Table of Content

25 November 2025, Volume 33 Issue 11 Previous Issue   

Select

Investment Diversification, Business Similarity and Systemic Risk Chao Wang, Jianmin He, Xiaoxing Liu 2025, 33 (11):  1-13.  doi: 10.16381/j.cnki.issn1003-207x.2021.2663 Abstract ( 10 )   HTML ( 0 )   PDF (1466KB) ( 7 )   Save The relationship between diversification and similarity is explored through the systemic model of banking originated losses to measure systemic risk in the banking of China when facing stress tests. The impact of diversification on the systemic risk is then analyzed using similarity as a mediating variable to reveal the contagion process of systemic risk and clarify the formation mechanism of systemic risk. The results show that large banks are usually able to reduce their business similarity through diversification， and for some small and medium-sized banks the promotion of business similarity by diversification is more obvious. The contagion risks caused by excessive business similarity is currently a key factor affecting the stability of the banking market in China. Although business similarity promotes the contagion of systemic risk， it has a double effect for large state-owned commercial banks， which can disperse shocks from other banks through the advantage of being “too big to fail” without serious systemic risks. The above findings provide regulatory references for the business transformation and systemic risk prevention of commercial banks in China. Figures and Tables | References | Related Articles | Metrics

Select

A Novel Nonlinear Credit Risk Evaluation Model and Its Empirical Analysis Based on Minimizing the Inversion Number of Loss Given Default Sequence Yang Lu, Baofeng Shi, Guotai Chi, Yizhe Dong 2025, 33 (11):  14-28.  doi: 10.16381/j.cnki.issn1003-207x.2023.0192 Abstract ( 8 )   HTML ( 0 )   PDF (1558KB) ( 5 )   Save The purpose of credit evaluation is to reduce information asymmetry and reduce the credit risk of banks. However， the existing credit risk evaluation models are prone to result in the “Score-Risk” mismatch phenomenon of “high credit score sometimes matches high level of default risk”. To solve this mismatch， inversion numbers are introduced to measure the level of mismatch. Then， a nonlinear credit risk evaluation model is developed by minimizing the inversion number of related loss given default sequence. There are some innovations and features in this study. （1） The functional relationship among the indicators of the credit evaluation of small and medium-sized enterprises （SMEs）， the inversion number IN{V}_Y(\mathit{P}) of its corresponding default state sequence \mathit{P}， and the inversion number IN{V}_{LGD}({\mathit{P}}_{LGD}) of its corresponding loss given default sequence {\mathit{P}}_{LGD} are constructed. （2） Inspired by the concept of AUC and GINI coefficients and to measure the mismatch between credit score and credit risk， this paper establishes a kind of indicator based on the distribution of default lenders， which is used to describe the mismatch level of “Score-Risk”. （3） Particle Swarm Optimization（PSO） algorithm is used to solve the nonlinear programming model and find that the model would result in a low level of mismatch with the initial number of particles， the number of iterations， and the diversity of initial positions of particles increasing.To compare with other weighting methods， the loan data of 1231 small enterprises in China are analyzed， the empirical results show that there is indeed a “Score-Risk” mismatch in the existing credit evaluation methods and the model established in this paper can improve the “Score-Risk” mismatch well. Further， the proposed model is compared with six prediction measurements （AUC， Accuracy， etc） and seven other models （Support Vector Machine， Decision Tree， etc） in the credit data of Germany， Australia and Chinese Taiwan published by UCI. By post-hoc analysis， it is found that although there is a small difference in predictive performance among these models， the proposed model still has certain advantages over the artificial intelligence credit evaluation model. Different from existing models which focus on the accuracy of prediction， it aims to solve the problem of “Score-Risk” mismatch in this paper， which may provide a new perspective for credit evaluation. Figures and Tables | References | Related Articles | Metrics

Select

Research on Predicting Corporate Fraud of Listed Companies Based on Multi-Source Text Data and Feature-Augmented Tree Models Gang Li, Chaochao Qiu, Zhipeng Zhang, Simeng Qin, Xingnan Xue 2025, 33 (11):  29-40.  doi: 10.16381/j.cnki.issn1003-207x.2024.0438 Abstract ( 13 )   HTML ( 0 )   PDF (1235KB) ( 4 )   Save The existing financial fraud prediction of listed companies are mainly based on financial features， but the research on the combination of text information and multi-source text information for fraud prediction needs to be further explored. It is based on multi-source text data in this paper， such as the annual reports of listed companies， work reports of provincial governments， and monetary policy reports of central bank. Textual features， including text similarity， text tone， and text readability， are extracted using text mining technology. These features， along with the financial and other non-text features of listed companies， are utilized by the feature-enhanced tree model （Augboost） to predict the fraud of listed companies. Its accuracy is evaluated in prediction scenarios combining multi-source textual information along with other prediction models （such as Logistic Regression， Naive Bayes model， Random Forest， etc.）. The empirical results based on China's A-share listed companies in the manufacturing industry from 2001 to 2020 indicate that： （1） Additional incremental information on the financial fraud of listed companies is provided by multi-source textual features. （2） The incremental information provided by different types of texts varies. Compared with the annual reports of listed companies and the work reports of provincial governments， the monetary policy of central bank offers the most significant incremental information. （3） Compared with common algorithms such as logistic regression， the Augboost model is used in this paper to predict the fraudulent status of listed companies more accurately. The prediction framework integrating multi-source text information proposed in this paper constitutes an expansion of the existing research on financial fraud prediction of listed companies， which can enhance the prediction accuracy of financial fraud of listed companies and holds practical significance in corporate regulation and decision-making. Figures and Tables | References | Related Articles | Metrics

Select

Multi-area Multi-Microgrid System Expansion Planning Based on Deep Reinforcement Learning Algorithm Jian Zhou, Xiaoting Nie, Kexin Pang, Xiaoyue Wang, Yizhong Ma 2025, 33 (11):  41-53.  doi: 10.16381/j.cnki.issn1003-207x.2023.1947 Abstract ( 10 )   HTML ( 0 )   PDF (1927KB) ( 5 )   Save Microgrids have shown great potential in improving the resilience of power supply and reducing greenhouse gas （GHG） emissions. The interconnection of island microgrids into a multi-area multi-microgrids （MMGs） system will help improve the economy and power supply resilience of microgrids. Aiming at the expansion planning problem for MMGs， a long-term expansion planning framework is proposed with the goal of minimizing the total cost of the MMGs while taking power supply resilience and environmental benefits as constraints. The energy sharing between adjacent microgrids is also considered. Based on the real data， a MMGs system containing three microgrids is constructed as a case study to demonstrate the effectiveness of the proposed model. The dynamic and stochastic optimization problem is solved by deep reinforcement learning algorithm. The results show that the planning framework for MMGs can improve the resilience of the microgrid power supply and reduce GHG emissions. The proposed framework also considers the impact of the interconnection structure of MMGs and appropriately adjusts strategies based on the frequency of outages and outage losses of individual microgrid. This research has important practical significance for the expansion planning of MMGs. Figures and Tables | References | Related Articles | Metrics

Select

Research on Identifying Influencing Factors and Improvement Strategies for Production Equipment Operation Management and Control Performance Based on fsQCA Keqin Dou, Jun Li, Jinsong Liu, Qing Li, Yong Zhou, Zhongcheng Guan 2025, 33 (11):  54-64.  doi: 10.16381/j.cnki.issn1003-207x.2025.0032 Abstract ( 9 )   HTML ( 0 )   PDF (964KB) ( 1 )   Save In the context of industrial interconnectivity， the factors that directly or indirectly affect the operation management and control efficiency and effectiveness of production equipment are increasingly numerous， making it difficult to precisely define the key factors that decisively influence the performance outcomes of equipment operation management and control. The intrinsic mechanisms and interplay paths remain unclear， which constrains the optimization of operation management control efficiency and effectiveness. There is an urgent need to conduct in-depth research on the key influencing factors of production equipment operation management and control efficiency and effectiveness， to reveal the configurational effects and mechanisms of these factors， and to develop effective strategies for enhancing the performance of production equipment operation management and control， thereby supporting the maximization of operation management and control efficiency and effectiveness in an industrial interconnected environment. Against this backdrop， a thorough analysis of domestic and international standards， literature， and other relevant materials related to the production equipment operation management and control performance is conducted， and an analysis framework for evaluating performance is constructed based on “influencing factors-outcomes-action paths”. Using the data from 76 manufacturing enterprises， the fuzzy-set qualitative comparative analysis （fsQCA） method is employed to explore the key influencing factors and enhancement strategies for production equipment operation management and control performance from three dimensions： high-load output， lean management and control， and low-failure operation.The high-load output mode represents enterprises maintaining high， consistent performance of various types of production equipment through scientific production planning and task scheduling， supplemented by high-level equipment maintenance and daily upkeep， to effectively achieve production goals and attain high operation management and control performance. The lean management and control mode represents enterprises， on the basis of good production task scheduling， using production process routes to control process flows and parameters， optimize the supply balance of production materials and energy， and timely handle equipment anomalies and potential failures， ensuring stable equipment operation and consistent product quality performance， thereby achieving high production equipment operation management and control performance. The low-failure operation mode represents enterprises focusing on the health status of production equipment， implementing dynamic monitoring and real-time sensing of equipment operation status through cloud platforms， and conducting predictive maintenance and early warning based on data， thereby enhancing the effective uptime of production equipment and achieving high operation management and control performance. Taking a manufacturing workshop for an aviation engine transmission unit as an example， and combining its current production equipment operation management and control status， a predictive maintenance system solution based on the “low-failure operation mode” was developed. The operation management and control performance of the enterprise significantly improved， with the average process capability index of the workshop's production equipment increasing from 1.28 to approximately 1.60， the average repair time for equipment failures decreasing from 8 hours to 3 hours， and the average comprehensive efficiency of production equipment rising from 56.43% to 68.57%. The effectiveness and rationality of the proposed method for analyzing influencing factors of production equipment operation management and control performance and enhancement strategies were verified through practice. Figures and Tables | References | Related Articles | Metrics

