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Full Length Article | Open Access

Barriers and drivers for sustainable public transportation in Indian context

Department of Mechanical Engineering, Indian Institute of Technology, Varanasi, India
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HIGHLIGHTS

● Analysing, Categorizing and Evaluating the primary factors that influence the adoption and utilisation of electric buses.

● Determining the correlations between deployment barriers and latent and observable variables for electric buses.

● Performance of a hybrid analysis (combining Exploratory Factor Analysis and Confirmatory Factor Analysis).

● Providing key insights and managerial implications for the decision-makers.

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Abstract

Rising negative externalities, including greenhouse gas emissions, climate change, and environmental pollution, shows the need for sustainable and environmentally friendly modes of transportation. Adopting zero-emission, environmentally friendly electric buses in public transportation systems can be an effective solution for both developing and developed countries, including India. While the Indian government is making numerous efforts to promote electric buses in commercial and public transportation systems, it faces several formidable obstacles. This research objective is to analyze and evaluate the primary factors influencing the adoption and usage of electric buses in the Indian public transportation system, within the limited available resources. A survey questionnaire is prepared with several perceptual subjects for the key perceived barriers. An empirical analysis using Structural Equation Modeling (SEM) is then performed to identify the critical barriers. The result of this study demonstrates that the infrastructural barriers substantially impact the adoption and utilization of electric buses. Further, the study provides critical insights and managerial implications for decision-makers.

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Green Energy and Intelligent Transportation
Article number: 100141
Cite this article:
R G, Pathak DV, Pratap S, et al. Barriers and drivers for sustainable public transportation in Indian context. Green Energy and Intelligent Transportation, 2024, 3(1): 100141. https://doi.org/10.1016/j.geits.2023.100141
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