中国科学院数学与系统科学研究院期刊网

25 March 2024, Volume 44 Issue 3
    

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  • MENG Xiangxu, YU Changlin
    Systems Engineering - Theory & Practice. 2024, 44(3): 773-793. https://doi.org/10.12011/SETP2023-0414
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    Human capital is the core driving force for technological innovation. The transnational flow of human capital determines the spatial distribution and international diffusion of technological innovation. This paper investigates the impact of human capital outflow and internet penetration on domestic technological innovation in developing countries. Empirical tests using panel data of 62 developing countries from 2000 to 2017 confirm that transnational outflow of human capital is harmful to domestic technological innovation in developing countries. The increase of internet penetration in developing countries can alleviate the adverse impact of transnational outflow of human capital on domestic technological innovation, and may even make transnational outflow of human capital have a net positive effect on domestic technological innovation. Reverse technology spillover is an important mechanism. When the outflow of labor with stronger innovation capabilities, the negative impact of emigration on the technological innovation in developing countries is greater. When the inflow country is a developed country, the positive regulatory effect of the internet on the technological innovation effect of human capital outflow is greater, but technological innovation in high-tech fields cannot be obtained through reverse technology spillover. The research findings of this paper have important implications for the formulation of talent policies and technological innovation policies in developing countries.
  • LIU Erzhuo, LIU Fangge
    Systems Engineering - Theory & Practice. 2024, 44(3): 794-812. https://doi.org/10.12011/SETP2022-3238
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    This paper examines the impact and potential mechanisms of exchange rate exposure on corporate bond risk premiums using all listed company bonds issued in China from 2006 to 2019. The research findings indicate that higher exchange rate exposure of a company increases its bond risk premiums and expected default probability. Specifically, for one standard deviation increase in a company’s exchange rate exposure, its bond risk premium increases by 5 basis points. Higher quality of information disclosure is expected to attenuate the positive correlation between exchange rate exposure and corporate bond risk premiums. More empirical evidence shows that exchange rate exposure increases the value loss that a company incurs in debt default events. A company’s exchange rate exposure intensifies the conflict of interests between shareholders and bondholders, leading to more ineffcient investments. In companies with stricter financing constraints, exchange rate exposure significantly increases the risk premium of their bonds. By leveraging the “811 Exchange Rate Reform”, we identify the causal relationship between exchange rate exposure and corporate bond risk premiums. This study provides new evidence on the impact of exchange rate exposure on corporate bond financing behavior and explains the inherent logic of how exchange rate exposure affects bond risk premiums from the perspective of uncertainty and information asymmetry.
  • XI Yuqin, ZHANG Kaige, HU Jinyue, JIN Chenxi, JIN Yonghong, YANG Xiaoguang
    Systems Engineering - Theory & Practice. 2024, 44(3): 813-835. https://doi.org/10.12011/SETP2022-1837
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    In order to avoid the risk of being closed out, controlling shareholders should have an incentive to reduce the risk of share price volatility after pledging their equity, which has been explored in the existing literature but the conclusions are inconsistent and the specific mechanisms are unclear. This paper theoretically analyses the negative relationship between corporate controlling shareholder equity pledges and corporate share price volatility and its specific mechanisms and paths, and selects A-share listed companies’ data from 2007 to 2021 for empirical testing. It is found that: The share price volatility of a company does decrease significantly after controlling shareholders’ equity pledge; in order to maintain short-term share price stability, listed companies increase the short-term remuneration of company executives after controlling shareholders’ equity pledge, both in terms of absolute quantity and relative weighting; and executive incentives play a partially mediating role between controlling shareholders’ equity pledge and corporate share price volatility. Further research shows that the smoothing effect of controlling shareholders in making equity pledges on share price volatility is not achieved by increasing the firm’s performance capabilities and surplus management levels, reducing information asymmetries and tunneling by large shareholders. The heterogeneous results also fully illustrate that non-state-controlled listed firms are more sensitive to equity pledges by controlling shareholders. This paper explores the role of controlling shareholders’ equity pledges on share price volatility and its mechanism, which theoretically complements the literature on share price volatility and provides corresponding suggestions for external investors, financial institutions and government departments, offering new ideas to enhance the effciency of corporate governance of listed companies.
