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Hu, J.; Wang, T. Strategies of Participants in the Carbon Trading Market. Encyclopedia. Available online: https://encyclopedia.pub/entry/47394 (accessed on 14 June 2024).
Hu J, Wang T. Strategies of Participants in the Carbon Trading Market. Encyclopedia. Available at: https://encyclopedia.pub/entry/47394. Accessed June 14, 2024.
Hu, Jieli, Tieli Wang. "Strategies of Participants in the Carbon Trading Market" Encyclopedia, https://encyclopedia.pub/entry/47394 (accessed June 14, 2024).
Hu, J., & Wang, T. (2023, July 28). Strategies of Participants in the Carbon Trading Market. In Encyclopedia. https://encyclopedia.pub/entry/47394
Hu, Jieli and Tieli Wang. "Strategies of Participants in the Carbon Trading Market." Encyclopedia. Web. 28 July, 2023.
Strategies of Participants in the Carbon Trading Market
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To effectively understand the collaborative and evolutionary mechanisms of three stakeholders in carbon trading namely, government, emission reduction enterprises, and emission control enterprises, it is important to identify the factors that affect decision-making behaviors amongst game players, ultimately contributing to the goal of “double carbon”. Researchers constructed a tripartite game model, analyzing the selection mechanism for game strategies related to carbon trading participants through replicated dynamic equations. Researchers also discussed the main factors that influence the evolutionary and stable outcomes of carbon trading through scenario simulations. Additionally, researchers introduced prospect theory to examine the impact of risk sensitivity and loss avoidance levels amongst decision-makers on the optimal outcome of the system. The findings reveal that in the initial game model, the three decision-makers show a cyclical behavior pattern, but the system stabilizes in the optimal equilibrium state (1,1,1) when certain conditions are satisfied. Furthermore, the initial willingness of decision-makers impacts the ability of the game system to reach a stable point. Moreover, larger values for the risk sensitivity coefficient and loss avoidance coefficient can promote the evolution of the game system toward an optimal, stable point.

carbon trading evolutionary game prospect theory scenario simulation

1. Introduction

Climate change, caused by the emissions of carbon dioxide, presents a major challenge to humanity [1]. Nations around the world were compelled to collaborate and formulate novel strategies to mitigate the adverse effects of CO2 emissions. From the 1992 United Nations Framework Convention on Climate Change to the signing of the Kyoto Protocol in 1997, culminating in the Paris Climate Change Conference in 2015, the participation of numerous countries was apparent in the pursuit of climate governance as well as efforts to combat and mitigate climate change [2]. In recent years, China’s CO2 emissions continued to increase, especially since 2000, carbon emissions continued to increase rapidly, and China became the world’s largest country in terms of carbon emissions, and the issue of carbon emission reduction in China became the focus of the international community. In the face of increasingly serious environmental problems, China put forward the goal of “peaking carbon emissions by 2030 and achieving carbon neutrality by 2060” [3], and brought this goal into the overall layout of ecological civilization construction to achieve the goal of low-carbon transformation and contribute to global climate governance.
The carbon trading mechanism is an essential tool that can facilitate the promotion of carbon emission reduction and support sustainable development [4]. With the establishment of the national carbon market in 2017, followed by the creation and continual upgrade of an online trading system in 2021, China developed a well-functioning carbon market model. Results from the Blue Book on Low Carbon Development indicate that as of 2022, approximately 230 million tons of carbon emission allowances were traded within the national carbon market at a total value of 8.602 billion yuan [5], making it the largest carbon spot market in the world. As the main participants in the carbon trading market, the participation behavior of enterprises determines the implementation effect and emission reduction effect of carbon trading policy. Therefore, it is important to study how enterprises make behavioral decisions under the carbon trading mechanism, but their carbon trading behavior is influenced by multiple factors, such as participating parties and the external environment.

