1702. Towards Digitally Trusted Blockchain-enabled-Supply Chain- A Causal Analysis of Challenges
Invited abstract in session TD-28: Risk and Financial Decision Making, stream Decision Support Systems.
Tuesday, 14:30-16:00Room: Maurice Keyworth 1.03
Authors (first author is the speaker)
| 1. | Rajeev Agrawal
|
| Mechanical Engineering, Malaviya National Institute of Technology Jaipur | |
| 2. | Vaibhav Sharma
|
| Mechanical Engineering, Malaviya National Institute of Technology Jaipur |
Abstract
The ongoing digital transformation, where organizations collaborate through digital technologies like blockchain, requires sharing critical information in their supply chain. Digital trust (DT) in blockchain (BC)-enabled supply chain (SC) is crucial and remains unexplored. With the involvement of the stakeholders' information on the BC platform, the protection of the participant data has a significant role to play. The study underscores the need to assess DT for cybersecurity enhancements, regulatory alignment, and governance frameworks to foster DT. Therefore, this study investigates the challenges to DT in BC-enabled SCs. To address the challenges, this study identifies and establishes a causal relationship among the challenges by a Decision-Making Trial and Evaluation Laboratory-Machine Learning (DEMATEL-ML) integrated approach. The DEMALTEL identifies the causal relationship, while the ML is used to validate the expert inputs. Experts from the Indian manufacturing sector were consulted, whose inputs categorize 13 key challenges into six causal and seven effect factors. The primary causal barriers include organizational culture, data privacy and security concerns, high costs, system complexity, regulatory diversity, and limited data sharing. Effect factors, such as credential loss risks, immutability issues, a lack of robust on-chain analytics, and scalability limitations, further hinder trust and adoption. The study also provides the limitations and future directions.
Keywords
- Supply Chain Management
- Machine Learning
- Developing Countries
Status: accepted
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