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主管:中国科学院
主办:中国优选法统筹法与经济数学研究会
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Table of Content

    20 December 2020, Volume 28 Issue 12 Previous Issue    Next Issue
    Articles
    Asset Pricing and The Proportion of Labor Cost
    LIU Wei-qi, ZHANG Yan
    2020, 28 (12):  1-11.  doi: 10.16381/j.cnki.issn1003-207x.2020.0043
    Abstract ( 466 )   PDF (1123KB) ( 149 )   Save
    Classical economic theoretical models usually assume that there is no friction in the labor market, so the study of classical asset pricing mainly focuses on capital factors, the study of labor factors is in a relatively "weak" position, however, according to production function, the relevant changes of labor factors should be reflected in the level of enterprise value, so what is the impact of labor factors on stock market?
    Based on the stickiness of labor cost, a measure index of the proportion of labor cost is constructed and the influence of the proportion of labor cost on stock market pricing is studied for first time based on China's A-share market from 1999 to 2017. There is a positive correlation between the proportion of labor cost and enterprise risk by theoretical analysis and model derivation, furthermore, it is proved that the proportion of labor cost is positively related to enterprise risk through regression analysis. According to the compensation principle of positive correlation between risk and return,it is found that the proportion of labor cost has positive prediction ability for stock return through regression analysis and portfolio analysis, the impact of labor cost ratio on stock returns is not related to the nature of property rights, R&D investment level, firm competitiveness and industry nature. Inspired by the above conclusions, this paper explores whether the proportion of labor cost can be used as a pricing factor? First, the labor cost risk factor is constructed with the help of long-short portfolio. Fama-MacBeth regression proves that the proportion of labor cost is a risk factor for stock return. Second, the proportion of labor cost is not a redundant factor relative to Fama-French five factors. Finally compared with Fama-French three factor model and five factor model, the pricing models including FF3 factors or FF5 factors and the proportion of labor cost have better explanatory capability on cross-sectional stock returns.
    This paper has reference value for the investment decision of investors, the formulation of enterprise salary system, the government's promulgation of labor protection policy and the reform about labor cost. In addition, it enriches the literature about the influencing factors of stock returns and economic consequences of labor cost.
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    The Characteristics and Macroeconomic Effects of China's Financial Cycle
    WANG Chao, CHEN Le-yi, LI Yu-shuang
    2020, 28 (12):  12-22.  doi: 10.16381/j.cnki.issn1003-207x.2019.0990
    Abstract ( 419 )   PDF (2431KB) ( 204 )   Save
    It is of great significance to measure China's financial cycle reasonably and to accurately grasp its characteristics and economic impact for maintaining national financial security and keeping the economy running smoothly. A new method for China's financial cycle measurement is provided. On the basis of GARCH model, this paper dynamically weights the gap values of M2, housing price, stock price, interest rate and exchange rate to synthesize China's Financial Condition Index and uses it to measure China's financial cycle. According to it, the nonlinear characteristics of China's financial cycle analyzed by using Markov-Switching model and investigates the four-zone system for the first time. Furthermore, VAR model is used to investigate the macroeconomic effects of China's financial cycle. The results show that:Firstly, the relative importance of the variables used to synthesize China's FCI changes over time.To measure financial cycle in China, the dynamic weighting method based on GARCH model is superior to many existing methods. Secondly, China's financial cycle has a strong inertia in state transition. At the same time, China's financial cycle has asymmetric characteristics of more expansion and less contraction and of long expansion and short contraction. Moreover, imbalance in China's overall financial situation is very common. Thirdly, the effect of China's financial expansion on output is only a short-term stimulus for 10 months, while it has a lasting impact on price rising.
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    Does Real Estate Stock Investment Hedge Inflation? Research on Correlation Measurement Based on Markov-switching GRG Copula
    WANG Wei-qing, LIU Xiang-dong, LI Hui-zhong
    2020, 28 (12):  23-34.  doi: 10.16381/j.cnki.issn1003-207x.2018.1848
    Abstract ( 434 )   PDF (2104KB) ( 130 )   Save
    In recent years, the real estate industry is an important engine of Chinese economy. The economy has achieved sustained high-speed growthdriven bythe real estate industry. Meanwhile, the money supply (M2) has been growing at an average annual rate of 15.84 percent, which has also raised concerns about inflation. In this context, whether real estate stock investment can hedge inflation is a very concerned issue for investors.
