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<metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>Combatting climate change through message framing?</dc:title><dc:creator>Ropret Homar,	Aja	(Avtor)
	</dc:creator><dc:creator>Knežević Cvelbar,	Ljubica	(Avtor)
	</dc:creator><dc:subject>tourism</dc:subject><dc:subject>environment</dc:subject><dc:subject>consumer behaviour</dc:subject><dc:subject>sustainable development</dc:subject><dc:subject>loss framing</dc:subject><dc:subject>voluntary carbon offsets</dc:subject><dc:subject>pro-environmental behavior</dc:subject><dc:subject>attitude-behavior gap</dc:subject><dc:subject>online experiment</dc:subject><dc:description>Findings from behavioral economics suggest the currently low take-up of voluntary carbon offsets (VCOs) could be increased by changing the way choices are presented. In this article, we lean on prospect theory to test the effect of loss framing on air traveler's VCO behavior and whether this contrasts with attitudes and behavioral intentions. Borrowing from experimental economics, we conduct an incentive-compatible online experiment with a real-effort task. We find that under certain conditions a loss-framed VCO message leads to higher likelihood of offsetting, indicating some presence of loss aversion. The results also reveal a substantial attitude-behavior gap and intention-behavior gap, previously postulated to be particularly strong in the tourism setting but not yet quantified. Importantly, 28% of participants with a negative attitude toward VCOs chose to offset nonetheless, indicating positive attitudes are not a pre-requisite for behavior, as hitherto stipulated. Practical, theoretical, and methodological implications of the findings are discussed.</dc:description><dc:date>2024</dc:date><dc:date>2023-09-05 14:34:39</dc:date><dc:type>Članek v reviji</dc:type><dc:identifier>149240</dc:identifier><dc:identifier>UDK: 338.48</dc:identifier><dc:identifier>ISSN pri članku: 0047-2875</dc:identifier><dc:identifier>DOI: 10.1177/00472875231179400</dc:identifier><dc:identifier>COBISS_ID: 155243267</dc:identifier><dc:language>sl</dc:language></metadata>