2. Carbon Trading Mechanism

The carbon trading mechanism originated from the SO2 emission control program in the United States in 1968. Later, Europe and the United States utilized this program to regulate greenhouse gas emissions, which was since implemented in numerous countries. Presently, with the implementation of the national carbon market and its promotion of achieving “double carbon” targets, carbon trading emerged as one of the primary measures for the Chinese government. This trend not only directly impacts the efficiency of emission reduction and regulation in China, but also indirectly impacts enterprises’ business risks and strategic decisions, making it a subject of interest among policymakers operating within the sphere of carbon trading.
Academic research on carbon trading mechanisms primarily focuses on two facets: the design of carbon trading mechanisms and the emission reduction effect of the carbon market. Concerning the former, for example, Qi and Han assessed non-price factors by taking environmental externalities as an entry point to clarify the driving factors and mechanism of the proportion of intertemporal transactions [6]. Zhang et al. explored the optimal product pricing and carbon emission reduction benefit distribution of covered enterprises in cooperative supply chains based on carbon allowance allocation rules in carbon trading pilot regions [7]. Xu et al. examined robust emission reduction operation strategies for enterprises under historical and baseline carbon allowance allocation methods [8]. Chen et al. investigated the impact of different rent-seeking environments on the operational efficiency of carbon markets and demonstrated that price-based sale or auction methods of allocating carbon allowances clarify price signals [9]. The second facet focuses on investigating the formation mechanism of carbon trading prices and related factors. For instance, Lin et al. employed a regression model to study the possible nonlinear relationship between the carbon price and its influencing factors [10]. Xie and Dou simulated the process of carbon quota trading in China’s immature carbon market [11]. Lv et al. conducted a sensitivity analysis of relevant parameters affecting the transaction price of carbon emission rights, using data collected from pilot areas to demonstrate that the carbon price was significantly influenced by economic development level and energy prices [12].
Carbon trading is a governing environmental policy tool that directly influences emission reduction effectiveness and indirectly affects enterprise operational decisions and costs [13]. On one hand, scholars hold positive attitudes towards carbon trading policies, believing that firms with lower abatement costs will take the lead in reducing emissions and sell excess carbon emission rights to those with higher abatement costs [13]. Shi et al. verified the significant long-term effect of implementing carbon trading market policies on reducing carbon emissions through a difference-in-difference model [14]. Cao et al. demonstrated the effectiveness of carbon trading in reducing carbon emissions in the power sector by significantly reducing the coal consumption of regulated coal-fired power plants in pilot areas [15]. Pan and Wang confirmed carbon trading’s significant CO2 reduction capabilities by employing the double difference method [16]. Hu et al. found that carbon dioxide emissions in pilot areas were reduced by 15.5% compared to non-pilot areas [17]. Their finding indicated that carbon trading achieved substantial energy savings and emission reductions. On the other hand, the current performance of the Chinese carbon market revealed low carbon prices, limited activity, and low liquidity, which raises concerns regarding the practical effectiveness of carbon trading. For instance, Wen et al. concluded that the impact of carbon trading on industrial carbon emissions remained negligible due to ineffective environmental regulations by local governments and inadequate allocation of carbon quotas [18]. Lyu et al. argued that China’s carbon market lacked activity and exhibited insufficient stability with frequent fluctuations [19]. Zhang et al. developed an evaluation index system to assess the maturity of carbon markets, which demonstrated that China’s carbon market was still far from maturity and feasibility [20]. Lin and Huang also contended that non-market mechanisms were more effective in achieving carbon emission reductions [21]. Furthermore, if the market remains immature and a suitable pricing mechanism is yet to be established, then participants lack the motivation to implement carbon emission reductions. Lower carbon prices would minimize their costs, and they might not benefit significantly from reducing emissions. Therefore, carbon trading cannot sufficiently alter their emission behavior [22].

3. Carbon Trading Behavior

Recently, many scholars conducted a series of studies on the carbon trading behavioral game. For example, Perera applied the Stackelberg game theory to investigate how the government could determine continuous incentives for power plants in a competitive electricity market [23]. Feichtinger et al. analyzed the dynamic game between the government and enterprises in the case of environmental taxes [24]. Lu and Fang compared carbon trading with two different carbon allocation methods [25]. Zhu et al. proposed a decision-driven model to analyze construction market interest players [26]. Huang and Ling constructed a game model between the government and enterprises under the carbon trading scenario [27]. Additionally, Jiao et al. considered the evolutionary game of localized governments and enterprise group behavior with carbon constraints under carbon emission reduction reward and penalty mechanisms [28].
Enterprises play a crucial role in the carbon trading market and are significant drivers of energy conservation and emission reduction. Scholars worldwide increasingly focused on the innovative implications of firms’ participation in carbon trading. For instance, Calel and Dechezlepretre revealed that regulated enterprises could witness a 10% increase in low-carbon innovation due to carbon trading [29]. Zhu believed that the government can promote carbon emission reduction by increasing the activity of enterprises participating in the carbon trading market [30]. In contrast, China’s carbon trading market emerged comparatively late as compared to its foreign counterparts, and current research on corporate conduct in the carbon trading domain remains at an incipient stage. Liu and Zhang provided empirical evidence that company participation in carbon trading could stimulate R&D innovation alongside inducing higher levels of green R&D investments [31]. Yu and Liu also corroborated these outcomes through their empirical analysis [32].
The carbon trading behavior of enterprises is a significant indicator for assessing the effectiveness of the carbon trading market, primarily concerning the supply and demand dynamics within this market. Reviewing the historical progression of leading carbon trading markets worldwide, it is observed that during the early stages of carbon trading, a limited number of industries were covered, with only a few emission-controlled enterprises participating. This resulted in a low level of enterprise participation, which worsened year by year as carbon quotas were reduced. Consequently, enterprises held on to their quotas rather than trading them, perpetuating a shortage of carbon quotas in the market. This imbalance between supply and demand caused the carbon trading market to become sluggish. Many businesses held sufficient quotas while there were few potential buyers on the market, leaving little incentive for enterprises to reduce their carbon emissions. However, a healthy and regulated carbon trading market can improve the economic performance of enterprises, encourage low-carbon investment behavior, and motivate energy-saving and emission reduction practices.

