Ports are the gateway of international trade and play a vital role in global economic and social development. However, the carbon emission pollution generated by ports should not be underestimated ^[1]. According to the statistics of China’s Ministry of Transport, China’s port cargo throughput in 港口是国际贸易的门户，在全球经济和社会发展中发挥着至关重要的作用。然而，港口产生的碳排放污染不应被低估[1]。据中国交通运输部统计，2022 is about 年我国港口货物吞吐量约为15.685 billion tons. However, the carbon emissions of fossil fuels consumed by port enterprises each year are nearly 100 million tons, accounting for about 3% of the global greenhouse gas emissions. Therefore, port enterprises are facing increasing pressure of decarbonization, and port emission reduction is imminent ^[2][3]. To this end, the Chinese government has provided subsidies to encourage port enterprises to invest in green energy-saving and emission reduction technologies, such as replacing oil with shore power, liquefied natural gas (亿吨。然而，港口企业每年消耗的化石燃料碳排放量近100亿吨，约占全球温室气体排放量的3%。因此，港口企业面临越来越大的脱碳压力，港口减排迫在眉睫[2，3]。为此，中国政府提供补贴，鼓励港口企业投资绿色节能减排技术，如岸电替代石油、液化天然气（LNG) terminals, and clean energy trucks, in order to speed up the construction of green ports and alleviate port carbon emission pollution. Some powerful evidence is provided as follows: from ）接收站、清洁能源卡车等，以加快绿色港口建设，缓解港口碳排放污染。一些有力的证据如下：2016 to 2018, China’s Ministry of Transport awarded subsidies for the construction of port shore power facilities and the renovation of ship power receiving facilities; In September 2022, Guangzhou Port Authority issued the measures for the implementation of subsidy funds for ship emission control in Guangzhou port. In addition, governments of various countries have also begun to implement corresponding measures in the shipping industry, such as carbon emission trading policy. The evidence includes that the shipping industry will be included in the European Union Emission Trading System (EUETS) from 2024, and port enterprises such as Shanghai international port group and Shanghai Shengdong international container terminal have been included in the list of carbon emission quota management units of Shanghai in 2022. Therefore, under the government’s subsidy incentives and carbon trading policy, how to control and reduce the carbon emission of port enterprises, accelerate the investment and construction of green ports, and help the sustainable development of the shipping industry is the first research motivation.年至2018年，中国交通运输部对港口岸电设施建设和船舶受电设施改造给予补贴;2022年2024月，广州港务局印发《广州港船舶排放控制补贴资金实施办法》。此外，各国政府也开始在航运业实施相应的措施，如碳排放交易政策等。证据包括，航运业将从2022年起纳入欧盟碳排放交易体系（EUETS），上海国际港务集团、上海盛东国际集装箱码头等港口企业已列入<>年上海市碳排放配额管理单位名单。因此，在政府的补贴激励和碳交易政策下，如何控制和减少港口企业的碳排放，加快绿色港口的投资建设，助力航运业的可持续发展，是本文的第一研究动机。

As a world-changing and disruptive technology, blockchain technology is gradually being applied to the shipping industry, and port enterprises are benefiting from it ^[4]. There is much evidence here. For example, 作为一种改变世界和颠覆性的技术，区块链技术正逐渐应用于航运业，港口企业正在从中受益[4]。这里有很多证据。例如，国际商业机器公司（International Business Machines Corporation (IBM) and Maersk jointly built a shipping blockchain solution (M）和马士基共同构建了航运区块链解决方案（TradeLens) to realize the digital operation of ports and shipping. Shanghai Port Group and China Ocean Shipping (Group) Company (COSCO) realize transparent and paperless operations with the support of blockchain technology. In 2021, Guangzhou Port successfully completed the docking with the electronic cargo release platform of the port and shipping blockchain, and all the main terminals were connected to the chain. Since 2022, the blockchain electronic cargo release platform of Shanghai Port has released a total of 335,000 bills of lading, totaling about 1.03 million TEUs, which effectively realized the cost reduction and efficiency increase in the logistics of imported cargo, and during the “Double 11” period, it even made a new history and realized the rapid release of imported e-commerce goods. The main reason why blockchain technology is so popular is that compared with traditional technology, blockchain technology has unique advantages. Specifically, it is a decentralized, point-to-point distributed database system, which is traceable, tamper-proof, open, and transparent. The traditional common technologies such as bar codes and radio frequency identification (RFID) tags may be copied and forged, and cannot be compared wit），以实现港口和航运的数字化运营。上海港集团和中国远洋运输（集团）公司（COSCO）在区块链技术的支持下实现透明无纸化运营。2021年，广州港顺利完成与港口电子放行平台和航运区块链的对接，所有主要码头均对接链条。2022年以来，上海港区块链电子货物放行平台累计发放提单335.000万张，合计约1万标准箱，有效实现了进口货物物流降本增效，“双03”期间更创造了新的历史，实现了进口电商商品的快速放行。区块链技术如此流行的主要原因是，与传统技术相比，区块链技术具有独特的优势。具体来说，它是一个去中心化的、点对点的分布式数据库系统，具有可追溯、防篡改、公开、透明等特点。条形码和射频识别（RFID）标签等传统通用技术可能会被复制和伪造，在信任其信息处理的真实性方面无法与区块链技术相提并论[11]。因此，本文的第二个研究动机是介绍智能合约、绿色认证、市场信息披露等区块链技术在港口企业减排中的应用价值，以提高政府的补贴激励和碳交易政策，以刺激和规范港口减排。

