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Computer Modeling Approaches for Blockchain-Driven Supply Chain Intelligence: A Review on Enhancing Transparency, Security, and Efficiency

Puranam Revanth Kumar¹, Gouse Baig Mohammad², Pallati Narsimhulu³, Dharnisha Narasappa⁴, Lakshmana Phaneendra Maguluri⁵, Subhav Singh^6,7,8, Shitharth Selvarajan^9,10,11,*

1 Department of Artificial Intelligence and Machine Learning, Malla Reddy University, Hyderabad, 500043, India
2 Department of Computer Science and Engineering, Vardhaman College of Engineering, Hyderabad, 501218, India
3 Department of Computer Science and Engineering, Symbiosis Institute of Technology, Hyderabad, 509217, India
4Versa Networks, Santa Clara, CA 95054, USA
5 Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, 522302, India
6 Chitkara Centre for Research and Development, Chitkara University, Himachal Pradesh, 174103, India
7 Division of Research & innovation, Uttaranchal University, Dehradun, 248007, India
8 Division of Research and Development, Lovely Professional University, Phagwara, 144411, India
9 School of Built Environment, Engineering and Computing, Leeds Beckett University, Leeds, LS6 3HF, UK
10 Department of Computer Science and Engineering, Chennai Institute of Technology, Chennai, 600069, India
11 Centre for Research Impact & Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, 140401, India

* Corresponding Author: Shitharth Selvarajan. Email:

(This article belongs to the Special Issue: Key Technologies and Applications of Blockchain Technology in Supply Chain Intelligence and Trust Establishment)

Computer Modeling in Engineering & Sciences 2025, 144(3), 2779-2818. https://doi.org/10.32604/cmes.2025.066365

Received 07 April 2025; Accepted 15 August 2025; Issue published 30 September 2025

Abstract

Blockchain Technology (BT) has emerged as a transformative solution for improving the efficacy, security, and transparency of supply chain intelligence. Traditional Supply Chain Management (SCM) systems frequently have problems such as data silos, a lack of visibility in real time, fraudulent activities, and inefficiencies in tracking and traceability. Blockchain’s decentralized and irreversible ledger offers a solid foundation for dealing with these issues; it facilitates trust, security, and the sharing of data in real-time among all parties involved. Through an examination of critical technologies, methodology, and applications, this paper delves deeply into computer modeling based-blockchain framework within supply chain intelligence. The effect of BT on SCM is evaluated by reviewing current research and practical applications in the field. As part of the process, we delved through the research on blockchain-based supply chain models, smart contracts, Decentralized Applications (DApps), and how they connect to other cutting-edge innovations like Artificial Intelligence (AI) and the Internet of Things (IoT). To quantify blockchain’s performance, the study introduces analytical models for efficiency improvement , security enhancement , and scalability , enabling computational assessment and simulation of supply chain scenarios. These models provide a structured approach to predicting system performance under varying parameters. According to the results, BT increases efficiency by automating transactions using smart contracts, increases security by using cryptographic techniques, and improves transparency in the supply chain by providing immutable records. Regulatory concerns, challenges with interoperability, and scalability all work against broad adoption. To fully automate and intelligently integrate blockchain with AI and the IoT, additional research is needed to address blockchain’s current limitations and realize its potential for supply chain intelligence.

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Supplementary Material

Supplementary Material File

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