Supply Chain Analytics, Definitions, Characteristics and Applications: A Systematic Literature Review

Desmond Mwangi Wairimu

doi:doi:10.11648/j.ebm.20241005.11

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Supply Chain Analytics, Definitions, Characteristics and Applications: A Systematic Literature Review

Desmond Mwangi Wairimu^*

Published in European Business & Management (Volume 10, Issue 5)

Received: 11 August 2024 Accepted: 2 September 2024 Published: 26 November 2024

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Abstract

While there is a high uptake of BDA in the realm of supply chain management, in the view of automation supply chains and improving their value proposition by providing more accurate data for demand forecasting. There are material knowledge gaps on the SC-specific analytics applied to match demand, albeit the existing knowledge could be more amorphous. From this backdrop, the study endeavored to analyze extant literature within the ambit of BDA to unpack the current trends and possible future research directions to foster the application of BDA in SC contexts. The study adopted a systematic literature review of the extant literature published between 2014-2023. The study adopted the five-stage iterative procedure used in the systematic review methodology. The review's findings depict extensive use of big data analytics in matching demand and supply and supply chain optimization. The findings of this study adduce almost non-rebuttable evidence that big data analytics can be applied in procurement, inventory control, logistics, and order processing. Under the auspices of BDA is the SCA. Arguably, extant research has demonstrated the capability of SCA in mitigating contemporary SC risks such as mismatches between demand and supply, sub-optimal SCs, and underutilization of the supply chain infrastructures at the cusps of various echelons.

Published in	European Business & Management (Volume 10, Issue 5)
DOI	10.11648/j.ebm.20241005.11
Page(s)	76-84
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Supply Chain, Big Data Analytics, Supply Chain Analytics, Systematic Literature Review

References

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APA Style

Wairimu, D. M. (2024). Supply Chain Analytics, Definitions, Characteristics and Applications: A Systematic Literature Review. European Business & Management, 10(5), 76-84. https://doi.org/10.11648/j.ebm.20241005.11

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ACS Style

Wairimu, D. M. Supply Chain Analytics, Definitions, Characteristics and Applications: A Systematic Literature Review. Eur. Bus. Manag. 2024, 10(5), 76-84. doi: 10.11648/j.ebm.20241005.11

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AMA Style

Wairimu DM. Supply Chain Analytics, Definitions, Characteristics and Applications: A Systematic Literature Review. Eur Bus Manag. 2024;10(5):76-84. doi: 10.11648/j.ebm.20241005.11

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@article{10.11648/j.ebm.20241005.11,
  author = {Desmond Mwangi Wairimu},
  title = {Supply Chain Analytics, Definitions, Characteristics and Applications: A Systematic Literature Review
},
  journal = {European Business & Management},
  volume = {10},
  number = {5},
  pages = {76-84},
  doi = {10.11648/j.ebm.20241005.11},
  url = {https://doi.org/10.11648/j.ebm.20241005.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ebm.20241005.11},
  abstract = {While there is a high uptake of BDA in the realm of supply chain management, in the view of automation supply chains and improving their value proposition by providing more accurate data for demand forecasting. There are material knowledge gaps on the SC-specific analytics applied to match demand, albeit the existing knowledge could be more amorphous. From this backdrop, the study endeavored to analyze extant literature within the ambit of BDA to unpack the current trends and possible future research directions to foster the application of BDA in SC contexts. The study adopted a systematic literature review of the extant literature published between 2014-2023. The study adopted the five-stage iterative procedure used in the systematic review methodology. The review's findings depict extensive use of big data analytics in matching demand and supply and supply chain optimization. The findings of this study adduce almost non-rebuttable evidence that big data analytics can be applied in procurement, inventory control, logistics, and order processing. Under the auspices of BDA is the SCA. Arguably, extant research has demonstrated the capability of SCA in mitigating contemporary SC risks such as mismatches between demand and supply, sub-optimal SCs, and underutilization of the supply chain infrastructures at the cusps of various echelons.
},
 year = {2024}
}

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TY  - JOUR
T1  - Supply Chain Analytics, Definitions, Characteristics and Applications: A Systematic Literature Review

AU  - Desmond Mwangi Wairimu
Y1  - 2024/11/26
PY  - 2024
N1  - https://doi.org/10.11648/j.ebm.20241005.11
DO  - 10.11648/j.ebm.20241005.11
T2  - European Business & Management
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JO  - European Business & Management
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PB  - Science Publishing Group
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AB  - While there is a high uptake of BDA in the realm of supply chain management, in the view of automation supply chains and improving their value proposition by providing more accurate data for demand forecasting. There are material knowledge gaps on the SC-specific analytics applied to match demand, albeit the existing knowledge could be more amorphous. From this backdrop, the study endeavored to analyze extant literature within the ambit of BDA to unpack the current trends and possible future research directions to foster the application of BDA in SC contexts. The study adopted a systematic literature review of the extant literature published between 2014-2023. The study adopted the five-stage iterative procedure used in the systematic review methodology. The review's findings depict extensive use of big data analytics in matching demand and supply and supply chain optimization. The findings of this study adduce almost non-rebuttable evidence that big data analytics can be applied in procurement, inventory control, logistics, and order processing. Under the auspices of BDA is the SCA. Arguably, extant research has demonstrated the capability of SCA in mitigating contemporary SC risks such as mismatches between demand and supply, sub-optimal SCs, and underutilization of the supply chain infrastructures at the cusps of various echelons.

