IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i21p6124-d283093.html
   My bibliography  Save this article

Analysis of the Performance of Transporting Soybeans from Mato Grosso for Export: A Case Study of the Tapajós-Teles Pires Waterway

Author

Listed:
  • 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)

  • Ilton Curty Leal Junior

    (Graduate Program in Administration, Federal Fluminense University, Volta Redonda 27.213-145, RJ, Brazil)

  • José Carlos Cesar Amorim

    (Military Institute of Engineering, Rio de Janeiro 22290-270, Brazil)

  • Marcelino Aurélio Vieira da Silva

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

  • Vanessa de Almeida Guimarães

    (Celso Suckow da Fonseca Federal Center for Technological Education, CEFET, Angra dos Reis 23.953-030, RJ, Brazil)

Abstract

The inefficiency of Brazil’s logistics system to handle the outflow of farm products impairs the sector’s performance. From the economic perspective, the high freight rates put the country’s agricultural sector at a competitive disadvantage in the global market. Besides this, the reliance on highway transport causes problems of an environmental (high CO 2 emissions) and social nature (large occurrence of accidents). As an alternative to this dependence, Brazil has an extensive network of actually and potentially navigable rivers that could serve as a key element to improve the performance of the agricultural sector. Therefore, the objective of this study is to analyze the possible influence of the Tapajós-Teles Pires Waterway on the sustainable performance of 19 Brazilian soybean export routes, using data envelopment analysis (DEA). Of these, only three would use the Tapajós-Teles Pires Waterway, which is not yet in operation. The origins of the routes are four soybean-producing centers located in Mato Grosso, the Brazilian state that produces the most soybeans, destined for 12 seaports. The inputs considered are Accident Cost and CO2 Emissions, while the output is Cargo Carried per US$. For this, we use the DEA-VRS (Variable Return Scale) input-oriented model. The results obtained from the DEA model revealed satisfactory performance of the routes using the Tapajós-Teles Pires Waterway from three of the four production centers. In Campo Novo do Parecis, some 16% (471 km) of the route is composed of highways and the rest of the waterway (84%, 1576 km). In Sorriso, only 3% (85 km) of the route consists of highways, while waterway transport is responsible for 97% (2388 km), and in Querência, 24.55% of the route to the Port of Barcarena consists of highways. The use of these routes and the combination of the two transport modes presented the best efficiency indexes, making development of the waterway a key element to improve the outflow of soybeans for export. The results of this study may help Brazilian authorities to define public policies and apply resources to improve the deficiencies of the transportation system, which can lead to a better balance of the Brazilian transportation matrix.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:21:p:6124-:d:283093
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/21/6124/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/21/6124/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Barth, Matthew & Boriboonsomsin, Kanok, 2010. "Real-World Carbon Dioxide Impacts of Traffic Congestion," University of California Transportation Center, Working Papers qt07n946vd, University of California Transportation Center.
    2. 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.
    3. Guimarães, Vanessa de Almeida & Leal Junior, Ilton Curty & da Silva, Marcelino Aurélio Vieira, 2018. "Evaluating the sustainability of urban passenger transportation by Monte Carlo simulation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 732-752.
    4. Christos Zikopoulos, 2019. "Determination of freight rates under stochastic demand and freight consolidation savings," International Journal of Production Research, Taylor & Francis Journals, vol. 57(17), pages 5556-5573, September.
    5. Yang, Hongliang & Pollitt, Michael, 2010. "The necessity of distinguishing weak and strong disposability among undesirable outputs in DEA: Environmental performance of Chinese coal-fired power plants," Energy Policy, Elsevier, vol. 38(8), pages 4440-4444, August.
