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Evaluating agriculture 4.0 decision support systems based on hyperbolic fuzzy-weighted zero-inconsistency combined with combinative distance-based assessment

Agriculture 4.0 plays a crucial role in shaping sustainable cities and societies by revolutionizing urban food systems. By incorporating advanced technologies like precision farming, vertical gardening, and data analytics, Agriculture 4.0 improves local food production, reduces food transportation,...

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Main Authors:	Alamoodi A., Garfan S., Deveci M., Albahri O.S., Albahri A.S., Yussof S., Homod R.Z., Mohamad Sharaf I., Moslem S.
Other Authors:	57205435311
Format:	Article
Published:	Elsevier B.V. 2025
Subjects:	Agriculture decision support system Combinative distance-based assessment Decision supports Distance-based Fuzzy-weighted zero-inconsistency Hyperbolic fuzzy set Multi criteria decision-making Multicriteria decision-making Multicriterion decision makings Support systems alternative agriculture assessment method benchmarking decision making decision support system optimization resource use stakeholder supply chain management Sensitivity analysis
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spelling	my.uniten.dspace-361162025-03-03T15:41:24Z Evaluating agriculture 4.0 decision support systems based on hyperbolic fuzzy-weighted zero-inconsistency combined with combinative distance-based assessment Alamoodi A. Garfan S. Deveci M. Albahri O.S. Albahri A.S. Yussof S. Homod R.Z. Mohamad Sharaf I. Moslem S. 57205435311 57213826607 55734383000 57201013684 57201009814 16023225600 36994633500 17435789800 57203017976 Agriculture decision support system Combinative distance-based assessment Decision supports Distance-based Fuzzy-weighted zero-inconsistency Hyperbolic fuzzy set Multi criteria decision-making Multicriteria decision-making Multicriterion decision makings Support systems alternative agriculture assessment method benchmarking decision making decision support system optimization resource use stakeholder supply chain management Sensitivity analysis Agriculture 4.0 plays a crucial role in shaping sustainable cities and societies by revolutionizing urban food systems. By incorporating advanced technologies like precision farming, vertical gardening, and data analytics, Agriculture 4.0 improves local food production, reduces food transportation, and optimizes resource utilization. This paper introduces an innovative approach using Multi-Criteria Decision Making (MCDM) to assess Agriculture 4.0 Decision Support Systems (ADSS), contributing significantly to the selection of optimal systems that can drive sustainability in smart agriculture. The novelty of this research lies in developing a comprehensive evaluation framework that extends the hyperbolic fuzzy-weighted zero-inconsistency method for criteria weighting, combined with the combinative distance-based assessment method for benchmarking ADSS. The assessment matrix evaluates 13 ADSS across eight key criteria, including ?accessibility,? ?re-planning,? ?expert knowledge,? ?interoperability,? ?scalability,? ?uncertainty and dynamic factors,? ?prediction and forecast,? and ?historical data analysis?. Results from the hyperbolic fuzzy-weighted zero-inconsistency approach highlight ?re-planning? (0.143) and ?prediction and forecast? (0.140) as the most significant criteria, while ?expert knowledge? ranked lowest (0.113). In the combinative distance-based assessment, the system labelled ?OCCASION? achieved the highest score (3.843), positioning it as the most favourable ADSS, whereas the ?MOLP-based beef supply chain? system scored lowest (?3.519). Sensitivity analysis, conducted using varying sets of weights, confirms the robustness and reliability of the proposed approach. This research provides a powerful decision-making tool that can guide stakeholders in selecting the best ADSS, ultimately promoting sustainability and resource optimization in Agriculture 4.0. The findings have important implications for farmers, agribusiness, and smart agriculture, demonstrating the potential of the methodology to enhance decision-making processes in a critical sector. ? 2024 Elsevier B.V. Final 2025-03-03T07:41:24Z 2025-03-03T07:41:24Z 2024 Article 10.1016/j.compag.2024.109618 2-s2.0-85208673914 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208673914&doi=10.1016%2fj.compag.2024.109618&partnerID=40&md5=eaf7777ed950b10ae57b711d243deddc https://irepository.uniten.edu.my/handle/123456789/36116 227 109618 Elsevier B.V. Scopus
institution	Universiti Tenaga Nasional
building	UNITEN Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tenaga Nasional
content_source	UNITEN Institutional Repository
url_provider	http://dspace.uniten.edu.my/
