TY - JOUR
T1 - Environmental performance assessment in the transport sector using nonparametric frontier analysis
T2 - A systematic literature review
AU - Hatami-Marbini, A
AU - Asu, John Otu
AU - Khoshnevis, Pegah
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2024/3/1
Y1 - 2024/3/1
N2 - The increasing environmental issues relating to carbon dioxide emissions are a primary concern globally and have triggered excessive research to investigate possible ways to reduce such emissions, especially in the transport sector, as initiated by Sustainable Development Goal (SDG) 13. This study investigates the importance of the nonparametric frontier analysis methodology, particularly Data Envelopment Analysis, in measuring environmental performance in the transport sector, emphasising how EU countries are working on meeting the recommendations of SDG 13. Researchers and policymakers have indisputably identified the transport sector as the primary source of global emissions. This paper aims to underline the significant environmental trends in the transport sector, including research topics, key works, research methods, future research direction, and recommendations to explore possible global or regional research agendas. In this regard, we mainly focus on various techniques used to measure the environmental performance within the transport sector. This research considers 186 articles from 46 journals. The survey's main findings show the ever-increasing attention paid to studying the transport sector's emissions, emphasising road and passenger car CO2 emissions as the major source of emissions in the transport sector. In the existing literature, the top three frequently adopted methodologies for measuring environmental performance in transportation include Data Envelopment Analysis, emission analysis, and simulation. This study shows research gaps and future directions on environmental performance assessment within the transport sector, particularly maritime and aviation.
AB - The increasing environmental issues relating to carbon dioxide emissions are a primary concern globally and have triggered excessive research to investigate possible ways to reduce such emissions, especially in the transport sector, as initiated by Sustainable Development Goal (SDG) 13. This study investigates the importance of the nonparametric frontier analysis methodology, particularly Data Envelopment Analysis, in measuring environmental performance in the transport sector, emphasising how EU countries are working on meeting the recommendations of SDG 13. Researchers and policymakers have indisputably identified the transport sector as the primary source of global emissions. This paper aims to underline the significant environmental trends in the transport sector, including research topics, key works, research methods, future research direction, and recommendations to explore possible global or regional research agendas. In this regard, we mainly focus on various techniques used to measure the environmental performance within the transport sector. This research considers 186 articles from 46 journals. The survey's main findings show the ever-increasing attention paid to studying the transport sector's emissions, emphasising road and passenger car CO2 emissions as the major source of emissions in the transport sector. In the existing literature, the top three frequently adopted methodologies for measuring environmental performance in transportation include Data Envelopment Analysis, emission analysis, and simulation. This study shows research gaps and future directions on environmental performance assessment within the transport sector, particularly maritime and aviation.
KW - Data envelopment analysis
KW - Transportation
KW - Environment
KW - Performance assessment
KW - CO2
KW - CO
UR - http://www.scopus.com/inward/record.url?scp=85186625608&partnerID=8YFLogxK
U2 - 10.1016/j.cie.2024.109968
DO - 10.1016/j.cie.2024.109968
M3 - Review article
VL - 189
JO - Computers and Industrial Engineering
JF - Computers and Industrial Engineering
SN - 0360-8352
M1 - 109968
ER -