<?xml version="1.0" encoding="UTF-8"?><rss version="2.0">
	<channel>
		<title><![CDATA[Mode choice modeling of electric air taxis for long-distance airport trips - ]]></title>
		<description><![CDATA[]]></description>
		<link>https://mail.businessaviation.aero/</link>
										<item>
								<title><![CDATA[Mode choice modeling of electric air taxis for long-distance airport trips: Groundbreaking research]]></title>
				<link>https://mail.businessaviation.aero/directory/white-papers/urban-air-mobility-uam/discussions/review?id=9</link>
				<category><![CDATA[Urban Air Mobility (UAM)]]></category>
				<guid isPermaLink="false">https://mail.businessaviation.aero/directory/white-papers/urban-air-mobility-uam/discussions/review?id=9</guid>
				<description><![CDATA[
				<img src="https://businessaviation.aero/media/reviews/photos/thumbnail/120x120c/94/48/5f/mode-choice-modeling-of-electric-air-taxis-for-long-distance-airport-trips-59-1748519721.webp" decoding="async" loading="lazy" alt="Mode choice modeling of electric air taxis for long-distance airport trips" title="Mode choice modeling of electric air taxis for long-distance airport trips" class="jrMediaPhoto" align="right" />				<div>This groundbreaking research provides essential insights into the future of airport transportation through rigorous analysis of electric air taxi preferences. The comprehensive methodology, incorporating 1,028 participants and advanced ICLV modeling, delivers actionable findings for industry stakeholders. The study's identification of critical factors like access time, service frequency, and psychological barriers offers a roadmap for successful EAT implementation. Particularly valuable is the quantification of time value and the nuanced understanding of consumer psychology, making this an indispensable resource for aviation innovators and policymakers shaping tomorrow's transportation landscape.</div>				]]></description>
				<pubDate>Thu, 29 May 2025 12:32:03 +0000</pubDate>
			</item>
						</channel>
</rss>