Evolutionary game analysis on the recycling strategy of household medical device enterprises under government dynamic rewards and punishments
Under the background of the aging population and the improvement of people's quality of life, the demand for household medical devices is expanding, which has huge market potential. However, the recycling of waste household medical devices has become a problem that must be faced by the market e...
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2021
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oai:doaj.org-article:ae29fe4471e14372becf0917357a65212021-11-11T01:29:31ZEvolutionary game analysis on the recycling strategy of household medical device enterprises under government dynamic rewards and punishments10.3934/mbe.20213201551-0018https://doaj.org/article/ae29fe4471e14372becf0917357a65212021-07-01T00:00:00Zhttps://www.aimspress.com/article/doi/10.3934/mbe.2021320?viewType=HTMLhttps://doaj.org/toc/1551-0018Under the background of the aging population and the improvement of people's quality of life, the demand for household medical devices is expanding, which has huge market potential. However, the recycling of waste household medical devices has become a problem that must be faced by the market expansion. In order to reduce the environmental pollution caused by abandoned household medical devices, based on the dynamic punishment and dynamic subsidy measures adopted by the government, the evolutionary game model between the government and the household medical device enterprises is constructed. The strategic choice of the government and the domestic medical equipment enterprises is studied from the perspective of system dynamics. It is found that when the government adopts static measures, there is no stable equilibrium point in the game between the government and enterprises, while when the government adopts dynamic punishment or subsidies, there is a stable equilibrium point in the evolutionary game. In addition, the government can increase the penalty or reduce the subsidy to promote the probability of household medical device enterprises to choose recycling strategy and reduce environmental pollution.Zheng LiuLingling Lang Lingling LiYuanjun ZhaoLihua ShiAIMS Pressarticlehousehold medical devicesevolutionary gamegovernment supervisiondynamic strategypunishment and subsidy measuresBiotechnologyTP248.13-248.65MathematicsQA1-939ENMathematical Biosciences and Engineering, Vol 18, Iss 5, Pp 6434-6451 (2021) |
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household medical devices evolutionary game government supervision dynamic strategy punishment and subsidy measures Biotechnology TP248.13-248.65 Mathematics QA1-939 |
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household medical devices evolutionary game government supervision dynamic strategy punishment and subsidy measures Biotechnology TP248.13-248.65 Mathematics QA1-939 Zheng Liu Lingling Lang Lingling Li Yuanjun Zhao Lihua Shi Evolutionary game analysis on the recycling strategy of household medical device enterprises under government dynamic rewards and punishments |
description |
Under the background of the aging population and the improvement of people's quality of life, the demand for household medical devices is expanding, which has huge market potential. However, the recycling of waste household medical devices has become a problem that must be faced by the market expansion. In order to reduce the environmental pollution caused by abandoned household medical devices, based on the dynamic punishment and dynamic subsidy measures adopted by the government, the evolutionary game model between the government and the household medical device enterprises is constructed. The strategic choice of the government and the domestic medical equipment enterprises is studied from the perspective of system dynamics. It is found that when the government adopts static measures, there is no stable equilibrium point in the game between the government and enterprises, while when the government adopts dynamic punishment or subsidies, there is a stable equilibrium point in the evolutionary game. In addition, the government can increase the penalty or reduce the subsidy to promote the probability of household medical device enterprises to choose recycling strategy and reduce environmental pollution. |
format |
article |
author |
Zheng Liu Lingling Lang Lingling Li Yuanjun Zhao Lihua Shi |
author_facet |
Zheng Liu Lingling Lang Lingling Li Yuanjun Zhao Lihua Shi |
author_sort |
Zheng Liu |
title |
Evolutionary game analysis on the recycling strategy of household medical device enterprises under government dynamic rewards and punishments |
title_short |
Evolutionary game analysis on the recycling strategy of household medical device enterprises under government dynamic rewards and punishments |
title_full |
Evolutionary game analysis on the recycling strategy of household medical device enterprises under government dynamic rewards and punishments |
title_fullStr |
Evolutionary game analysis on the recycling strategy of household medical device enterprises under government dynamic rewards and punishments |
title_full_unstemmed |
Evolutionary game analysis on the recycling strategy of household medical device enterprises under government dynamic rewards and punishments |
title_sort |
evolutionary game analysis on the recycling strategy of household medical device enterprises under government dynamic rewards and punishments |
publisher |
AIMS Press |
publishDate |
2021 |
url |
https://doaj.org/article/ae29fe4471e14372becf0917357a6521 |
work_keys_str_mv |
AT zhengliu evolutionarygameanalysisontherecyclingstrategyofhouseholdmedicaldeviceenterprisesundergovernmentdynamicrewardsandpunishments AT linglinglang evolutionarygameanalysisontherecyclingstrategyofhouseholdmedicaldeviceenterprisesundergovernmentdynamicrewardsandpunishments AT linglingli evolutionarygameanalysisontherecyclingstrategyofhouseholdmedicaldeviceenterprisesundergovernmentdynamicrewardsandpunishments AT yuanjunzhao evolutionarygameanalysisontherecyclingstrategyofhouseholdmedicaldeviceenterprisesundergovernmentdynamicrewardsandpunishments AT lihuashi evolutionarygameanalysisontherecyclingstrategyofhouseholdmedicaldeviceenterprisesundergovernmentdynamicrewardsandpunishments |
_version_ |
1718439616055345152 |