Blockchain technology is a new digital technology that has been disrupting the way businesses are performing. It is a decentralized and distributed ledger that enables transactions of any form of value. As blockchain technology provides visibility, transparency, and security through the multi-agent system, the supply chain sector is one of its critical and promising applications. In a highly dynamic environment, the supply chain's efficiency needs to be measured from a blockchain perspective. As the main benefit of blockchain technology is the visibility and real-time access to data, blockchain technology's preeminent affected areas within the supply chain are the responsiveness to the customer and the inventory efficiency among the supply chain partners. This research developed a dynamic model to measure supply chain efficiency from the blockchain perspective. The developed model is based on system dynamics methodology to model a typical three-tier supply chain; manufacturer, distributor, and retailer. It consists of three components; chain system, backlog system, and supply chain efficiency evaluation system. First, an introduction to the supply chain and blockchain technology is provided. Second, a literature review of supply chain and blockchain technology is presented. From the literature analysis, a research gap is identified with the research questions and objectives. Third, the methodology proposed in this research to answer the research problems is discussed with a literature review about applying system dynamics methodology within the supply chain, and technology adoption is provided. Forth, an illustration of the proposed model is given. Fifth, the dynamic analysis of the supply chain's performance according to various scenarios is evaluated. Finally, a conclusion with the future work is provided.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-1945 |
| Date | 01 January 2021 |
| Creators | Ali, Rehab |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations, 2020- |
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