    To test the positive and negative synergistic effect between the real estate stock index return and inflation, AR(m)-EGARCH(p, q)-GED is employed to model the edge distribution of financial time series, and a correlation measurement model is constructed based on Markov-switching GRG copula. In this model, Markov state transformation is mainly used to control the parameters of correlation between two different states. GRG copula does not fix the weight coefficient of mixed copula, which can more flexibly connect the edge distribution according to the data characteristics. This correlation measurement model can not only measure the instantaneous tail correlation between Chinese real estate stock index return and inflation, but also measure the correlation based on quantilebetween them in non-extreme cases.
    The empirical results show that from January 2001 to December 2017, there exist two positive and negative structural states of Markov transformation between the real estate stock index return and inflation. Among them, the positive correlation structure between the two is the main state of the economic system. In this state, real estate stock investment has a certain ability to hedge inflation. In the negative correlation dependent structure, real estate stock investment can not hedge inflation. In addition, there exist significant differences in the intensity of correlation between extreme and non-extreme cases. In the main state, the positive correlation between them is stronger in the non-extreme condition than that in the extreme condition. Moreover,in the quantile with the same distance on both sides of α=0.5, the correlation between the two rises is higher than that between the two falls.
    The correlation measure model based on Markov-switching GRG copula can be extended to more application fields to analyze the nonlinear correlation between two time series.The empirical results will provide some useful enlightenments for the formulation of macroeconomic policies and the establishment of investment decisions.
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    Evolution Characteristics of Financial Institutions' Interrelationships from the Perspective of Multilayer Network
    LI Shou-wei, WEN Shi-hang, WANG Lei, HE Jian-min, GONG Chen
    2020, 28 (12):  35-43.  doi: 10.16381/j.cnki.issn1003-207x.2019.0002
    Abstract ( 489 )   PDF (2789KB) ( 353 )   Save
    The linear correlation between stock returns can be described by Pearson correlation, but the very important non-linear characteristics of stock markets and the correlation between stock returns when extreme events occur are not measured by Pearson correlation. However, correlation information between stock returns that Pearson correlation cannot measure can be provided by Kendall rank correlation and Tail correlation. Therefore, in order to analyze the dependence structure of stocks, it is very important to adopt different correlation measures to characterize the relationship between stock returns. Therefore, based on Pearson correlation, Kendall rank correlation and Tail correlation of stock returns, the evolution characteristics of multilayer network structures of financial institutions in China is empirically studied by this paper.
    Firstly, the method of building the multilayer network model of financial institutions is given, which consists of two steps. One is to calculate Pearson, Kendall and Tail correlation of stock returns. The other is to filter the correlation between stocks by using the minimum spanning tree method. Secondly, based on the above model and the financial stock data from October 2010 to March 2018 in China, the evolution characteristics of multilayer network structures of financial institutions is analyzed through the structural indicators, such as average weight, edge uniqueness, degree correlation and similarity in the multilayer network.
    Empirical results show that:the average weights of the Kendall and Tail layers are higher than those of the Pearson layer; the trends of average weights of the Pearson and Kendall layers are similar, but the fluctuation amplitude of the former is obviously larger than that of the latter; the trends of edge uniqueness of the Pearson layer and the Kendall layer are very similar, but that of the Tail layer is quite different from them; the degree correlation of any two layers is positive, but it fluctuates sharply with time; the Pearson layer and the Kendall layer have higher similarity, the similarity between the Tail layer and the Pearson layer and the Kendall layer is lower overall; the structural indicators such as average weight, edge uniqueness, degree correlation and similarity in the multilayer network are related to the stock market quotation.From the perspective of the multilayer network theory, the evolutionary characteristics of multilayer correlation among financial institutions in China and its internal relationship with the stock market quotation are explored by this paper, which enriches the study of the multilayer network theory in the financial field. And the relevant research results have a certain practical significance for maintaining the stability of financial markets.
