中国科学院数学与系统科学研究院期刊网

25 April 2024, Volume 44 Issue 4
    

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  • JIANG Tanfei, SHI Chunlai, XIE Yongping, NIE Jiajia
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(4): 879-895. https://doi.org/10.12341/jssms23248
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    With the rapid development of the platform economy, more and more manufacturers sell the products through their own channels (i.e., the direct channel) besides the retailers (the indirect one), i.e., the dual-channel supply chain. Traditional wisdoms also refer to the dual-channel as the manufacturer encroachment, endowing manufacturers with absolute control over prices. Intuitively, one finds the manufacturer can have more carbon emission, which increases the manufacturer's purchase cost of carbon emissions (i.e., carbon cost) because of the increasing sales with channel competition, especially under the carbon cap-and-trade, namely channel competition effect. On the other hand, the research and development (R&D) cost per the unit product of the carbon reduction can be alleviated due to channel competition, which results in the lower unit carbon mission and wholesale price, namely, spillover effect. Motivated by the observations, we employ a Stackelberg game between a manufacturer (she) and a retailer (he) to explore the manufacturer's channel decisions under carbon cap-and-trade. It shows that the manufacturer always has an incentive to develop the direct channel. Counterintuitively, whether the manufacturer's carbon emissions in the dual-channel supply chain are higher than that in the single channel one depends on the manufacturer's reduction cost in carbon emission. To be specific, when the manufacturer's reduction cost in carbon emission is low, her carbon emission in the dual-channel supply chain is lower than that in the single channel; Otherwise, her carbon emission in the dual-channel supply chain is higher. For the retailer, he can benefit from the manufacturer encroachment. When the carbon price is high and the manufacturer's reduction cost in carbon emission is low, the retailer benefits from the manufacturer encroachment; Otherwise, his profit in the dual-channel supply chain is lower. In addition, we identify the region in which the retailer's profit is higher and the carbon emission is lower in the dual channel supply chain than those in the single one.
  • GE Zehui, LI Xinyu, WANG Daoping, ZHANG Yunhuan
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(4): 896-918. https://doi.org/10.12341/jssms22862
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    Information asymmetry is the main reason that prevents manufacturers from actively participating in carbon market trading and investing in emission reduction technologies. Based on the carbon trading mechanism, this paper studies the choice of manufacturers' emission reduction and retailers' information sharing strategies under the condition that retailers hide consumers' low-carbon preference information. In this paper, Stackelberg model is used to investigate the optimal decisions of each member of the supply chain, in which retailers have private information (consumers' low-carbon preferences) and decide whether to share this information with manufacturers. By using game theory and static comparative analysis, it is found that retailers' sharing of information is beneficial to the supply chain, and under the condition of asymmetric information, manufacturers and retailers can improve their own profits by formulating revenue sharing contracts. When the manufacturer's risk aversion is low, retailers are willing to share information; When consumers have high low-carbon preferences and are insensitive to product prices, the emission reduction rate of manufacturers will increase; For products with high emission reduction costs and low consumer preference for low-carbon emission reduction, increasing carbon quotas will reduce the price of products, thereby reducing manufacturers' incentive to reduce emissions. Therefore, manufacturers can appropriately reduce their risk aversion behavior to attract retailers to share information. In addition, it is beneficial for the supply chain to establish revenue sharing contracts between manufacturers and retailers; In order to strengthen the manufacturer's investment in emission reduction technology, retailers can give priority to the promotion and promotion of low-carbon products to non-price sensitive users.
