IDEAS home Printed from https://ideas.repec.org/a/mth/bmh888/v5y2017i2p84-111.html
   My bibliography  Save this article

An Optimal Redesign Approach for Optimal Global Supply Chain Redesign: Brazilian Soybean Grain Study

Author

Listed:
  • Juan Jos¨¦ Uchuya Lop¨¦z
  • Raad Yahya Qassim

Abstract

Brazil and the United States are the leading soybean grain producing and exporting countries in the world. Although crop production cost is significantly lower in Brazil than in the United States due to more advanced crop production technology, this competitive advantage vanishes in view of the higher logistics costs in Brazil than in the United States, in view of the dominance of road transportation in Brazil, whilst river and rail transportation are prevalent in the United States. In order to regain its competitive advantage, there is a clear need for a redesign of the inland supply chain in Brazil through the use and expansion of existent inland waterways and rail networks. In this paper, an optimal supply chain redesign methodology is presented to achieve the aforesaid objective, with a focus on Mato Grosso which is the largest producer and exporting state in Brazil. This methodology is in fact applicable to multiply echelon global supply chains in general.

Suggested Citation

  • Juan Jos¨¦ Uchuya Lop¨¦z & Raad Yahya Qassim, 2017. "An Optimal Redesign Approach for Optimal Global Supply Chain Redesign: Brazilian Soybean Grain Study," Business and Management Horizons, Macrothink Institute, vol. 5(2), pages 84-111, December.
    • Handle: RePEc:mth:bmh888:v:5:y:2017:i:2:p:84-111
    as

    Download full text from publisher

    File URL: http://www.macrothink.org/journal/index.php/bmh/article/view/12284/9735
    Download Restriction: no
    File URL: http://www.macrothink.org/journal/index.php/bmh/article/view/12284
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cao, Dong & Chen, Mingyuan, 2006. "Capacitated plant selection in a decentralized manufacturing environment: A bilevel optimization approach," European Journal of Operational Research, Elsevier, vol. 169(1), pages 97-110, February.
    2. Nicky J. Welton & Howard H. Z. Thom, 2015. "Value of Information," Medical Decision Making, , vol. 35(5), pages 564-566, July.
    3. Hyland, Michael F. & Mahmassani, Hani S. & Bou Mjahed, Lama, 2016. "Analytical models of rail transportation service in the grain supply chain: Deconstructing the operational and economic advantages of shuttle train service," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 294-315.
    4. Nagurney, Anna, 2010. "Optimal supply chain network design and redesign at minimal total cost and with demand satisfaction," International Journal of Production Economics, Elsevier, vol. 128(1), pages 200-208, November.
    5. Cao, D. & Leung, L. C., 2002. "A partial cooperation model for non-unique linear two-level decision problems," European Journal of Operational Research, Elsevier, vol. 140(1), pages 134-141, July.
    6. Reis, Silvia Araújo & Leal, José Eugenio, 2015. "A deterministic mathematical model to support temporal and spatial decisions of the soybean supply chain," Journal of Transport Geography, Elsevier, vol. 43(C), pages 48-58.
    Full references (including those not matched with items on IDEAS)

