Table of Content

    20 March 2022, Volume 30 Issue 3 Previous Issue    Next Issue
    Corporate Social Responsibility, Mediacoverage and Stock Pricecrash Risk
    HUANG Jin-bo, CHEN Ling-xi, DING Jie
    2022, 30 (3):  1-12.  doi: 10.16381/j.cnki.issn1003-207x.2020.2183
    Abstract ( 718 )   PDF (1182KB) ( 889 )   Save
    In theory, the disclosure of corporate social responsibility may mitigate or increase the stock price crash risk. As an important carrier of social responsibility disclosure, news media may weaken or strengthen the effect. These problems above become hot issues in the field of corporate finance in recent years. The bidirectional mechanism of social responsibility disclosure on stock price crash risk is first derived in theory, and then news media is introduced to study its possible transmission path. Based on the panel data of all companies in Chinese A-share market from 2010 to 2018, the research show that companies can reduce the risk of stock price crash by disclosing corporate social responsibility index. CSR fulfillment will increase the number of media reports, and the increasing number of media reports will decrease the risk of stock price crash. In other words, media reports play an internal role in the process of CSR affecting the risk of stock price crash. Further research shows that shareholders’ responsibility in the CSR index has the greatest influence on the risk of stock price crash, while the influence of suppliers’, customers’ and consumers’ rights and interests and social responsibility is not significant. The mediating effect of positive media reports and negative media reports is stronger than neutral media reports.
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    Customer Perspectives and Online Customisation Strategies: A Simulation Model of Online Community-Based Dynamic Customisation in Small and Medium-Sized Enterprises
    LIN Li, WANG Yu, WU Jia-cong
    2022, 30 (3):  13-29.  doi: 10.16381/j.cnki.issn1003-207x.2020.0796
    Abstract ( 394 )   PDF (7910KB) ( 345 )   Save
    With the growth of customers’ personalised needs and the improvement of supply chain technology, more and more enterprises are offering customised products to enhance their competitiveness in the market. Although several enterprises have already successfully implemented online customisation toolkits to achieve mass customisation, some enterprises have abandoned similar initiatives due to project failures. Most small and medium-sized enterprises (SMEs) face the challenges that include insufficient customers using customisation services, low sales conversion rates, and low enterprise profits, due to the limitations of customized production capacity and the characteristics of personalised needs.
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    Study on Environmental Policy Selection for Green Technology Innovation Based on Evolutionary Game: Government Behavior vs. Public Participation
    XU Le, MA Yong-gang, WANG Xiao-fei
    2022, 30 (3):  30-42.  doi: 10.16381/j.cnki.issn1003-207x.2020.1786
    Abstract ( 498 )   PDF (2608KB) ( 794 )   Save
    To relieve the pressure of energy conservation and emission reduction, how to drive green technology innovation through effective environmental policies is an important practical issue that needs to be solved urgently, in the context of China’s “double carbon” goal. Based on multi-agent relationship analysis, evolutionary game theory, and scenario simulation method, the two-party evolutionary game model of government and enterprise, the two-party evolutionary game model of public and enterprise, and the three-party evolutionary game model of government, public, and enterprise are constructed. Besides, policy simulation under different scenario modes and execution strengths are conducted to comprehensively explore the behavioral strategy selection and system evolution trajectory of the government, public, and enterprises in green technology innovation. The results show that: (1) In the two-party evolutionary game, the green technology innovation behavior of enterprises is closely related to its cost and benefit. However, effective public participation provides the possibility for enterprises to conduct green technology innovation behavior when the cost is less than the benefit. In other words, public participation is the key factor for enterprises to change short-sighted behavior and carry out forward-looking innovation; (2) In the three-party evolutionary game, the steady-state conditions of government and public are the same as those in two-party evolutionary game models. However, the steady-state condition of enterprises needs to consider the impact of the public report on corporate reputation, which is an important reference factor for enterprises to make decisions on green technology innovation behavior; (3) With the increase of environmental protection publicity, technology innovation incentive, environmental regulation, public concern, and public report, the evolution of enterprises’ innovation behavior of choosing green technology is accelerating, and green technology innovation is promoted by government behavior and public participation significantly. To sum up, on the basis of exogenous guidance of government behavior, public participation should be encouraged to guide the green technology innovation behavior into the endogenous evolution path considering the enterprise profit.
