gxceed
← 論文一覧に戻る

Determinants of Public Intention and Acceptance Behavior Toward Biomass Supply for Electricity Generation: The SEM-PLS Approach

発電のためのバイオマス供給に対する公衆の意図と受容行動の決定要因:SEM-PLSアプローチ (AI 翻訳)

Meiri Triani, Ahyahudin Sodri, Haruki Agustina

Jurnal Ilmu Ekonomi Terapan📚 査読済 / ジャーナル2026-06-20#エネルギー転換経営インパクト: 調達リスク対象セクター: power
DOI: 10.20473/jiet.v11i1.90109
原典: https://doi.org/10.20473/jiet.v11i1.90109
📄 PDF

🤖 gxceed AI 要約

日本語

本研究は、インドネシアの石炭火力発電所でのバイオマス混焼に対する公衆の受容行動の決定要因を、技術受容モデル(TAM)と計画行動理論(TPB)に情報普及変数を加えて調査した。414人のデータをSEM-PLSで分析した結果、態度と知覚行動制御が意図の強い予測因子であり、意図が参加行動に有意な影響を与えることが示された(パス係数=0.594)。情報普及は態度と知覚行動制御を強化する。実務的には、地域社会への実益を効果的に伝えるコミュニケーション計画の重要性を強調している。

English

This study examines determinants of public acceptance for biomass supply in coal-fired power plants in Indonesia, using TAM and TPB extended with information dissemination. SEM-PLS on 414 respondents shows attitude and perceived behavioral control strongly predict intention, which significantly influences participation behavior (path coefficient 0.594). Information dissemination enhances both attitude and perceived behavioral control. Findings highlight the need for stakeholder collaboration and effective communication of practical benefits to communities.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

インドネシアの事例だが、日本でも石炭火力のバイオマス混焼や地域バイオマス活用において住民受容性は重要。本モデルは日本での実証や市民参加型プロジェクト設計に示唆を与える。ただし、SSBJや開示とは直接関係しない。

In the global GX context

While focused on Indonesia, this study provides a validated model for assessing public acceptance of biomass co-firing, relevant to global decarbonization of coal power. For countries like Japan relying on biomass co-firing, understanding behavioral determinants can improve community engagement strategies. Not directly tied to TCFD/ISSB disclosure, but supports project-level transition finance and social license.

👥 読者別の含意

🔬研究者:Researchers studying public acceptance of renewable energy or biomass co-firing can use this extended TAM-TPB model for similar contexts.

🏢実務担当者:Corporate sustainability teams planning biomass co-firing projects can use findings to design community engagement that communicates practical benefits.

🏛政策担当者:Policymakers designing bioenergy support schemes should consider information dissemination to shape public attitudes and perceived control.

📄 Abstract(原文)

Objective: This study aims to examine the determinants of public acceptance behavior regarding biomass provision for co-firing in coal-fired power plants (CFPPs), to encourage community participation in supporting the sustainability of biomass co-firing initiatives while promoting circular economy practices in the transition toward low-carbon energy systems. Methods: A quantitative survey was conducted using a conceptual model based on the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB), extended by integrating the information dissemination variable to examine public intentions and behaviors regarding biomass energy. Data from 414 individuals were analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS). Findings: The results show that attitude and perceived behavioral control are the strongest predictors of intention, while intention has a substantial effect on community participation behavior (path coefficient = 0.594). The model explains 35.3% of the variance in behavior, indicating a moderate level of explanatory capability. Information dissemination significantly strengthens both attitudes and perceived behavioral control. Originality: This study addresses a gap in the existing literature by examining public intention and acceptance regarding biomass provision within a developing country context in Indonesia. Practical/Policy implication: The findings of this study highlight the importance of collaboration among stakeholders in designing community engagement programs that effectively communicate the practical benefits of participation to local communities.

🔗 Provenance — このレコードを発見したソース

🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録(無料・3キーワードまで)。

gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。