Preferences for Alternative Fuel Trucks among International Transport Companies

Tannaz Jahaniaghdam, Amir Reza Mamdoohi (), Salman Aghidi Kheyrabadi, Mehdi Mehryar and Francesco Ciari
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Tannaz Jahaniaghdam: Economics and System Department, Institute for Management and Planning Studies, Tehran 1978914116, Iran
Amir Reza Mamdoohi: Faculty of Civil & Environmental Engineering, Tarbiat Modares University, Tehran 1411713116, Iran
Salman Aghidi Kheyrabadi: Faculty of Civil & Environmental Engineering, Tarbiat Modares University, Tehran 1411713116, Iran
Mehdi Mehryar: Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran 1584715414, Iran
Francesco Ciari: Department of Civil, Geological and Mining Engineering, Polytechnique Montréal University, Montreal, QC H3T 1J4, Canada

World, 2023, vol. 4, issue 4, 1-21

Abstract: Fossil-fuel consumption in land freight is over 19%. Alternative fuel trucks (AFTs) help decrease greenhouse gas emissions. However, AFT preferences in international land transit have received little attention due to passing through various countries with different financial and regulation plans. This variety affects AFTs’ market share. This study analyzes factors influencing AFT preferences in international land transit. A questionnaire (designed in four sections) was distributed among international transport companies in Iran and Europe. A principal component analysis helped extract principal components composed of cognitive, environmental, policy, practical, and economic variables. The multinomial logit models include 26 meaningful variables. The marginal effect analysis shows that the service quality of the manufacturer, importance of greenhouse gas mitigation, and social responsibility do not significantly elevate AFT preferences. In addition, cargo type influences AFT choice. The results of this study help to identify the barriers affecting AFTs’ market share, which can positively impact air pollution.

Keywords: alternative fuel; greenhouse gas emissions; heavy-duty truck; international land freight; multinomial logit model; principal component analysis (search for similar items in EconPapers)
JEL-codes: G15 G17 G18 L21 L22 L25 L26 Q42 Q43 Q47 Q48 R51 R52 R58 (search for similar items in EconPapers)
Date: 2023
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