    6. Dan He & Peng Gao & Zhijing Sun & Yui-yip Lau, 2017. "Measuring Water Transport Efficiency in the Yangtze River Economic Zone, China," Sustainability, MDPI, vol. 9(12), pages 1-13, December.
    7. Dekker, Rommert & Bloemhof, Jacqueline & Mallidis, Ioannis, 2012. "Operations Research for green logistics – An overview of aspects, issues, contributions and challenges," European Journal of Operational Research, Elsevier, vol. 219(3), pages 671-679.
    8. Barkenbus, Jack N., 2010. "Eco-driving: An overlooked climate change initiative," Energy Policy, Elsevier, vol. 38(2), pages 762-769, February.
    9. 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.
    10. Caitlin D. Cottrill & Sybil Derrible, 2015. "Leveraging Big Data for the Development of Transport Sustainability Indicators," Journal of Urban Technology, Taylor & Francis Journals, vol. 22(1), pages 45-64, January.
    11. Olli-Pekka Hilmola & Harri Lorentz & Dawna L Rhoades, 2015. "New environmental demands and the future of the Helsinki−Tallinn freight route," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 17(2), pages 198-220, June.
    12. Santos, Georgina & Maoh, Hanna & Potoglou, Dimitris & von Brunn, Thomas, 2013. "Factors influencing modal split of commuting journeys in medium-size European cities," Journal of Transport Geography, Elsevier, vol. 30(C), pages 127-137.
    13. World Commission on Environment and Development,, 1987. "Our Common Future," OUP Catalogue, Oxford University Press, number 9780192820808.
    14. Fazlollahi, Ariyan & Franke, Ulrik, 2018. "Measuring the impact of enterprise integration on firm performance using data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 200(C), pages 119-129.
    15. Kaiser, Ilza Machado & Bezerra, Barbara Stolte & Castro, Leslie Ivana Serino, 2013. "Is the environmental policies procedures a barrier to development of inland navigation and port management? A case of study in Brazil," Transportation Research Part A: Policy and Practice, Elsevier, vol. 47(C), pages 78-86.
    16. Asoke Dey & Paul LaGuardia & Mahesh Srinivasan, 2011. "Building sustainability in logistics operations: a research agenda," Management Research Review, Emerald Group Publishing Limited, vol. 34(11), pages 1237-1259, October.
    17. Rizos, Vasileios & Tuokko, Katja & Behrens, Arno, 2017. "The Circular Economy: A review of definitions, processes and impacts," CEPS Papers 12440, Centre for European Policy Studies.
    18. Sahoo, Biresh K. & Luptacik, Mikulas & Mahlberg, Bernhard, 2011. "Alternative measures of environmental technology structure in DEA: An application," European Journal of Operational Research, Elsevier, vol. 215(3), pages 750-762, December.
    19. Vasco Correa, Carlos Andrés, 2012. "Economic evaluation of current conditions of competition and efficiency of automotive and rail systems in Colombia," Energy Policy, Elsevier, vol. 46(C), pages 78-87.
    20. Todd Litman & David Burwell, 2006. "Issues in sustainable transportation," International Journal of Global Environmental Issues, Inderscience Enterprises Ltd, vol. 6(4), pages 331-347.
    21. Genovese, Andrea & Acquaye, Adolf A. & Figueroa, Alejandro & Koh, S.C. Lenny, 2017. "Sustainable supply chain management and the transition towards a circular economy: Evidence and some applications," Omega, Elsevier, vol. 66(PB), pages 344-357.
    22. 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.
    23. 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.
    24. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, December.
    25. Luis Miguel Fonseca & José Pedro Domingues & Maria Teresa Pereira & Florinda Figueiredo Martins & Dominik Zimon, 2018. "Assessment of Circular Economy within Portuguese Organizations," Sustainability, MDPI, vol. 10(7), pages 1-24, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Gustavo Rodrigues de Morais & Yuri Clements Daglia Calil & Gabriel Faria de Oliveira & Rodney Rezende Saldanha & Carlos Andrey Maia, 2023. "A Sustainable Location Model of Transshipment Terminals Applied to the Expansion Strategies of the Soybean Intermodal Transport Network in the State of Mato Grosso, Brazil," Sustainability, MDPI, vol. 15(2), pages 1-27, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shih-Heng Yu, 2019. "Benchmarking and Performance Evaluation Towards the Sustainable Development of Regions in Taiwan: A Minimum Distance-Based Measure with Undesirable Outputs in Additive DEA," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 144(3), pages 1323-1348, August.
