Modelling motivating factors for individuals’ participation in carbon trading in the construction industry: a fuzzy synthetic evaluation technique
建設業における個人の炭素取引参加の動機要因のモデル化：ファジィ合成評価手法 (AI 翻訳)
Augustine Senanu Komla Kukah, Xiaohua Jin, Robert Osei-Kyei, Srinath Perera
🤖 gxceed AI 要約
日本語
本研究は、建設業における個人の炭素取引への参加を促進する要因を分析する。オーストラリアの業界専門家への調査から13の要因を特定し、因子分析で態度・動機要因と炭素取引認知要因の2群に分類。ファジィ合成評価により個人要因の重要度が高いことを示した。
English
This study evaluates motivating factors for individuals to participate in carbon trading in the construction industry. Through a survey of Australian industry experts, 13 factors were identified and grouped into attitudes/motivation and awareness of carbon trading. Fuzzy synthetic evaluation revealed that individual motivating factors are highly important for carbon trading adoption.
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
オーストラリア建設業界の炭素取引参加動機に関する研究。日本でも建設業の脱炭素化が進む中、個人レベルの動機付け要因の理解は企業のカーボンマネジメント施策に示唆を与える。
In the global GX context
This paper adds to the understanding of individual-level drivers for carbon trading participation, which is critical for the effectiveness of carbon pricing mechanisms globally. The fuzzy synthetic evaluation method is a novel approach for assessing factor importance.
👥 読者別の含意
🔬研究者:Researchers can use the factor list and methodology for further studies on carbon trading motivation in other industries or regions.
🏢実務担当者:Corporate sustainability teams in construction can identify key factors to encourage employee participation in carbon trading schemes.
🏛政策担当者:Policymakers designing carbon market participation incentives may consider the importance of awareness and motivation factors highlighted in this study.
📄 Abstract（原文）
Purpose This study aims to evaluate the factors that motivate individuals to adopt carbon trading in the construction industry and develop an overall factor index level adopting the fuzzy synthetic evaluation technique. Design/methodology/approach A comprehensive review of past literature identified a 13-factor list that was ranked in a survey by industry experts in Australia. The purposive sampling technique was used. Statistical software comprised Statistical Package for Social Sciences version 25 and R-Studio. Findings Component factor analysis was used to cluster the factors into groups, and they served as input variables for the fuzzy synthetic evaluation analysis. The two components were: attitudes and motivation factors and awareness of carbon trading factors (ACTF). From the findings, it can be seen that overall individual factor level is high, indicating ACTF that the influence of individuals’ motivation factors in carbon trading in construction is important. Originality/value This study is significant and contributes towards the construction industry’s climate change reduction agenda. In addition, the research gives a demonstration of the application of fuzzy synthetic evaluation in the evaluation of carbon trading.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1108/ci-04-2025-0174first seen 2026-05-15 18:23:44
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