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    The Framework for the Risk Feature Extraction Method on Corporate Financial Fraud George
    YUAN Xianzhi, ZHOU Yun-peng, YAN Cheng-xing, LIU Hai-yang, QIAN Guo-qi, WANG Fan, WEI Li-jian, LI Zhi-yong, LI Bo, David Li, ZENGTu
    2022, 30 (3):  43-54.  doi: 10.16381/j.cnki.issn1003-207x.2020.2201
    Abstract ( 438 )   PDF (2438KB) ( 695 )   Save
    By employing the Gibbs sampling skill under the Markov Chain Monte Carlo (MCMC), weestablish a general framework for corporate financial fraud detection by using fintech method related big data analysis. In the empirical analysis, based on those event “bad” samples from Chinese A-share listed companies enquired by China Securities Regulatory Commission (CSRC)due to behaviors such as violating (at least potentially violating) the rules of the disclosure during time period from the beginning of year 2017 to the end of year 2018 under the Rule of the Disclosure from CSRC, the analysis for key risk factors which could represent the information for the exposure of financial fraud behavior is conducted byudetecting the difference between their financial reports from others. In general, the feature extraction (or variable selection) from around two hundred related factors of financial reports will be a NP problem because of the diversity of financial ratio indexes. However, in this paper by employing the Gibbs sampling method under MCMC, 8 key factors are extracted which are highly correlated with the behavior of corporate financial fraud. They are: ROE, the growth construction-in-process, the growth of advance payment, interest expense / revenue, investment income / revenue, other income / revenue, other receivables / total assets, andlong term loan / total assets.
    The key contribution of this paper is that a general framework is established for the extraction of key risk factors which could be used not only to detect the behavior of financial fraud, but also to predict the financial fraud under the supporting of ROC testing numerical results based on more than 3,500 A share listed companies in China.
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    Green Finance and Economic Growth Quality: Construction of General Equilibrium Model with Resource Constraints and Empirical Test
    WEN Shu-yang, LIN Ze-fu, LIU Xi-liang
    2022, 30 (3):  55-65.  doi: 10.16381/j.cnki.issn1003-207x.2020.2173
    Abstract ( 1012 )   PDF (1335KB) ( 837 )   Save
    It is widely believed that green finance is an important means to promote green growth. However, there is barely any theoretical research or empirical evidence on the relationship between green finance and economic growth quality. Is green finance truly influencing economic growth quality? How? A deep understanding of the relationship between the two is important for both green finance practice and research. Starting from the theoretical context of green finance research, a general equilibrium model with environmental constraints and financial sector is constructed. In the model, the “public goods problem” of natural resources causes the economic growth path to deviate from the optimal level, and green financial institutions can improve the economic growth path byoptimizing capital allocation; as a result, the steady-state resource consumption level is reduced, and economic growth quality is improved. Based on the theoretical model, a provincial panel data from 2005 to 2017 shows that financial support for energy conservation and environmental protection can significantly reduce the resource cost of economic growth; it strongly supports the theoretical inferences. Therefore, it is argued that the core of the development of green finance is to “green” the operating philosophy and investment decisions of financial institutions, which will improve financial resource allocation, and thus promote green growth. In addition, the theoretical model of this article combines the research of green finance with the economic growththeoryand provides a reference for the construction of theoretical models of green finance.
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    Research on High-quality Development Considering Inter Regional Environmental Investment Strategy Interaction
    SONG Yan, ZHANG Ming
    2022, 30 (3):  66-75.  doi: 10.16381/j.cnki.issn1003-207x.2020.2191
    Abstract ( 261 )   PDF (1795KB) ( 352 )   Save
    On the basis of considering the strategic interaction characteristics of regional environmental protection investment, a model is established to analyze the impact of endowment and financial capacity differences on the policy objectives of local governments, and the impact of ecological transfer payment policy balancing regional resource endowment on the regional environmental protection joint output level is discussed. The results show that: the introduction of strategic interaction characteristics of regional environmental protection investment can maximize the joint output of environmental protection, corresponding to the moderate difference degree of local government resource endowment. The difference degree is too large or too average, which is not conducive to stimulate the vitality of local governments, and provides stable conditions for high-quality economic sustainable development. In addition, compared with the lump-sum transfer payment policy, the earmarked transfer payment policy can more effectively encourage the local governments to invest in the ecological environment; reducing the information symmetry requirements of the earmarked transfer payment in practice and establishing the horizontal transfer payment based on market-oriented operation fund pool are feasible policies to further increase the regional environmental protection level. From the aspects of coordinating regional economic development differences, ensuring the effectiveness of environmental protection investment, measuring the regional ecological spillover effect, optimizing the earmarked transfer payment policy, establishing market-oriented operation fund pool and increasing the proportion of horizontal transfer payment, countermeasures and suggestions are put forward to improve the utilization efficiency of environmental protection investment funds in China.
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    Research on the Influence Mechanism of Online Health Information Seeking Behavior of Middle-aged and Older Adults Based on the IMB Model in the Context of COVID-19
    ZHOU Pei-yu, LIANG Chang-yong, MA Yi-ming
    2022, 30 (3):  76-84.  doi: 10.16381/j.cnki.issn1003-207x.2020.2177
    Abstract ( 352 )   PDF (1362KB) ( 432 )   Save
    Due to the huge impact of COVID-19 on the health of middle-aged and older adults, the demand for health information and the frequency of online health information seeking behavior of middle-aged and older adults have increased significantly during the epidemic. Thus, it is necessary to explore the internal mechanism and influencing factors of the online health information seeking behavior of middle-aged and older adults in the context of COVID-19.