Select

Production Decision-making Optimization and Emission Behavioral Analysis under Emission Permits Price Uncertainty Jinfeng Sun, Hongxi Sheng, Xiangpei Hu 2025, 33 (11):  65-80.  doi: 10.16381/j.cnki.issn1003-207x.2023.0343 Abstract ( 9 )   HTML ( 0 )   PDF (4569KB) ( 4 )   Save The key challenge for emission enterprises is how to weigh the rationality of production decision and the legality of emission behavior under the price uncertainty of emission permits. In view of the measurability and availability of historical prices of emissions trading under different trading mechanisms in reality， a data-driven approach based on kernel density estimation is proposed to construct an uncertainty set for a given confidence level to characterize the uncertainty of emissions trading prices. And a robust optimization model based on the minimum-maximum regret value criterion is used to study the production decision optimization and emission behavior of emission enterprises under two commonly used mechanisms： the government reserve offer/buyback mechanism and the enterprise transfer transaction mechanism. The results show that the optimal production decisions of emission rights sellers and conservative producers are not directly related to the trading price of emission rights under the government reserve transfer/buy-back mechanism， while the production decisions of emission rights buyers are directly related to the trading price and the profit maximization can be achieved by choosing illegal over-emissions when the robust trading price is below a certain level. Under the enterprise transfer transaction mechanism， the production decisions of enterprises are closely related to the trading price of emission rights， and when the robust trading price of emission rights is higher than a certain value， the purchasing enterprises can obtain the maximum profit by following the legal emission. The empirical analysis not only reveals the characteristics and laws of the market behavior of emissions trading under the two trading mechanisms， but also indicates what emissions trading strategies enterprises should adopt to achieve their optimal production decisions under different mechanisms， and provides a scientific basis for the government to set the amount of fines for illegal over-emissions， so that the research results are more practical guidance for the implementation of the “efficient market and effective government” system of emissions trading. Figures and Tables | References | Related Articles | Metrics

Select

Integrated Recovery for Irregular Flight with Crew Bidding Mechanism Huifen Zhong, Tianwei Zhou, Zhaotong Lian, Ben Niu 2025, 33 (11):  81-92.  doi: 10.16381/j.cnki.issn1003-207x.2023.0288 Abstract ( 8 )   HTML ( 0 )   PDF (1593KB) ( 0 )   Save Irregular flights deviate from their schedules， which causes a great of financial losses for airlines. In the process of recovery， aircraft and crew resources play a vital role and can be controlled by the airlines. However， due to the complex and stringent constraints in the aviation industry， previous studies have primarily focused on single-resource independent recovery or simple integrated cases， overlooking the importance of crew satisfaction in service quality and airline reputation. To address this gap and better reflect real-world scenarios， an integrated aircraft and crew recovery model that incorporates a crew satisfaction evaluation mechanism is proposed in this paper. In the modeling， crews are given the opportunity to bid for the earliest off-duty task in the event of temporary airport closure. To achieve the best possible recovery scheme， five recovery options are simultaneously considered： flight delay， flight cancellation， crew exchange， standby crew utilization， and cruise speed increase. Although this leads to increased problem dimension and solution difficulty， it ensures a comprehensive approach to recovery. Given the high constraints and coupled solution difficulties of the model， an ad-hoc intelligent algorithm based on Particle Swarm Optimization （PSO） is designed. A novel tripartite competition strategy and model information-guided method are innovatively incorporated to enhance the performance of the algorithm. Specifically， tripartite competition strategy involves randomly selecting a particle from three subpopulations to generate “win”， “lo{s}_{\mathrm{1}}” and “lo{s}_{\mathrm{2}}” based on their fitness and feasibility values. These particles are then updated using different evolutionary strategies. The information-guided method facilitates neighbor searching for feasible and optimal solutions， thereby improving solution performance and avoiding algorithmic stagnation. Additionally， a set of infeasible solution repair mechanisms， such as boundary and extension handlings， are designed to increase the probability of finding feasible solutions.Finally， to validate the effectiveness of our proposed solving algorithm， it is compared with two classical algorithms （PSO and ABC）， two novel algorithms （MSEFA and MSRCS）， and three algorithms used for aircraft and crew recovery problems （GA_arp， SA_arp， and IFWA_arp） on three different-scale instances from Shenzhen Airlines and the 2017 Competition. The results， evaluated from both computational and statistical perspectives， demonstrate that our proposed algorithm outperforms the competitors in terms of precision in solving the recovery problem， irrespective of the problem scale. Furthermore， it is recommended to increase the iteration number to more than 3000 for large-scale instances， which can yield approximately 10% cost savings for recovery operations. To sum， an effective intelligent tool for addressing complex aircraft and crew integrated recovery problems is offered in this study， reducing labor-intensive and experience-dependent challenges associated with manual recovery processes. Figures and Tables | References | Related Articles | Metrics

Select

Optimization of Outbound Relocating for Four-way Shuttle System Based on Improved A* Algorithm Yunfeng Ma, Cong Sheng, Xijie Yang, Liang Ren, Zhigang Zhou 2025, 33 (11):  93-102.  doi: 10.16381/j.cnki.issn1003-207x.2023.0911 Abstract ( 5 )   HTML ( 0 )   PDF (1964KB) ( 4 )   Save A new type of storage and retrieval system based on shuttles， known as the four-way shuttle storage system， is introduced， which is assured to meet the high demand for inbound and outbound capabilities for massive orders in e-commerce environments. The performance of the four-way shuttle system can be enhanced by the establishment of dual-end inbound and outbound ports， and outbound efficiency can be improved through sequential picking. The feature of the system having multiple depth could cause relocation during the retrieval process. It starts from practical application scenarios in this paper. The existing research mainly focuses on the congestion issues related to single-end entry and exit in traditional automated warehouses， as well as the relocation problem of container yards. Therefore， in a dual-end output four-way shuttle system， the selection of suitable relocation and landing operations to minimize the total number of relocations is deemed critical.The shortest path approach is adopted in this paper to address the ordered dual-end outbound relocating problem with limited conditions in the four-way shuttle storage system， aiming to minimize the number of relocations. The state of each block after each relocation operation is treated as a node， and heuristic upper bounds and evaluation functions are designed to enhance the A* algorithm for finding the optimal solution to the shortest path problem.Numerical experiments were performed on a large scale， with various system layouts generated in different test cases. The results indicate that the improved A* algorithm， when compared to the heuristic algorithm HEUR based on the optimal lane rules， reduced the average number of relocations by 16.62%. The number of relocations can be further reduced by rectangular layouts under the same scale， and the number of relocations can be decreased by an average of 70.43% with a dual-end outbound layout compared to a single-end outbound layout. The algorithm's optimization effect improves as the system size increases， and the negative correlation between storage density and the number of relocations gradually weakens. Figures and Tables | References | Related Articles | Metrics

Select

Robust Optimization of Procurement and Routing Strategy of Multi-period Multimodal Transport in Uncertain Environment Fang Guo, Runliu Niu, Zhihong Huang 2025, 33 (11):  103-113.  doi: 10.16381/j.cnki.issn1003-207x.2023.1059 Abstract ( 10 )   HTML ( 0 )   PDF (1064KB) ( 1 )   Save Facing the operation practice of cross-border e-commerce enterprises under the background of the “Belt and Road”，a collaborative optimization strategy for multi-time procurement and multimodal transportation considering cost factors such as procurement， transportation， transshipment， and storage costs incurred for early arrival is proposed. A mixed-integer planning model is established to minimize the overall operating costs of cross-border e-commerce enterprises by arranging procurement， transportation， and storage strategies. Considering the fluctuation of procurement costs with the market environment， this study constructs robust optimization models under the uncertain environment of procurement costs and also develops linear robust equivalence models through mathematical transformation to improve the efficiency of problem solving.To solve the above problem， a hybrid heuristic algorithm called KIGALNS is proposed， based on the K-shortest path algorithm， Iterative Greedy algorithm （IG）， and Adaptive Large Neighborhood Search （ALNS）. Then， through the different size case experiments verify the validity of the proposed model， the effectiveness of the algorithm and the collaborative optimization strategy. Finally， through a series of numerical experiments show that the purchasing strategy helps to save operating cost in advance， the robust model can well deal with multimodal transport path optimization problem such as purchasing cost uncertainty， in promoting the transport link authors efficiency at the same time， considering purchasing plan and the influence of uncertain factors， provide theoretical guidance for enterprise procurement - transport joint decision and scientific solutions. Figures and Tables | References | Related Articles | Metrics

