Blockchain-Driven Supply Chain Analytics and Sustainable Performance: Analysis Using PLS-SEM and ANFIS

Shervin Espahbod, Arash Tashakkori, Mahsa Mohsenibeigzadeh, Mehrnaz Zarei, Ghasem Golshan Arani, Maria Dzikuć () and Maciej Dzikuć
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Shervin Espahbod: Department of Management Science, Shannon School of Business, Cape Breton University, Sydney, NS B1P 6L2, Canada
Arash Tashakkori: School of Business, Stevens Institute of Technology, Hoboken, NJ 07030, USA
Mahsa Mohsenibeigzadeh: Department of Management, College of Business, University of Central Florida, Orlando, FL 32816, USA
Mehrnaz Zarei: Department of Business Administration, Alfred Lerner College of Business and Economics, University of Delaware, Newark, DE 19716, USA
Ghasem Golshan Arani: Department of Business Administration, Alfred Lerner College of Business and Economics, University of Delaware, Newark, DE 19716, USA
Maria Dzikuć: Faculty of Economics and Management, University of Zielona Góra, Licealna Street 9, 65-417 Zielona Góra, Poland
Maciej Dzikuć: Faculty of Economics and Management, University of Zielona Góra, Licealna Street 9, 65-417 Zielona Góra, Poland

Sustainability, 2024, vol. 16, issue 15, 1-16

Abstract: This study investigated the impact of blockchain-driven supply chain analytics on the dimensions of lean, agile, resilient, green, and sustainable (LARGS) supply chain management, as well as supply chain innovation (SCI) and sustainable supply chain performance (SSCP). The research involved 262 managers and vice presidents of supply chains from large- and medium-sized manufacturing companies listed in the Tehran Stock Exchange. A hybrid approach utilizing structural equations modelling with partial least squares-structural equation modeling (PLS-SEM) and the adaptive neuro-fuzzy inference systems (ANFIS) technique was employed for data analysis. The findings demonstrated a significantly positive effect of blockchain-driven supply chain analytics on SCI, the LARGS supply chain, and SSCP. Additionally, SCI exhibited a significantly positive impact on the LARGS supply chain and SSCP. Moreover, the LARGS supply chain was shown to have a significantly positive influence on SSCP. Both SCI and the LARGS supply chain played positive and significant mediating roles in the impact of blockchain-driven supply chain analytics on SSCP. Furthermore, the LARGS supply chain also acted as a significant mediator in the effect of SCI on SSCP. Lastly, SCI had a positive and significant mediating role in the impact of blockchain-driven supply chain analytics on the LARGS supply chain. In conclusion, it can be inferred that blockchain-driven supply chain analytics contributes to the enhancement of SSCP through the facilitation of SCI and the promotion of LARGS supply chain principles.

Keywords: blockchain; supply chain innovation; LARGS supply chain; sustainable supply chain performance (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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