  • HE Linjie, XIE Zhihua, DENG Fang, CHANG Lu
    Systems Engineering - Theory & Practice. 2024, 44(3): 836-852. https://doi.org/10.12011/SETP2022-1128
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    The increasingly complex network of cross-holding among listed companies makes it easier for enterprises to acquire information and resources in terms of risk sharing. Nonetheless, the transmission mechanism as to how this network exerts an effect in crash risk of stock price is not obvious. In this paper, we investigate how the ownership network structure influences corporate stock crash price risks by using the Chinese stock market data from 2007 to 2021. It is unraveled that being in the center of the network brings about synergistic governance advantage. Corporations in the core can partially offset the asymmetric information between board and manager through advantages in information, resources, and reputation. They are capable of dealing with negative information withheld by the managers so as to alleviate the crash risk of stock price. This result holds under a series of robustness check. We further show that property ownership and regional development heterogeneity do not affect the fact that equity network structure reduces the risk of stock crash, yet this reduction effect is more pronounced in nonstate-owned enterprises and firms in less developed areas. This paper corroborates that the complicated network of cross shareholding in modern enterprises helps improve the internal corporate governance, extends and deepens the research in the factors that lead to equity price risks.
  • WU Xiting, YOU Jiaxing, YU Mingyang
    Systems Engineering - Theory & Practice. 2024, 44(3): 853-873. https://doi.org/10.12011/SETP2022-2987
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    In this paper, through the manual reading of each city’s government work report to construct the government’s actions according with words, and takes the A-listed companies in China from 2003 to 2018 as the sample to examine the impact of the degree of government’s actions according with words on the stock price crash risk. This study finds that the degree of government’s actions according with words is higher, the corporate stock price crash risk is lower. The above conclusion remains stable after a series of robustness tests. Moreover, the mechanism test finds that, on the one hand, at the regional level, the degree of government’s actions according with words is higher, the regional group norms are stronger and the level of rule of law is higher; on the other hand, this paper also finds that the degree of government’s actions according with words is higher, the level of the corporate earnings management and the abnormal tone of the MD&A reports are lower. In addition, the heterogeneity analysis shows that when a company doesn’t have political networks, the negative relationship between the degree of government’s actions according with words and corporate stock price crash risk is stronger. This paper has certain enlightenment significance for how the government can promote the modernization of governance capabilities and complete the goal of high-quality development.
  • WANG Yutao, WANG Song, DUAN Mengran
    Systems Engineering - Theory & Practice. 2024, 44(3): 874-892. https://doi.org/10.12011/SETP2023-0011
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    Green and low-carbon economic and social development is a key factor to achieve high-quality development. Although there is a plenty of relevant policies support till now, the green investment willingness of individual enterprises is not enough, which causes a contradiction between the demand for high-quality economic development and the insuffcient green investment willingness of enterprises. This paper tries to explore the solution from the view of “peer effect” of corporate green investment and hence could provide a new incentive to lead enterprises more resources to green investment. This study uses the data of A-share listed companies in Shanghai and Shenzhen to explore the existence, mechanism and economic consequences of industrial peer effect of green investment behavior of listed companies in China. The results show that there is a significant peer effect on corporate green investment. There are learning mechanism and pressure mechanism in the peer effect of enterprises’ green investment. The peer effect of corporate green investment is more pronounced when followers in the same industry are more willing to learn from leaders and when the enterprises facing higher external pressure. The additional analysis show that the peer effect of corporate green investment reduces the operating cost and hence increases firms’ valuation. The study not only helps to clarify the potential real motivation of corporate green investment, but also provides strong empirical evidences for the formulation of the relative policy and regulation.