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    Can the Right of Data Portability Govern Big Data-based Price Discrimination?
    XING Gen-shang, LU Fang, ZHOU Zhong-bao, YE Jin-long
    2022, 30 (3):  85-95.  doi: 10.16381/j.cnki.issn1003-207x.2020.2232
    Abstract ( 569 )   PDF (2621KB) ( 595 )   Save
    It is not uncommon for e-commerce platforms to set higher price for frequent customers by using big data. However, because of the hidden nature of the algorithms of e-commerce platforms, the Chinese government has been difficult to supervise the the phenomenon of big data-based price discrimination. So can the EU’s right to data portability control it? In view of the fact that it is a long-term dynamic process for consumers to exercise right to data portability to deal with big data-based price discrimination, an evolutionary game model composed of consumers and e-commerce platforms is considered. First, the evolutionary game model of big data-based price discrimination considering the right of data portability is constructed, the evolutionary stability strategies of consumers and e-commerce platforms are analyzed, and the factors affecting the evolutionary stability strategies of both parties are obtained. Then, based on the evolutionary game model, the stability of the equilibrium point is analyzed, and the conditions of the evolutionary stable equilibrium are obtained. Finally, a numerical simulation analysis is carried out using Matlab software. Research shows that if the proportion of regular customers among platform users is relatively high, and the additional utility gained by regular customers by exercising their data portability rights to the new platform is greater than a certain threshold, granting consumers the data portability rights can curb the phenomenon of big data-based price discrimination. But when the proportion of dissatisfied customers among regular customers is relatively high, the right to data portability by consumers will hinder the improvement of e-commerce platform products or services; the increase in the value of personal data will simultaneously promote e-commerce platforms to exercise price discrimination and consumers to exercise data portability, but the increase in the value of observational data will have a negative impact on consumers' exercise of data portability, and the increase in the value of derivative data will inhibit e-commerce platforms' price discrimination. This paper is of great significance for solving the phenomenon of big data-based price discrimination and enriching research on price discrimination.
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    Manufacturer Encroachment in E-commerce Channel with Retailer’s Advantage of Information Possession
    ZHAO Hua, ZHANG Han, LI Zhi-guo
    2022, 30 (3):  96-105.  doi: 10.16381/j.cnki.issn1003-207x.2020.2244
    Abstract ( 416 )   PDF (1668KB) ( 598 )   Save
    In recent years, the rapid development of online retailing has attracted many manufacturers to establish e-commerce direct sales channel on the basis of traditional retail channel. However, in the supply chain the retailer has more consumer information than the manufacturer to predict market demand, the manufacturer often faces asymmetric demand information relative to the retailer when building direct sales channel. A supply chain composed of a manufacturer and a retailer is considered, where the retailer orders products from the manufacturer and sells to the end market, and the manufacturer has the incentive to establish direct sales channel to consumers. Three scenarios are modelled to investigate the manufacturer’s encroachment decision and the retailer's order decision, including no manufacturer encroachment scenario, manufacturer encroachment under symmetric information scenario and manufacturer encroachment under asymmetric information scenario. The results are further verified through numerical simulation.
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    Research on the Customer Value Portrait Model of Industrial Power Enterprise in China Based on Spectral Clustering Technology and Rough Set Theory
    YU Shun-kun, YAN Hong-xu, DU Shi-yue, LIN Yi-qing
    2022, 30 (3):  106-116.  doi: 10.16381/j.cnki.issn1003-207x.2021.1324
    Abstract ( 333 )   PDF (4479KB) ( 351 )   Save
    For Chinese power supply enterprises, the value portrait of power customers has important practical significance for improving the resource allocation efficiency of marketing service, promoting the smart marketing management, and therefore maximizing the comprehensive benefits. However, the reported models fail to reflect the development requirements of China’s industrial enterprises in the latest national energy policy, cannot cope well with the sparsity of real power customers’ electricity consumption data, and has room for improvement in the accuracy of new customers’ value rating prediction. Therefore, based on the spectral clustering (SC) technology and the rough set (RS) theory, an optimized industrial power customer value portrait model termed as SC-RS is constructed. The new model is constructed according to the logical framework of “knowledge extraction-knowledge reasoning-knowledge service”. Firstly, in the knowledge extraction part, an optimized China’s industrial power customer rating index system is constructed, based on the China’s “Peak Carbon Dioxide Emissions” goal and “Carbon Neutrality” vision. In addition, the grid search strategy combined with the SC technology is used to refine user’s value grade information. Secondly, in the knowledge reasoning part, the RS theory is used to build a four-dimensional rule mining model to generate the rule base of the user value grade, based on the framework of three-dimensional rule mining. It consists of row reduction based on the ChiMerge discretization method and coefficient of variation, column reduction based on the system dependence, cell reduction based on the object certainty factor, and rule extraction based on the rule strength. Finally, in the knowledge service part, the user value grade intelligence is applied to portray the value portrait of group users. The rule base is used to present understandable value knowledge and construct a ruled-soft classifier to achieve value grade prediction and individual value portrait description of new users. The model is further applied on the data of actual industrial power customers. The results show that the constructed rating index system closely copes with the latest developments in Chinese power industry. The SC-RS model is compatible with sparse data and has low data requirements. The constructed four-dimensional rule mining model based on RS theory is feasible and effective, and can robustly predict the value grade of new customers. Moreover, the SC-RS model can realize the value intelligence mining and utilization of big data of electric power customers, which is a powerful tool for empowering the smart marketing management of China’s electric power enterprises.