2. 航运业的区块链技术

近年来，区块链技术在供应链管理中越来越受欢迎，引起了许多学者的关注（例如，Ch blockchain technology in trusting the authenticity of its information processing ^[5]i [10]， Sun et al. Therefore,[11]， tShe second research motivation is to introduce the application valuesn et al. [12]， of blockchaLin technology such as smart contracts, green certification, and market information disclosure (which will be explained in detail later) in port enterprises’ emission reduction to improve the government’s subsidy incentives and carbon trading policy to stimulate and regulate port emission reductionu et al.

In addition,[13]， although the existing literature has considered the investment and application of blockchain technology in the shipping industry (e.g.,Guo et al. ^[4][6][7]),[14]， there are few stXudies on the government’s incentive contract design for port enterprises to reduce emissions by introducing the different application values of blockchain technology. Espec et al. [15]）。同时，作为跨境贸易的重要载体，区块链技术应用于航运业的研究也逐渐成为热门话题[6]。相关研究主要包括两个方面。首先，一些学者重点分析了区块链技术在航运业的应用现状和未来发展前景。例如，Yially from the perspective of the principal–agent, bg等人[16]指出，区块链技术通过推动航运业的数字化，可以帮助提高相关企业的运营效率，降低与贸易活动相关的风险和不必要的时间成本。为了分析区块链等新技术对造船业性能和可持续性的潜在影响，Rased on the change in the status of port emission reductions and considering the carbon trading policy, there are even fewer studies on the dynamic incentive contract model of the government to port enterprises to reduce emissionsrez等人[17]从工业4. Therefore, based on the above realistic background of emission reduction of port enterprises in the shipping industry, three scenarios will be considered, namely, the scenario of no blockchain, the scenario where blockchain adoption without considering carbon trading policy, and the scenario where carbon trading policy is also considered under blockchain technology0的角度开发了造船供应链的性能模型，探索了精益，敏捷，弹性和绿色的供应链管理模式，并提出了两个阶段来实现造船供应链4. Although there are many studies in the literat0所需的整体可见性和连接性。为了探索区块链技术在港口物流管理中的潜在应用领域，Ahmad等人[4]进一步讨论了区块链在港口运营和物流管理中的应用和架构。此外，Pure on different optim等人[18]提出了区块链技术在海运业应用的概念框架，他们认为管理人员在采用该技术之前应充分了解区块链及其自身的具体问题和需求至关重要。随后，Bal control methods ^[8][9]. The advantage of the work is that researchers focus on the optimal control for carbon trading, and study the dynamic incentive of government for port emission reduction in the shipping industry from the perspective of the principal–agent.

