| Abstrakt: |
European Union cargo and container ports are under pressure to reduce GHG emissions and achieve carbon neutrality by 2050, as mandated by the European Commission. The pace of progress varies among ports. This study examined the characteristics influencing GHG reduction measures in European cargo and container ports and their implications for sustainable investing. The methods used in this study, such as linear regression models to analyze predictive variables, can be applied in sustainable investing to assess which factors most strongly predict a company's environmental, social, and governance performance. Using linear regression models to analyze data from the 33 busiest European ports, we identified five predictive variables: port size, cargo mix, surrounding population density, access to the sea, and the economic wealth of the host country. Our findings revealed that the port size significantly correlates with the adoption of measures to reduce scope 1, 2, and 3 emissions. This study underscores the importance of contextual and operational factors in evaluating sustainability efforts across sectors. The results contribute to drawing parallels with the field of sustainable investing within finance. This offers valuable insights for sustainable investing, emphasizing the importance of considering various contextual and operational factors when evaluating the sustainability efforts of entities in different sectors. [ABSTRACT FROM AUTHOR] |