  • SHI Ruoshi, HE Yinjie, ZHAO Yanlong, BAO Ying
    Systems Engineering - Theory & Practice. 2024, 44(3): 893-911. https://doi.org/10.12011/SETP2023-0678
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    In recent years, stress testing has played an increasingly important role in modern bank risk management, because of its properties to measure financial risk in extreme environments. Accurately measuring the driving effect of systematic factors on portfolio risk is the key to effectively controlling tail risk and preventing financial crises. This paper studies the problem of parameter estimation and stress testing of portfolio credit risk, and establishes a Vasicek credit transfer model including systemic factors and multi-level correlation coeffcients. After analyzed the influence of correlation on the credit transfer probability between ratings, the correlation coeffcient conditions of rating monotonically consistent is given to ensure the monotonic consistency of the credit rating transfer probability. In this paper, a parameter estimation method based on the degradation probability distribution is constructed. Using the transition probability matrix, the rating lifetime distribution under the market equilibrium state is derived, and then the estimation algorithm of the correlation coeffcient and the systemic factor is given. Compared with the existing algorithms, the proposed method weakens the influence of the fixed bias of the systematic factor, overcomes the dependence of the distribution of the systematic factor, so that improves the accuracy of the estimation while reducing the computational cost. Simulation results show that the proposed method not only effectively improves the calculation speed, but also significantly outperforms the existing methods in estimating the systematic factor, correlation coeffcient and portfolio loss. Besides, the extreme loss estimated by this method can fully cover the out-of-sample portfolio loss, it follows that the financial risks can be better predicted and prevented in stress testing, and the financial market stability can be maintained.
  • SHEN Long, ZHOU Ying
    Systems Engineering - Theory & Practice. 2024, 44(3): 912-931. https://doi.org/10.12011/SETP2022-3095
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    To enhance the identification and management of credit risk for commercial bank corporate customers, we present a systematic approach for predicting default. Firstly, in constructing high-dimensional big data variable sets, we determine the optimal cutoff point for dividing the indicator interval by minimizing the Gini index. This ensures that each path of the decision tree maximizes the distinction between customer default and non-default. We treat each path as a dummy variable, where the value of the variable is 1 if the customer belongs to this path, otherwise, it is 0. Secondly, to reduce the dimensionality of dummy variables, we utilize Lasso regression to minimize prediction error and infer the optimal set of variables. Thirdly, we calculate the optimal default prediction threshold of the logistic regression model with the highest sum of customer judgment ratio, which improves the accuracy of default firm prediction. Our results show that decision tree path variables have stronger default discriminatory power than raw credit indicators and contain richer information. Additionally, the indicators of net profit cash content, per capita disposable income of urban residents, and legal dispute situation of enterprises have a significant impact on the default prediction of Chinese small enterprises. Although these three indicators represent only 3.704% of the total number of indicators, their contribution to accuracy is 41.639%. Our proposed methodology outperforms the comparison model in terms of accuracy and robustness. It can unveil the key factors and thresholds that affect the credit risk of enterprises, thus providing a basis for commercial banks’ credit approval and pre-loan review work. The methodology’s effectiveness has been proven across multiple credit datasets, and it can be extended to constructing default prediction models for individuals as well as large and medium-sized enterprises.
  • CHEN Feng'e, JI Kunpeng, PENG Xingchun
    Systems Engineering - Theory & Practice. 2024, 44(3): 932-946. https://doi.org/10.12011/SETP2023-0267
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    This paper studies the optimal investment and reinsurance strategy for an lossaversed insurer under partial information. First, the filtering technique is used to transform the problem. Then, under the expected S-shaped utility maximization criterion, the semi-analytical expression of optimal investment and reinsurance strategy is derived by using martingale method, partial differential equation, Fourier transform and inverse transform method. Finally, the Monte Carlo method is used in the numerical analysis. The results show that the optimal ratios of investment and reinsurance under ignoring learning are lower than that under filtering estimation. When the reference point level is higher, compared with the ratios of optimal reinsurance and investment in inflation index bond, ignoring learning has a greater effect on the optimal ratio of investment in stock. On the other hand, the optimal strategy under the power utility is more aggressive than the optimal strategy under the S-shaped utility, and the optimal reinsurance ratio has the largest difference under the two types of utility functions, which shows that psychological factors have the most significant impact on the reinsurance strategies.