    2. Cheng, Gang & Zervopoulos, Panagiotis & Qian, Zhenhua, 2013. "A variant of radial measure capable of dealing with negative inputs and outputs in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 225(1), pages 100-105.
    3. 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.
    4. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min & Lin, Bruce J.Y., 2013. "Data envelopment analysis 1978–2010: A citation-based literature survey," Omega, Elsevier, vol. 41(1), pages 3-15.
    5. Mehdiloozad, Mahmood & Zhu, Joe & Sahoo, Biresh K., 2018. "Identification of congestion in data envelopment analysis under the occurrence of multiple projections: A reliable method capable of dealing with negative data," European Journal of Operational Research, Elsevier, vol. 265(2), pages 644-654.
    6. Amineh Ghazi & Farhad Hosseinzadeh Lotfi & Masoud Sanei, 2020. "Hybrid efficiency measurement and target setting based on identifying defining hyperplanes of the PPS with negative data," Operational Research, Springer, vol. 20(2), pages 1055-1092, June.
    7. Vicente J. Bolós & Rafael Benítez & Vicente Coll-Serrano, 2023. "Continuous models combining slacks-based measures of efficiency and super-efficiency," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(2), pages 363-391, June.
    8. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min & Lin, Bruce J.Y., 2013. "A survey of DEA applications," Omega, Elsevier, vol. 41(5), pages 893-902.
    9. Liu, John S. & Lu, Wen-Min, 2010. "DEA and ranking with the network-based approach: a case of R&D performance," Omega, Elsevier, vol. 38(6), pages 453-464, December.
    10. Bougnol, M.-L. & Dulá, J.H. & Estellita Lins, M.P. & Moreira da Silva, A.C., 2010. "Enhancing standard performance practices with DEA," Omega, Elsevier, vol. 38(1-2), pages 33-45, February.
    11. Zou, Bo & Kafle, Nabin & Chang, Young-Tae & Park, Kevin, 2015. "US airport financial reform and its implications for airport efficiency: An exploratory investigation," Journal of Air Transport Management, Elsevier, vol. 47(C), pages 66-78.
    12. Chen, Chien-Ming, 2013. "Super efficiencies or super inefficiencies? Insights from a joint computation model for slacks-based measures in DEA," European Journal of Operational Research, Elsevier, vol. 226(2), pages 258-267.
    13. Shiu-Wan Hung & Chao-Liang Chang & Shu Ming Liu, 2019. "Innovation System Assessment Model for Sustainability Planning in Taiwan," Sustainability, MDPI, vol. 11(24), pages 1-24, December.
    14. Brissimis, Sophocles N. & Zervopoulos, Panagiotis D., 2012. "Developing a step-by-step effectiveness assessment model for customer-oriented service organizations," European Journal of Operational Research, Elsevier, vol. 223(1), pages 226-233.
    15. Beltrán-Esteve, Mercedes & Picazo-Tadeo, Andrés J., 2015. "Assessing environmental performance trends in the transport industry: Eco-innovation or catching-up?," Energy Economics, Elsevier, vol. 51(C), pages 570-580.
    16. Gerami, Javad & Mozaffari, Mohammad Reza & Wanke, Peter F. & Correa, Henrique L., 2022. "Improving information reliability of non-radial value efficiency analysis: An additive slacks based measure approach," European Journal of Operational Research, Elsevier, vol. 298(3), pages 967-978.
    17. Andrés J. Picazo-Tadeo & Juana Castillo & Mercedes Beltrán-Esteve, 2013. "A dynamic approach to measuring ecological-economic performance with directional distance functions: greenhouse gas emissions in the European Union," Working Papers 1304, Department of Applied Economics II, Universidad de Valencia.
    18. Victor V. Podinovski & Robert G. Chambers & Kazim Baris Atici & Iryna D. Deineko, 2016. "Marginal Values and Returns to Scale for Nonparametric Production Frontiers," Operations Research, INFORMS, vol. 64(1), pages 236-250, February.
    19. Mehdi Toloo, 2021. "An Equivalent Linear Programming Form of General Linear Fractional Programming: A Duality Approach," Mathematics, MDPI, vol. 9(14), pages 1-9, July.
    20. Chen, Chien-Ming, 2013. "A critique of non-parametric efficiency analysis in energy economics studies," Energy Economics, Elsevier, vol. 38(C), pages 146-152.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:11:y:2019:i:21:p:6124-:d:283093. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.