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    A Hybrid Modeling Framework and Its Application for Exchange Traded Fund Options Pricing
    YANG Chang-hui, SHAO Zhen, LIU Chen, FU Chao
    2020, 28 (12):  44-53.  doi: 10.16381/j.cnki.issn1003-207x.2020.12.005
    Abstract ( 446 )   PDF (2844KB) ( 134 )   Save
    The scientific and reasonable exchange traded fund (ETF) options price contributes to implementing risk hedging function. This complex modeling process needs to consider the economic significance and accurately grasp the market rules. The issue of pricing ETF options is studied and a hybrid ETF options model is proposed. It combines the Nested-LSTM neural network model and the Heston model for the modeling, and dynamically corrects the option pricing deviation. The high-frequency data of ChinaAMC China 50 ETF, Harvest SZSE SME-CHINEXT 300 ETF and Huatai-PB CSI 300 ETF are taken as examples to verify the effectiveness of the proposed model. The experiment results show that the volatility characteristics of different types of ETF options prices are significantly different. Therefore, neither the Black-Scholes model nor the Heston model can be adapted to handle complex variation rules of ETF option prices accurately. By introducing Nested-LSTM neural network model into the Heston model, the proposed model can effectively capture the dynamic change rules of different types of ETF options, thus improving the estimation accuracy of ETF option prices effectively.
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    Artificial Intelligence,Technological Change and Low-skill Employment. Empirical Evidence from Chinese Manufacturing Firms
    XIE Meng-meng, XIA Yan, PAN Jiao-feng, GUO Jian-feng
    2020, 28 (12):  54-66.  doi: 10.16381/j.cnki.issn1003-207x.2019.1251
    Abstract ( 700 )   PDF (1084KB) ( 352 )   Save
    As Artificial Intelligence (AI) is remodelling the core competitiveness for Chinese manufacturing industry, there is an increasing concern about a substitution for low-skilled labor.This study provides evidence on how AI affects the patterns of skill demands, measured by the share of low-skilled staff in Chinese manufacturing firms. Employing panel data on Chinese firms listed on the SSE, SZSE, and NEEQ over 2011-2017, the introduction of AI is treated as a quasi-natural experiment and use a robust DID model to estimate the effects of AI on patterns in the relative demand for low-skilled labor. AI firms are defined by investigating the AI production and application scenarios in manufacturing and select AI firms based on policy support, industry application, R&D output, and market recognition. The timing of the initial introduction of AI is defined based on firm-level information. In addition, using a PSM model, the control group whose skill patterns follow the parallel trend assumption is developed.
    The empirical analysis results demonstrate that AI has significant influences on skill demands. First, AI significantly decreases the share of employment of low-skilled labor, which means a small portion of the low-skilled potential employment has been substituted by AI. Second,the negative effect of AI on the share of employment of low-skilled labor has dynamic heterogeneity, and the effect tends to rise over time. Third, AI creates the employment of low-skilled labor through capital accumulation and income expansion while finally urges to decrease the low-skilled share through cutting down marginal output of low-skilled labor.
    Finally, several possible directions for future studies can be extended in two aspects:First, due to the limitations of the data sources, the range of sample observations is only seven years, and data from a longer period can be used to verify the long-term casual effects in further research. Second, the mechanisms related to different forms of AI introduction and firm-level skill premium can be analyzed.
