Towards supply chain visibility using Internet of Things: a dyadic analysis review

Ahmed, S., Kalsoom, T., Ramzan, N., Pervez, Z., Azmat, M., Zeb, B. and Ur Rehman, M. (2021) Towards supply chain visibility using Internet of Things: a dyadic analysis review. Sensors, 21(12), 4158. (doi: 10.3390/s21124158)

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Abstract

The Internet of Things (IoT) and its benefits and challenges are the most emergent research topics among academics and practitioners. With supply chains (SCs) gaining rapid complexity, having high supply chain visibility (SCV) would help companies ease the processes and reduce complexity by improving inaccuracies. Extant literature has given attention to the organisation’s capability to collect and evaluate information to balance between strategy and goals. The majority of studies focus on investigating IoT’s impact on different areas such as sustainability, organisational structure, lean manufacturing, product development, and strategic management. However, research investigating the relationships and impact of IoT on SCV is minimal. This study closes this gap using a structured literature review to critically analyse existing literature to synthesise the use of IoT applications in SCs to gain visibility, and the SC. We found key IoT technologies that help SCs gain visibility, and seven benefits and three key challenges of these technologies. We also found the concept of Supply 4.0 that grasps the element of Industry 4.0 within the SC context. This paper contributes by combining IoT application synthesis, enablers, and challenges in SCV by highlighting key IoT technologies used in the SCs to gain visibility. Finally, the authors propose an empirical research agenda to address the identified gaps.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Ur Rehman, Dr Masood
Creator Roles:
Ur Rehman, M.Formal analysis, Resources, Writing – review and editing
Authors: Ahmed, S., Kalsoom, T., Ramzan, N., Pervez, Z., Azmat, M., Zeb, B., and Ur Rehman, M.
College/School:College of Science and Engineering > School of Engineering > Systems Power and Energy
Journal Name:Sensors
Publisher:MDPI
ISSN:1424-8220
ISSN (Online):1424-8220
Published Online:17 June 2021
Copyright Holders:Copyright © 2021 The Authors
First Published:First published in Sensors 21(12): 4158
Publisher Policy:Reproduced under a Creative Commons License

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