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Group Decision and Negotiation

, Volume 28, Issue 1, pp 11–42 | Cite as

Allocation of Disputable Zones in the Arctic Region

  • Fuad AleskerovEmail author
  • Sergey Shvydun
Article
  • 152 Downloads

Abstract

As a result of the climate change the situation in Arctic area leads to several important consequences. On the one hand, fossil fuels can be exploited much easier than before. On the other hand, their excavation leads to serious potential threats to fishing by changing natural habitats which in turn creates serious damage to the countries’ economies. Another set of problems arises due to the extension of navigable season for shipping routes. Thus, there are already discussions on how should resources be allocated among countries. In Aleskerov and Victorova (An analysis of potential conflict zones in the Arctic Region, HSE Publishing House, Moscow, 2015) a model was presented analyzing preferences of the countries interested in natural resources and revealing potential conflicts among them. We present several areas allocation models based on different preferences over resources among interested countries. As a result, we constructed several allocations where areas are assigned to countries with respect to the distance or the total interest, or according to the procedure which is counterpart of the Adjusted Winner procedure. We consider this work as an attempt to help decision-making authorities in their complex work on adjusting preferences and conducting negotiations in the Arctic zone. We would like to emphasize that these models can be easily extended to larger number of parameters, to the case when some areas for some reasons should be excluded from consideration, to the case with ‘weighted’ preferences with respect to some parameters. And we strongly believe that such models and evaluations based on them can be helpful for the process of corresponding decision making.

Keywords

Arctic region Oil and gas deposits Fishing resources Arctic shipping Zones of mutual interests Areas allocation 

Notes

Acknowledgements

The paper was prepared within the framework of the Basic Research Program at the National Research University Higher School of Economics (HSE) and supported within the framework of a subsidy by the Russian Academic Excellence Project ‘5-100’. The work was conducted by the International Laboratory of Decision Choice and Analysis (DeCAn Lab) of the National Research University Higher School of Economics. We thank two anonymous referees for helpful comments.

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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.National Research University Higher School of EconomicsV.A. Trapeznikov Institute of Control Sciences of Russian Academy of SciencesMoscowRussia

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