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    Analysis on Policy Effects of Integration of Yangtze River Economic Belt Based on a Multi-regional CGE Model
    LI Na, SHI Min-jun, ZHANG Zhou-ying, CHEN Zhi-gang
    2020, 28 (12):  67-76.  doi: 10.16381/j.cnki.issn1003-207x.2020.12.007
    Abstract ( 436 )   PDF (1877KB) ( 140 )   Save
    The Yangtze River Economic Belt is the most potential economic region in China. How to give full play to the role of the Yangtze golden waterway, promote the industrial division of labor, cooperation and orderly transfer, and accelerate the integrated development of the Yangtze River Economic Belt has become an important issue to promote the high-quality development of the Yangtze River Economic Belt. What kind of policies the government makes and how effective the policies are will be crucial to the integrated development of the Yangtze River Economic Belt. A multi-regional CGE model of China's Yangtze River economic belt is built with the database of 2012 interregional input-output table, and it is used to quantitatively simulate the impacts of different potential policies (reduce transportation costs, promote industrial spatial transfer, and mixed policy) for the integration of the Yangtze River Economic Belt, on the regional economy and the integration within the Yangtze River Economic Belt. The results show that:(1) Enhancing the east-west land transportation construction and reducing the transportation cost in the Yangtze River Economic Belt will facilitate the development of integration within the Yangtze River Economic Belt. The Yangtze River Delta and Sichuan will benefit significantly, while Chongqing will suffer a lot because of severer competition. (2) By implementation of different taxing rate across regions to enhance industrial spatial transfer, heavy chemical industry transfer can be promoted from the Yangtze River Delta with limited environmental bearing capacity to Chongqing-Sichuan and other upstream and middle stream regions. As a result, the income gap will narrow but economic integration effect in the Yangtze River Economic Belt will be not improved. (3) By combined use of abovementioned two policy, industry spatial transfer can be promoted while negative influence for less-developed area can be decreased, which contributes to the integration development and income gap reduction in the Yangtze River Economic Belt. Therefore, to boost the integration development in the Yangtze River Economic Belt, it is necessary to promote industrial space reconstruction while strengthening transportation infrastructure construction. Spatially differentiated tax policy can be adopted to encourage industrial transfer, and industrial chains and clusters can be developed in the central and western regions. At the same time, the environmental risk of industrial transfer should be well controlled. The research results of this paper can provide important theoretical reference and decision support for the policy-making of the integrated development of the Yangtze River Economic Belt.
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    Study on Coordination Mechanism of Two-period Closed-loop Supply Chain Considering CSR Exhibiting
    LI Xin-ran, LI Gang
    2020, 28 (12):  77-86.  doi: 10.16381/j.cnki.issn1003-207x.2019.1235
    Abstract ( 415 )   PDF (1324KB) ( 287 )   Save
    For a closed-loop supply chain system composed of a manufacturer and a retailer with new products and remanufactured products different pricing, corporate social responsibility (CSR) is taken into research. Closed-loop supply chain models respectively under centralized decision, decentralized decision making by the manufacturer alone and the retailer alone to exhibit CSR are constructed. The study discusses the impact of CSR and the optimal CSR exhibiting mode of the closed-loop supply chain. Besides, the study establishes a combined contract model with quantity discount and CSR performance cost sharing to achieve coordination. It is found that when the manufacturer or the retailer exhibits CSR alone, there is no clear evidence to distinguish which is better. For both of them, there is a great gap between the optimal decision of exhibiting CSR alone and the result of centralized decision. With the increasing of the replacement coefficient of new products and remanufactured ones, the competition between them becomes intensified, and the profits of each member and the whole supply chain also increase. If the manufacturer and the retailer can jointly exhibit CSR according to the combined contract of quantity discount and CSR performance cost sharing, the closed-loop supply chain system can achieve a coordinated effect and gain greater social welfare.
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    Recovery Decision of Altruistic Fairness Concern on E-Commerce Closed-Loop Supply Chain
    WANG Yu-yan, SU Mei, SHEN Liang, LIANG Jia-ping
    2020, 28 (12):  87-97.  doi: 10.16381/j.cnki.issn1003-207x.2020.12.009
    Abstract ( 401 )   PDF (1666KB) ( 88 )   Save
    At present, the recycling of waste as a development strategy has received increasing attention. Through the e-commerce platform, the waste products are recycled from customers and disposed of or reused, which forms E-commerce Closed-loop Supply Chain (EC-CLSC). In order to avoid the conflict with the e-commerce platform because of the profit division, the altruistic fairness concern behavior is adopted by the remanufacturer. In order to analyze the impact of altruistic fairness concern on the operation of EC-CLSC, a decision model composed of a single remanufacturer and a single e-commerce platform is constructed in this paper. Then, the optimal decision of each decision-making model is given and the impact of the altruistic fairness concern on recovery pricing, commission and members' profits are analyzed.
