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Pollution sensitive global crude steel production–transportation model under the effect of corruption perception index

Author

Listed:
  • Kousik Bhattacharya

    (Midnapore College (Autonomous))

  • Sujit Kumar De

    (Midnapore College (Autonomous))

  • Anup Khan

    (Midnapore College (Autonomous))

  • Prasun Kumar Nayak

    (Midnapore College (Autonomous))

Abstract

This article explores global crude steel production transportation problem under the effect of corruption perception index of major steel producing countries. Also, pollution from production process as well as from the transportation system plays vital role towards sustainable development of any country. The development by means of reduction of health hazards, increase of gross domestic product (GDP) in real sense of several country, minimize the number of hungers and also controlling the corruptions in industrial sectors throughout the world. First of all, we have developed functional dependencies among the decision variables like production rate, consumption rate, corruption perception index and pollution indexes of different countries. However, we incorporate pollution due to rail freight transport in a simple production-supply model so as to minimize the average system cost with respect of several constraints for global sustainability in production-consumption-pollutions-corruptions process. In this study we have shown how GDP relates to corruptions, production, and pollution and reduce poverty exclusively. Taking secondary data of 61 countries from world steel annual report 2017, utilizing MATLAB software and LINGO software for data analysis and numerical computation we have come to several decision points. Using fuzzy system, we have shown how human resource development is possible by taking a considerable limit of corruption and pollution indexes. Graphical illustrations and sensitivity analysis are made to show the model validation by means of consumer’s adaptations with such global production set-up.

Suggested Citation

  • Kousik Bhattacharya & Sujit Kumar De & Anup Khan & Prasun Kumar Nayak, 2021. "Pollution sensitive global crude steel production–transportation model under the effect of corruption perception index," OPSEARCH, Springer;Operational Research Society of India, vol. 58(3), pages 636-660, September.
    • Handle: RePEc:spr:opsear:v:58:y:2021:i:3:d:10.1007_s12597-020-00498-x
    DOI: 10.1007/s12597-020-00498-x
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    References listed on IDEAS

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    1. Candau, Fabien & Dienesch, Elisa, 2017. "Pollution Haven and Corruption Paradise," Journal of Environmental Economics and Management, Elsevier, vol. 85(C), pages 171-192.
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    5. Mr. Vito Tanzi & Mr. Hamid R Davoodi, 2000. "Corruption, Growth, and Public Finances," IMF Working Papers 2000/182, International Monetary Fund.
    6. Arvind K. Jain, 2001. "Corruption: A Review," Journal of Economic Surveys, Wiley Blackwell, vol. 15(1), pages 71-121, February.
    7. Paolo Mauro, 1995. "Corruption and Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(3), pages 681-712.
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    Cited by:

    1. Wu, Zhengtian & Gao, Qing & Jiang, Baoping & Karimi, Hamid Reza, 2021. "Solving the production transportation problem via a deterministic annealing neural network method," Applied Mathematics and Computation, Elsevier, vol. 411(C).

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