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    Robust Scheduling Optimization of Project Resources with Activity Splitting under Complex and Uncertain Environments
    MA Zhi-qiang, XU Xiao-feng, HE Zheng-wen, WANG Neng-min
    2022, 30 (3):  117-130.  doi: 10.16381/j.cnki.issn1003-207x.2020.2176
    Abstract ( 358 )   PDF (2341KB) ( 345 )   Save
    In practice, faced with the complex and uncertain environment, it is really necessary for project managers to construct a robust resource allocation schedule with a strong anti-interference ability. At the stage of schedule generation, activities may be not divided into the smallest units, so project managers can choose to further split activities into subactivities under specific constraints. When taking activity splitting into account, on the one hand, it will be more flexible for activity scheduling; on the other hand, it will be more complex for resource allocation between the subactivities.
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    Green Supply Chain Decisions with Consideration of Tariffs, Power Structures and Consumer Preference
    LIU Ming-wu, LIU Ya-qiong, FU Qiao-ling
    2022, 30 (3):  131-141.  doi: 10.16381/j.cnki.issn1003-207x.2020.2249
    Abstract ( 408 )   PDF (3398KB) ( 412 )   Save
    The Chinese economy is moving from a stage of rapid growth to a stage of high-quality development. The high-quality development of the manufacturing industry is an important support for the high-quality development of the economy. The green supply chain has become the inherent meaning of the high-quality development of China's manufacturing industry. However, international trade frictions have occurred frequently in recent years. Especially, the tariffs have brought risks and challenges to the green development of China’s manufacturing supply chain, which has affected the global operation of the supply chain. Therefore, in the context of trade frictions, China’s manufacturing supply chain operation related issues urgently need to be resolved. That is, how the imposition of tariffs and tax rates affect the decision-making of green supply chain? What is the influence of the power structure of supply chain on the decision-making of green supply chain under the circumstance of additional tariff? How much do consumers’ green preferences offset the negative effects of tariffs? Considering these problems, the green supply chain decision is studied under the influence of tariff, power structure and consumers’ green preference. This paper is beneficial to supply chain green development policy making and supply chain enterprise operation decision.
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    Research on Sustainable Investment of Maritime Supply Chain Considering Double Equilibrium
    LIU Jia-guo, KONG Yu-dan, ZHEN Lu
    2022, 30 (3):  142-153.  doi: 10.16381/j.cnki.issn1003-207x.2020.2348
    Abstract ( 514 )   PDF (2477KB) ( 346 )   Save
    As an indispensable part of the international trade logistics system, maritime supply chain playsa positive role in promoting trade globalization. Under the background of global energy shortage, environmental capacity decline, carbon tax policy and customers green preference,the development of maritime supply chain is facing the challenges of energy and environment.Port and shipping companies will inevitably follow the principle of sustainable development to seek benign development. Aiming at the problem of joint carbon emission reduction between ports and shipping companies, a linkage model of static Stackelberg equilibrium and dynamic evolutionary game is constructed. Under the influence of government carbon emission regulation and carbon trading market, the research considers sustainable development of low-carbon technology investment strategies in the maritime supply chain. It shows that with the increase in the proportion of investment cost sharing, under the static Stackelberg equilibrium, the willingness of shipping companies to invest gradually decreases, but the port always prefers to invest by itself. In this condition, the system equilibrium strategy changes from the prisoner’s dilemma of shipping companies’ investment to the pareto optimum of port investment.Under the dynamic evolutionary game, the stable result is that the investment is transform from shipping companies to port. In addition, from the perspective of the government-market-enterprise tripartite, it is found that: (1) There is no relation between the low-carbon investment of companies and the government carbon emission quota; (2) Companies need to pay attention to carbon trading market prices, shippers’ sensitivity to sustainability levels, and price sensitivity, whose increase will result in carbon emissions’ reduction; (3) With the increase in the share ratio, carbon emissions will show an upward trend. Finally, combining static and dynamic investment strategies, it can be seen that the dynamic game strategy of maritime supply chain is consistent with the static equilibrium strategy. Because in long-term investment, maritime supply chain companies consider the strategies that are beneficial to both parties, rather than for themselves. On this basis, suggestions on sustainable investment are put forward from three angles of government, port and shipping companies.
