Research Article

Evaluation of Blockchain Technology for Supply Chains using an Integrated Fuzzy Cognitive Map-QFD Methodology

Volume: 10 Number: 2 June 25, 2024
EN

Evaluation of Blockchain Technology for Supply Chains using an Integrated Fuzzy Cognitive Map-QFD Methodology

Abstract

The rapid advancement of technology has made it imperative for supply chains to adapt to the changing landscape. Blockchain technology holds immense potential to transform supply chain processes, but the challenge lies in identifying the most suitable blockchain characteristics to meet the various performance indicators of a supply chain. To overcome this challenge, this study aims to prioritize the most critical blockchain characteristics in a supply chain. The study adopts a two-stage Quality Function Deployment (QFD) methodology to rank blockchain characteristics based on supply chain and software requirements. The methodology evaluates the supply chain performance indicators using the Supply Chain Operations Reference (SCOR) model and software needs using the International Organization for Standardization (ISO) software quality characteristics. After determining the problematic SCOR and ISO software-related metrics, the study utilizes the QFD Stage 1 to obtain the weights of ISO software characteristics and employs the Fuzzy Cognitive Map (FCM) to determine the most crucial blockchain characteristics for QFD Stage 2. The results of this study show that the top priorities for blockchain characteristics in a supply chain are smart contract functionality, privacy, transaction per second, tokenization, security, permissioned network, scalability, cost, modularity, and licensing, in order of importance.

Keywords

References

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Details

Primary Language

English

Subjects

Industrial Engineering

Journal Section

Research Article

Early Pub Date

June 25, 2024

Publication Date

June 25, 2024

Submission Date

August 3, 2023

Acceptance Date

November 14, 2023

Published in Issue

Year 2024 Volume: 10 Number: 2

APA
Maden, A., & Alptekin, E. (2024). Evaluation of Blockchain Technology for Supply Chains using an Integrated Fuzzy Cognitive Map-QFD Methodology. Journal of Advanced Research in Natural and Applied Sciences, 10(2), 252-271. https://doi.org/10.28979/jarnas.1337409
AMA
1.Maden A, Alptekin E. Evaluation of Blockchain Technology for Supply Chains using an Integrated Fuzzy Cognitive Map-QFD Methodology. JARNAS. 2024;10(2):252-271. doi:10.28979/jarnas.1337409
Chicago
Maden, Ayça, and Emre Alptekin. 2024. “Evaluation of Blockchain Technology for Supply Chains Using an Integrated Fuzzy Cognitive Map-QFD Methodology”. Journal of Advanced Research in Natural and Applied Sciences 10 (2): 252-71. https://doi.org/10.28979/jarnas.1337409.
EndNote
Maden A, Alptekin E (June 1, 2024) Evaluation of Blockchain Technology for Supply Chains using an Integrated Fuzzy Cognitive Map-QFD Methodology. Journal of Advanced Research in Natural and Applied Sciences 10 2 252–271.
IEEE
[1]A. Maden and E. Alptekin, “Evaluation of Blockchain Technology for Supply Chains using an Integrated Fuzzy Cognitive Map-QFD Methodology”, JARNAS, vol. 10, no. 2, pp. 252–271, June 2024, doi: 10.28979/jarnas.1337409.
ISNAD
Maden, Ayça - Alptekin, Emre. “Evaluation of Blockchain Technology for Supply Chains Using an Integrated Fuzzy Cognitive Map-QFD Methodology”. Journal of Advanced Research in Natural and Applied Sciences 10/2 (June 1, 2024): 252-271. https://doi.org/10.28979/jarnas.1337409.
JAMA
1.Maden A, Alptekin E. Evaluation of Blockchain Technology for Supply Chains using an Integrated Fuzzy Cognitive Map-QFD Methodology. JARNAS. 2024;10:252–271.
MLA
Maden, Ayça, and Emre Alptekin. “Evaluation of Blockchain Technology for Supply Chains Using an Integrated Fuzzy Cognitive Map-QFD Methodology”. Journal of Advanced Research in Natural and Applied Sciences, vol. 10, no. 2, June 2024, pp. 252-71, doi:10.28979/jarnas.1337409.
Vancouver
1.Ayça Maden, Emre Alptekin. Evaluation of Blockchain Technology for Supply Chains using an Integrated Fuzzy Cognitive Map-QFD Methodology. JARNAS. 2024 Jun. 1;10(2):252-71. doi:10.28979/jarnas.1337409

 

 

 

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