scholarly journals An Evolutionary Game Theory Study for Construction and Demolition Waste Recycling Considering Green Development Performance under the Chinese Government’s Reward–Penalty Mechanism

2020 ◽  
Vol 17 (17) ◽  
pp. 6303 ◽  
Author(s):  
Hongyu Long ◽  
Hongyong Liu ◽  
Xingwei Li ◽  
Longjun Chen
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Construction And Demolition Waste ◽  
Decision Making Process ◽  
Game Model ◽  
Demolition Waste ◽  
Green Development ◽  
Evolutionary Paths

The low efficiency of the closed-loop supply chain in construction and demolition waste (CDW) recycling has restricted the green development of China’s construction industry. Additionally, the government’s reward–penalty mechanism has a huge influence on green development. This study aimed to investigate the effect of green development performance (GDP) and the government’s reward–penalty mechanism on the decision-making process of production and recycling units, as well as to reveal the optimal strategies under different conditions. Therefore, the strategies’ evolutionary paths of production and recycling units were investigated by using evolutionary game theory. Firstly, an evolutionary game model between production units and recycling units was proposed under the government’s reward–penalty mechanism. Then, the evolutionary stability strategies in different scenarios were discussed. Finally, the effects of the relevant parameters on the evolutionary paths of the game model were analyzed using numerical simulations. The main conclusions are as follows. (1) When the range of GDP changes, the evolutionary stable strategy changes accordingly. GDP plays a positive role in promoting the high-quality development of the CDW recycling supply chain, but an increase in GDP can easily lead to the simultaneous motivation of free-riding. (2) The government’s reward–penalty mechanism effectively regulates the decision-making process of production and recycling units. An increase in the subsidy rate and supervision probability helps to reduce free-riding behavior. Moreover, the incentive effect of the subsidy probability on recycling units is more obvious, while the effect of the supervision probability on improving the motivation of active participation for production units is more remarkable. This paper not only provides a decision-making basis to ensure production and recycling units to make optimal strategy choices under different conditions but also provides a reference for the government to formulate a reasonable reward–penalty mechanism that is conducive to a macro-control market.

scholarly journals A Study of Taxi Service Mode Choice Based on Evolutionary Game Theory

2019 ◽  
Vol 2019 ◽  
pp. 1-17
Author(s):  
Zhu Bai ◽  
Mingxia Huang ◽  
Shuai Bian ◽  
Huandong Wu
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Mode Choice ◽  
Evolutionary Game ◽  
Payoff Matrix ◽  
Game Model ◽  
Stable States ◽  
Taxi Service ◽  
Service Mode ◽  
The Impact

The emergence of online car-hailing service provides an innovative approach to vehicle booking but has negatively influenced the taxi industry in China. This paper modeled taxi service mode choice based on evolutionary game theory (EGT). The modes included the dispatching and online car-hailing modes. We constructed an EGT framework, including determining the strategies and the payoff matrix. We introduced different behaviors, including taxi company management, driver operation, and passenger choice. This allowed us to model the impact of these behaviors on the evolving process of service mode choice. The results show that adjustments in taxi company, driver, and passenger behaviors impact the evolutionary path and convergence speed of our evolutionary game model. However, it also reveals that, regardless of adjustments, the stable states in the game model remain unchanged. The conclusion provides a basis for studying taxi system operation and management.

Trust strategy simulation of corporation–NPO cross alliance using evolutionary game theory

Kybernetes ◽  
2017 ◽  
Vol 46 (3) ◽  
pp. 450-465 ◽  
Author(s):  
Yidan Chen ◽  
Lanying Sun
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Nonprofit Organizations ◽  
Bounded Rationality ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Stable State ◽  
Evolutionary Strategies ◽  
Content Type ◽  
Trust Relationships

Purpose The purpose of this paper is to investigate the dynamics and evolution of trust in organizational cross alliances. Design/methodology/approach In alliances between corporations and nonprofit organizations, trust in decision-making is a dynamic process. Using the replicated dynamics model of evolutionary game theory, this paper provides a trust decision model and analyzes four scenarios under different parameters. A numerical simulation is developed to present an intuitive interpretation of the dynamic development of trust decisions and the effects of incentive and punishment mechanisms. Findings Under different parameters, bounded rationality and utilities result in different but stable evolutionary strategies; the initial probability of adopting a trust strategy leads directly to whether participants adopt the strategy when the system reaches stability after continued games; and incentive and punishment mechanisms can significantly reduce the initial probability of adopting a trust strategy where the system evolves to meet stable state needs. Practical implications The establishment of trust relationships is an important influence on the stable and coordinated development of an alliance. The proposed model can help the alliance build closer trust relationships and provide a theoretical basis for the design of the trust mechanism. Originality/value Incentive and punishment bound by some degree of trust are introduced to address the problems of trust decisions and their dynamics; the model created reflects the bounded rationality and utility of each game stage. Useful evolutionary stable strategies using different variables are proposed to address the decision-making problems of trust in cross alliances.

