Navigating the Digital Landscape: An Analysis of Digital Business Models in Agri-Food Supply Chain Networks
Year: 2024
Type: dissertation
Abstract: : The agri-food supply chain industry is currently at a critical juncture, as it struggles with the challenges posed by its supply chain's intricate and fragmented nature. overcoming these challenges in the agri-food domain requires business models driven by digital technologies that provide enhanced transparency, efficiency, and sustainability. These technologies enable real-time data sharing, improved traceability, optimized resource use, and better decision-making processes, ultimately leading to a more resilient and adaptive agri-food supply chain. In the agri-food domain, digital business models that use digital technologies such as IoT, AI, and blockchain are growing. Even then, the available literature about these businesses in the agri-food supply chain domain is scarce. Through a systematic literature review, this thesis investigates the current state of digital business models within agri-food networks and, delves into the specific digital business models that utilize blockchain technology. This research uses case study analysis and desk research to assess the role of blockchain in enhancing the management of agri-food supply chain networks and identify how different roles are impacted by blockchain and how blockchain enhances the relationship between the involved stakeholders in the agri-supply chain. The results from the literature review and real-world use cases are analyzed later in the study to be mapped into an existing taxonomy, to identify any gaps in the existing taxonomy and make suggestions and enhancements for efficient categorization of business models in the future based on it. Files Description: This repository contains the resources used for my thesis, including images, publication analysis, and the main LaTeX code.
Author: Gandham, Sudheer Kumar
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6948811767
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