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    Recycling Decisions of E-commerce Closed-loop Supply Chain Undercapital Constraint of E-commerce Platform
    WANG Yu-yan, YU Zhao-qing, SHEN Liang
    2022, 30 (3):  154-164.  doi: 10.16381/j.cnki.issn1003-207x.2020.2170
    Abstract ( 348 )   PDF (2793KB) ( 382 )   Save
    Considering whether the e-commerce platform alone bears the recycling service cost or shares the cost of recycling service cost with the remanufacturer, and taking into account whether the e-commerce platform chooses a loan strategy to lift the capital constraint or not, game models of e-commerce closed-loop supply chain under platform’s capital constraint are constructed. The corresponding optimal strategies are solved and analyzed, and the conditions for the remanufacturer to share the service costs and for the E-commerce platform to choose a loan strategy are given. The results show thatwhen the e-commerce platform has capital constraint, though the remanufacturer shares part of recycling service costs, alsosplits profit of the e-commerce platform, which can achieve a win-win situation for both parties. When the e-commerce platform does not choose a loan strategy, the more self-owned funds, the more beneficial the remanufacturer will be. But when the e-commerce platform chooses a loan strategy, the more self-owned funds, the more favorable to the e-commerce platform but the remanufacturer is no longer influenced. Moreover, as self-owned funds increases,the proportion of service costs shared by the remanufacturer will be reduced, and the degree of recycling service improvement will be reduced. It is the best choice for the e-commerce platform to induce the remanufacturer to share the recycling service costs and choose a loan strategy together to lift the capital constraint.
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    The Equilibrium Strategy Analysis of a Capacity-sharing Supply Chain with Order Processing and Excess-shortage Transaction Service
    XIE Lei, MENG Qing-chun, HAN Hong-shuai
    2022, 30 (3):  165-175.  doi: 10.16381/j.cnki.issn1003-207x.2020.2187
    Abstract ( 269 )   PDF (1454KB) ( 216 )   Save
    Considering the mismatch between the orders and actual deliveries due to information asymmetry, a capacity sharing supply chain consisting of a capacity buyer, a capacity seller and a third-party order processing supervisor is built, and the impacts of “excess-shortage transaction” and “order processing” services on the capacity delivery rate improvement are investigated. Considering the capacity seller's decision whether to choose the excess-shortage transaction and the capacity buyer's decision whether to accept the order processing service, the dominant strategies of capacity buyer and seller and the equilibrium strategy combinations of both sides are analyzed. It is found that both excess-shortage transaction and order processing services can lower the entry barrier for capacity sharing, enabling more SMEs to join capacity sharing. When the defective rate is relatively high, or the order processing service effect is relatively good, buyer and seller tend to accept the order processing service and adopt the common trading mode; on the contrary, when the defective rate is relatively low, or the order processing service effect is relatively poor, buyer and seller tend to adopt the excess-shortage transaction mode and do not accept the order processing service. The equilibrium strategy and the conditions for the excess-shortage transaction and order processing service are further given, which provides a basis for the buyers and sellers to choose the cooperative objects and the related decisions.
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    Decisions and Contract Selection of Closed-loop Supply Chain Considering Different Competitive Behaviors of Retailers under Government Subsidy
    ZHOU Xiao-yang, CHEN Ke-xin, WEN Hao-yu, WANG Shou-yang
    2022, 30 (3):  176-188.  doi: 10.16381/j.cnki.issn1003-207x.2020.0231
    Abstract ( 395 )   PDF (2649KB) ( 398 )   Save
    The increasing global pollution and consuming resources promote industry and academia to pay attention to closed-loop supply chain. Adding recycling and remanufacturing to the traditional supply chain can effectively reduce resource consumption, so the development of closed-loop supply chain is guided by governments through subsidies.In view of the gap in previous studies, the decisions and contract selection of a closed-loop supply chain consisting of one manufacturer and two competing retailers under government subsidy are considered. The manufacturer acts as the leader of Stackelberg game in the supply chain and two retailers act as followers.Based on centralized decision-making, two decision models under different competitive behaviors of retailers are established, including Cournot duopoly game and Stackelberg game. According to different game sequences, and the equilibrium results of each model are obtained by reverse solution.Then the effects of competition behaviors, competition intensity and government subsidy on the optimal decisions and maximum profits are analyzed. Finally, the role of cost-sharing contract and revenue-sharing contract in the decisions of supply chain members is discussed when retailers adopt the Cournot duopoly game. Since a single contract cannot perfectly coordinate the supply chain, these two contracts are combined and improved to design a new contract that can achieve supply chain coordination.
