Understanding environmental decision-making in forest restoration: the role of latent attitudes, attribute non-attendance, and choice behavior

Introduction As forests face growing threats from fires, pests, and disease, understanding public preferences for restoration policies has become increasingly urgent. This study addresses the need for more behaviorally realistic approaches in environmental valuation. Methods A discrete choice experiment was conducted in Korea to explore how individuals make environmental decisions. The study incorporates latent environmental attitudes, attribute non-attendance (ANA), and heterogeneous choice behavior using advanced econometric models, including the independent availability logit and latent class analysis. Results Findings reveal that respondents do not ignore entire attributes but selectively disregard specific attribute levels. Distinct behavioral classes were identified, ranging from deterministic to probabilistic decision types. Latent attitudes significantly influenced willingness to pay (WTP), with some groups showing reluctance to pay due to self-benefit orientation. Discussion These results highlight the importance of recognizing behavioral subgroups when designing restoration policies. Integrating behavioral insights into valuation enhances the relevance and acceptability of forest restoration programs. This research provides practical guidance for developing targeted, socially accepted environmental policies.

Authors

Institutions

Publication Details

Journal
Frontiers in Behavioral Economics
Published
2025-05-20
DOI
https://doi.org/10.3389/frbhe.2025.1596416
Citations
3
Primary Topic
Economic and Environmental Valuation
Type
article
Field-Weighted Citation Impact
9.39

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Understanding environmental decision-making in forest restoration: the role of latent attitudes, attribute non-attendance, and choice behavior

Chulhyun Jeon
3 citations
Frontiers in Behavioral Economics
Economic and Environmental Valuation
9.39
article

Understanding environmental decision-making in forest restoration: the role of latent attitudes, attribute non-attendance, and choice behavior

Chulhyun Jeon
article en
3 citations

Abstract

Introduction As forests face growing threats from fires, pests, and disease, understanding public preferences for restoration policies has become increasingly urgent. This study addresses the need for more behaviorally realistic approaches in environmental valuation. Methods A discrete choice experiment was conducted in Korea to explore how individuals make environmental decisions. The study incorporates latent environmental attitudes, attribute non-attendance (ANA), and heterogeneous choice behavior using advanced econometric models, including the independent availability logit and latent class analysis. Results Findings reveal that respondents do not ignore entire attributes but selectively disregard specific attribute levels. Distinct behavioral classes were identified, ranging from deterministic to probabilistic decision types. Latent attitudes significantly influenced willingness to pay (WTP), with some groups showing reluctance to pay due to self-benefit orientation. Discussion These results highlight the importance of recognizing behavioral subgroups when designing restoration policies. Integrating behavioral insights into valuation enhances the relevance and acceptability of forest restoration programs. This research provides practical guidance for developing targeted, socially accepted environmental policies.

Frontiers in Behavioral EconomicsVol. 4
University of Stirling (GB)
University of Stirling
Openalex Percentile: Top 3%
Economic and Environmental Valuation
9.39
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.