Investigation of IoT applications in supply chain management with fuzzy hierarchical analysis

Ramez Kian ()

Journal of Data Analytics, 2022, vol. 1, issue 1, 8-15

Abstract: The IoT is currently growing rapidly and uses technologies such as smart barcode sensors, RFID, wireless communications, cloud computing, and more. The Internet of Things, in addition to being a revolutionary technology for all industries; has also demonstrated its potential in processes such as supply chain. Management, forecasting, and monitoring applications help managers improve the operational efficiency of their company distribution and increase transparency in their decisions. So more than ever, the benefits of using the Internet of Things are evident in the supply chain. The existence of comprehensive and valid information platforms is one of the requirements of supply chain management. Therefore, the most accurate use of integrated information devices such as Internet technology of objects in this part of the management of the organization is important. Coverage of this information accurately and in an instant facilitates matters and makes the process progress more transparent. To improve this process, cloud computing is used as a solution. In addition, other cloud computing capabilities can be used, such as facilitating object communication, integrating monitoring devices, and IoT storage, analyzing data, and paving the way for cyberspace to provide the customer with supply chain management. This requires a model that defines how Internet technology relates to objects, cloud computing, and supply chain management. The purpose of this study is to identify and prioritize IoT applications in the supply chain management sector with a multi-criteria decision-making approach. The results show that applications such as intelligent control and intelligent maintenance have the highest priorities.

Keywords: IoT; Supply Chain Management; Multi-Criteria Decision Making; Fuzzy Prioritization (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journal-data.ir/index.php/JDA/article/view/2/2 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bao:jdaisn:v:1:y:2022:i:1:p:8-15:id:2

Access Statistics for this article

Journal of Data Analytics is currently edited by Martha Sabogal

More articles in Journal of Data Analytics from International Scientific Network (ISNet)
Bibliographic data for series maintained by International Scientific Network (ISNet) ().