  • JIANG Zhongzhong, HOU Xingze, LI Kunyang
    Systems Engineering - Theory & Practice. 2024, 44(3): 947-968. https://doi.org/10.12011/SETP2023-0162
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    Recent years have witnessed the rapid development of new energy vehicle (NEV) industry. Process innovation and mode innovation are the two main directions for the innovative development of NEV companies at the present stage. Therefore, choosing an innovation strategy has become a key issue for NEV companies that traditionally adopt the charging mode. We construct an optimization model under process innovation and mode innovation for a NEV company that traditionally adopt the charging mode. We propose applicable conditions of two innovation strategies and the optimal pricing strategy of the NEV company under different innovation strategies. We also extend the model to include government subsidy. Our findings indicate that the optimal innovation strategy of the NEV company is determined by mode innovation cost in the case without government subsidy. However, in the case with government subsidy, the optimal innovation strategy of the NEV company is jointly determined by production cost, market structure and mode innovation cost. Furthermore, there exists an interactive effect between innovation strategy and government subsidy on the pricing of the NEV company. Meanwhile, we reveal the impact of government subsidy on the decision of the NEV company, and analyze the social welfare under different innovation strategies. We also provide useful managerial implications for both NEV companies and the overall industry.
  • CHEN Jianjian, FENG Nan, FENG Haiyang, ZHANG Hanyue
    Systems Engineering - Theory & Practice. 2024, 44(3): 969-985. https://doi.org/10.12011/SETP2022-3231
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    In recent years, self-operated sellers and third-party sellers often independently or jointly promote their products to increase their sales on e-commerce platforms. Unlike independent promotions, joint promotions represented by “cross-store full reduction” are generally initiated by the platform, but the joint promotional cost set by the platform company is shared by the platform and the third-party seller. Considering the characteristics of different promotion modes in the two-sided market, the impact of the commission rate, the market expansion effect caused by the promotions, etc. on product pricing decisions, the optimal sharing ratio of the joint promotional cost, and promotion mode selection are explored by a three-stage game model. The results show that: 1) If and only if the commission rate and the sharing ratio of the joint promotional cost are both relatively high or low, the product original prices and promotional efforts in the joint promotion case are both higher than those corresponding to independent promotion. And when the market expansion effect is relatively strong, consumers should not purchase products during the promotional activity. 2) Whether in a monopoly or competitive situation, If and only if third-party sellers have a higher cost and a weak market expansion effect of conducting promotional activities, and the sharing ratio of the joint promotional cost is moderate, the implementation of joint promotional strategy by the platform enterprise and the third-party seller will be superior to independent promotional strategy and non-promotional strategy. 3) When the commission rate is suffciently high, third-party sellers will pay for the joint promotional cost separately in joint promotional activities; otherwise, the joint promotional cost will be jointly borne by the platform and third-party sellers, and when the commission rate is low, the sharing ratio of the joint promotional cost paid by the platform decreases with the market expansion effect increasing.
  • LIN Qiang, ZHAO Zhenzheng, HUO Baofeng, LIN Xiaogang, LI Wenzhuo
    Systems Engineering - Theory & Practice. 2024, 44(3): 986-1002. https://doi.org/10.12011/SETP2023-0827
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    In order to deal with the severe challenge of climate change, carbon emission reduction has become a global goal and consensus. However, manufacturing companies often face the diffculties of funding shortages or lack of technology when reducing carbon emissions and cooperation among supply chain members is an effective way to solve this problem. Based on this, under the carbon trading market and carbon quota restrictions, this paper builds a low-carbon supply chain cooperative emission reduction decision model consisting of a funding-constrained manufacturer and a retailer. The paper discusses how retailers can choose appropriate emission reduction strategies according to their own profits and carbon emission reduction. The results show that: 1) Financing cooperative reduction strategy carries manufacturer bankruptcy risk due to market uncertainty, while technology cooperative reduction strategy does not. Retailer’s optimal profit decreases as carbon reduction cost increases with technology cooperative reduction. 2) When retailers choose emission reduction strategies based on profits, if there is no bankruptcy risk for the manufacturer, the premise for retailers to choose technological emission reduction strategies is that the demand uncertainty is small and the carbon reduction cost difference is large. If there is a risk of bankruptcy for the manufacturer, the premise for retailers to choose technological emission reduction strategies is that the carbon reduction cost difference is large and the initial carbon quota is small. 3) When retailers choose emission reduction strategies based on carbon emissions, the cooperative reduction strategy selection depends on the initial carbon emissions per unit and the carbon reduction cost difference. In addition, the expanded research find that the manufacturer’s production cost does not affect the above conclusions.