Select

Analysis of Cooperation and Competition Strategies Between Shipping Logistics Blockchain Platform and Shipping Companies Considering Shippers’ Information Preference Yanting Chen, Dengfeng Li 2025, 33 (11):  114-124.  doi: 10.16381/j.cnki.issn1003-207x.2022.2337 Abstract ( 6 )   HTML ( 0 )   PDF (1546KB) ( 1 )   Save Blockchain technology in the application of the shipping logistics industry is the industry that has been focused on the topic， so it is necessary to discuss how the application of blockchain technology affects shipping logistics enterprises’ cooperation and competition. Therefore， a shipping logistics supply chain composed of a freight forwarding company building a shipping logistics blockchain platform and two competing shipping companies is taken as the research object， then the impact of different equilibrium decisions on operational decisions is compared and analyzed by establishing game models of competition and cooperation under different circumstances. The results are as follows：（1） When the intensity of competition among the shipping companies is high and the information disclosure level of shipping logistics is low， the freight forwarders can profit from maintaining the competitive situation of the traditional logistics chain， and shipping companies have the incentive to form alliances. （2） When the intensity of competition between shipping companies is low and the information disclosure level of shipping logistics is high， the construction of shipping logistics blockchain platform by freight forwarding companies and the shipping companies “uplink” in the form of alliance to form a competitive situation can obtain greater benefits. （3） It is highlighted that using the decentralized characteristics of shipping logistics blockchain platform to form a cooperative alliance with shipping companies as a whole can make the revenue of cooperative game reach Pareto optimum. The research conclusions can provide a theoretical basis for the cooperation and competition strategies formed by the application of blockchain technology in logistics enterprises. Figures and Tables | References | Related Articles | Metrics

Select

Service-oriented Manufacturing Coordination Super-GERT Network Based on Value Flow Hongda Liu, Haifeng Zhao, Ying Zhang 2025, 33 (11):  125-138.  doi: 10.16381/j.cnki.issn1003-207x.2023.0149 Abstract ( 12 )   HTML ( 0 )   PDF (1297KB) ( 3 )   Save Service oriented manufacturing is promoting the accelerated integration of manufacturing and service industries. With the improvement of factor agglomeration configuration， service-oriented manufacturing creates new value added and promotes the improvement of production quality. However， in practice， there are many difficulties in generating value-added capabilities for service-oriented manufacturing. On the one hand， service-oriented manufacturing faces coordination difficulties in manufacturing， service， and innovation activities； On the other hand， there are too many elements within service-oriented manufacturing that need to be sorted out， and the insufficient flow of elements may lead to the suppression of value appreciation. In this context， a conceptual system of service-oriented manufacturing is constructed and the network structure of service-oriented manufacturing is examined. Form a network of manufacturing， service， and innovation activities based on production and operation relationships. Secondly， based on the analysis of the relationship between service-oriented manufacturing and value added， a network hierarchy guided by manufacturing value flow， service value flow， and innovation value flow is constructed. Combining network principles and preference utility， a service-oriented manufacturing super network system is constructed. Then， based on the balanced expression and value flow solution of the hypernetwork， combined with the production operation node characteristics and GERT network relationships of service-oriented manufacturing， a service-oriented manufacturing hyperGERT network system is constructed to clarify the value-added mechanism of service-oriented manufacturing under multi-dimensional value flow. Finally， the scale of value added at each node is calculated within service-oriented manufacturing E\left[y(m)\right]=\frac{\partial }{\partial S_m}\left[\frac{W_{ij}(S_{\mathrm{1}},S_{\mathrm{2}},\dots ,S_m,\dots ,S_n)}{W_{ij}(\mathrm{0,0},\dots ,\mathrm{0},\dots ,\mathrm{0})}\right]\left|{}_{S_{\mathrm{1}}=S_{\mathrm{2}}=\dots =S_m=\dots =S_n=\mathrm{0}}\right.， and the evolution of value added in service-oriented manufacturing is analyzed from both static and dynamic perspectives， as well as the adjustment mechanism for value added. Research has found that： （1） in the value network， the manufacturing value flow under manufacturing relationships forms a “U” pattern along the industrial chain； The service value flow around the market is strong， and the value flow in the service network shows a “√” flow trend； The innovation value network mainly relies on the innovation chain to expand， with a trend of point like emission characteristics. （2） The increase in intrinsic value flow leads to the disorder of value-added in service-oriented manufacturing. Optimizing the input-output system under value allocation is the key to guiding service-oriented manufacturing enterprises to surpass traditional development models； （3） The value-added of service-oriented manufacturing shows significant differentiation on the input-output side， but the overall value structure performance is better， and the value-added ability of each node is good； （4） Each node has different preferences for dependence on various value flows， but there is a clear law of diminishing marginal utility of value flows. During the process of value appreciation， invalid value streams must be stripped off. Figures and Tables | References | Related Articles | Metrics

Select

Research on the Introduction Strategy of Blockchain Based on the Information Leakage Qiuxiang Li, Ge Zhang, Huimin Ji, Yimin Huang, Ershi Qi 2025, 33 (11):  139-150.  doi: 10.16381/j.cnki.issn1003-207x.2023.0081 Abstract ( 9 )   HTML ( 0 )   PDF (1463KB) ( 4 )   Save With the increasing demand from consumers for product authenticity recognition， the demand for product information sharing among enterprises is also constantly increasing. The information tracking and sharing functions of blockchain technology have attracted the attention of a large number of enterprises and scholars. However， supply chain members who have access to information on the blockchain may intentionally or unintentionally disclose one party's key information to the other for their own interests， leading to information leakage issues. Information leakage will inevitably change profits， exacerbate the sense of unfairness among the leaked parties， and ultimately lead to the breakdown of cooperation. At the same time， the phenomenon of "free riding" among supply chain members （one party pays the cost to introduce blockchain technology， while the other party enjoys the technology dividend without paying the cost） also creates a strong sense of unfairness among the leaders of blockchain technology introduction， which undermines the security and stability of the operation of supply chain. How to reduce the possibility of information leakage and prevent free riding is the key to improving the sense of fairness of the leading party in cooperation， and also the key to maintaining the security and stability of the supply chain. Based on the rational economic man hypothesis and the reference dependency hypothesis， if the blockchain technology introduction strategy and contract parameters can be adjusted to transfer more profits to partners， the breeding of supply chain unfairness will be avoided. The introduction of blockchain technology by manufacturers in a supply chain system composed of a single manufacturer and a retailer is considered. From the perspective of the manufacturer introducing blockchain technology， it compares and analyzes the equilibrium benefits of the manufacturer in unilateral and cooperative introduction strategies. In addition， when collaborating with retailers to introduce blockchain technology， incentive issues and information leakage threats are considered， and the cost sharing ratio is adjusted to effectively motivate retailers to achieve cooperation， The price discount adjustment based on cost sharing price discount contract effectively prevents retailers from threatening information leakage.It focuses on the identification of product authenticity by blockchain technology， focusing on product traceability， and considering that the application of blockchain technology is top-down， that is， only when the manufacturer apply blockchain technology can retailers obtain the necessary conditions for applying blockchain. According to the scope of blockchain technology promotion， it is proposed to build three game models： no blockchain technology introduction， manufacturer introduction （such as Mercedes Benz manufacturers）， and manufacturer retailer cooperation introduction （such as Wal Mart）. The main conclusions and management implications are as follows.（1） Based on a sense of fairness， the manufacturer chooses a cooperative introduction strategy rather than a unilateral introduction strategy. In the unilateral introduction strategy， although the profits of supply chain members increase， the perceived benefit of the manufacturer who leads the technology is the lowest， and the perceived benefit decrease with the increase of his own introduction effort， resulting in a strong sense of unfairness from the manufacturer. Collaborating with the retailer under a certain cost sharing ratio can not only increase the total revenue of the supply chain and achieve Pareto optimality， but also consider the fairness psychology to maximize the perceived revenue of the manufacturer. Therefore， the cooperation strategy is superior to the unilateral introduction strategy.（2） Manufacturer can incentivize the retailer to collaborate by adjusting the cost sharing ratio， while maximizing their own interests. When the price discount is within a certain range， the retailer will not leak information， and the price discount value will decrease with the increase of the cost sharing ratio. Retailer profits are more sensitive to the cost sharing ratio， while the profit of the manufacturers is more sensitive to the price discount. The manufacturer offering a certain range of price discounts can effectively prevent retailer information leakage（3） The service provider who do not participate in the introduction of cooperation can also obtain free ride benefits， which increase with the decrease of cost sharing ratio and price discount. In reality， the supply chain structure is more complex， with multiple upstream and downstream enterprises. Not all enterprises are willing to participate in the introduction of blockchain technology， and these enterprises also hope to see a stable cooperation situation. Figures and Tables | References | Related Articles | Metrics

Select

Online Doctor Recommendation Considering the Uncertainty of Deep Learning Models Fulai Cui, Yidong Chai, Yuanchun Jiang, Yang Qian, Jianshan Sun, Yezheng Liu 2025, 33 (11):  151-161.  doi: 10.16381/j.cnki.issn1003-207x.2023.1494 Abstract ( 9 )   HTML ( 0 )   PDF (1096KB) ( 1 )   Save The rapid development of Internet medical treatment has greatly improved the convenience of seeking medical advice， and at the same time， it has also caused patients to face the difficulty of finding a suitable doctor from the massive doctor database. Effective doctor recommendation has become an important way to improve the experience of patients on the Internet medical platform. As it is related to life and health， compared with ordinary product and service recommendation， doctor recommendation has higher requirements for the reliability of results. Deep learning models have been widely used in personalized recommendations in recent years. However， the inherent uncertainty of the deep learning models can easily lead to uncertain recommendation results， thereby affecting the reliability of the doctor recommendation. To address this， the inherent uncertainty of deep learning models is considered and a Multi-Modal Bayesian Neural Collaborative Filtering model （MM-BNCF） is proposed based on Bayesian learning theory. First， a Bayesian deep learning model is constructed based on Monte Carlo Dropout， with structured patient feedback and unstructured doctor and patient text data as input， to obtain representations of doctors and patients separately. Second， the Bayesian deep model is used to analyze the compatibility between doctors and patients， and to assess the uncertainty of doctor-patient matching. Then， doctor recommendation results are generated based on compatibility. Final， experimental results based on real data from the haodf.com online platform validate that the proposed recommendation method in this paper can be more effectively applied to online doctor recommendation tasks. There is theoretical and practical significance for improving the performance and patient satisfaction of Internet medical websites in this study. Figures and Tables | References | Related Articles | Metrics