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    Pricing and Ordering Decisions for Fresh Produce Based on Different Fresh-keeping Methods
    TANG Yue-wu, FAN Ti-jun, CHENG Yong-wei
    2022, 30 (3):  189-198.  doi: 10.16381/j.cnki.issn1003-207x.2020.2248
    Abstract ( 286 )   PDF (2150KB) ( 311 )   Save
    Fresh produce is perishable and needs to be kept fresh. In most cases, there are different fresh-keeping methods to preserve fresh produce. For example, Seafood can be chilled or frozen to keep fresh. Fresh produce with different fresh-keeping methods have different deterioration rates, and their product demands have a mutual substitution effect. In addition, due to the limitation of the special fresh-keeping area and equipment in fresh produce retail stores, the inventory constraints of fresh produce order quantity are generated. Therefore, the pricing and ordering decision making environment of fresh produce with different fresh-keeping methods for the retailer are very complex. In sales practice, fresh produce with different fresh-keeping methods often lose the balance of supply and demand, which leads to the coexistence of unsalable and out of stock. Thus, it is challenging and valuable to study the pricing and ordering decisions of fresh produce under different fresh-keeping methods, and discuss the influence of fresh deterioration rate, demand substitution rate and inventory constraints on these decisions.
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    Research on Decomposition-Ensemble Approach for Predicting E-waste Recovery Scale Driven by Seasonal Data Characteristics
    WANG Fang, YU Le-an, ZHA Rui
    2022, 30 (3):  199-210.  doi: 10.16381/j.cnki.issn1003-207x.2020.2171
    Abstract ( 270 )   PDF (2247KB) ( 242 )   Save
    The prediction of e-waste recovery scale is the basis for the government to formulate the development plan of circular economy and relevant subsidy policies, and for enterprises to evaluate the value of resource recovery and optimize production capacity. In this paper, the CH-X12 /STL-X framework for e-waste recycling scale prediction is proposed based on the idea of “Decomposition-ensemble”, considering that the seasonal data characteristics of the quarterly e-waste recycling scale data may lead to large prediction errors by using traditional single model and unstable prediction results. Firstly, the seasonal data characteristics of the time series of e-waste recovery scale are identified based on Canova-Hansen (CH) test, and then the time series suitable for seasonal decomposition is extracted with X12 or seasonal -trend decomposition procedure based on loess (STL) model for seasonal components. Then, the Holt-Winters model is used to predict the seasonal component, and the support vector regression (SVR) model is used to predict the other components. Finally, the linear sum of the prediction results of each component is used to obtain the final prediction result. The empirical results show that the proposed CH-X12/STL-X prediction framework can better meet the modeling requirements of time series prediction driven by different seasonal data characteristics and has better and more stable prediction performance than the traditional single models (Holt-Winters model, Seasonal Autoregressive Integrated Moving Average model, and SVR model).
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    A Trimmed Average Based Neural Network Ensemble Approach for Time Series Forecasting
    ZHAO Yang, HAO Jun, LI Jian-ping
    2022, 30 (3):  211-220.  doi: 10.16381/j.cnki.issn1003-207x.2018.0326
    Abstract ( 357 )   PDF (1156KB) ( 306 )   Save
    As structural breaks and outliers exist in complex time series data, they may easily affect the training process of a forecasting model, and the forecasting model can generate extreme forecasting results. In this case, a trimmed average is proposed based neural network ensemble forecasting approach. This approach first generates multiple training sets, then the training sets are used to training multiple neural network model. Finally, the forecasting results are combined using trimmed average strategy. Compared with simple average, trimmed average is less sensitive to outliers, and makes the ensemble model has better forecasting accuracy. In the empirical study, two neural network ensemble models are built, namely trimmed average based bootstrap neural network ensemble (TA-BNNE) and trimmed average based Monte Carlo neural network ensemble (TA-MCNNE). These two models are used to forecast the NN3 competition datasets. The results show that they both have better forecasting accuracy than simple average based ensemble models. Moreover, the performance of our proposed model is compared with those that ranks the first 10 place in NN3 competition in the competition context, and their performance is found both surpass that of the 6th ranking model for all datasets and 1st ranking model for complex datasets, indicating that our proposed approach is very effective. Our approach extends the trimmed average strategy to time series forecasting and shows promising forecasting accuracy especially for time series with structural breaks and outliers. Moreover, this approach can be easily extended to different time series forecasting applications, since neural network ensemble as a popular forecasting tool has been shown to be very effective for time series forecasting in an extensive body of literatures.