topic	Agriculture decision support system Combinative distance-based assessment Decision supports Distance-based Fuzzy-weighted zero-inconsistency Hyperbolic fuzzy set Multi criteria decision-making Multicriteria decision-making Multicriterion decision makings Support systems alternative agriculture assessment method benchmarking decision making decision support system optimization resource use stakeholder supply chain management Sensitivity analysis
spellingShingle	Agriculture decision support system Combinative distance-based assessment Decision supports Distance-based Fuzzy-weighted zero-inconsistency Hyperbolic fuzzy set Multi criteria decision-making Multicriteria decision-making Multicriterion decision makings Support systems alternative agriculture assessment method benchmarking decision making decision support system optimization resource use stakeholder supply chain management Sensitivity analysis Alamoodi A. Garfan S. Deveci M. Albahri O.S. Albahri A.S. Yussof S. Homod R.Z. Mohamad Sharaf I. Moslem S. Evaluating agriculture 4.0 decision support systems based on hyperbolic fuzzy-weighted zero-inconsistency combined with combinative distance-based assessment
description	Agriculture 4.0 plays a crucial role in shaping sustainable cities and societies by revolutionizing urban food systems. By incorporating advanced technologies like precision farming, vertical gardening, and data analytics, Agriculture 4.0 improves local food production, reduces food transportation, and optimizes resource utilization. This paper introduces an innovative approach using Multi-Criteria Decision Making (MCDM) to assess Agriculture 4.0 Decision Support Systems (ADSS), contributing significantly to the selection of optimal systems that can drive sustainability in smart agriculture. The novelty of this research lies in developing a comprehensive evaluation framework that extends the hyperbolic fuzzy-weighted zero-inconsistency method for criteria weighting, combined with the combinative distance-based assessment method for benchmarking ADSS. The assessment matrix evaluates 13 ADSS across eight key criteria, including ?accessibility,? ?re-planning,? ?expert knowledge,? ?interoperability,? ?scalability,? ?uncertainty and dynamic factors,? ?prediction and forecast,? and ?historical data analysis?. Results from the hyperbolic fuzzy-weighted zero-inconsistency approach highlight ?re-planning? (0.143) and ?prediction and forecast? (0.140) as the most significant criteria, while ?expert knowledge? ranked lowest (0.113). In the combinative distance-based assessment, the system labelled ?OCCASION? achieved the highest score (3.843), positioning it as the most favourable ADSS, whereas the ?MOLP-based beef supply chain? system scored lowest (?3.519). Sensitivity analysis, conducted using varying sets of weights, confirms the robustness and reliability of the proposed approach. This research provides a powerful decision-making tool that can guide stakeholders in selecting the best ADSS, ultimately promoting sustainability and resource optimization in Agriculture 4.0. The findings have important implications for farmers, agribusiness, and smart agriculture, demonstrating the potential of the methodology to enhance decision-making processes in a critical sector. ? 2024 Elsevier B.V.
author2	57205435311
author_facet	57205435311 Alamoodi A. Garfan S. Deveci M. Albahri O.S. Albahri A.S. Yussof S. Homod R.Z. Mohamad Sharaf I. Moslem S.
format	Article
author	Alamoodi A. Garfan S. Deveci M. Albahri O.S. Albahri A.S. Yussof S. Homod R.Z. Mohamad Sharaf I. Moslem S.
author_sort	Alamoodi A.
title	Evaluating agriculture 4.0 decision support systems based on hyperbolic fuzzy-weighted zero-inconsistency combined with combinative distance-based assessment
title_short	Evaluating agriculture 4.0 decision support systems based on hyperbolic fuzzy-weighted zero-inconsistency combined with combinative distance-based assessment
title_full	Evaluating agriculture 4.0 decision support systems based on hyperbolic fuzzy-weighted zero-inconsistency combined with combinative distance-based assessment
title_fullStr	Evaluating agriculture 4.0 decision support systems based on hyperbolic fuzzy-weighted zero-inconsistency combined with combinative distance-based assessment
title_full_unstemmed	Evaluating agriculture 4.0 decision support systems based on hyperbolic fuzzy-weighted zero-inconsistency combined with combinative distance-based assessment
title_sort	evaluating agriculture 4.0 decision support systems based on hyperbolic fuzzy-weighted zero-inconsistency combined with combinative distance-based assessment
publisher	Elsevier B.V.
publishDate	2025
_version_	1825816096370851840
score	13.244109

Evaluating agriculture 4.0 decision support systems based on hyperbolic fuzzy-weighted zero-inconsistency combined with combinative distance-based assessment

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