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A cloud-based supply chain management system: effects on supply chain responsiveness
Open accessAbstract
Purpose Despite the ongoing calls for the incorporation of the cloud utility model, the effect of the cloud on elements of supply chain performance is still an evolving area of research. The purpose of this paper is to develop the architecture of a cloud-based supply chain management (C-SCM) ecosystem and explore how it enhances supply chain responsiveness (SCR). Design/methodology/approach First, the authors discuss the potential benefits that cloud computing can yield, compared to existing mature SCM information systems and solutions through a comprehensive literature review. The authors conceptualise SCR in terms of the level of visibility in the supply chain, supply chain flexibility and rapid detection and reaction to changes, and then the authors build the detailed architecture of a C-SCM system. The proposed ecosystem introduces a view of SCM and the associated practices when transferred to cloud environments. The potential to enhance SCR through the cloud is explored with scenarios on a case of supply chain operations in fashion retail industry. Findings The findings show that the proposed system can enhance all three dimensions of SCR. Implications for supply chain practice and how companies can migrate to a cloud supply chain are drawn. Originality/value Given that the development, creation and delivery of goods and services are increasingly becoming a joint effort of several parties in a supply chain, the authors contribute to the existing literature by introducing a comprehensive C-SCM system and show how companies can enhance their SCR.
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“Most importantly, the data sharing experience provides better collaboration, optimization, and transparency of the supply chain flows for all the stakeholders involved (Giannakis et al., 2019).”
From Metaverse beyond the hype: Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy (2022) · cites this paper as Giannakis et al., 2019
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Metadata
- Authors
- Giannakis, M., Spanaki, K., & Dubey, R.
- Affiliations
- Audencia Business School (FR)
- Loughborough University (GB)
- MBS School of Business (FR)
- Venue
- Journal of Enterprise Information Management
- Publisher
- Emerald
- Published
- 2019-07-03
- Volume
- 32
- Issue
- 4
- Pages
- 585-607
- ISSN
- 1741-0398 (ISSN-L)
- OpenAlex
- W2943850763
- Cited by
- 149
- References
- 82
- Citations by year
- 2026: 12 · 2025: 32 · 2024: 27 · 2023: 28 · 2022: 22 · 2021: 15 · 2020: 11 · 2019: 2
- FWCI
- 21.02
- Type
- journal article
- Language
- en
- Open access
- green
- dspace.lboro.ac.uk
- Licence
- cc-by-nc-nd
- www.emerald.com/insight/site-policies (tdm)
- Locations
- Journal of Enterprise Information Management (publishedVersion)
- Loughborough University Institutional Repository (Loughborough University) (submittedVersion, cc-by-nc-nd)
- Loughborough University Research Repository (Loughborough University) (submittedVersion, cc-by-nc-nd)
- Topics
- Social Sciences › Business, Management and Accounting › Management of Technology and Innovation › Collaboration in agile enterprises
- Social Sciences › Business, Management and Accounting › Management Information Systems › Quality and Supply Management
- Social Sciences › Decision Sciences › Management Science and Operations Research › Supply Chain and Inventory Management
- Keywords
- supply chain responsiveness, cloud computing, supply chain visibility, supply chain flexibility, cloud migration, supply chain information systems
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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