Select

Research on Recommender System Deployment and Cost Strategy in Mobile Health Platform Peilun Li, Qiuju Yin, Zhijun Yan 2025, 33 (11):  162-172.  doi: 10.16381/j.cnki.issn1003-207x.2023.1159 Abstract ( 4 )   HTML ( 0 )   PDF (1246KB) ( 3 )   Save The mobile health platforms offer users lots of exercise courses. And the platforms often employ recommender systems to enhance users' awareness of fitness exercise courses， helping them better manage their personal health. Recommender systems can predict the users’ preferences based on their historical data and recommend suitable fitness courses. One of the key objectives of deploying recommender systems is to earn higher commission fees from course providers. However， if the systems intensify market competition and subsequently reduces course sales， platform’s commission fees will correspondingly decline. This potential decrease in platform fees may prevents deploying recommender systems.The impact of recommender systems on the competitive market environment remains ambiguous. While enhancing product visibility， they also intensify competition among substitutable products. In the mobile health platforms， recommender systems increase user awareness of course offerings and expand the pool of potential customers， but they also heighten the competition among course providers. Course providers must adjust their business strategies according to the market shifting caused by recommender systems. Apart from attracting users， they need set reasonable prices to expand potential market from the extra exposure provided by the recommender system. Cost strategy of providers is intricately linked to the product price strategy. Effective cost control enhances the market competitiveness of products. A low-cost approach to producing fitness courses makes it more feasible to lower sales prices. Such low-price courses are more likely to be recommended but not necessarily favored by users. Conversely， high-quality fitness courses resulting from high-cost strategies offer greater value to users. High-cost courses provide users more health benefits， but their corresponding high selling prices reduce the likelihood of obtaining additional exposure from recommender systems. Three questions are primarily investigated： Under what conditions does a platform have the incentive to deploy a recommender system？ How does the recommender system affect market price competition and course providers' sales profits under different cost strategies？ And under various levels of user awareness and market conditions， how should course providers decide their cost strategies？The results show that　（1） Regardless of whether course providers adopt a high- or low-cost strategy， deploying a recommender system can enhance platform profits. （2） When providers uniformly adopt a high-cost strategy， the recommender system intensifies price competition among them， but simultaneously increases user demand and provider profits. （3） When providers uniformly opt for a low-cost strategy， the recommender system mitigates price competition among them. The systems may not necessarily increase user demand but can still enhance provider profits. （4） The choice of cost strategy for providers is jointly influenced by user characteristics and market conditions. When the degree of course mismatch， production costs， user health value conversion coefficients， or market cognitive levels are high， providers should choose a high-cost strategy. Conversely， when users gain a high fixed health value from courses， adopting a low-cost strategy is beneficial to provider profits. Figures and Tables | References | Related Articles | Metrics

Select

From Supply Chain to Ecological Chain: Management Challenges and Potential Research Directions Yongbo Xiao, Min Liu, Cui Zhao, Chun Liu 2025, 33 (11):  173-184.  doi: 10.16381/j.cnki.issn1003-207x.2023.0063 Abstract ( 13 )   HTML ( 0 )   PDF (834KB) ( 8 )   Save The great success of ecological chains， exemplified by companies such as Xiaomi， JD.com， and TikTok， has attracted an increasing number of firms to establish their own eco-chains. By sharing resources within the supply chain， including technology， brand， sales platforms， and customer bases， eco-chains have created a win-win ecosystem for firms across different industries. Specifically， from the perspective of eco-chain “owner，” the establishment of collaborative relationships with eco-chain members through equity investment， extensive incubation， and joint operations enables them to swiftly penetrate more market segments and capitalize on the growth of eco-chain members. From the perspective of eco-chain member， on the other hand， joining such a network allows them to benefit from the rapid development of high-quality products and the explosive growth of market size facilitated by the eco-chain “owner.” In contrast to traditional supply chains， the relationships between firms （i.e.， owner and members） within an eco-chain are much more complicated， with a more pronounced symbiotic effect， and a heightened focus on long-term interests. Consequently， eco-chains have given rise to many new business models and supply chain structures， while also presenting numerous new management challenges to related firms.According to the investigation， there are three typical eco-chain structures. The first type involves eco-chains where manufacturers， as the core entities， have unique advantages in product development and supply chain resources. For instance， Xiaomi， a globally leading smartphone manufacturer， has accumulated core advantages through iterative smartphone development. These include incorporating continuous user feedback for quality improvement， enhancing technology accumulation and product development capabilities， and fostering a stronger brand image. From the perspective of Xiaomi's eco-chain members， they can quickly develop high-quality products with financial support and shared resources from Xiaomi. The second type encompasses eco-chains with core retailers. These retailers possess key capabilities， such as a demand-oriented brand image， extensive channel resources， and a loyal customer base. JD.com， a globally leading online retailer， exemplifies this type by providing financing， warehousing， logistics， and after-sales services to various eco-chain members. The third type is eco-chains in which platforms are core entities. These platforms excel in system construction and service provision， with distinctive advantages in technology and bilateral matching. For example， the live streaming e-commerce eco-chain， TikTok， quickly realizes high profits by accumulating a large number of users from short videos and opening e-commerce modules to attract members such as Multi-Channel Network （MCN） agencies and brand merchants. In practice， the above three types of eco-chain structures give rise to different eco-chain business models， including the equity investment model and the operation cooperation model. The equity investment model involves the eco-chain “owner” holding the equity of its eco-chain members. In contrast， in operation cooperation model， eco-chain “owner” and members allocate the total operational benefits in the system.In the context of the three types of eco-chain structures and two eco-chain business models， the eco-chain “owner” forms into a different competition and collaboration relationship with the member firms， manifesting unique sources of income compared to traditional supply chains. Consequently， both the eco-chain “owner” and members confront several new challenges in eco-chain management relative to traditional supply chain management. Through careful analysis， this paper summarizes five new management challenges of eco-chains， including complicated competition and cooperation， inconsistent objectives among eco-chain firms， the trade-off between the long-term benefits and the short-term profits， financing， and innovation and optimization within eco-chains. Specifically， first， various interactions， such as investment and ownership， product collaboration， or complementarity competition between eco-chain firms， create complicated competition and cooperation relationships. For instance， investment and ownership relationships prompt the eco-chain “owner” to provide technical support and share resources for the member firms， whereas the member firms need to decide whether to compete or collaborate with the “owner.” Further， the complex relationships may result in significant goal conflicts between eco-chain “owner” and member firms， which can evolve dynamically. For example， startups （member firms） initially rely almost entirely on the eco-chain “owner” for their operations but may later compete with the “owner.” Therefore， eco-chain firms should carefully design contracts to facilitate cooperative operations. Third， in models involving investment and incubation， the eco-chain “owner” may prioritize long-term benefits such as market size and industry layout， over short-term profits， influencing the short-term decisions. Consequently， eco-chain firms must strike a careful balance between short-term profits and long-term benefits. Fourth， unlike the direct upstream and downstream relationships of traditional supply chain firms， eco-chain financing is more complex due to the intertwined relationships. Traditional supply chain financing model may not be applicable to eco-chains， necessitating the development of new financing models. Lastly， innovation and optimization in eco-chains often require the balance of efficiency and benefits to ensure collaboration and sustainability. The establishment of data-sharing platforms to address privacy and security concerns may serve as an effective solution.Through the above analysis， this paper surveys the existing relevant literature and summarizes the research gaps. Based on the new management challenges in eco-chains and research gaps in existing related studies， this paper proposes some potential research issues and directions of eco-chains from the perspective of operations and supply chain management， including analysis of consumer behavior， operational decision optimization， competition and cooperation strategies within and across eco-chains， and coordination mechanisms between eco-chain members. Specifically， first， new business models may have different influences on consumer behavior and knowledge acquisition in eco-chains compared to traditional supply chains. Therefore， it is crucial to develop a framework for analyzing consumer behavior by understanding the pivotal role of fans （consumers） and their engagement within eco-chain firms. Second， new structures and business models in eco-chains may affect firms’ operational decisions such as pricing， financing， and investment approaches， through changes in consumer behavior. Focusing on the distinctive characteristics between eco-chain “owners” and member firms， it is of great research value in exploring dynamic pricing strategies leveraging machine learning techniques， financing strategies amidst resource sharing and interactivity， investment strategies tailored to different eco-chain business models， and the trade-off between long-term benefits and short-term profits. Third， when extending the perspective to multiple members rather than single firm within an eco-chain， it is essential not to overlook the effects of evolving competition and cooperation relationships among eco-chain firms. Investigating the dynamics of contracts and incentive-compatible coordination mechanisms holds important theoretical and practical contributions. Finally， from the perspective of competition and cooperation across eco-chains， future research avenues should explore global competitiveness， societal implications， and technological innovation for sustainable development. Figures and Tables | References | Related Articles | Metrics