  • Li Dan, Liu Yongmei
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(4): 919-934. https://doi.org/10.12341/jssms22658
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    Consider a supply chain that composed of a manufacturer and an online platform which owns private demand information. By comparing the equilibrium results under different situations, the impact of private brand introduction and information sharing on the firms' profit and social welfare are discussed, the optimal selling mode selection for the manufacturer and the platform are given before and after the private brand introduction. The results show that the platform chooses to retain demand information in the reselling mode, while he prefers to share information with the manufacturer in the agency mode. Meanwhile, sharing information will improve the manufacturer's profit and social welfare, and the value of information sharing improves with the improvement of the information accuracy. Moreover, after the private brand introduction, a higher proportional fee increases the platform's incentive to protect the manufacturer's products, and the private brand introduction benefits the social welfare when the competition intensity is low. Finally, the selection of selling mode relates to the proportional fee, the information accuracy and competition intensity.
  • GAO Jianwei, HUANG Ningbo, GOU Xunjie, GAO Fangjie, ZHAO Shutong, XIONG Chao
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(4): 935-961. https://doi.org/10.12341/jssms23512
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    To solve the problems of high subjectivity of "self-confidence" and lack of correspondence moderation mechanism in the self-confident double hierarchy linguistic, proposing a new decision-making term based on the self-confidence double hierarchy linguistic and a multi-attribute group decision-making method based on the preference relationship of the duality-confident double hierarchy linguistic preference relation is developed. Firstly, using the social network method to acquire the "trust-relationship" between experts is completed by considering the OWA operator and the shortest link principle, coupling the "trust-relationship" and the self-confidence double hierarchy linguistic to create the duality-confident double hierarchy linguistic, expanding the duality-confident double hierarchy linguistic preference relation, and study its consistency and consensus indicators. Secondly, the feedback adjustment mechanism of the duality-confident double hierarchy linguistic is constructed. Then a new expert empowerment model is constructed for the adjusted "self-confidence" and "credibility" indicators in the duality-confident double hierarchy linguistics. Finally, combined with the feedback moderation mechanism and expert empowerment model, a multi-attribute group decision-making method is proposed based on the duality-confident double hierarchy linguistic preference relationship. Through the analysis of renewable energy investment projects in Hunan Province, the applicability and effectiveness of the method are verified.
  • QIN Yanhong, WANG Ke, LIU Li
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(4): 962-980. https://doi.org/10.12341/jssms22768
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    Under adverse weather affecting output of agricultural products, this paper considers financial budget constraint and altruism preference to set game models in five cases: Non-government subsidy, product subsidy, purchase subsidy, one-time subsidy to company and one-time subsidy to farmer. The study compares the influence of different subsidy methods on the optimal decision-making of agricultural products supply chain and analyzes government's optimal subsidy strategy from three perspectives: Consumer surplus, overall social welfare and subsidy capital efficiency. Research shows that when government implements subsidy to agricultural products supply chain, it can always improve the utility of farmer and overall welfare of society, and government subsidy will enhance the promotion impact of altruism preference on the farmer's effort. Furthermore, when the financial budget is abundant, implementing product subsidy and purchase subsidy always provides leverage; Purchase subsidy is the optimal strategy in terms of improving overall social welfare and consumer surplus, and product subsidy is the optimal strategy in terms of capital subsidy efficiency. When the financial budget is insufficient, one-time subsidy to company can provide leverage. Both from consumer surplus and overall social welfare and from capital subsidy efficiency, one-time subsidy to company is always better than one-time subsidy to farmer.
  • LIU Wei, WANG Yingming
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(4): 981-998. https://doi.org/10.12341/jssms23460
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    With the increasingly complex environment faced by decision-making, individual decision-making is difficult to meet the standards of effective decision-making due to its limitations, making group decision-making more common; when decision-makers take action, they often need to consider the judgments and behaviors of others, making conformity behavior an important influencing factor in group decision-making. Therefore, this paper proposes a new group consensus decision-making method based on fuzzy preference relationships that considers conformity behavior, which can effectively save the cost of reaching consensus. Firstly, in order to provide reliable preference relationships for subsequent consensus building, consistency testing methods and adjustment models are designed according to the characteristics of fuzzy preference relationships. Secondly, considering that when experts are under pressure from group norms, they will exhibit conformity behavior, so we need to modify the initial utility value. Then, a minimum cost consensus model considering conformity behavior is proposed, and corresponding consensus reaching algorithms are further designed. Finally, we calculate the distance from each selected solution to the ideal point, use TOPSIS method to rank the selected solutions, and analyze and demonstrate the effectiveness and feasibility of the proposed method through an example of enterprise product upgrading and improvement.
