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Download fileData supply chain (DSC): Research synthesis and future directions
journal contribution
posted on 2017-10-26, 13:17 authored by Konstantina Spanaki, Zeynep Gurguc, Richard Adams, Catherine MulliganIn the digital economy, the volume, variety and availability of data produced in myriad forms from a diversity of sources has become an important resource for competitive advantage, innovation opportunity as well as source of new
management challenges. Building on the theoretical and empirical foundations of
the traditional manufacturing Supply Chain (SC), which describes the flow of physical artefacts as raw materials through to consumption, we propose the Data Supply Chain (DSC) along which data are the primary artefact flowing. The purpose of this paper is to outline the characteristics and bring conceptual
distinctiveness to the context around DSC as well as to explore the associated and
emergent management challenges and innovation opportunities. To achieve this,
we adopt the systematic review methodology drawing on the operations management and supply chain literature and, in particular, taking a framework synthetic approach which allows us to build the DSC concept from the preexisting SC template. We conclude the paper by developing a set of propositions
and outlining an agenda for future research that the DSC concept implies.
Funding
This work was supported by the Engineering and Physical Sciences Research Council (EPSRC -Research Councils UK) under Grant EP/K039504/1.
History
School
- Business and Economics
Department
- Business
Published in
International Journal of Production ResearchVolume
56Issue
13Pages
4447-4466Citation
SPANAKI, K. ...et al., 2018. Data supply chain (DSC): Research synthesis and future directions. International Journal of Production Research, 56 (13), pp.4447-4466.Publisher
© Taylor & FrancisVersion
- AM (Accepted Manuscript)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Acceptance date
2017-10-15Publication date
2017-11-09Copyright date
2018Notes
This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research on 9 November 2017, available online: http://www.tandfonline.com/10.1080/00207543.2017.1399222.ISSN
0020-7543Publisher version
Language
- en