However, the existing studies mainly focused on the pricing decisions and benefit distribution of port and shipping enterprises under blockchain technology and blockchain investment strategies in the shipping industry. Differing from them, researchers focuse on the dynamic incentive strategy of the government and the emission reduction investment (等人[23]将区块链去中心化的技术特征与港口和航运供应链成员的投资选择相结合，从航运市场价格和数量以及航运市场的经济效应等方面探讨了是否集中化和是否投资投资组合策略的问题。 然而，现有的研究主要集中在区块链技术下港口和航运企业的定价决策和利益分配以及航运业的区块链投资策略。有不同之处在于，本文重点研究了区块链技术下政府的动态激励策略和港口减排投资（ERI) decision of the port under blockchain technology, especially researchers analyze the value and effect of blockchain technology in the government’s dynamic incentive contract.

The study is closely related to port emission reduction and government subsidy in the shipping industry, which is one of the important research topics in the field of shipping at present. Regarding the research on port emission reduction strategies, ）决策，特别分析了区块链技术在政府动态激励契约中的价值和效果。

3. 港口减排和政府补贴

我们的研究与航运业的港口减排和政府补贴密切相关，是目前航运领域的重要研究课题之一。关于港口减排策略的研究，Acciaro et al. ^[24] argued that active energy management in ports could improve their service efficiency, promote the development of new alternative sources of income, and ultimately enhance their competitive position. 等人[24]认为，港口的积极能源管理可以提高其服务效率，促进新的替代收入来源的发展，并最终增强其竞争地位。Innes and 和Monios ^[25] analyzed ship docking data to calculate energy demand and found that installing cold ironing technology in medium-sized ports is feasible, which will consume less energy than traditional ships connected to shore power. [25]分析了船舶停靠数据以计算能源需求，发现在中型港口安装冷熨烫技术是可行的，这将比连接到岸电的传统船舶消耗更少的能源。Poulsen and 和Sampson ^[26] confirmed the existence of idle time in ports, detailed the reasons for it, and pointed out some previously overlooked factors. [26]证实了港口存在空闲时间，详细说明了其原因，并指出了一些以前被忽视的因素。Wang et al. ^[27] stud等人[27]通过系统审查和Cied the development process of port emission reduction from early “environmental factors and energy scheduling” to “low-carbon and green ports” through system review and Citespace visual analysis. Zhou et al. ^[28], based on the field theory in physics, combined with the characteristics of ship emission trajectory data, analyzed the spatio-temporal aggregation law of ship carbon emissions in the Wuhan Port.

Moreover, some scholars have taken into account the government’s regulatory and subsidy mechanisms in port emission reduction. espace视觉分析，研究了港口减排从早期的“环境因素和能源调度”到“低碳绿色港口”的发展过程。Zhou等[28]基于物理学场论，结合船舶排放轨迹数据特征，分析了武汉港船舶碳排放的时空聚集规律。 此外，一些学者还考虑了政府在港口减排方面的监管和补贴机制。赵等[29]考虑了政府、港口公司和港口公司之间的三方进化博弈模型，发现只有政府选择被动监管，港口公司实施岸边电力，环境效益才能最大化。Zhao et al. ^[29] considered a three-way evolutionary game model between the government, a port company, and another port company, and found that the environmental benefits can be maximized only if the government chooses passive regulation and the port company implements shore-side electricity. Zheng et al. ^[30] modeled two commonly used regulatory policies for port adaptation investments (minimum demand regulation and subsidies), making explicit the ambiguity in the probability of disasters and the policymaker’s attitude towards risk. 等人[30]模拟了两种常用的港口适应投资监管政策（最低需求监管和补贴），明确了灾害概率的模糊性和政策制定者对风险的态度。Meng et al. ^[31] explored the impact of government regulation on cooperative emission reduction between ports and shipping companies by establishing a differential game model. They found that when the government only provides incentives to ports, if the port subsidizes shipping companies and the decision-making power is dispersed among shipping companies, the emission reduction effect is best, but it is unfavorable for port revenue. 等人[31]通过建立差分博弈模型，探讨了政府监管对港口和航运公司合作减排的影响。他们发现，当政府只向港口提供激励时，如果港口补贴航运公司，决策权分散在航运公司手中，减排效果最好，但不利于港口收入。Meng et al. ^[32] constructed an evolutionary game model with the participation of the government, port enterprises, and shipping enterprises, and analyzed the evolutionary process of the selection of carbon reduction strategies among the three parties. 等[32]构建了政府、港口企业和航运企业参与的演化博弈模型，分析了三方碳减排策略选择的演化过程。Wang et al. ^[33] considered the interaction between governments, ports, and ships to develop a 等人[33]考虑了政府、港口和船舶之间的相互作用，开发了Stackelberg model to optimize government subsidy schemes to maximize the environmental benefits of unit currency subsidies. They found that in an optimal government subsidy structure, subsidies for ships should take precedence over subsidies for ports. 模型，以优化政府补贴计划，使单位货币补贴的环境效益最大化。他们发现，在最佳的政府补贴结构中，对船舶的补贴应优先于对港口的补贴。Song et al. ^[34] constructed a Nash game between two shipping companies on shore rights usage decisions and analyzed the effect of government intervention on the equilibrium that can be achieved between the two shipping companies. 等人[34]构建了两家航运公司之间关于岸权使用决策的纳什博弈，并分析了政府干预对两家航运公司之间可以实现的平衡的影响。Tan et al. ^[35] argued that the use of both environmental incentives and infrastructure subsidies mechanisms by the government influences port authorities to change the capacity decisions of port-specific terminals, which in turn affects the total emission reductions.