  • FANG Debin, XIE Qianjiao
    Systems Engineering - Theory & Practice. 2024, 44(3): 1003-1017. https://doi.org/10.12011/SETP2023-0688
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    The carbon market is an important policy tool for the thermal power industry to achieve carbon emission reduction targets. It is an urgent issue to explore whether carbon market can affect carbon emission reduction in thermal power industry. This study constructs a Stackelberg game model for power generation enterprises to participate the trading in the electricity and carbon markets. And it reveals the theoretical mechanism of the “inverted U” effect of carbon price on carbon emission reduction in thermal power industry. Based on this, considering the effect of carbon price, this study employs differences-in-differences to test the carbon reduction effect of carbon market on thermal power industry by using inter-provincial panel data from 2005–2019. The results show that the carbon market promotes carbon emission reduction in the thermal power industry, but its impact has a lag effect. Moreover, it is robust to the “inverted U” type relationship between carbon price and carbon emission reduction in thermal power industry. This study can offer empirical support for carbon price driving carbon emission reduction in the thermal power industry and provide an important reference for the improvement of the carbon market institutional system.
  • CHU Tao, ZHONG Yongguang, SUN Hao, JIA Weiqiang
    Systems Engineering - Theory & Practice. 2024, 44(3): 1018-1033. https://doi.org/10.12011/SETP2023-0652
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    The low-carbon transformation of the household appliance industry is an important way to help realize “carbon neutrality” and high-quality development, while the implementation of the “dual-carbon” goal for the household appliance industry is a systematic project that involves changes in production and lifestyles. At present, low-carbon transformation policies mainly focus on the supply side of production and the design of environmental responsibility norms for producers. However, there is insuffcient attention to carbon emission reduction on the demand side of consumption with a lack of carbon responsibility regulation measures directly targeting consumers. To address this research gap, this paper examines the supply and demand synergistic carbon neutral program for the household appliance industry based on the consideration of consumers’ carbon responsibility, and proposes to establish a green consumption incentive mechanism with electricity price regulation, environmental protection credit system, and deposit system as the main content, to guide the green transformation of the supply side from the demand side. Then, an evolutionary game model between consumers, governments and producers is established to explore the mechanism of the three-party synergy in promoting the green transformation of the household appliance industry, and the main influencing factors at different stages of evolution are explored by using the system dynamics theory. This study finds that there are three evolutionary stability points in the gaming system, corresponding to the three stages of carbon neutrality in the household appliance industry. Among them, the government plays a leading role in the beginning and developing stages of the low-carbon transformation of the industry, while the mature stage of value co-creation driven by the market mechanism is the ideal state, and the development of the recycling economy is the necessary path for industrial carbon neutrality. Besides, the decision-making behavior of producers is influenced by the strategic choices of consumers, reflecting the fact that the low-carbon transition in consumer behavior forces green innovation and clean production on the production side. In addition, incentive policies such as personal carbon credits and electricity price regulation can effectively promote the transformation and upgrading of consumption behavior patterns, while environmental deposits will inhibit green consumption willingness to a certain extent. Based on the results from game analysis and system simulation, this study puts forward countermeasures and suggestions for green transformation of the industry, and expounds on the development path of carbon neutrality of the household appliance industry according to the system evolution law.