Select

Supply Chain ESG: Research Framework, Challenges and Future Research Directions Jiaguo Liu, Yatao Zhao, Jian Li, Yu Gong 2025, 33 (11):  185-196.  doi: 10.16381/j.cnki.issn1003-207x.2024.1775 Abstract ( 14 )   HTML ( 0 )   PDF (803KB) ( 6 )   Save With the intensification of global economic， social and environmental challenges， ESG has gradually become the key to enhancing corporate reputation and supply chain competitiveness. However， the current academic research on ESG mostly focuses on single-point enterprises， and there are relatively few systematic studies on ESG at the supply chain level. In view of this， the existing research on ESG is reviewed at the enterprise level and the supply chain level. Secondly， the concept of supply chain ESG is defined based on the understanding of supply chain ESG by different organizations and institutions. Then， the research framework of supply chain ESG is constructed around five aspects： supply chain member behavior， supervision and compliance， information disclosure， driving mechanism and risk management. After that， the challenges faced by supply chain ESG are analyzed. Finally， it provides the future research direction of supply chain ESG from the perspectives of standardization and policy drive， competition and cooperation relationship， technology drive and innovation. Figures and Tables | References | Related Articles | Metrics

Select

Study on the Impacts of Linkage Response and Digital Technology Empowerment on Emergency Operations Decision-making in Logistics Service Supply Chain Di Wang, Weihua Liu, Wanying Wei, Yanjie Liang 2025, 33 (11):  197-210.  doi: 10.16381/j.cnki.issn1003-207x.2024.1212 Abstract ( 10 )   HTML ( 0 )   PDF (2534KB) ( 0 )   Save As global emergencies continue to increase and intensify， comprehensively improving emergency support capability has become an inevitable requirement for balancing high-quality development and high-level security， and also a prerequisite for bolstering the resilience of China's logistics industry. In practice， in the face of the double changes in the management environment and the technical environment， strengthening the emergency linkage response among the supply chain members and releasing the potential of digital technology empowerment have become two important levers for improving the emergency logistics system. Specifically， based on different leaders in the emergency linkage process， emergency linkage responses can be divided into two types： “LSI-led linkage response” and “LSP-led linkage response”， in which the members complement each other's capabilities， creating a positive external impact on mutual emergency support capabilities， while the core role of digital technology empowerment is reflected in helping supply chain members reduce costs and increase efficiency. To clarify the impact of linkage response and digital technology empowerment on emergency operations decision-making， a logistics service supply chain consisting of a logistics service integrator （LSI） and a logistics service provider （LSP） is constructed， and the optimal emergency operations decision-making results of the Stackelberg game under the background of demand and cost disturbances are explored. It is found that， firstly， the degree of “LSI-led linkage response” and “LSP-led linkage response” in the logistics service supply chain have a positive impact on emergency service pricing， emergency support capability， as well as consumer surplus. Contrary to intuition， if the LSP's price-sharing ratio cannot be set appropriately， increasing the level of linkage response will lead to a loss of profit for LSI or LSP even if the linkage response cost can be controlled at a reasonable level. When the price-sharing ratio of LSP is low， it is crucial to rely on the LSI to spearhead emergency linkage responses， fostering a robust emergency response ecosystem within the logistics service supply chain. Conversely， when the price-sharing ratio is high， the LSP should take a more proactive role in the linkage response process， providing strong support by enhancing the emergency level of the terminal network. Secondly， the level of digital technology empowerment has a positive impact on the optimal decisions and consumer surplus. Its impact on LSI’s profit depends on the investment coefficient of the digital technology empowerment， while its impact on LSP’s profit is related to the consumer’s price sensitivity. Higher price sensitivity motivates LSP to embrace digital technology empowerment to achieve cost reductions and efficiency gains. However， if the consumer price sensitivity coefficient is low， the LSP’s profit actually decreases with the degree of digital technology empowerment. Thirdly， demand disturbance in emergency situations have a positive impact on optimal decisions， profits of members， and consumer surplus， while cost disturbance have a negative impact on optimal decisions， LSI’s profit， and consumer surplus. Interestingly， when the consumer’s price sensitivity is at a lower level， LSP’s profit will increase with the degree of cost disturbance. These conclusions can assist logistics enterprises in gaining a comprehensive understanding of the supply and demand disturbances stemming from emergencies and in formulating appropriate emergency responses that integrate operational management and technological empowerment strategies. Figures and Tables | References | Related Articles | Metrics

Select

Trade-in and Product Durability Design Strategies with Considering Online Platforms Shu Hu 2025, 33 (11):  211-220.  doi: 10.16381/j.cnki.issn1003-207x.2023.0021 Abstract ( 9 )   HTML ( 0 )   PDF (1067KB) ( 6 )   Save China is a big country in the production and consumption of electrical and electronic products. How to properly dispose of waste household appliances has become an urgent question to be solved. In recent years， in addition to selling new products， online platforms have begun to assist manufacturers in launching trade-in programs for a variety of home appliances （for example， air conditioners， refrigerators， and televisions） and provide rebates to consumers who participate in trade-in programs. Although online platforms can effectively promote the trade-in of home appliances， the different sales models provided by online platforms will affect the strategic interaction between online platforms and manufacturers， thus bringing new challenges for them. In view of this， there is an urgent need to provide decision-making suggestions for online platforms and manufacturers to operate trade-ins.To address the above issues， a two-period model framework is constructed， in which products will be treated as new in the first period and old in the second period. The consumers are considered to behave strategically： consumers make optimal decisions by comparing their total utility from two periods under different options. Therefore， the number of consumers under different options can be endogenously given by analyzing heterogeneous consumer behaviors， and then the profit functions of manufacturers and online platforms can be constructed， and their optimal trade-in operation strategies can be formulated. In this paper， online platforms provide manufacturers with two sales format： reselling format and agency selling format， and manufacturers rely on online platforms to implement trade-ins. Based on the above two sales format， game-theoretic models are established， that incorporating manufacturers， online platforms and consumers， in the case of with trade-in and without trade-in programs， respectively. Then， these two firms’ preferences for trade-ins can be analyzed by comparing their profits with and without trade-ins. In addition， the impacts of product depreciation rate on the profits of the manufacturer and the online platform are analyzed， in order to obtain the manufacturer's product durability design strategy and the impact of that strategy on the profit of the online platform.It is implied that both the sales format and the implementation of trade-ins would affect the manufacturer and online platform's preferences for product durability. In particular， it is only necessarily for the manufacturer to adopt a “planned obsolescence” strategy if the product is sold through an agency selling format without trade-ins， and this strategy also benefits the online platform. Finally， regardless of the format in which the manufacturer's products are sold， the manufacturer should carry out trade-in for the products. However， it is better for the online platform to consider the sales format， the product depreciation rate and the manufacturer's production cost when deciding whether to assist the manufacturer to implement the trade-in. Only when the manufacturer implements trade-in for those products with relatively low depreciation rate and production cost， should the online platform assist the manufacturer in both sales format. Otherwise， when the manufacturer implements trade-ins for those products with high depreciation rates， the online platform should only assist the manufacturer in implementing trade-ins under the reselling format， but refuse to assist under the agency selling format. Figures and Tables | References | Related Articles | Metrics

Select

Research on Information Sharing and Incentive Contract Design of Green Agricultural Product Supply Chain Yu Cao, Lan Tao 2025, 33 (11):  221-230.  doi: 10.16381/j.cnki.issn1003-207x.2022.1414 Abstract ( 9 )   HTML ( 0 )   PDF (1023KB) ( 1 )   Save A green agricultural product supply chain consisting of a cooperative， an agricultural enterprise and consumers is constructed， in which the agricultural enterprise has demand information advantage. It addresses the demand information sharing strategies of the agricultural enterprise and their impacts on the cooperative and the agricultural enterprise to enhance greening efforts， then explores the design of the incentive contract for information sharing. Research shows that whether the agricultural enterprise shares information is mainly influenced by consumers’ sensitivity to the greenness of agricultural products. Specifically， when consumers’ sensitivity to the greenness of agricultural products is small， the agricultural enterprise does not share demand information with the cooperative； when consumers’ sensitivity to the greenness of agricultural products is large， the agricultural enterprise takes the initiative to share demand information with the cooperative； and when consumers’ sensitivity to the greenness of agricultural products is moderate， the cooperative incentivizes the agricultural enterprise to share demand information by setting up contracts. In addition， the demand sharing strategies of the agricultural enterprise are also regulated by the contribution of green production （processing） efforts to the greenness of the final products. It is also found that the designed transfer payment contract can incentivize the agricultural enterprise to share demand information and achieve a win-win situation for both the agricultural enterprise and the cooperative. Figures and Tables | References | Related Articles | Metrics