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    Construction of Linear Time-varying Parameters DLDGM(1,N) Model Based on Driving Factors Control
    LI Ye, DING Yuan-ping
    2022, 30 (3):  221-229.  doi: 10.16381/j.cnki.issn1003-207x.2020.2182
    Abstract ( 264 )   PDF (1181KB) ( 184 )   Save
    Aiming at the problem that the dynamic change characteristics of parameters with time is not considered, and the mechanism of driving factors is not clarified in the traditional GM(1,N) model, a linear time-varying parameters discrete GM(1,N) model based on driving factors control is constructed by introducing linear time-varying parameters and driving factor control function, which is abbreviated as DLDGM(1,N) model. The new model has more reasonable modeling process, more stable structure, and the traditional multi-variable model’s defects are eliminated in it. To identify the mechanism of driving factor control parameters, calculation methods based on the two situations of sufficient and lack of whitening information are given. In addition, it is proved that DLDGM(1,N) model is entirely compatible with the single variable grey prediction model GM(1,1), DGM(1,1), NDGM(1,1) and TDGM(1,1), and the multi-variable grey prediction model DGM(1,N) and DCDGM(1,N) by adjusting the parameter values,. Finally, to verify the practicality and effectiveness of DLDGM(1,N) model, the model is used to simulate and predict the grain yield in Henan Province and the sample data is obtained by Henan Statistical Yearbook. The mean relative simulation and prediction percentage errors of DLDGM(1,N) model are 0.49% and 1.23%, in comparison with those of DGM(1,N) model and traditional GM(1,N) model, which are 1.00%, 3.12% and 4.68%, 5.25% respectively. The results show that DLDGM(1,N) model has the best performance in simulation and prediction, which on one hand testifies the effectiveness of improving model’s structure, and on the other hand proves that the model has good practicability in the system with time-varying parameters and complex driving factors mechanism.
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    Optimal Pricing and Advertising Decisions for Online Video Services Considering Word of Mouth
    LI Zhi-peng, XIE Ting, CHEN Sha
    2022, 30 (3):  230-239.  doi: 10.16381/j.cnki.issn1003-207x.2020.2163
    Abstract ( 317 )   PDF (3004KB) ( 345 )   Save
    In recent years, online video has become an important part of online content consumption, and its diffusion is significantly affected by online word of mouth (WOM). Considering the impact of online WOM on the diffusion process of online videos during the premium period, the optimal decisions of the online video operator on video price and advertising volume are studied, and how the WOM attributes, free trial, video quality and premium period affect the optimal decision results is analyzed. Results show that when the experience quality of the subscribers is sufficiently higher than that of the non-subscribers, the operator chooses the advertising-oriented strategy (with advertising level relatively higher than pricing level); otherwise, the operator chooses the payment-oriented strategy (with pricing level relatively higher than advertising level). The operator is more likely to choose the payment-oriented strategy when the video is with better WOM attributes, when the free-trial time is shorter, when the premium content is with lower quality, or when the free content is with higher quality. Based on the above optimal decision results, the operator can further improve the premium period according to the video’s WOM attributes.This study contributes to the literature at the intersection of innovation diffusion and online content marketing.
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    Study on Evaluation and Prediction of Scientific Research Platforms of Universities using a GCA-DEA-MSVC Methodology
    LIU Chuan-bin, DAI Wei, YU Le-an, YANG Jian-an
    2022, 30 (3):  240-247.  doi: 10.16381/j.cnki.issn1003-207x.2020.0388
    Abstract ( 285 )   PDF (1724KB) ( 517 )   Save
    The evaluation and prediction of the operation state of university scientific research platforms plays an important role in promoting the healthy and efficient development of scientific research work. However, the complexity of data indicators, complex logical relationships, and numerous influencing factors have greatly increased the difficulty. From the perspective of big data, a method based on GCA-DEA-MSVC is explored. First, the GCA method is used to mine and extract key feature indicators that are closely related to the evaluation results from the database and classify to build a feature indicator database. After that, the DEA method is used to fuse the feature index database data to improve the data quality and build a relative efficiency index database. Finally, the feature index library and the relative efficiency index library were re-fused, and an efficient classification and prediction model for the evaluation of the operating status of the scientific research platform is constructed based on the improved MSVC method. An experimental study is conducted using the evaluation data of the key laboratory of the Ministry of Education to verify the effectiveness of the proposed method.
