictive big-data analytics in supply chain demand forecasting: The proposed model, built on blockchain technologies, can indeed make use of complementary predictive big-data analytical applications to address future demands through customer behavior analysis, trend analysis, and demand prediction (34). Data collected through the Internet of things (IoT) can also feed real-time data from various sources for big-data analytics (35).…”

Section: Proposal For New Strategies Of the Supply Chain To Meet Pandmentioning

confidence: 99%

“…Data collected through the Internet of things (IoT) can also feed real-time data from various sources for big-data analytics (35). The predictive analytics uses various algorithms (e.g., time-series forecasting, support vector machines, K-nearest-neighbors, neural networks) in supply chain demand forecasting to allow the stakeholders to prepare supplies in advance (34). This could also include artificial intelligence platforms toward data-driven proactive demand forecasting which could be useful during infectious disease outbreaks (35).…”

Section: Proposal For New Strategies Of the Supply Chain To Meet Pandmentioning

confidence: 99%

At the Epicenter of COVID-19–the Tragic Failure of the Global Supply Chain for Medical Supplies

Bhaskar

Tan

Bogers

et al. 2020

Front. Public Health

106

102

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The tragic failure of the global supply chain in the face of the current coronavirus outbreak has caused acute shortages of essential frontline medical devices and personal protective equipment, crushing fear among frontline health workers and causing fundamental concerns about the sustainability of the health system. Much more coordination, integration, and management of global supply chains will be needed to mitigate the impact of the pandemics. This article describes the pressing need to revisit the governance and resilience of the supply chains that amplified the crisis at pandemic scale. We propose a model that profiles critical stockpiles and improves production efficiency through new technologies such as advanced analytics and blockchain. A new governance system that supports intervention by public-health authorities during critical emergencies is central to our recommendation, both in the face of the current crisis and to be better prepared for potential future crises. These reinforcements offer the potential to minimize the compromise of our healthcare workers and health systems due to infection exposure and build capacity toward preparedness and action for a future outbreak.

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“…BDA has demonstrated high relevance and applicability to the SCP activities (Brinch, 2018). Advanced analytics, such as forecasting and optimisation techniques, provide fundamental support to demand planning, production planning, inventory plans and logistics planning by improving planning accuracy and flexibility (Russom, 2011; Seyedan and Mafakheri, 2020; Wang et al , 2016).…”

Section: Research Backgroundmentioning

confidence: 99%

On relating big data analytics to supply chain planning: towards a research agenda

Pero

Ciccullo

et al. 2021

IJPDLM

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PurposeThis paper aims to examine how the extant publication has related big data analytics (BDA) to supply chain planning (SCP). The paper presents a conceptual model based on the reviewed articles and the dominant research gaps and outlines the research directions for future advancement.Design/methodology/approachBased on a systematic literature review, this study analysed 72 journal articles and reported the descriptive and thematic analysis in assessing the established body of knowledge.FindingsThis study reveals the fact that literature on relating BDA to SCP has an ambiguous use of BDA-related terminologies and a siloed view on SCP processes that primarily focuses on the short-term. Looking at the big data sources, the objective of adopting BDA and changes to SCP, we identified three roles of big data and BDA for SCP: supportive facilitator, source of empowerment and game-changer. It bridges the conversation between BDA technology for SCP and its management issues in organisations and supply chains according to the technology-organisation-environmental framework.Research limitations/implicationsThis paper presents a comprehensive examination of existing literature on relating BDA to SCP. The resulted themes and research opportunities will help to advance the understanding of how BDA will reshape the future of SCP and how to manage BDA adoption towards a big data-driven SCP.Originality/valueThis study is unique in its discussion on how BDA will reshape SCP integrating the technical and managerial perspectives, which have not been discussed to date.

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Predictive big data analytics for supply chain demand forecasting: methods, applications, and research opportunities

Cited by 230 publications

References 122 publications

Informal governance in the digital transformation

Informal governance in the digital transformation

At the Epicenter of COVID-19–the Tragic Failure of the Global Supply Chain for Medical Supplies

On relating big data analytics to supply chain planning: towards a research agenda

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