Select

Exploring Supply Chain Emission Reduction Strategies within Voluntary Emission Reduction Trading Mechanisms Tie Wei, Ciling Ma, Pin Xie, Bangzhu Zhu 2025, 33 (11):  231-242.  doi: 10.16381/j.cnki.issn1003-207x.2023.1047 Abstract ( 8 )   HTML ( 0 )   PDF (1301KB) ( 0 )   Save China's carbon market features two primary trading mechanisms： the mandatory emission reduction mechanism which trades carbon quotas， and the voluntary emission reduction trading mechanism （CCER）. CCER incentivizes various social entities to voluntarily reduce emissions， fostering widespread awareness and contributing to China's goals for green， low-carbon development， and carbon emission reduction. Compared to the established mandatory emission reduction mechanism， the CCER is still in its early stages， particularly concerning the growing trend of supply chain emission reduction cooperation. The impact of the CCER mechanism on the emission reduction strategies of supply chain enterprises still remains uncertain. Given the significant investment， substantial costs and uncertain market returns associated with carbon emission reduction， effective coordination of costs and benefits within the supply chain is crucial for cooperative emission reduction efforts. Hence， it is imperative to investigate the impact of the CCER market's revival on supply chain emission reduction， focusing on cost-sharing and benefit-sharing contracts.To investigate the effects of introducing a voluntary emission reduction trading mechanism in China's carbon market on both emission reduction efforts and enterprise income within the supply chain， a supply chain comprising manufacturers and retailers is examined， and an emission reduction game model is developed， comparing scenarios with and without a voluntary emission reduction trading mechanism. Compared the emission reduction efforts， prices， outputs and profits of the supply chain under three scenarios： No contract， cost-sharing contract and benefit-sharing contract， in the absence of a voluntary emission reduction trading mechanism. This analysis offers enterprises a foundation for decision-making in selecting optimal emission reduction strategies and supply chain cooperation modes amidst the relaunch of the CCER market.Results indicates that， the voluntary emission reduction trading mechanism incentivizes manufacturers to reduce emissions， consequently boosting profits for both manufacturers and retailers under specific conditions. If the CCER trading price falls below the carbon quota trading price， manufacturers may purchase CCER quotas at a lower cost to compensate. Additionally， they can sell surplus carbon quotas in the carbon market， leading them to increase investment in emission reduction to gain a competitive edge. Under these circumstances， the rise in output and demand due to market expansion further motivates manufacturers to invest in emission reduction. Conversely， if the CCER trading price exceeds the carbon quota trading price， the voluntary emission reduction trading mechanism becomes ineffective. In such cases， manufacturers opt out of CCER trading and may fulfill carbon compliance by reducing production or purchasing minimal carbon quotas. Regardless of whether the voluntary emission reduction trading mechanism is implemented， emission reduction efforts and profits are consistently higher under cost-sharing and benefit-sharing contracts compared to scenarios without contracts. Notably， benefit-sharing contracts consistently yield the highest emission reduction efforts and profits， with the added advantage of lower prices. Hence， manufacturers can alleviate compliance pressure and enhance investment motivation for emission reduction by purchasing CCER under specific circumstances. Through the adoption of cost-sharing and revenue-sharing contracts， manufacturers and retailers can mitigate the adverse effects of the double marginal effect， thereby enhancing the overall emission reduction level of the supply chain. When formulating carbon trading policies， the government can base decisions on the disparity between CCER trading prices and carbon quota trading prices. Additionally， the CCER purchase restriction coefficient and the manufacturer's original unit carbon emissions collectively influence the CCER trading price. The government can adjust the purchase restriction coefficient based on manufacturers' carbon emissions， thereby regulating the CCER trading price. Figures and Tables | References | Related Articles | Metrics

Select

Sales Mode Selection of Supply Chain Members Considering the Introduction of Platform Private Brand and Production Modes Lihao Zhang, Shiqing Zhou, Luyu Chang 2025, 33 (11):  243-253.  doi: 10.16381/j.cnki.issn1003-207x.2022.1262 Abstract ( 9 )   HTML ( 0 )   PDF (1119KB) ( 3 )   Save With the development of e-commerce， the agency selling mode， which is different from the traditional reselling mode， has emerged and developed on the platform. Driven by the growth of online retail， platforms are beginning to introduce their store brand products. The sales mode within the supply chain will have an impact on the introduction decision of the platform. In addition， when the platform introduces the store brand， the decision on how the product is produced is an important issue for the platform. On this basis， the competitive factors between two different brand products are considered with different quality difference， and game theory is used to discuss the sales mode selection of the manufacturer and platform， the introduction of platform-owned store brand product and production decisions.In the rest of this paper， the profit models of supply chain members are constructed when the platform introduces store brand products and chooses three production modes （in-house production， outsourcing to the on/off chain manufacturer） under two sales modes （i.e.， reselling or agency selling）. Second， the corresponding optimal solutions are obtained and the platform’s store brand introduction decision is discussed. Finally， the sales mode decision of the manufacturer and the platform is explored， and on this basis， the sales mode equilibrium decision after Pareto improvement of the supply chain is obtained.The results show that， firstly， there is a conflict between the manufacturer and the platforms’ sales mode selection， but the Pareto improvement can achieve the coordination of the sales mode of the supply chain members. Secondly， the sales mode will affect the platform’s introduction decision. In the reselling mode， the platform always introduces its store brand. In the agency selling mode， for a high competition - medium/high value product， the platform has the motivation not to introduce store brand； otherwise， the introduction of private brands is the optimal strategy. Finally， the decision on how the platform’s store brand products is produced is related to the type of product and sales mode. For a product with low （high） value， the platform will always choose the in-house production （outsourcing to the off-chain manufacturer）. For a product with medium value， the platform chooses the in-house production （outsourcing to the off-chain manufacturer） in the reselling （agency selling） mode. Figures and Tables | References | Related Articles | Metrics

Select

Long-term Revenue Allocation Structure and Dynamic Incentive Mechanism in Supply Chain Jianheng Zhou, Bo Wu 2025, 33 (11):  254-263.  doi: 10.16381/j.cnki.issn1003-207x.2022.1952 Abstract ( 5 )   HTML ( 0 )   PDF (1722KB) ( 0 )   Save Multiperiod revenue allocation structure and dynamic incentive problem of supply chain considering newsvendor demand driven by long-term payment. The incentive model of moral hazard for single-period retailers is first explored under demand uncertainty. Based on this， the retailer moral hazard incentive model under long-term payment structure is analyzed. Further， the multiperiod is extended to infinite periods， the specific characteristics of the payment incentive system is discussed under infinite periods， and the smoothing mechanism of manufacturers’ incentive costs is elaborated. It is found that risk-averse agents have moral hazard under single-period cooperation. At the same time， it is found that multiperiod moral hazard contracts have two important properties， namely， memorability and harnessing， and that manufacturers prefer to smooth the burden of incentive constraints between the present and the future. Moreover， under multiperiod cooperation it is found that the total reward generated by the retailer’s effort is not fully realized in the current period， and it is also found the phenomenon of equal shares of payment for each subsequent period. However， when the parties do not know when the partnership will end， the manufacturer can derive additional benefits from repeating the game over time， i.e.， the incentive cost is the same for each period. If the retailer places a high value on future revenue， the manufacturer’s expected revenue will tend to be Pareto optimal， i.e.， the retailer does not have to take any risk in the long-run game. This mechanism of action is known as the “smoothing effect” of the manufacturer’s revenue allocation structure system. Figures and Tables | References | Related Articles | Metrics

Select

The Influence of Government Reward-penalty Mechanism on the Recycling of WEEE under the Tripartite Evolutionary Game Wenbin Wang, Jinyu Qi, Mengxin Zhang, Jie Guan, Wenxin Yu 2025, 33 (11):  264-274.  doi: 10.16381/j.cnki.issn1003-207x.2022.2196 Abstract ( 8 )   HTML ( 0 )   PDF (1549KB) ( 0 )   Save The recycling of waste electrical and electronic equipment （WEEE） is an important part of the development of circular economy. The government has issued numerous departmental regulations and formulated industry planning， and manufacturers and recyclers have actively responded to the recycling policy， which has improved the recovery rate of WEEE. In addition， WEEE contains some effective parts， which can be dismantled， reassembled and reused， which can help enterprises save production costs， promote green and low-carbon transformation development， and help realize the goal of “carbon peak and carbon neutrality”.Therefore， an evolutionary game model of government， manufacturer and recycler is constructed， the stability of strategy selection of each game player is analyzed， and then Jacobian matrix is used to further analyze the stability of equilibrium points in the three-party game system. Finally， simulation analysis is carried out to discuss the influence of key parameters on the behavior evolution of participants. It is found： （i） the government's incentive and punishment intensity and the recovery rate of WEEE under the low price strategy of recyclers affect the cost range of the government's implementation of the incentive and punishment mechanism， and the cost range of the government's implementation of the incentive and punishment mechanism further affects the probability of the government's implementation of the incentive and punishment mechanism. However， the recovery （purchase） rate of recyclers and manufacturers under the high price strategy is not affected by cost changes. They vary inversely with the probability that the government will impose rewards and punishments； （ii） the increase in the probability of government implementing rewards and punishments can promote recyclers and manufacturers to choose high-price WEEE recycling as a stabilizing strategy， and the low price strategy of recyclers and manufacturers can in turn affect the probability of government implementing rewards and punishments mechanism； （iii） when the sum of the recovery price and the additional cost of recovery of the recycler under the high-price strategy is greater than the sum of the two under the low-price strategy， the additional cost of recovery of the recycler under the low-price strategy is lower， the recovery rate of the recycler under the high-price strategy is higher， and the government increases the incentives and punishments， all of the three situations will lead the recycler to choose the high-price recovery strategy. However， when the recovery price of the recycler is equal to the sum of the additional cost of recovery under the high price and low price strategies， the recycler will only choose the high price recovery strategy.Some management insights are offered based on our findings. At the early stage of the evolution， the government can increase the amount of WEEE in the recycling system by strengthening the incentives and punishments to promote recyclers and manufacturers to evolve to a stable high price strategy. Recyclers and manufacturers can improve the recovery rate of WEEE by changing the recycling channels and other measures to control the total cost of recycling. When a relatively perfect waste electronic recycling system is formed in the market， the government can adopt the strategy of not implementing rewards and punishments. Figures and Tables | References | Related Articles | Metrics