  • LI Jiaming, LI Yibo, LIU Yulin
    Systems Engineering - Theory & Practice. 2024, 44(3): 1034-1052. https://doi.org/10.12011/SETP2022-2953
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    From the perspective of VAT input tax credit, the article considers how enterprises optimize their assets allocation under the effects of the tax burden and tax dividend sharing (or tax burden transfer) caused by the VAT rate deduction. Tax dividend sharing (or tax passthrough) can affect the following prices: (i) VAT exclusive sales price and purchase price, (ii) VAT exclusive sales price and VAT inclusive purchase price, (iii) VAT inclusive sales price and VAT exclusive purchase price, (iv) VAT inclusive sales price and purchase price. The results find that: 1) When the output tax rate decreases: If returns to scale are diminishing, enterprises will increase investment in capital and labor and reduce investment in financial assets. 2) When the input tax rate reduces: In case (i), if returns to scale are decreasing, enterprises will reduce investment in capital and labor. However, in other cases, if returns to scale are decreasing, enterprises will reduce investment in capital and labor and increase investment in financial assets. 3) When the VAT output and input tax rate reduce simultaneously: In case (i) or (iii), if returns to scale are increasing and the expected return rate of financial assets is higher than the additional tax rate, the enterprise will reduce investment in capital and labor and increase investment in financial assets. But if returns to scale are decreasing and the expected return rate of financial assets is higher than the additional tax rate, the enterprise will increase investment in capital and labor. The paper simulates the various relationships between the VAT rates and enterprises assets under the mentioned prices to verify our conclusions using relevant industries’ data. The article also uses the data of China’s A-share listed companies from 2016 to 2021, finding that the empirical results also confirmed the conclusion. Under the current national conditions of diminishing returns to scale in our country, the research results also explain the rational necessity of the VAT rate reduction from the microscopic behavior of enterprises.
  • WANG Yuyan, GAO Junhong
    Systems Engineering - Theory & Practice. 2024, 44(3): 1053-1067. https://doi.org/10.12011/SETP2023-1468
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    Consider a closed-loop supply chain (CLSC) composed of a single manufacturer and a single retailer. Construct centralized and decentralized decision models for the government’s dynamic subsidy on blockchain technology and conduct an analysis and comparison. Based on this, design coordination mechanisms to maximize the effectiveness of government dynamic subsidies, ensuring the operation of the CLSC. The research indicates the following: 1) Consumer preference for traceability promotes the adoption of blockchain technology in CLSCs. 2) Government dynamic subsidies reduce wholesale prices, positively impacting the promotion of product recycling and the enhancement of blockchain traceability levels, increasing the profits of the CLSC system and its members. When consumer preference for traceability falls below a specific threshold, government dynamic subsidies lead to a reduction in product retail prices. 3) Under centralized decision-making, the CLSC system achieves higher profits. Cost-sharing contracts for recycling efforts under decentralized decision-making result in win-win outcomes for manufacturers and retailers. Through asymmetric Nash equilibrium negotiations, the distribution of dynamic surplus gains after contract coordination can be realized. This study provides a theoretical basis for the formulation of support strategies by government departments and offers important managerial insights for CLSC enterprises when implementing blockchain technology. These insights contribute to enhancing supply chain effciency and sustainability.
  • WANG Junjin, ZHANG Baiyu, LIU Jiaguo
    Systems Engineering - Theory & Practice. 2024, 44(3): 1068-1082. https://doi.org/10.12011/SETP2022-3111
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    In view of the fact that high-quality national brands are more likely to experience stock-outs than low-quality retailer’s private labels, this paper constructs a two-stage game model of “procurement + selling”. The three-dimensional differences in product quality, procurement cost, and supply stability are considered. The pricing and procurement strategies for a combination of national brand and private label are explored. The findings show that when national brand is unable to deliver their products, compared with the case where both products are delivered, the retailer typically reduces the selling price of private label and purchase more quantities of private label and fewer quantities of national brand, thereby mitigating the negative impact of supply disruption risk if products’ quality varies significantly. As supply uncertainty rises and the retailer order more private label product, in this case, the inventory of private label may occurs. Interestingly, when the quality differentiation in the product is small, the retailer will develop a sale strategy around the national brand. Instead, the threat of supply disruptions will lead to a rise in national brand product orders, which will encourage customers to purchase more national brand products by driving up the price of private label.