4. Evolutionary Game Theory and Its Applications

Evolutionary game theory was first introduced by Maynard Smith, which since became a well-established mathematical tool for resolving multi-agent decision problems where there is incomplete information and limited rationality [33]. The evolutionary game theory extends traditional game theory and offers compelling advantages. In the realm of real economic activities, due to internal and external environmental factors, it is challenging for both governments and enterprises to act rationally with full confidence. Thus, a process of observation, imitation, and mutual learning often takes place in decision-making processes [34]. An evolutionary game enables participating agents’ strategies to eventually converge to an evolutionarily stable strategy through a dynamic process of behavioral adjustment toward equilibrium [35].
Evolutionary game theory is increasingly applied to resolve economic management problems related to corporate behavior decisions and regulation. This area of research attracted significant attention from scholars, especially regarding the applications of corporate and government regulations [36]. Liu et al. constructed an evolutionary game model and found that manufacturers tend to adopt low-carbon technologies, and synergistic effects resulting from a combination of subsidies and taxes were better than the impact of implementing a single policy [37]. Zhao and Zhang developed an evolutionary game model between the government and power producers based on carbon trading, which indicated that both lowering unit subsidies and raising unit fines promote power producers’ participation in carbon trading [38]. Chen and Wang employed the evolutionary game theory to analyze the strategic choices made by enterprises and households concerning photovoltaic subsidy withdrawal and found that photovoltaic projects were unlikely to succeed without subsidies [39]. Similarly, Zhang et al. used evolutionary game theory to provide evidence that the carbon tax and carbon subsidy were complementary based on the government–firm–consumer synergy perspective [40]. Fan et al. considered environmental taxes and local government preferences and confirmed that penalties function effectively in enhancing corporate pollution control and emission reductions by establishing a tripartite evolutionary game [41].
In fact, carbon trading participants are confronted with numerous uncertainties, such as uncertainty in the external environment and subjective limited rationality. Though evolutionary games based on this assumption possess theoretical advantages over traditional games, they lack a construct for cognitive levels of subjectivity amongst players [42]. However, a combination of prospect theory and evolutionary game theory can compensate for this limitation. Shen et al. studied local government and polluters within a watershed area while integrating prospect theory into their evolutionary game analysis [43]. Sun et al. combined prospect theory with evolutionary game studies to investigate the innovative strategies of governments and businesses under different quality deterioration level risks [44]. Uchida et al. incorporated prospect theory into evolutionary game analysis and proposed peer punishment as a mechanism to resolve social dilemmas [45]. Yang and Chen also combined prospect theory and evolutionary game studies, delineating underlying mechanisms and behavioral patterns of firms regarding breakthrough technological innovation [46]. Liu et al. adopted prospect theory in an evolutionary game approach to explore low-carbon production behavior among companies [47]. In sum, research combining prospect theory with evolutionary game theory offers insight through the examination of uncertain situations where objective and subjective factors play sizeable roles in shaping actors’ behavior.
The previously mentioned studies were refined, but still exhibit some limitations. Firstly, the emphasis of most scholars is on the macro-level aspects, such as the construction of carbon trading markets and their efficacy, but they seldom consider the micro-level factors that influence enterprise carbon trading strategies. Secondly, domestic and international researchers chiefly combined prospect theory and evolutionary games in their investigations into collaborative behavior, regulatory behavior, and social governance, yet few studies integrated the pair specifically for carbon trading behavior. Thirdly, the current literature centers on analyzing the extent of effectiveness of China’s carbon trading policy pilots in reducing carbon emissions; however, there is a dearth of comprehensive examinations into the inner workings of the Chinese carbon trading market’s operational mechanisms, and sparse research focuses on carbon trading market supply and demand. This situation left room for debate on how to construct an efficient carbon trading market encompassing the entire sector’s supply perspective.

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