Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Stackelberg model and public-private partnerships in the natural resources sector of Russia. / Lavlinskii, Sergey; Panin, Artem; Plyasunov, Aleksandr V.
Mathematical Optimization Theory and Operations Research - 18th International Conference, MOTOR 2019, Proceedings. ed. / Michael Khachay; Panos Pardalos; Yury Kochetov. Springer-Verlag GmbH and Co. KG, 2019. p. 158-171 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11548 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
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TY - GEN
T1 - Stackelberg model and public-private partnerships in the natural resources sector of Russia
AU - Lavlinskii, Sergey
AU - Panin, Artem
AU - Plyasunov, Aleksandr V.
N1 - Publisher Copyright: © Springer Nature Switzerland AG 2019.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - A comparative analysis is conducted of the efficiency of different partnership models in the natural resources sector of Russia. The first one is a classic public-private partnership (PPP) model used in developed countries, whereby a private company builds an object of public property and transfers it to the government either immediately after the construction or after a certain period of operation of the object. The second model represents for the government a costly alternative of the former and is used in Russia in underdeveloped regions. This model assumes that the government supports the investor in infrastructure development and, in part, in the implementation of mandatory environmental protection measures and can also provide tax incentives. In practical terms, this work aims to look into possible ways of transforming the current Russian PPP model towards the classic forms of partnership. To conduct the comparative analysis of the PPP models, Stackelberg models are formulated and original iterative algorithms are developed for solving the corresponding bilevel Boolean programming problems based on probabilistic local search. The properties of the equilibrium solutions are studied using real data for the Transbaikal krai. Based on the modeling results, the different partnership models are compared to find out the conditions under which the private investor would choose to invest in publicly owned industrial infrastructure facilities in Russia.
AB - A comparative analysis is conducted of the efficiency of different partnership models in the natural resources sector of Russia. The first one is a classic public-private partnership (PPP) model used in developed countries, whereby a private company builds an object of public property and transfers it to the government either immediately after the construction or after a certain period of operation of the object. The second model represents for the government a costly alternative of the former and is used in Russia in underdeveloped regions. This model assumes that the government supports the investor in infrastructure development and, in part, in the implementation of mandatory environmental protection measures and can also provide tax incentives. In practical terms, this work aims to look into possible ways of transforming the current Russian PPP model towards the classic forms of partnership. To conduct the comparative analysis of the PPP models, Stackelberg models are formulated and original iterative algorithms are developed for solving the corresponding bilevel Boolean programming problems based on probabilistic local search. The properties of the equilibrium solutions are studied using real data for the Transbaikal krai. Based on the modeling results, the different partnership models are compared to find out the conditions under which the private investor would choose to invest in publicly owned industrial infrastructure facilities in Russia.
KW - Bilevel mathematical programming problems
KW - Mineral resources development program
KW - Probabilistic local search algorithm
KW - Stackelberg game
UR - http://www.scopus.com/inward/record.url?scp=85067662189&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-22629-9_12
DO - 10.1007/978-3-030-22629-9_12
M3 - Conference contribution
AN - SCOPUS:85067662189
SN - 9783030226282
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 158
EP - 171
BT - Mathematical Optimization Theory and Operations Research - 18th International Conference, MOTOR 2019, Proceedings
A2 - Khachay, Michael
A2 - Pardalos, Panos
A2 - Kochetov, Yury
PB - Springer-Verlag GmbH and Co. KG
T2 - 18th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2019
Y2 - 8 July 2019 through 12 July 2019
ER -
ID: 20643646