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Internet of Things (IoT) in Smart Systems and Applications
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General Information
ISSN:
1798-2340 (Online)
Frequency:
Monthly
DOI:
10.12720/jait
Indexing:
ESCI (Web of Science)
,
Scopus
,
CNKI
,
etc
.
Acceptance Rate:
12%
APC:
1000 USD
Average Days to Accept:
87 days
Journal Metrics:
Impact Factor 2023: 0.9
4.2
2023
CiteScore
57th percentile
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Editor-in-Chief
Prof. Kin C. Yow
University of Regina, Saskatchewan, Canada
I'm delighted to serve as the Editor-in-Chief of
Journal of Advances in Information Technology
.
JAIT
is intended to reflect new directions of research and report latest advances in information technology. I will do my best to increase the prestige of the journal.
What's New
2025-02-10
All the 141 papers published in JAIT in 2024 have been indexed by Scopus.
2025-01-23
JAIT Vol. 16, No. 1 has been published online!
2024-06-07
JAIT received the CiteScore 2023 with 4.2, ranked #169/394 in Category Computer Science: Information Systems, #174/395 in Category Computer Science: Computer Networks and Communications, #226/350 in Category Computer Science: Computer Science Applications
Home
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Published Issues
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2022
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Volume 13, No. 4, August 2022
>
JAIT 2022 Vol.13(4): 338-346
doi: 10.12720/jait.13.4.338-346
Proposals for Addressing Research Gaps at the Intersection of Data Analytics and Supply Chain Management
Chibuzor Udokwu, Patrick Brandtner, Farzaneh Darbanian, and Taha Falatouri
University of Applied Sciences Upper Austria, Steyr, Austria
Abstract
—Data Analytics (DA) plays an important role in improving and optimizing the processes in a Supply Chain (SC) network. Due to a huge amount of data generated in the various SC processes, the role of DA in Supply Chain Management (SCM) is becoming increasingly evident. Organizations have already invested heavily in applying various DA technologies to their SC networks. Several reviews have been conducted in different domains of SCM indicating applications and limitations of DA in SCM. As the research domain of DA applications in SCM matures, it is necessary to identify and address the research gaps that exist at the intersection of these domains. The paper qualitatively examines recent review papers in the domain of DA in SCM to identify and outline prominent ways that DA is currently applied in SCM, what potential future opportunities stated and what challenges affecting DA application in SCM are existing. Prominent use cases of DA in SCM include i) forecasting demand, ii) product development, iii) logistics route planning and iv) lean SC development. However, there is no prominent, unique future application list of DA in SCM since the findings vary across the papers. Prominent challenges affecting DA in SCM include i) lack of collaboration, ii) data sharing problems, iii) risks associated with BD management and iv) lack of skilled experts. Lastly, this article provides two conceptual ideas for addressing these prominent DA challenges in SCM: first, a framework for data analytics enabling collaboration in SCM by using transparent data questions and second, a blockchain-based data management approach in SC networks.
Index Terms
—data analytics, supply chain management, SCM challenges, SCM research gaps, data analytics research gaps
Cite: Chibuzor Udokwu, Patrick Brandtner, Farzaneh Darbanian, and Taha Falatouri, "Proposals for Addressing Research Gaps at the Intersection of Data Analytics and Supply Chain Management," Journal of Advances in Information Technology, Vol. 13, No. 4, pp. 338-346, August 2022.
Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License (
CC BY-NC-ND 4.0
), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.
6-S1004-Austria
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