  • ZHANG Faming, LI Meixing, NIU Yufei
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(4): 999-1013. https://doi.org/10.12341/jssms23006
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    With respect to the problems that there is little research on group evaluation based on subject-object collaboration and most of the existing researches don't consider the predefined social relationship between subject and object, a new group evaluation method based on subject-object collaboration considering the predefined social relationship is proposed. Firstly, according to the "reliability" of object, the objective aggregation information of the predefined social relationship closeness between subject and object is obtained, and it is adjusted based on the predefined social relationship closeness interval provided by the subjective evaluation information. So, the first information adjustment collaboration is completed. Secondly, the predefined social relationship closeness between subject and object is used to measure the "integrity" of subject, and the subjective evaluation information is revised accordingly. So, the second information correction collaboration is completed. Thirdly, through the "vertical" and "horizontal" comparison of the predefined social relationship closeness, the "fairness" of the subjective evaluation information is measured, and the "fairness" is used to aggregate the revised evaluation information of subject. So, the final collaborative evaluation results of subject and object are obtained after the third information aggregation collaboration. Finally, the proposed method is implemented, verified and comparatively analyzed with the example of university teachers' work evaluation, and the results show that the proposed method has good feasibility and effectiveness.
  • WANG Nengfa, YANG Zhe
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(4): 1014-1030. https://doi.org/10.12341/jssms23090
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    We consider a market game generated from a production economy with infinitely many agents and an infinite dimensional commodity space. We shall define the transferable utility core, and prove the existence of the transferable utility core for market games. Our main contributions are to establish the market game with infinitely many players and an infinite dimensional commodity space and prove the existence of the transferable utility core.
  • WANG Meng, OU Haiying, LIU Chongyu, ZHANG Yunbo
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(4): 1031-1047. https://doi.org/10.12341/jssms23087
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    In this paper, dynamic governance strategy of negative online public opinion is studied by using evolutionary game and system dynamics. First, three players involved in the negative online public opinion are presented and analyzed. Second, evolutionary game is used to construct the relationship among the government, rumormongers and netizens. Finally, heat factor of negative online public opinion is proposed in the model and analyzed with system dynamics tools.
  • LING Aifan, LI Longqi, YOU Xin
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(4): 1048-1063. https://doi.org/10.12341/jssms23263
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    Many companies get actively involved in targeted poverty alleviation, which plays an important role in ridding of absolute poverty and winning the battle against poverty alleviation in our country. This paper discusses whether companies participating in targeted poverty alleviation have the higher investment value from the perspective of volatility and tail risk of corporate assets. This paper establishes a single-cycle company investment decision model including poverty alleviation projects, and obtains in theory relationship between participating in poverty alleviation and company asset volatility and tail risk. Then, using the data of A-share listed companies from 2016 to 2020, this paper examines the impact of involvement in targeted poverty alleviation on the company's stock risk. The empirical results show that, being consistent with theoretical expectations, involvement in targeted poverty alleviation can significantly reduce volatility, idiosyncratic volatility and tail risk of the company's stock. And the impact of poverty alleviation on company asset risk is particularly significant in non-state-owned companies, companies with high investor confidence and those with good poverty alleviation effects. The mechanism analysis shows that involvement in targeted poverty alleviation can reduce the risk of company stock through improving the company's operating performance and the quality of company information disclosure. The research of this paper provides strong theoretical and empirical support for companies to actively fulfill their social responsibilities, and believes that companies participating in targeted poverty alleviation have relatively high investment value both from the perspective of risk management and value investment.
