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2026 Vol.8, Issue 3 Preview Page

Research Article

Priority analysis of smart agriculture-based sustainable agriculture evaluation factors using an integrated AHP-Fuzzy approach
SanHo Kim1*
,
MinSun Kim2
,
GunIl Bae3
1Department of Consulting, Graduate School, Kumoh National Institute of Technology, Gumi 39177, Republic of Korea
2Business Development Team 1, Data Intelligence Business Division, KT Corporation, Seoul 03154, Republic of Korea
3Department of Consulting, Graduate School, Kumoh National Institute of Technology, Gumi 39177, Republic of Korea
*Corresponding Author
30 September 2026. pp. 240-255
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Abstract

This study aimed to prioritize evaluation factors for smart agriculture-based sustainable agriculture by integrating the Analytic Hierarchy Process (AHP) with fuzzy set theory. The evaluation framework consisted of six major dimensions—economic, environmental, social, and technological sustainability, governance, and government policy—and 24 sub-factors. Data were collected from 254 experts and stakeholders in fields related to smart agriculture and sustainable agriculture. First, AHP was applied to estimate the relative weights and structural priorities of the evaluation factors. The importance ratings were transformed into triangular fuzzy numbers (TFNs), and the confidence ratings were converted into confidence coefficients and applied to the TFNs, followed by defuzzification to derive defuzzified values (DVs). Finally, an integrated AHP-Fuzzy index was obtained by combining the AHP weights with the defuzzified values. The results showed that economic sustainability had the highest priority among the six major dimensions, followed by technological, environmental, and social sustainability, governance, and government policy. Among the 24 sub-factors, big data-based production forecasting ranked first, followed by increased farm income, improved quality of life, reduced pesticide use, and data-driven agricultural management. In particular, agricultural data platform development, water-soil-low-carbon agricultural technologies, and AI-based agricultural decision-making systems showed relatively higher priorities in the integrated analysis than in the AHP-only analysis. These findings indicate that sustainable smart agriculture requires an integrated approach that goes beyond technology adoption by linking agricultural data collection and analysis with production forecasting and decision-making and by extending technological benefits to economic, environmental, and social outcomes.

Keywords
AHP-Fuzzy analysis
Precision agriculture
Smart agriculture
Sustainable agriculture
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Information
  • Publisher :Korean Society of Precision Agriculture
  • Publisher(Ko) :한국정밀농업학회
  • Journal Title :Precision Agriculture Science and Technology
  • Journal Title(Ko) :정밀농업과학기술
  • Volume : 8
  • No :3
  • Pages :240-255
  • Received Date : 2026-08-20
  • Revised Date : 2026-09-02
  • Accepted Date : 2026-09-02
  • DOI :https://doi.org/10.22765/pastj.20260018
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