VL  - 10
IS  - 5
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Author Information

Desmond Mwangi Wairimu

Graduate School, University of Kigali, Kigali, Rwanda

Contact Email

http://orcid.org/0000-0003-3823-2168

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Wairimu, D. M. (2024). Supply Chain Analytics, Definitions, Characteristics and Applications: A Systematic Literature Review. European Business & Management, 10(5), 76-84. https://doi.org/10.11648/j.ebm.20241005.11

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ACS Style

Wairimu, D. M. Supply Chain Analytics, Definitions, Characteristics and Applications: A Systematic Literature Review. Eur. Bus. Manag. 2024, 10(5), 76-84. doi: 10.11648/j.ebm.20241005.11

Copy | Download

AMA Style

Wairimu DM. Supply Chain Analytics, Definitions, Characteristics and Applications: A Systematic Literature Review. Eur Bus Manag. 2024;10(5):76-84. doi: 10.11648/j.ebm.20241005.11

Copy | Download

@article{10.11648/j.ebm.20241005.11,
  author = {Desmond Mwangi Wairimu},
  title = {Supply Chain Analytics, Definitions, Characteristics and Applications: A Systematic Literature Review
},
  journal = {European Business & Management},
  volume = {10},
  number = {5},
  pages = {76-84},
  doi = {10.11648/j.ebm.20241005.11},
  url = {https://doi.org/10.11648/j.ebm.20241005.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ebm.20241005.11},
  abstract = {While there is a high uptake of BDA in the realm of supply chain management, in the view of automation supply chains and improving their value proposition by providing more accurate data for demand forecasting. There are material knowledge gaps on the SC-specific analytics applied to match demand, albeit the existing knowledge could be more amorphous. From this backdrop, the study endeavored to analyze extant literature within the ambit of BDA to unpack the current trends and possible future research directions to foster the application of BDA in SC contexts. The study adopted a systematic literature review of the extant literature published between 2014-2023. The study adopted the five-stage iterative procedure used in the systematic review methodology. The review's findings depict extensive use of big data analytics in matching demand and supply and supply chain optimization. The findings of this study adduce almost non-rebuttable evidence that big data analytics can be applied in procurement, inventory control, logistics, and order processing. Under the auspices of BDA is the SCA. Arguably, extant research has demonstrated the capability of SCA in mitigating contemporary SC risks such as mismatches between demand and supply, sub-optimal SCs, and underutilization of the supply chain infrastructures at the cusps of various echelons.
},
 year = {2024}
}

Copy | Download

TY  - JOUR
T1  - Supply Chain Analytics, Definitions, Characteristics and Applications: A Systematic Literature Review

AU  - Desmond Mwangi Wairimu
Y1  - 2024/11/26
PY  - 2024
N1  - https://doi.org/10.11648/j.ebm.20241005.11
DO  - 10.11648/j.ebm.20241005.11
T2  - European Business & Management
JF  - European Business & Management
JO  - European Business & Management
SP  - 76
EP  - 84
PB  - Science Publishing Group
SN  - 2575-5811
UR  - https://doi.org/10.11648/j.ebm.20241005.11
AB  - While there is a high uptake of BDA in the realm of supply chain management, in the view of automation supply chains and improving their value proposition by providing more accurate data for demand forecasting. There are material knowledge gaps on the SC-specific analytics applied to match demand, albeit the existing knowledge could be more amorphous. From this backdrop, the study endeavored to analyze extant literature within the ambit of BDA to unpack the current trends and possible future research directions to foster the application of BDA in SC contexts. The study adopted a systematic literature review of the extant literature published between 2014-2023. The study adopted the five-stage iterative procedure used in the systematic review methodology. The review's findings depict extensive use of big data analytics in matching demand and supply and supply chain optimization. The findings of this study adduce almost non-rebuttable evidence that big data analytics can be applied in procurement, inventory control, logistics, and order processing. Under the auspices of BDA is the SCA. Arguably, extant research has demonstrated the capability of SCA in mitigating contemporary SC risks such as mismatches between demand and supply, sub-optimal SCs, and underutilization of the supply chain infrastructures at the cusps of various echelons.

VL  - 10
IS  - 5
ER  -

Copy | Download