  • WU Xu, LUO Fei, PENG Chong, LI Hesen
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(4): 1064-1080. https://doi.org/10.12341/jssms23527
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    Accurately measuring the correlation between assets is a prerequisite for building an effective portfolio model. In view of the reality of the fractal correlation of asset return, this paper firstly constructs the fractal correlation statistical measure by detrendeding cross correlation analysis (DCCA) and other methods to measure the correlation between assets. Then, by incorporating the fractal correlation statistical measure into the return-risk criterion, a portfolio model Mean-PDCCA (fractal portfolio model) under multi-time scale preposition is constructed, and the analytical solution of the model is given. Finally, the empirical analysis finds that under the constraint of typical facts with fractal correlation of asset return, fractal investment portfolio is superior to traditional investment portfolio on the whole, which can not only improve investment performance, but also have better robustness, providing effective decision-making reference for investors.
  • ZHANG Xuejing, HU Huanling, LING Liwen, ZHANG Dabin
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(4): 1081-1096. https://doi.org/10.12341/jssms23195
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    In order to better control the fluctuation range of agricultural price fluctuations and improve the prediction accuracy, this paper proposes a combined interval prediction model based on singular spectrum analysis (SSA), least squares support vector machine (LSSVM) and kernel density estimation (KDE) based on the idea of decomposition and integration, referred to as SSA-LSSVM-KDE model. Firstly, to solve the problem that the window dimension is difficult to be determined in SSA method, Cao method is introduced to optimise the window dimension of SSA minimum embedding, and the multiple components are reconstructed by singular value decomposition; Secondly, LSSVM with strong learning ability is selected, and the components are used as inputs to the LSSVM to obtain the combined prediction outputs; and finally, KDE model is optimised by using least squares cross validation based on B-spline bases (B-spline-LSCV) optimised KDE model to estimate the error probability distribution function for different intervals of the combined prediction output, and obtain the final prediction intervals at a given confidence level. In order to verify the effectiveness of the proposed model, interval forecast of wheat spot price and corn spot price are made, and compared with four single models, three combined models and four distribution functions with various forecasting performance evaluation criteria. The results show that the accuracy of the proposed model in both point and interval forecasts has been significantly improved.
  • Lü Yibing, PENG Yan
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(4): 1097-1107. https://doi.org/10.12341/jssms23464
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    In this paper, we mainly focus on the method for solving a class of trilevel programming problem, where the objective functions of the upper, middle, and lower levels are nonlinear, linear, and linear, respectively. Firstly, based on the Karush-Kuhn-Tucker (K-K-T) optimality condition of the lower level problem, the original problem is transformed into a nonlinear bilevel programming problem with complementary constraints. Subsequently, the complementary constraints of the lower level problem are added to the upper level objective as penalties. Then, we use the K-K-T optimality condition of the inside problem to transform the nonlinear bilevel programming problem into a nonlinear single-level programming problem, and the obtained complementary constraints are again used as the penalty term for the upper level objective. Therefore, a penalized problem for the nonlinear trilevel programming problem is constructed. Through the analysis of the characteristics of the penalized problem, the necessary conditions for the optimal solution of the nonlinear trilevel programming problem are obtained, and the penalty function algorithm is designed. The numerical results show that the proposed penalty function algorithm is feasible and effective.
  • DU Liping, SUN Zhimeng
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(4): 1108-1129. https://doi.org/10.12341/jssms22807
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    In this paper, we adopt the spatial error model to describe the network structure relationship between individuals, and propose both estimation and imputation methods of the varying-coefficient partially linear spatial error model with missing responses. We firstly construct the estimator of the model parameter through profile maximum likelihood method and a matrix blocking technique. We prove the asymptotic normality of the parametric estimators and show the convergence rate of the nonparametric estimator. We then propose imputation estimators of missing response based on this model. Finally, we conduct Monte-Carlo simulation studies to detect the infinite sample performance of the estimator and analyze the QQ data set using the proposed method.
