EVERGREEN

Joint Journal of Novel Carbon Resource Sciences and Green Asia Strategy

ISSN:2189-0420 (Print until Mar 2020)
ISSN:2432-5953 (Online)

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Extraction of Consumer Behavior Patterns Toward Quality Labels Using a Fuzzy Inference System Based on the Hierarchy of Effects Model

Meilinda Ayundyahrini1,*, Fitri Trapsilawati2, Mirwan Ushada3, Danar Agus Susanto1, Ellia Kristiningrum1, Teguh Pribadi Adinugroho4, Febrian Isharyadi1, Ajun Tri Setyoko1
1Research Center for Sustainable Industrial and Manufacturing Systems, National Research and Innovation Agency, Indonesia
2Faculty of Engineering, Gadjah Mada University, Indonesia
3Faculty of Agricultural Technology, Gadjah Mada University, Indonesia
4Research Center for Equipment Manufacturing Technology, National Research and Innovation Agency, Indonesia
*Author to whom correspondence should be addressed:
E-mail: meil004@brin.go.id (MA)
Evergreen, Vol. 13, Iss. 02, pp. 673–689, 2026
DOI: 10.5109/7429614
Creative Commons Attribution 4.0 International Creative Commons Attribution 4.0 International
Received: May 19, 2025 | Revised: January 28, 2026 | Accepted: April 13, 2026 | Published: June 2026
Abstract
This study explores the influence of quality labels on consumer purchasing behavior using a Fuzzy Inference System (FIS) aligned with the Hierarchy of Effects (HoE) model. The methodology involved four main phases: primary data collection, fuzzy rule extraction from HoE-based attributes, model validation, and pattern interpretation. A total of 76 fuzzy rules were generated to classify consumer behavior across four HoE stages: Not Aware, Cognitive, Affective, and Conative. The overall model accuracy reached 78.59%. However, performance was uneven across stages, particularly in the not aware stage, which achieved only 45.5% accuracy, with 36.4% of its cases not covered by any rule. In contrast, the Cognitive, Affective, and Conative stages exceeded 80% accuracy. Statistical validation through literature review and multinomial logistic regression confirmed the significant roles of trust, perceived quality, and perceived risk as predictors of consumer transitions across HoE stages. At the same time, the model offers interpretable insights for strategic communication and label design. Limitations of methodology such as imbalanced class representation that causing local overfitting highlight the need for parameter simplification and future integration with adaptive learning models to enhance generalizability.
Keywords
Decision making; fuzzy inference system; hierarchy of effects; perceptual reasoning; quality label
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