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    Weapon Target Assignment Method for Multiple UAVs in Beyond-Visual-Range Air Combat
    MA Ying-ying, WANG Guo-qiang, HU Xiao-xuan, LUO He
    2022, 30 (3):  248-257.  doi: 10.16381/j.cnki.issn1003-207x.2020.2293
    Abstract ( 294 )   PDF (2006KB) ( 262 )   Save
    Weapon target assignment is one of the key decision-making problems in beyond-visual-range (BVR) air combat of multiple UAVs. It refers to that in BVR air combat, multiple UAVs determine the optimal weapon target assignment scheme according to the battlefield situation, the UAV’s capabilities, threat of opponents and other factors, so as to occupy an advantage in the process of BVR confrontation. Considering the new challenge of weapon target assignment problem caused by the strong confrontation and uncertainty of BVR air combat, based on the idea of Nash equilibrium game, the weapon target assignment problem of multiple UAVs in BVR air combat is modeled as a bimatrix matrix game model by constructing the strategic action space and utility function of the game, in which the validity of attacking effect of multiple UAVs against multiple targets is calculated based on the evidence theory. Then according to the relationship between the probability and regret value of the strategy in Nash equilibrium and the demand of BVR air combat, the solution of bimatrix game model is transformed into solving mixed integer programming optimization model. The effectiveness of the proposed method is analyzed through three aspects of experiments. Firstly, based on the typical case of weapon target assignment of multiple UAVs in BV air combat, the calculation process of the proposed method is analyzed; secondly, the effectiveness of the proposed solution is analyzed through numerical experiments; finally, simulation experiments are carried out to verify the effectiveness of the proposed method for multi UAV BVR air combat. The experimental results show that the proposed method can give an effective weapon target assignment scheme for multiple UAVs in BVR air combat in a short time, improve the probability of winning and reduce the ratio of the number of destroyed UAVs to the number of destroyed targets.
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    Studying on the Influence of Recycling Promotion Models on the Waste Products Recycling and Coordination Mechanism
    ZHAO Qiang, XIA Xi-qiang
    2022, 30 (3):  258-268.  doi: 10.16381/j.cnki.issn1003-207x.2020.1357
    Abstract ( 299 )   PDF (2907KB) ( 270 )   Save
    The consumer awareness of the environmental is one of the key factors affecting waste product recycling, and recycling promotion could effectively enhance consumer awareness. However, there will be some recycling promotion cost in the process of recycling promotion, thus, how to allocate the cost directly affects the upstream and downstream publicity efforts of recycling.The game models (YD model is the cost of the recycling promotion by the processor; YR model is the cost of the recycling promotion by therecyclers; YG model is the cost of the recycling promotion by theprocessor and the recycler; C model is centralized decision model)between a processor and a recycler are constructed based on different recycling models in order to analyze the impact of different recycling models on the recycling of waste products. Basing on the game models, firstly,the impact of recycling promotion models on the unit waste product entrusted recycling price, the unit recycling price, recycling volume and profits is comparative analyzed;secondly, using the revenue sharing-cost sharing contract achieves the coordination mechanism of upstream and downstream simultaneous recycling promotion and make the profits reach the optimal. The main results are as follows: when it is decentralized decision, it is better for the recycler to be responsible for recycling promotion when the difference between the recycling cost coefficient of the recycler and the processor is less than a certain threshold, otherwise, the processor is better for recycling promotion; when the upstream and downstream carry out recycling promotion at the same time, the unit efforts of recycling promotion, the volume of recycled waste products and the profits are greater than when only one party carries out recycling promotion, that is, when upstream and downstream recycling promotion simultaneously, the recycling of waste products is more effective for one party to carry out recycling promotion; when it is centralized decision, the unit recycling price, volume and total profits are greater than the upstream and downstream simultaneous recycling promotion, however, through the revenue sharing-cost sharing contract could make the upstream and downstream recycling promotion model to achieve the optimal.
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    Research on Grey Inertial Model and Its Application Property
    DUAN Hui-ming, XIAO Xin-ping
    2022, 30 (3):  269-279.  doi: 10.16381/j.cnki.issn1003-207x.2019.0195
    Abstract ( 272 )   PDF (1050KB) ( 365 )   Save
    Studying the evolution process of grey prediction model modeling can better understand the essential characteristics and state changes of the model. Inertial grey model mainly studies the evolution process of grey prediction model modeling to understand the state of system change. In this paper, the mechanical properties of data and the matrix analysis method are used to study the modeling steps of the inertial grey model, simplify the structural parameters and component parameters of the inertial model in reference [1], summarize the mechanical transformation formulas for solving various data sequences, and obtain the modeling mechanism of various inertial grey models. Finally, the evolution process of system state is studied through examples, the inertial gray GM(1,1) model is applied to the determination of traffic flow state, and the corresponding relationship between three-phase traffic flow and three inertial gray GM(1,1) models is obtained. At the same time, the simulation results of the three inertial models are used to accurately judge the state of the traffic flow, reveal the real-time characteristics of the traffic system, and provide a reliable theoretical basis for traffic planning, control and optimization.
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    Estimation of Grey Verhulst Model Parameter Based on LS-SVM Method and Its Application
    ZHOU De-qiang
    2022, 30 (3):  280-286.  doi: 10.16381/j.cnki.issn1003-207x.2017.1233
    Abstract ( 227 )   PDF (855KB) ( 305 )   Save
    The grey Verhulst model is modeled for small sample data.To use the grey Verhulst model for prediction,the grey parameters in the model must be determined first. The prediction accuracy of the model is directly affected by the quality of grey parameter estimation. It is estimated that the parameters in the grey Verhulst model usually use the least squares method. However,this empirical risk minimization method based on the large sample theory can not guarantee the generalization performance of the model under small sample prediction.
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