  • XIONG Pingping, WU Yurui, TAN Chengwei, TONG Weijie, YANG Kaiyin
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(4): 1130-1146. https://doi.org/10.12341/jssms22406
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    The MGM(1,m,N) model has three problems: Non-homologous parameters, simple model structure, and multicollinearity between variables. In order to solve this defects of MGM(1,m,N) model, the new structure MGM(1,m,N) is built, which modifies the model structure by introducing the linear correction term and the grey action term into the original model. In order to solve the defects in the parameter application, using the derivative first-order difference formula and recursive method to solve the time response function of NSMGM(1,m,N) model. To address the adverse effects of multicollinearity, the parameter estimation method is improved from reducing the variance of parameter estimators. The L2 regularization term is introduced into the ordinary least square estimation and the optimal L2 regular term parameter is solved by the particle swarm algorithm. Finally, the novel model is applied to the forecast of China's three major staple grain yields. The results show that the novel model solves the problems in the parameter application and model structure of MGM(1,m,N) model in certain degree. The optimized model can effectively alleviate the influence of model's predictive performance by multicollinearity and improves the MGM(1,m,N) the model's predictive precision.
  • XIAO Yujia, XIONG Fengjing, LI Hongyi
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(4): 1147-1158. https://doi.org/10.12341/jssms23258
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    The Hyper-Graeco-Latin square design can control experimental errors from multiple different directions, and is widely used in many fields such as medicine and agricultural production. Therefore, it is of great significance to perform analysis of variance on the Hyper-Graeco-Latin square design. In this paper, the analysis of variance for the Hyper-Graeco-Latin square design is presented, and the analysis of variance for the Hyper-Graeco-Latin square design is discussed under three different repetition modes. Finally, some examples are provided for supporting the theoretical results.
  • SHANG Changchun, MA Xuan, JIANG Fen, ZHAO Jianhua
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(4): 1159-1188. https://doi.org/10.12341/jssms23125
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    Factor analysis (FA) is a popular statistical technique that is used to identify the latent common factors among a set of variables. Nevertheless, it is only applicable to vector-valued data, where observations are vectors. To apply FA to matrix-valued data, where observations are matrices, one common solution is to first vectorize the matrix observations. However, the vectorization may cause FA to suffer from two problems: Poor interpretability and curse of dimensionality. To solve the two problems, the authors utilize the inherent matrix data structure and propose bilinear factor analysis (BFA) in this paper. The novelties are that BFA uses a bilinear transformation, which greatly reduces the model parameters and thus can overcome the curse of dimensionality; Moreover, it can simultaneously identify the interesting common row, column factors among the row, column variables, respectively. The authors develop two efficient algorithms for finding the maximum likelihood (ML) estimates. The authors give the theoretical property of the ML estimator and derive explicitly the closed-form expression of Fisher information matrix to evaluate the estimator's accuracy. The authors then discuss the model selection issue. Unlike the traditional FA, where the factor score is a vector, the factor score in BFA is a matrix. The authors further develop the approaches for calculating the matrix factor scores and visualizing them. Empirical studies are constructed to understand the proposed BFA model and compare with relevant methods. The results reveal the superiority and practicability of BFA in matrix-valued data analysis.
  • liang Qing
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(4): 1189-1206. https://doi.org/10.12341/jssms23214
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    In this paper, the stability of the solutions for a class of neutral stochastic functional differential equations with Markovian switching and Lévy noise is investigated. First, an auxiliary functional differential equation is constructed. Then, under some suitable assumptions two sufficient conditions for the pth moment of the solutions for the neutral stochastic functional differential equations to be stable with general decay rate are obtained by means of the formula for the variation of parameters of the auxiliary functional differential equation, some inequality technique and comparison principle. The obtained results generalize the results in some earlier publications. Finally, two examples and numerical simulations are given to illustrate the effectiveness of the results.