Select

Research on Cause Marketing Decision Considering the Competition of Manufacturer and E-commerce Platform's Private Brand Chuanliang Wu, Zhongjun Tian, Jing Chen 2025, 33 (11):  275-287.  doi: 10.16381/j.cnki.issn1003-207x.2023.0323 Abstract ( 10 )   HTML ( 0 )   PDF (1660KB) ( 7 )   Save Cause marketing （CM） is one of the important ways for enterprises to fulfil their social responsibilities.With the rapid development of e-commerce， more and more manufacturers have begun to develop their online sales channels and compete with private brand of e-commerce platforms. The implementation of CM by enterprises can increase brand competitiveness， so more enterprises are implementing CM. When competitive manufacturer's brand and the e-commerce platform's private brand sell in the market， should they implement CM， and how should they make pricing and donation decisions？The two-level supply chain composed of manufacturer and e-commerce platform is taken as the research object. It compares and studies the CM decision problems under the condition that the brands in the supply chain are competitive under different sales modes by constructing a game model for implementing CM between the manufacturer's brand and the e-commerce platform's private brand under the agency and reselling modes. It is found that under the agency mode， both the manufacturer's brand and the e-commerce platform's private brand implement CM， or only the manufacturer's brand implements CM， which may form a balanced strategy. Under reselling mode， implementing CM for both brands is the only balanced strategy. Under the agency mode， the manufacturer's brand unit donation amount is the smallest. Under the reselling mode， the unit donation amount of the manufacturer's and the e-commerce platform's private brands is the same. Implementing CM for both brands is more conducive to the e-commerce platform. When both brands implement cause marketing under different sales models with lower commission rates， the manufacturer's brand's implementation of cause marketing is more effective than the reselling model. Combining with numerical analysis， it is found that the private brand of e-commerce platform implements CM under the reselling mode is more effective than the agency mode. In addition， by comparing the total amount of donations and the size of social welfare under different sales modes， the relevant conclusions also provide a lot of theoretical bases for non-profit organizations to choose cooperative enterprises and for the government to formulate appropriate policies. Figures and Tables | References | Related Articles | Metrics

Select

Research on Two-sided Matching Employment Guidance Strategies for Self-employed Veterans Jian Wu, Zengwen Wang, Wenya Zhang 2025, 33 (11):  288-298.  doi: 10.16381/j.cnki.issn1003-207x.2023.0368 Abstract ( 14 )   HTML ( 0 )   PDF (1225KB) ( 6 )   Save In reality， when self-employed veterans are converted from the military filed to the social field， the weak transferability of their previously possessed military-specific human capital leads to a mismatch between their specific skills and those in demand in society. And low employment rates or low quality of employment for self-employed veterans are frequent， and the satisfaction of job is generally low. The employment guidance for self-employed veterans is an important way to optimize the resource allocation of veterans and achieve high-quality employment. The employment guidance strategy is affected by the employment preference and demand of veterans， the expectation and capacity of enterprises and institutions， the satisfaction of the government to the resettlement work， the uncertainty of information expression and psychological perception of the matching subjects. A multi-attribute one to many employment guidance matching model based on maximization of tripartite satisfaction under probabilistic hesitant fuzzy environment is constructed to analyze the different guidance strategies that form a stable result. To obtain the weights of attributes for each party， an approach based on WINGS method is proposed under probabilistic hesitant fuzzy environment. The results show that： （1） The main factors that affect the career choice of retired soldiers are career stability， enterprise cohesion， career risk， learning opportunities and so on. （2） Enterprises and institutions pay more attention to the personal characteristics and personal knowledge of the group of veterans， in turn， the sense of responsibility of veterans， the skills learned in pre-retirement training， etc. （3） There will be differences in the optimal matching between the optimization strategies based on the satisfaction of different matching subjects. Among them， the optimization strategy based on the satisfaction of the government will help to improve the optimal value of the matching results. Finally， it is suggested to establish a coordination and guidance mechanism for the employment of veterans and build an intermediary coordination service carrier with the government as the main body. At the same time， it is necessary to implement the adaptability training for veterans before retirement and improve the skill training policy. Figures and Tables | References | Related Articles | Metrics

Select

Low Carbon Services Considering Embeddedness under a Carbon Cap-and-trade Mechanism Contract Design and Coordination Qingsong Xing, Jing Wang, Fumin Deng 2025, 33 (11):  299-309.  doi: 10.16381/j.cnki.issn1003-207x.2023.0007 Abstract ( 9 )   HTML ( 0 )   PDF (2036KB) ( 1 )   Save In carbon reduction cooperation， the nature of the relationship between manufacturing enterprises and low-carbon service providers is a typical “principal-agent” relationship， in which both parties are “economic agents” who maximize their own interests. In view of this， manufacturers and embedded low-carbon service providers are taken as research objects， the carbon allowance trading mechanism， low-carbon service providers to business embedded and capital investment in the way of participating in the manufacturer's energy saving and emission reduction services are considered， different revenue sharing models are designed to reasonably carry out the distribution of revenues， the two sides of the low-carbon service contract preferences are analyzed under different contractual standards， supply chain carbon emission reduction efficiency and revenue sharing coordination， and the influence of relevant parameters on the optimal decision-making is explored， and verify the effectiveness of the decision-making model through numerical simulation analysis.The first part is to analyze the behavioral mechanism of the subject members on the basis of summarizing and organizing relevant literature. Taking a system composed of a manufacturer and an embedded low-carbon service provider aiming to promote energy saving and emission reduction through the consistency of low-carbon emission reduction service contract as the research object， the inconsistency of contractual preferences generated by both parties is considered， and a dynamic game model between the system subjects is constructed.The second part is to solve the optimal decision-making of the embedded low-carbon service participating subjects under different contract objectives. Firstly， different revenue sharing models are designed to reasonably distribute the revenue， and the optimal service cost of the manufacturer and the energy-saving and emission reduction efficiency and business investment of the low-carbon service provider are calculated； then， the impacts of embeddedness， energy-saving and emission reduction capacity and carbon trading price on the optimal decision-making of both parties under different contractual standards are analyzed， the upper and lower bounds of the embeddedness and the carbon trading price are determined， and further the optimal decision-making of the participating subjects under different contractual standards is analyzed. The preference of participating subjects for low-carbon service contracts with different contract objectives is also analyzed； finally， this is used as a benchmark to compare and the data sharing willingness of the e-commerce platform and the supply chain system as a whole is analyzed.The third part is to construct a transfer payment mechanism to coordinate the preference conflict. Under the premise of the valid interval of the two cooperation contracts being established at the same time， the environmental performance and economic benefits of embedded low-carbon service providers and manufacturers in these two contracts are analyzed， and then whether the contract conflict problem occurs between the two parties of the participating subjects is analyzed， as well as how to coordinate the contract conflict problem， so as to make the two parties reach a consistent contractual preference， thus realizing the long-term sustainable cooperation between the low-carbon service providers and manufacturers.The fourth part is a simulation analysis of the optimal decision-making of the embedded low-carbon service participants， which visualizes the contractual preferences of the participants and the effectiveness of the coordination mechanism. It is found that the establishment of the two low-carbon service contracts depends on the embeddedness of the participating parties and the carbon emissions trading price， whether the contract is based on the carbon emission reduction rate or the revenue from the sales of emission reduction products， and the validity of the two contracts can be ensured only if the two factors are within a certain threshold range at the same time. Although the emission reduction rate and manufacturer's profit are optimal under the technology trading-type contract， low carbon service providers do not necessarily agree to this contract from their own interests due to the difference in embeddedness， and the two parties will have a conflict of contractual preferences， which can be coordinated by the manufacturer to provide a transfer payment mechanism to achieve consistency in the contract of the two parties' choices.Finally， based on the above findings， targeted recommendations from manufacturers， low-carbon service providers and government decision-making are put forward， which provides theoretical and practical references to significantly improve economic efficiency and promote the transformation of China's manufacturing industry into a green and low-carbon industry. Figures and Tables | References | Related Articles | Metrics

Select

Achieving China's Regional Dual-carbon Goals by Adopting Differentiated Policies in Different Regions: Structural Decomposition and Clustering Analysis Based on Spatial Differences in Carbon Emissions in China Hongguang Nie, Cairui Jiang, Jianlei Mo 2025, 33 (11):  310-320.  doi: 10.16381/j.cnki.issn1003-207x.2023.0876 Abstract ( 8 )   HTML ( 0 )   PDF (2517KB) ( 3 )   Save Due to different resource endowments， industrial division and development stages， CO2 emissions pattern in different regions of China show spatial heterogeneity. The Action Plan for Carbon Peaking before 2030 points out that all regions should take measures by category and take orderly steps to achieve carbon peak based on their own economic and social development stages and resource and environmental endowments. By analyzing the key driving factors of carbon emissions in China's 30 provinces and cities and identifying their differences， a classification of Chinese provinces and cities is proposed， and strategies for each type of provinces and cities are put forward to reach carbon peaking and carbon neutrality in the future.In order to propose a scientific and reasonable spatial classification， the spatial differences and key drivers of carbon emissions in 30 provinces of China （except Tibet， Hong Kong， Macao and Taiwan） are quantified by constructing a multi-regional spatial structure decomposition analysis model. Based on the results of spatial structure decomposition analysis， a cluster analysis of 30 provinces in China is made， so as to identify the carbon emission characteristics of each type of provinces， and key strategies for achieving “dual carbon” goal in various provinces are put forward.The results show that there are six key factors leading to the spatial differences of carbon emissions among provinces in China， which are sectoral structure， demand allocation， final demand， energy intensity， production structure and energy mix effects. Based on the contribution of the above drivers to the spatial differences of carbon emissions among provinces in China， 30 provinces are classified into five categories through cluster analysis， i.e. growth-driven provinces， efficiency-driven provinces， balanced-developing provinces， extensive-growth provinces and provinces with great transformation potential. Although growth-driven provinces have a high level of carbon emissions， their energy intensity， energy mix and sectoral structure are better than the national average level， and economic growth is the main driver of the high level of carbon emissions in these provinces. The carbon emission level of efficiency-driven provinces is generally low， as a result of the higher energy efficiency and better energy mix in these provinces. The level of carbon emissions in the balanced-developing provinces is in the middle of all provinces in China， and the effects of various drivers are also in the middle of the whole country. The level of carbon emissions in extensive-growth provinces is high， as a result of low efficiency and unreasonable structure in these provinces. The provinces with great transformation potential have the lowest carbon emission level with rich renewable energy sources and thus large transition potential.The contributions of this paper are as follows. First， the spatial differences of carbon emissions among provinces in China are identied. Second， the drivers of the spatial differences of carbon emissions among provinces in China are analyzed. Third， it provides a methodology for the classification of provinces in China for the ‘Action Plan for Peak Carbon by 2030’， and the key strategies to achieve the "dual carbon" goal for various provinces are further proposed. Figures and Tables | References | Related Articles | Metrics

