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Analysis of the Influence of Training and Feedback Based on Event Data Recorder Information to Improve Safety, Operational and Economic Performance of Road Freight Transport in Brazil

Author

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  • Luid Pereira de Oliveira

    (Federal Institute of Education, Science and Technology of Southeastern Minas Gerais, Campus Santos Dumont 36240-000, Brazil)

  • Felipe Jiménez Alonso

    (University Institute for Automobile Research (INSIA), Universidad Politécnica de Madrid (UPM), 28031 Madrid, Spain)

  • Marcelino Aurélio Vieira da Silva

    (Transportation Engineering Program, Federal University of Rio de Janeiro—UFRJ, Rio de Janeiro 21949-900, Brazil)

  • Breno Tostes de Gomes Garcia

    (Transportation Engineering Program, Federal University of Rio de Janeiro—UFRJ, Rio de Janeiro 21949-900, Brazil)

  • Diana Mery Messias Lopes

    (Transportation Engineering Program, Federal University of Rio de Janeiro—UFRJ, Rio de Janeiro 21949-900, Brazil)

Abstract

Road transport is the principal means of transporting freight and passengers in most developing countries, but several factors, both alone and in conjunction, contribute to increased inefficiency, risk and instability in the sector. The main factors are related to the high number of accidents, structural precariousness, fleet obsolescence, low-skilled drivers and high rates of greenhouse gas emissions. This paper evaluates the influence of implementing a training and feedback procedure associated with event data recorder (EDR) systems for the promotion of better behavior among professional drivers based on safety, operation and economy criteria. The analyses are based on interventions that were carried out during four monitoring phases using data generated by vehicles collected over 13 months of research. The data were converted into indicators and evaluated individually against the criteria and through data envelopment analysis (DEA). The analyses led to the conclusions that the use of EDR systems had positive impacts on all three of the criteria under analysis, and that safety levels can be increased without having to reduce productivity or increase fuel consumption. However, the safety criterion was more sensitive to the association between the technology and training process applied, leading to significant reductions in the indicators analyzed. The study contributes to the association between the methods of analysis and the adoption of specific indicators derived from time variables, leading to the conclusion that the use of EDR systems associated with management training and monitoring procedures can improve economic and operational results in road freight transport (RFT). Furthermore, using the trip data as a structural basis for the training and feedback proved to be very promising for the reduction of unsafe behavior to avoid road accidents.

Suggested Citation

  • Luid Pereira de Oliveira & Felipe Jiménez Alonso & Marcelino Aurélio Vieira da Silva & Breno Tostes de Gomes Garcia & Diana Mery Messias Lopes, 2020. "Analysis of the Influence of Training and Feedback Based on Event Data Recorder Information to Improve Safety, Operational and Economic Performance of Road Freight Transport in Brazil," Sustainability, MDPI, vol. 12(19), pages 1-22, October.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:19:p:8139-:d:422960
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    References listed on IDEAS

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    1. William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), 2011. "Handbook on Data Envelopment Analysis," International Series in Operations Research and Management Science, Springer, number 978-1-4419-6151-8, September.
    2. Bartholomeu, Daniela Bacchi & Caixeta Filho, Jose Vicente, 2008. "Impactos econômicos e ambientais decorrentes do estado de conservação das rodovias brasileiras: um estudo de caso," Brazilian Journal of Rural Economy and Sociology (Revista de Economia e Sociologia Rural-RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 46(3), pages 1-36, September.
    3. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2014. "A review of recent research on green road freight transportation," European Journal of Operational Research, Elsevier, vol. 237(3), pages 775-793.
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. Breno Tostes de Gomes Garcia & Diana Mery Messias Lopes & Ilton Curty Leal Junior & José Carlos Cesar Amorim & Marcelino Aurélio Vieira da Silva & Vanessa de Almeida Guimarães, 2019. "Analysis of the Performance of Transporting Soybeans from Mato Grosso for Export: A Case Study of the Tapajós-Teles Pires Waterway," Sustainability, MDPI, vol. 11(21), pages 1-26, November.
    6. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
    7. Entani, Tomoe & Maeda, Yutaka & Tanaka, Hideo, 2002. "Dual models of interval DEA and its extension to interval data," European Journal of Operational Research, Elsevier, vol. 136(1), pages 32-45, January.
    8. Jaeheon Choi & Kyuil Lee & Hyunmyung Kim & Sunghi An & Daisik Nam, 2020. "Classification of Inter-Urban Highway Drivers’ Resting Behavior for Advanced Driver-Assistance System Technologies using Vehicle Trajectory Data from Car Navigation Systems," Sustainability, MDPI, vol. 12(15), pages 1-20, July.
    9. Joe Zhu, 2009. "Quantitative Models for Performance Evaluation and Benchmarking," International Series in Operations Research and Management Science, Springer, number 978-0-387-85982-8, September.
    10. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    11. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, December.
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    Cited by:

    1. Martin Vlkovský & Jiří Neubauer & Jiří Malíšek & Jaroslav Michálek, 2021. "Improvement of Road Safety through Appropriate Cargo Securing Using Outliers," Sustainability, MDPI, vol. 13(5), pages 1-16, March.
    2. Wang, Shuaian & Yan, Ran, 2023. "Fundamental challenge and solution methods in prescriptive analytics for freight transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 169(C).

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