    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. Vincenzo Varriale & Antonello Cammarano & Francesca Michelino & Mauro Caputo, 2021. "Sustainable Supply Chains with Blockchain, IoT and RFID: A Simulation on Order Management," Sustainability, MDPI, vol. 13(11), pages 1-23, June.
    2. Valeria Costantini & Francesco Crespi & Giovanni Marin & Elena Paglialunga, 2016. "Eco-innovation, sustainable supply chains and environmental performance in European industries," LEM Papers Series 2016/19, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    3. Lee, Alice J. & Ames, Daniel R., 2017. "“I can’t pay more” versus “It’s not worth more”: Divergent effects of constraint and disparagement rationales in negotiations," Organizational Behavior and Human Decision Processes, Elsevier, vol. 141(C), pages 16-28.
    4. Hussain, Hadia & Murtaza, Murtaza & Ajmal, Areeb & Ahmed, Afreen & Khan, Muhammad Ovais Khalid, 2020. "A study on the effects of social media advertisement on consumer’s attitude and customer response," MPRA Paper 104675, University Library of Munich, Germany.
    5. A. G. Fatullayev & Nizami A. Gasilov & Şahin Emrah Amrahov, 2019. "Numerical solution of linear inhomogeneous fuzzy delay differential equations," Fuzzy Optimization and Decision Making, Springer, vol. 18(3), pages 315-326, September.
    6. Cyril Chalendard, 2015. "Use of internal information, external information acquisition and customs underreporting," Working Papers halshs-01179445, HAL.
    7. Arun Advani & William Elming & Jonathan Shaw, 2023. "The Dynamic Effects of Tax Audits," The Review of Economics and Statistics, MIT Press, vol. 105(3), pages 545-561, May.
    8. Aghion, Philippe & Akcigit, Ufuk & Lequien, Matthieu & Stantcheva, Stefanie, 2017. "Tax simplicity and heterogeneous learning," LSE Research Online Documents on Economics 86613, London School of Economics and Political Science, LSE Library.
    9. Marie Bjørneby & Annette Alstadsæter & Kjetil Telle, 2018. "Collusive tax evasion by employers and employees. Evidence from a randomized fi eld experiment in Norway," Discussion Papers 891, Statistics Norway, Research Department.
    10. Chuangen Gao & Shuyang Gu & Jiguo Yu & Hai Du & Weili Wu, 2022. "Adaptive seeding for profit maximization in social networks," Journal of Global Optimization, Springer, vol. 82(2), pages 413-432, February.
    11. Koessler, Frederic & Laclau, Marie & Renault, Jérôme & Tomala, Tristan, 2022. "Long information design," Theoretical Economics, Econometric Society, vol. 17(2), May.
    12. Jamal El-Den & Pratap Adikhari & Pratap Adikhari, 2017. "Social media in the service of social entrepreneurship: Identifying factors for better services," Journal of Advances in Humanities and Social Sciences, Dr. Yi-Hsing Hsieh, vol. 3(2), pages 105-114.
    13. Tuğçe Taşkıner & Bilge Bilgen, 2021. "Optimization Models for Harvest and Production Planning in Agri-Food Supply Chain: A Systematic Review," Logistics, MDPI, vol. 5(3), pages 1-27, August.
    14. Annette Alstadsæter & Wojciech Kopczuk & Kjetil Telle, 2019. "Social networks and tax avoidance: evidence from a well-defined Norwegian tax shelter," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 26(6), pages 1291-1328, December.
    15. Xiongnan Jin & Sejin Chun & Jooik Jung & Kyong-Ho Lee, 0. "A fast and scalable approach for IoT service selection based on a physical service model," Information Systems Frontiers, Springer, vol. 0, pages 1-16.
    16. Jun Hong Park & Sang Ho Kook & Hyeonu Im & Soomin Eum & Chulung Lee, 2018. "Fabless Semiconductor Firms’ Financial Performance Determinant Factors: Product Platform Efficiency and Technological Capability," Sustainability, MDPI, vol. 10(10), pages 1-22, September.
    17. Sebastian Kaumanns, 2019. "“Some fuzzy math”: relational information on debt value adjustments by managers and the financial press," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 755-794, December.
    18. Samuel J Gershman, 2015. "A Unifying Probabilistic View of Associative Learning," PLOS Computational Biology, Public Library of Science, vol. 11(11), pages 1-20, November.
    19. Arun Advani, 2022. "Who does and doesn't pay taxes?," Fiscal Studies, John Wiley & Sons, vol. 43(1), pages 5-22, March.
    20. Steve Fortin & Ahmad Hammami & Michel Magnan, 2021. "Re‐exploring Fair Value Accounting and Value Relevance: An Examination of Underlying Securities," Abacus, Accounting Foundation, University of Sydney, vol. 57(2), pages 220-250, June.

    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:mth:bmh888:v:5:y:2017:i:2:p:84-111. 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: Technical Support Office (email available below). General contact details of provider: http://www.macrothink.org/journal/index.php/bmh .

    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.