Select

The Dual Control Effects of Carbon Emissions of Digital and Green Transitions: A Mechanistic Analysis Based on New Quality Productive Forces in Manufacturing Industries Qunwei Wang, Qian Du, Zhenran Li, Yaru Cao 2025, 33 (11):  321-335.  doi: 10.16381/j.cnki.issn1003-207x.2024.1615 Abstract ( 7 )   HTML ( 0 )   PDF (1853KB) ( 1 )   Save Digital and green transitions are crucial strategic deployments for achieving high-quality economic development and environmental sustainability， and they also serve as key drivers for advancing new quality productive forces. The policy effects of digital and green transformations on carbon emissions and carbon intensity （referred to as dual control of carbon emissions） is examined， deconstructing the new quality productive Forces in manufacturing industries from the perspectives of structural upgrading， total factor productivity optimization， and rational resource allocation， and the underlying mechanisms of these influences are analyzed.The empirical results indicate that， benefiting from the advancement of manufacturing structure and the optimization of total factor productivity， digital transformation contributes to the dual control of carbon emissions， while green transformation significantly reduces carbon emissions. However， the effect of factor allocation is not apparent. Further research shows that the synergistic effect of the “digital + green” dual transformation in reducing carbon intensity is greater than the sum of the individual policy effects， demonstrating a clear policy synergy effect. In addition， the heterogeneity analysis indicates that in regions with lower levels of structural upgrading or higher levels of total factor productivity optimization， the effect of the “digital + green” dual transition on reducing carbon emissions is weakened， but it significantly enhances the reduction of carbon intensity. It provides new evidence to further understand the complex relationship between digital and green transformations and the dual control of carbon emissions in this paper. Figures and Tables | References | Related Articles | Metrics

Select

Dynamic Optimization Model for Renewable Resource Development: An Example of Onshore Wind Lei Zhu, Yaofeng Cui, Jiarui Wang, Jiahao Wu 2025, 33 (11):  336-344.  doi: 10.16381/j.cnki.issn1003-207x.2024.1625 Abstract ( 11 )   HTML ( 0 )   PDF (1548KB) ( 1 )   Save Research on renewable energy， including wind power， is currently centered on the reduction of costs associated with large-scale deployment， the integration of intermittent resources into the power grid， and the formulation of supportive policy frameworks. In the realm of practical development， wind power， akin to non-renewable resources such as oil， is constrained by geographical limitations for exploitable locations， implying that there is an upper limit to the total potential installed capacity. The optimal control theory of exhaustible resources is applied to the context of wind energy， considering the regional wind energy reserves（remained capacity potential） as exhaustible resources. The model in this paper takes into account a multitude of factors， including the reserves of wind energy， the benchmark on-grid electricity prices for wind power， investment costs， construction and grid consumption costs， as well as the depreciation and eventual retirement of wind turbines. The primary aim of this study is the maximization of the long-term net benefits from wind power development. Consequently， a dynamic optimization model has been constructed to achieve this goal. In the analysis and resolution of the model， the Hamiltonian function and Pontryagin's Maximum Principle are utilized to find the optimal development path for the incremental installed capacity. Furthermore， under specific conditions， the existence and uniqueness of the optimal solution are established using Picard's existence and uniqueness theorem， as well as the theorem on the extensibility of solutions. An algorithm for finding an approximate optimal solution under general conditions is also presented. A case study analysis of the Jiuquan Wind Power Base in Gansu Province is also provided， assessing the congruence between the projected development outcomes and the model's predictions. Figures and Tables | References | Related Articles | Metrics

Select

'Identification-Assessment-Alert' Integration Model of Investment Risks in Renewable Energy Projects: Cases of Belt and Road Countries Hao Ding, Yu Su, Dequn Zhou, Siqi Zhao, Yining Zhang 2025, 33 (11):  345-356.  doi: 10.16381/j.cnki.issn1003-207x.2024.1609 Abstract ( 6 )   HTML ( 0 )   PDF (4041KB) ( 0 )   Save Growing global investments in renewable energy have heightened worldwide attention to risks stemming from uncertainties. Under China’s Belt and Road Initiative （BRI）， increased investments in host-country renewable energy projects underscore the critical need for effective risk management. A risk identification-assessment-early warning’ framework is employed to analyze investment risks across 64 BRI countries. Using data volatility （standard deviation） as a core metric， 2021 risks and project trends for 2023-2024 are quantified. First， an integrated risk model is constructed： BERTopic identifies risk themes， an entropy-weighted CRITIC model with Gaussian mixture distribution assesses risks based on standard deviation， and an early-warning system combines GM（1，1） forecasting with firefly algorithm-optimized SVM. Second， seven key risk dimensions are identified： political， economic， socio-environmental， market， technological， energy resource， and operational management. In 2021， risk levels varied substantially： 8 high-risk countries （e.g.， Yemen， Afghanistan）， 10 medium-high-risk （e.g.， Iraq， Turkey）， 11 medium-risk （e.g.， Mongolia， Indonesia）， 13 medium-low-risk （e.g.， Brunei）， and 22 low-risk （e.g.， Singapore）. Projections indicate 48 countries will experience risk-level shifts by 2023–2024， with 11 countries （e.g.， Malaysia， Israel， Ukraine） facing elevated risks. Third， installed capacity and power generation volatility emerge as critical indicators. Installed capacity reflects renewable energy development potential， while generation volatility signals technological maturity—countries with higher maturity exhibit better fluctuation control， ensuring stable supply and risk mitigation. Key policy insights are offered： Chinese investors should adopt granular strategies focused on sector-specific risks rather than relying solely on country risk ratings. Governments should strengthen BRI cooperation， enhance policy frameworks， and optimize financing environments to reduce investment risks. By centering on data volatility， investors with decision-support tools and advances risk assessment precision for China's BRI renewable energy investments are provided. Figures and Tables | References | Related Articles | Metrics

Select

Research on Integrated Demand Response Mechanism of Electricity Market Considering Renewable Energy Subsidies Yeming Dai, Yali Gao, Hui Yin, Xue Feng 2025, 33 (11):  357-368.  doi: 10.16381/j.cnki.issn1003-207x.2022.2441 Abstract ( 6 )   HTML ( 0 )   PDF (2158KB) ( 4 )   Save With the addition of renewable energy to the smart grid， there has been an increasing attention to demand response mechanism based on integrated energy market to guide users to change their electricity consumption behavior actively. Aiming at the integrated energy market with the coupling of traditional energy and a variety of renewable energy， an integrated demand response mechanism which combines price-based demand response with incentive-based demand response is proposed. The mechanism considers the impact of the users' electricity consumption behavior on system decision-making， and subsidizes the retailers to produce renewable energy for promoting renewable energy consumption. Finally， the strategy analysis is carried out by establishing a Stackelberg game model between the retailers and the users. The upper retailers aim to maximize their own profits， and the lower users aim to maximize their own welfares. It is also proved that there is a unique Stackelberg equilibrium in the game， and the equilibrium analytical solution is obtained. Numerical analysis verifies the effectiveness of proposed integrated demand response mechanism， and draws the following conclusions： （1） Under the integrated demand response mechanism， the government subsidies to electricity retailers and users' incentives can effectively adjust the peak-valley difference and flexibility of real-time electricity prices containing renewable energy. At the same time， it can also greatly improve the efficiency of renewable energy and reduce carbon emissions； （2） Integrated demand response mechanism can promote the adoption of renewable energy by users； （3） Increasing the incentive rate for users will increase the real-time electricity price and the optimal renewable energy load of users at equilibrium. Finally， the management enlightenment and relevant policy suggestions for the development of integrated demand response mechanism with renewable energy are given： （1） In the actual operation and management of electricity market， it is necessary to pay attention not only to the impact of load transfer and user incentives， but also to the impact of subsidies to the retailers on the supply of renewable energy in the wholesale market， so as to avoid excessive incentives for user demand transfer resulting in the squeeze of profits of the retailers and the reduction of renewable energy supply， and avoid the imbalance between supply and demand in electricity market； （2） The designers of top-level system in electricity market should pay attention to the influence of electricity users' behavior and psychology on policies， consider behavioral factors such as the users' environmental awareness， dissatisfaction， and fairness preference in policy design， and pay attention to reasonably setting relevant environment parameters to cultivate users' environmental awareness； （3） The electricity market should encourage the cultivation of diversified market players， such as encouraging power retailers to purchase renewable energy production equipment， encouraging users to equip distributed energy systems， promoting orderly competition between energy supply and demand， correcting energy imbalances， and improving grid stability. There is still room for further expansion， and the conclusions obtained mainly reflect the impact of expected value of renewable energy output on the real-time pricing mechanism， and paying attention to the intermittent and fluctuating impact of renewable energy generation will be an important topic for further research. In addition， the models and scenarios proposed in this paper are also applicable to other pricing mechanisms in electricity market， and various pricing mechanisms will be analyzed such as time-of-use pricing and key peak pricing in electricity market with renewable energy considering subsidies for power retailers under the integrated demand response mechanism. Figures and Tables | References | Related Articles | Metrics