  • ZHU Zhi, YANG Song, WANG Tao, WANG Weiping, ZHAO Yuehua
    Systems Engineering - Theory & Practice. 2024, 44(3): 1083-1096. https://doi.org/10.12011/SETP2022-3208
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    Simulation modeling, a classical model driven physics-based method, has always gained high priority in acquisition, design, and evaluation of various combat systems. In recent years, inspired by big data and artificial intelligence, more and more simulation modelers have paid attention to the combined use of data-driven data modeling methods. In this context, this research investigated the combat system modeling literature from model-driven, data-driven, and hybrid driven perspective, respectively. Thereafter, we proposed a model and data hybrid driven intelligent modeling approach in consideration of limitations of using simulation modeling or data modeling alone. Firstly, we designed a model and data two-wheel driven architecture. Secondly, we applied a novel behavioral modeling method, namely, the function decision tree (FDT), to represent combat behaviors properly. Thirdly, for decision points in a behavioral model, we used the deep reinforcement learning to train smart agents. As a proof of concept, we built a multi-targets assignment scenario of ballistic missile penetration, and the results revealed that the smart agent-embedded ballistic missile significantly increased the ratio of target hits when compared with the traditional rule-based behavioral model.
  • XU Jin, ZHAO Huiqi, ZHANG Zehui, LIU Dun
    Systems Engineering - Theory & Practice. 2024, 44(3): 1097-1113. https://doi.org/10.12011/SETP2023-0971
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    Engineering equipment intelligence is an important basis for the development of intelligent construction, and project knowledge is the knowledge source of engineering equipment intelligence. Therefore, the effective sharing and utilization of engineering equipment knowledge across projects is an important link to realize intelligent construction. In order to enhance the effciency and effectiveness of cross-project utilization of engineering equipment knowledge, this paper proposes a multi-source domain transfer learning framework based on feature difference enhancement. The framework uses a hybrid deep neural network to extract the common spatiotemporal feature representation of source items, screens transferable source items based on the project similarity measurement, and mines the domain special feature representation of multiple source domains through the designed feature difference enhancement method and integrates it, so as to avoid negative transfer and realize effective cross-project transfer of engineering equipment knowledge. In this paper, the data of several tunnel engineering projects are used to carry out experiments. In the two prediction objectives of six shield equipment attitude prediction knowledge transfer tasks, the average accuracy improvement of the framework compared with the baseline model is 86.48% and 117.01%, respectively, and it has good robustness and situational adaptability. Experiments show that the new framework designed in this paper can mine the characteristic knowledge of multiple source domain projects and integrate their common knowledge, improve the knowledge utilization rate by integrating the knowledge of multi-source domain transfer learning, provide an effective method and tool for the cross-project transfer of large-scale engineering equipment knowledge, and help improve the level of knowledge management and intelligent construction of construction projects.
  • HE Xiang, LI Li, ZHU Xingzhen, ZHANG Hua, YANG Wensheng
    Systems Engineering - Theory & Practice. 2024, 44(3): 1114-1128. https://doi.org/10.12011/SETP2022-1133
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    In recent years, customers’ webrooming behavior (i.e., gather information online and purchase offline) has become a common practice. With a focus on the effect of webrooming, we establish an analytical model in which online retailer and BM store sell the search-products and experience-products. By analyzing the equilibrium result, we firstly show that to searchproducts, whether customers engage webrooming is determined by the privacy cost, only when the privacy cost is in a high level, customers will engage webrooming; to experience-products, whether customers engage webrooming also concerned with the match probability between customer and BM store. Second, it is verified that the presence of webrooming strictly hurt online retailer’s profit whatever the seller sells search-products and experience-products. In addition, the price of search-products will become higher with the higher unit travel costs, lower online search costs, and lower privacy costs; the price of experience-products will decline with the increasing match probability between customer and BM store. To counter the behavior of webrooming, we find that targeted advertising will relax the competition and reduces the impact of webrooming behavior on online retailer. Counterintuitive, BM store also prefers targeted advertising to some extent since when online retailer invests more on targeted advertising. Finally, we compare the performance of targeted advertising to search-products and experience-products when online retailer counter with webrooming, and find that when the privacy cost is in a low level, targeted advertising performs better in experience-products; on the contrary, when the privacy cost is in a high level, targeted advertising performs better in search-products.