Intelligent Knowledge Management for Enhancing Sustainable Food Systems: The Case of Sweden

Azadeh Sarkheyli

2025

Abstract

Intelligent Knowledge Management (IKM) aims to establish intelligent integration of the food system to capture, organize, analyze, and utilize information and knowledge that promotes sustainable food production. With the growing importance of sustainable food systems, understanding consumer behavior, customer needs, food preferences, producer demands, and local regulations is necessary. However, integration challenges within the Swedish food system create significant obstacles. Inappropriate Knowledge Management systems, system complexity, dynamic environments, inability to learn from and reuse data, information overload, and insufficient data collection and analysis contribute to these challenges. This study uses a case study approach and literature review to collect and analyze data. The proposed solution is an IKM conceptual model based on the knowledge-based theory of the firm, leveraging AI-powered techniques to manage and analyze large datasets from various stakeholders in the food supply chain. This model enhances forecasting and planning capabilities, improving decision-making processes. Future research should further develop the IKM system to achieve the potential results outlined in this paper.

Paper Citation

in Harvard Style

Sarkheyli A. (2025). Intelligent Knowledge Management for Enhancing Sustainable Food Systems: The Case of Sweden. In Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KMIS; ISBN 978-989-758-769-6, SciTePress, pages 514-521. DOI: 10.5220/0013817600004000

in Bibtex Style

@conference{kmis25,
author={Azadeh Sarkheyli},
title={Intelligent Knowledge Management for Enhancing Sustainable Food Systems: The Case of Sweden},
booktitle={Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KMIS},
year={2025},
pages={514-521},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013817600004000},
isbn={978-989-758-769-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KMIS
TI - Intelligent Knowledge Management for Enhancing Sustainable Food Systems: The Case of Sweden
SN - 978-989-758-769-6
AU - Sarkheyli A.
PY - 2025
SP - 514
EP - 521
DO - 10.5220/0013817600004000
PB - SciTePress