Transition to carbon-neutral tourism: A demand-driven approach
カーボンニュートラル観光への移行:需要主導のアプローチ (AI 翻訳)
Pezhman Hatamifar
🤖 gxceed AI 要約
日本語
本博士論文は、フィンランドの若年層を対象に、旅行者の低炭素行動の意思決定プロセスを需要側から分析する。計画行動理論や規範活性化モデル、Avoid-Shift-Improveフレームワークを統合し、態度と行動のギャップや責任帰属に着目。951名の学生調査に基づき、カーボンニュートラル観光への移行には旅行者・業界・政府の協働が必要と結論づける。
English
This dissertation examines carbon-neutral tourism from a demand-side perspective, focusing on young adults in Finland. Integrating behavioral frameworks like the Theory of Planned Behavior and Avoid-Shift-Improve, it analyzes survey data from 951 university students to understand low-carbon travel decisions. Findings highlight the attitude-behavior gap and the need for collective action among travelers, industry, and government.
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
日本では観光分野の脱炭素が注目されるが、需要側の行動変容研究は少ない。本論文の枠組みは、日本の観光政策や地域活性化における低炭素行動促進策の設計に示唆を与える。
In the global GX context
Globally, tourism decarbonization often focuses on supply-side measures. This demand-side study offers a behavioral framework applicable to other countries, complementing policy efforts like the Glasgow Declaration and contributing to sustainable tourism scholarship.
👥 読者別の含意
🔬研究者:Provides an integrated behavioral framework for studying low-carbon travel decisions, useful for tourism and sustainability researchers.
🏢実務担当者:Offers insights into traveler motivations and barriers, informing the design of low-carbon tourism products and marketing.
🏛政策担当者:Highlights the need for multi-level governance and collective responsibility in promoting carbon-neutral tourism.
📄 Abstract(原文)
As the climate consequences of tourism become increasingly difficult to overlook, understanding how carbon implications shape travel decisions has emerged as a critical yet underexplored research focus. Although scholarship on tourism-related emissions has expanded substantially, the field has paid uneven attention to how climate considerations are integrated into travelers’ decision-making processes. This dissertation examines carbon-neutral tourism from a demand-side perspective with a specific focus on young adults and Finland. It focuses on how young travelers interpret, negotiate, and enact low-carbon choices in everyday travel contexts. Drawing on research on pro-environmental behavior, the study conceptualizes carbon-neutral travel behavior as a socially embedded, layered process shaped by individual motivations, moral considerations, perceived responsibility, and structural constraints. Particular attention is given to the persistence of the attitude–behavior gap and to the distribution of responsibility for climate action among travelers, industry stakeholders, and governments. The dissertation adopts an integrated and interdisciplinary framework to explain the attitudinal, normative, responsibility-based, and behavioral dimensions of carbon-neutral travel behavior. Drawing on behavioral and sustainability research, the study combines perspectives from the Theory of Planned Behavior, the Norm Activation Model, Attribution Theory, and the Avoid–Shift–Improve framework to examine low-carbon decision-making across different travel domains and levels of behavioral adoption. By differentiating awareness of positive and negative consequences, the study refines the understanding of personal norm activation, while the Avoid–Shift–Improve framework translates these underlying decision-making processes into differentiated behavioral pathways, structuring low-carbon decisions across key travel domains (e.g., mobility, accommodation, and consumption practices) and varying levels of adoption (e.g., weak, moderate, and strong engagement). Finland provides a specific context for studying carbon-neutral travel behavior because it presents a sustainability paradox in which strong environmental commitments coexist with mobility and consumption patterns that may sustain high carbon emissions. The dissertation comprises a set of interconnected studies based on survey data collected independently in two survey rounds conducted between 2023 and 2025, involving 951 university students. Young adults constitute an analytically significant group because their travel practices are still forming, while their long-term mobility and consumption patterns will substantially influence the future carbon trajectory of tourism. The analysis employs quantitative methods and is complemented by conceptual and theory-led qualitative data analysis. The dissertation contributes to tourism studies and tourism geography by advancing a theoretically informed and empirically grounded understanding of the transition to carbon-neutral tourism. The novelty of the study lies in its demand-side analytical focus and in the integration of multiple behavioral frameworks to provide a more comprehensive explanation of carbon-neutral tourism behavior. Adopting an interdisciplinary perspective that is situated within tourism geography, particularly research on tourism mobility, travel consumption, and socio-spatial behavior, and informed by behavioral psychology and sustainability research, it confirms that low-carbon travel behavior cannot be reduced to individual attitudes or intentions alone. Further on, it suggests that low-carbon behavior should be viewed in relation to social norms, awareness of the benefits of low-carbon actions, attribution of responsibility, and the specific social and structural contexts that influence travel choices. The findings indicate that moving toward carbon-neutral tourism requires collective effort across travelers, industry stakeholders, and governing bodies at multiple levels, with all playing interconnected roles. By treating carbon-neutral tourism as a demand-side perspective, the study provides a foundation for more detailed analyses of behavioral change across the social and spatial dimensions of tourism.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.30671/nordia.186943first seen 2026-08-14 05:05:13
🔔 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。