Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Decoding Green Transition: Unraveling Behavioral Catalysts in the Adoption of Low-Carbon Transportation for Heavy-Duty Vehicles and Off-Road Equipment in California

Version 1 : Received: 19 December 2023 / Approved: 20 December 2023 / Online: 20 December 2023 (13:01:08 CET)

A peer-reviewed article of this Preprint also exists.

Chowdhury, V.; Tuli, F.M.; Mitra, S.K. Sustainable Shift: Analyzing Drivers for Low-Carbon Transportation Adoption in California’s Heavy-Duty and Off-Road Sectors. Sustainability 2024, 16, 1722. Chowdhury, V.; Tuli, F.M.; Mitra, S.K. Sustainable Shift: Analyzing Drivers for Low-Carbon Transportation Adoption in California’s Heavy-Duty and Off-Road Sectors. Sustainability 2024, 16, 1722.

Abstract

The transportation sector stands out as California's primary contributor to greenhouse gas emissions, necessitating urgent action from government agencies to promote the adoption of low-carbon transportation (LCT) within the heavy-duty vehicles (HDV) and off-road equipment (ORE) sectors. This study conducts content analysis to delve into the impact of behavioral factors, specifically awareness and impression, on LCT adoption within these sectors. The analysis results are honed using a generative artificial intelligence (AI) tool. Positive associations emerge between the potential for LCT adoption and awareness, as well as factors linked to LCT (government incentives, environmental considerations). Notably, the study reveals that financial barriers and incentives hold greater significance for small-fleet organizations compared to their large-fleet counterparts. These findings offer actionable insights for government agencies to formulate targeted strategies, including mandates and incentives, tailored to the unique needs of organizations within the HDV and ORE sectors.

Keywords

low-carbon transportation; generative AI; California; heavy-duty vehicles; off-road equipment

Subject

Environmental and Earth Sciences, Sustainable Science and Technology

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