TheOur study is also related to the research of incentive contract design in operations management, which is a hot issue of academic concern and has a wider scope of research. Holmstrom and Milgrom [41] first proposed the principal–agent model and laid the foundation for the study of incentive contracts and incentive mechanisms. Subsequently, many scholars began to design contracts such as linear and commission to resolve conflicts of interest between principals and agents in different industries. For example, in the past, Zhou and Swan [42] investigated the optimality of piecewise linear incentive contracts and found evidence of the role of performance thresholds by examining Chief Executive Officer (CEO) compensation data. Yu and Kong [43] considered the ambiguity in the distribution of effort-related outputs and demonstrated that piecewise linear incentive contracts are uniquely optimal among salesperson compensation contracts. Gao and Tian [44] extended the single-period incentive contract model to the multi-period incentive contract model to constrain the behavior of the firms and motivate the firms to make greater efforts. Gao et al. [45] considered outsourcing a manufacturer to a supplier and proposed a quality incentive contract with asymmetric product manufacturability information. With the rise of the live-streaming industry, Zhang and Xu [46] discussed proportional incentive contracts based on target sales volume in the context of the live commerce supply chain and studied the optimization of contract design based on principal generation theory. They found that the optimal solution of the proportional incentive contract exists and is optimal under certain conditions. Meanwhile, Zhang et al. [47] further considered the moral hazard and adverse selection issues in contract design, studied incentive contracts in the live-streaming supply chain under the information asymmetry of streaming influence and recommendation efforts, and revealed that equilibrium contracts depend on the priori beliefs of Pinbo suppliers about streamer influence. Since changes in the market environment are often dynamic, the design of the contract between the principal and the agent may not always be static, so some scholars have carried out research on the dynamic incentive contract. For example, Barbos [48] carved out the optimal contract realized under stochastic monitoring in a stochastic dynamic setting where the type of agent cost varies over time. Hori and Osano [49] explored how the timing of compensation payments and contract termination are jointly determined in a continuous-time principal–agent model when the agent has loss aversion preferences and the principal has a discretionary termination policy. Szydlowski and Yoon [50] studied a continuous-time principal–agent model in which the subject is ambiguous and unwilling to influence the agent’s cost of effort, and this robust contract produces a pay performance that appears to be overly sensitive. Zhu et al. [51] proposed a dynamic incentive and reputation mechanism to improve energy efficiency and training performance in federated learning. Xie et al. [52] analyzed the optimal contract in continuous time under the principal–multi-agent moral hazard environment based on the behavioral relationship between agents, and gave the optimal contract for the generalized principal–agent dynamic problem based on the stochastic optimal control theory, analyzed the optimal behavioral choices of the agents and incentive mechanisms. Tan et al. [53], motivated by information asymmetry that makes it difficult for recycling companies to determine incentive strategies for collectors, formulated a dynamic moral hazard model and found that collectors are always motivated to voluntarily maintain a high-quality supply of C&D waste under the optimal mechanism. Unlike the above research, rethisearchers paper follows the relevant research on dynamic decision models (e.g., Ma et al. [54], Meng et al. [31]), considers that the port emission reduction market is uncertain, and based on the dynamic equation of port emission reductions, studies the dynamic incentive contract design of the government (principal) for port enterprise (agent) to reduce emissions in the blockchain era.