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Climate-friendly transport – analysing structural relationships

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The objective of this study is to assess the impacts of technology, and social, economic, and legal effects on climate-friendly transport. A model is created to identify the relationships between important factors that are creating the concept of climate-friendly transport. Structural equation modelling was used to identify the relationships between 21 measured influencing factors and four latent constructs: technology, legislative, and socioeconomic factors, and green transportation as abstract concepts used to group them. The relationships between all of the measured factors and constructs are calculated indicating the correlations, regression, and covariance between all elements of the study. The relationships between the abstract concepts and factors are calculated. The results of this research will improve insight into all environmentally friendly transport-influencing factors and concepts.
Rocznik
Tom
Strony
7--19
Opis fizyczny
Bibliogr. 20 poz., rys., tab.
Twórcy
  • Faculty of Maritime Studies, University of Rijeka, Studentska 2, 51 000 Rijeka, Croatia
  • Faculty of Maritime Studies, University of Rijeka, Studentska 2, 51 000 Rijeka, Croatia
  • Faculty of Maritime Studies, University of Rijeka, Studentska 2, 51 000 Rijeka, Croatia
  • Rijeka Plus d.o.o, Blaža Polića 2
Bibliografia
  • 1. Agency, U. E. P., 2020, Sources of Greenhouse Gas Emissions, 20.10.2020, https://www.epa.gov/-ghgemi-ssions/sources-greenhouse-gas-emissions.
  • 2. Allison, P.D., 2003, Missing Data Techniques for Structural Equation Modeling, Journal of Abnormal Psychology, vol. 112, no. 4, pp. 545–557.
  • 3. Anderson, J.C., Gerbing, D.W., 1988, Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach, Psychological Bulletin, vol. 103, no. 3, pp. 411–423.
  • 4. Asparouhov, T., Muthén, B., 2009, Exploratory Structural Equation Modeling, Structural Equation Modeling, vol. 16, no. 3, pp. 397–438.
  • 5. Bentler, P.M., 1990, Comparative Fit Indexes in Structural Models, Psychological Bulletin, vol. 107, no. 2, pp. 238–246.
  • 6. Bowen, N.K., Guo, S., 2012, Structural Equation Modeling. Pocket Guides to Social Work Research Methods, Oxford University Press (Copyrighted Material).
  • 7. Browne, M.W., Cudeck, R., 1992, Alternative Ways of Assessing Model Fit, Sociological Methods & Research, vol. 21, no. 2, pp. 230–258.
  • 8. Byrne, B.M., 2013, Structural Equation Modeling with AMOS: Basic Concepts, Applications, and Programming.
  • 9. Chin, W.W., 1998, Issues and Opinion on Structural Equation Modeling, MIS Quarterly: Management Information Systems, vol. 22, no. 1, pp. vii–xvi.
  • 10. Cho, E., Kim, S., 2015, Cronbach’s Coefficient Alpha: Well Known but Poorly Understood, Organizational Research Methods, vol. 18, no. 2, pp. 207–230.
  • 11. Čišić, D., Perić-Hadžić, A., Tijan, E., Ogrizović, D., 2011, Methods of Defining and Evaluating Future Research Priorities in Climate Friendly Transport: Preliminary Results from the REACT Open Consultation, pp. 346–349.
  • 12. Heck, R.H., Thomas, S.L., 2020, An Introduction to Multilevel Modeling Techniques, Routledge.
  • 13. Marsh, H.W., Hau, K.T., Wen, Z., 2004, In Search of Golden Rules: Comment on Hypothesis-Testing Approaches to Setting Cutoff Values for Fit Indexes and Dangers in Overgeneralizing Hu and Bentler’s (1999) Findings, Structural Equation Modeling, vol. 11, no. 3, pp. 320–341.
  • 14. Mohsen Tavakol, R.D., 2011, Making Sense of Cronbach’s Alpha, International Journal of Medical Education, vol. 2, pp. 53–55.
  • 15. Molenaar, K., Washington, S., Diekmann, J., 2000, Structural Equation Model of Construction Contract Dispute Potential, Journal of Construction Engineering and Management, vol. 126, no. 4, pp. 268–276.
  • 16. OECD, 2015, The Carbon Footprint of Global Trade.
  • 17. Radmilović, Z. Čišić, D., 2011, Shaping Climate Friendly Transport in Europe: Key Findings & Future Directions, REACT 2011, Proceedings. Belgrade: University of Belgrade – The Faculty of Transport and Traffic Engineering.
  • 18. Viswesvaran, C., Ones, D.S., 1995, Theory Testing: Combining Psychometric Meta-analysis and Structural Equations Modeling, Personnel Psychology, vol. 48, no. 4, pp. 865–885.
  • 19. Wayne, S.W., Sandoval, J.A., Clark, N.N., 2009, Emissions Benefits from Alternative Fuels and Advanced Technology in the U.S. Transit Bus Fleet, Energy and Environment, vol. 20, no. 4, pp. 497–515.
  • 20. Wolf, E.J., Harrington, K.M., Clark, S.L., Miller, M.W., 2013, Sample Size Requirements for Structural Equation Models: An Evaluation of Power, Bias, and Solution Propriety, Educational and Psychological Measurement, vol. 73, no. 6, pp. 913–934.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f80f108c-4fb4-4c13-8d98-d0814e1cdbec
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