Efficient supervision strategy for illegal dumping of construction and demolition waste: A networked game theory decision-making model

2021 ◽  
pp. 0734242X2110320
Author(s):  
Chenyu Liu ◽  
Chunxiang Hua ◽  
Jianguo Chen
Keyword(s):  
Decision Making ◽  
Forest Fires ◽  
Evolutionary Game ◽  
Small World ◽  
Economic Benefits ◽  
Construction And Demolition Waste ◽  
Demolition Waste ◽  
Illegal Dumping ◽  
Government Supervision ◽  
The Government

While the construction industry has brought substantial economic benefits to society, it has also generated substantial construction and demolition waste (CDW). Illegal dumping, which refers to dumping CDW in an unauthorized non-filling location, has become widespread in many countries and regions. Illegally dumping CDW destroys the environment, causing groundwater pollution and forest fires and causing significant economic impacts. However, there is a lack of research on the decision-making behaviours and logical rules of the main participants, construction contractors and the government in the illegal CDW dumping process. This paper constructs an evolutionary game model on a small-world network considering government supervision to portray the decision-making behaviours of illegal dumping participants and conducts a numerical simulation based on empirical equations to propose an effective supervision strategy for the government to manage illegal CDW dumping efficiently. It is found that the illegal dumping behaviours of contractors are mainly affected by the intensity of government supervision, the cost of fines and the income of illegal dumping; while for government, a supervision strategy is found to be necessary, and a supervision intensity of approximately 0.7 is the optimal supervision probability given supervision efficiency. Notably, under a low-level supervision probability, increasing the penalty alone does not curb illegal dumping, and a certain degree of supervision must be maintained. The results show that in addition to setting fines for illegal dumping, the government must enforce a certain level of supervision and purify the market environment to steadily reduce illegal dumping.

Behavior Analysis of Together-Conspired Bidding Based on the Evolutionary Game

2012 ◽  
Vol 209-211 ◽  
pp. 1513-1516
Author(s):  
Qian Li
Keyword(s):  
Game Theory ◽  
Behavior Analysis ◽  
Evolutionary Game Theory ◽  
Theoretical Basis ◽  
Evolutionary Game ◽  
Research Work ◽  
Game Model ◽  
Stable Strategy ◽  
Periodic Fluctuation ◽  
Construction Market

Based on the “replication dynamics” ideas, the paper establishes asymmetric evolutionary game model of together-conspired bidding using evolutionary game theory, and obtains its evolutionary stable strategy under the present governmental supervision that surround-bidder and accompanying-bidder’s proportion is periodic fluctuation of the center stability, explains the reason why together-conspired bidding is difficult to be prevented effectively. In order to find the decisive factor of the evolutionary drift, further investigation shows that the evolutionary drift is converged to the different evolutionary stable properties when evolution conditions change, such as the supervision target, supervision strength. Through the analysis to the punishment extent on surround-bidder and accompanying-bidder, the conclusion is arrived that the strength of punishment and execution on the surround-bidder can effectively control together-conspired bidding, which provides the theoretical basis to governmental supervision department for the management and research work on together-conspired bidding in the construction market.

scholarly journals The Decision-Making Analysis on End-of-Life Vehicle Recycling and Remanufacturing under Extended Producer Responsibility Policy

2021 ◽  
Vol 13 (20) ◽  
pp. 11215
Author(s):  
Syed Abdul Rehman Khan ◽  
Danish Iqbal Godil ◽  
George Thomas ◽  
Muhammad Tanveer ◽  
Hafiz Muhammad Zia-ul-haq ◽  
...  
Keyword(s):  
Decision Making ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Expected Profit ◽  
Third Party ◽  
Game Model ◽  
The Third ◽  
Evolutionary Stable Strategies ◽  
Dual Cycle ◽  
The Government

This research develops a dual-cycle ELV recycling and remanufacturing system to better understand and improve the efficiency of the ELV recycling and remanufacturing businesses. For the flawless operation of this system, the researchers employed evolutionary game theory to establish a game model between original vehicle manufacturers (OVMs) and third-party recyclers with the government involved. This research presents evolutionary stable strategies (ESS) that could promote an ELV recycling and remanufacturing system. Results show that OVMs’ expected profit difference between choosing and not choosing authorization is crucial in their ESS. The licensing fee plays a part of OVMs’ expected profit difference. Based on the results, optimal ESS could be achieved when the OVMs’ expected profit difference between choosing authorization and not choosing authorization and the third-party recyclers’ profit when paying the licensing fee are both positive. Then, the two groups’ involvement in dual-cycle ELV recycling and the remanufacturing system can be ensured. This research implicates the government to devise appropriate reward and punishment strategy to encourage OVMs and third-party recyclers to collaborate for efficient recycling and remanufacturing systems. Particularly, the government is suggested to impose strict restrictions on OVMs to carry ELV recycling and provide support to promote recycling quantity standards. Hence, the ELV recycling and remanufacturing system would be strengthened, thus improving waste management which is crucial for both environmental and resource efficiency.

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