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      The dynamic relationship between industrialization, urbanization, CO 2 emissions, and transportation modes in Korea: empirical evidence from maritime and air transport

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          Abstract

          This study investigates the causal relationship between logistics efficiency and factors affecting the logistics environment, such as industrialization, urbanization, and CO2 emissions. With the expectation that logistics efficiency will contribute to economic growth and enhance country competitiveness in the near future, it is necessary to confirm the impact of each factor on different transportation modes, such as maritime and air transport. To this end, this study identifies causal relationships between the factors affecting the logistics environment and specific modes of transportation using data from 2010 to 2018. We employed the panel unit root test, panel co-integration test, fully modified OLS (FMOLS), panel dynamic OLS (DOLS), and panel VECM Granger causality tests for the estimations. The results revealed that factors affecting the logistics environment have different effects depending on the modes of transportation. For maritime transportation, long-run bidirectional causal associations were found between port volume, total exports, industrialization, and urbanization. This implies that export promotion and the resulting economic and social environment changes can increase port throughput; this increase can, in turn, develop and improve economic growth and factors affecting the logistics environment. In contrast, for air transport, we detected a long-run, unidirectional causal relationship among these variables and air volume changes with growing exports, urbanization, and industrialization. Thus, this study suggests a theoretical framework for analyzing the causal relationship between the factors affecting the logistics environment and each mode of transportation, providing insights for policymakers to promote logistics efficiency.

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          Most cited references107

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          Testing for a unit root in time series regression

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            Testing for unit roots in heterogeneous panels

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              Unit root tests in panel data: asymptotic and finite-sample properties

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                Author and article information

                Contributors
                minju.song@plymouth.ac.uk
                y.seo@knu.ac.kr
                ilugit@ynu.ac.kr
                Journal
                Transportation (Amst)
                Transportation (Amst)
                Transportation
                Springer US (New York )
                0049-4488
                1572-9435
                19 August 2022
                : 1-27
                Affiliations
                [1 ]GRID grid.413028.c, ISNI 0000 0001 0674 4447, Department of International Economics and Business, , Yeungnam University, ; 280 Daehak-Ro, 38541 Gyeongsan, Gyeongbuk Korea
                [2 ]GRID grid.258803.4, ISNI 0000 0001 0661 1556, School of Economics & Trade, , Kyungpook National University, ; 80 Daehak-Ro, 41566 Daegu, Korea
                [3 ]GRID grid.11201.33, ISNI 0000 0001 2219 0747, Plymouth Business School, , University of Plymouth, ; Plymouth, UK
                Author information
                http://orcid.org/0000-0001-8605-3194
                Article
                10303
                10.1007/s11116-022-10303-x
                9390960
                e823e740-dc5a-4bc3-863b-01a34f11c8cb
                © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

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                Categories
                Article

                logistics efficiency,transportation mode,industrialization,urbanization,co2,panel vecm,granger causality

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