    Three decision models of EC-CLSC are constructed in this paper. The first is decentralized decision-making without altruistic fairness concern. In this model, the profit function of the remanufacturer is πm=(h-ρ-p)q, and the profit function of e-commerce platform is πe=ρq-2/2.The second is the decentralized decision-making with altruistic fairness concern. In this model, the decision-making function of the remanufacturer is its utility function Um=πm-θme).The third is joint decision-making. Then, the optimal decisions of three models are solved and analyzed. On this basis, the contract of "recovery cost sharing and joint revenue sharing" of EC-CLSC is designed to realize the coordination of the system. Finally, numerical analysis is used to verify the conclusions of the models. The results show that:(1) the altruistic fairness concern of remanufacturer is a strategy that has to be adopted in order to improve the recovery rate of waste products and maintain the stable development of the EC-CLSC system. This kind of fairness concern is disadvantageous to the remanufacturer. But when the degree of altruistic fairness concern is not more than 0.5, it will improve the profits of the e-commerce platform and the EC-CLSC system. Therefore, remanufacturers generally do not take the initiative to choose altruistic fairness concern, but are often under pressure to consider altruistic fairness concern, and the degree is limited. But in the long run, the altruistic fairness concern of remanufacturers reflects the sense of corporate social responsibility, which can stabilize the operation of EC-CLSC. (2) As the economic benefits of recycled products become more and more significant, consumers become more sensitive to recovery prices, and the recovery prices, the commission, and the profits of members all increase. (3) In the joint decision-making, the recovery price of waste products is the highest and the commission is the lowest. The system coordination can be realized through the contract of "recovery cost sharing and joint revenue sharing". Under this coordination mechanism, the proportion of costs shared by remanufacturers is exactly equal to the share of system profit. And in the coordination mechanism, with the decrease of commission, the proportion of remanufacturers sharing the service cost of e-commerce platform and the proportion of e-commerce platform sharing the profits of remanufacturers will increase.
    Thus it can be seen that in practice, remanufacturers should actively communicate with e-commerce platforms, not only pay attention to their own profits, but also pay attention to the benefits of e-commerce platforms. And, the remanufacturers should take the initiative to share the cost of e-commerce platform recovery services, make appropriate "altruism fairness concern" to e-commerce platforms, and prevent dissatisfaction from the e-commerce platforms.
    The conclusion of this paper can not only enrich the theoretical basis of e-commerce supply chain, but also provide theoretical reference for the recycling decision of EC-CLSC members.
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    The CVaR-based Robust Optimization Model for Retailer's Inventory Management under Supply and Demand Uncertainties
    QIU Ruo-zhen, ZHANG Duo-qi, SUN Yi-meng, GUAN Zhi-min
    2020, 28 (12):  98-107.  doi: 10.16381/j.cnki.issn1003-207x.2018.1013
    Abstract ( 466 )   PDF (2184KB) ( 194 )   Save
    Inventory management under uncertainty has been extensively studied in the past. However, most of literature focuses on finding optimal inventory policies for management under demand uncertainty while as suming no uncertainty on the supply side.As supply chains have been growing considerably, supply uncertainty that often arises from higher variability in suppliers' operations can adversely impact the performance of an inventory system, which suggests a need to simultaneously incorporate supply and demand uncertainties into inventory management.
    In this paper, the problem of inventory management for a risk-averse retailer is studied under both supply and demand uncertainties based on the classic newsvendor model. To cope with the risk caused by uncertainty, the conditional value-at-risk (CVaR) is used to measure the retailer's inventory performance, and then a CVaR-based inventory operational model is developed. Based on which the uncertainties in both the upstream supplier's supply capacity and the downstream market demand are considered.A series of discrete scenarios with unknown probabilities are used to describe uncertainties, and the CVaR-based robust optimization model for retailer's inventory management is established. To solve the proposed robust optimization model, the max-min robust counterpart is presented underthe box uncertainty set to which the unknown supply and demand scenarios probabilities belong. To deal with the non-convexity caused by considering supply and demand uncertainties simultaneously, the so-called canonical duality theory is introduced to equivalently transform the developed robust optimization model into a tractable mathematical programming problem.
    At last, some numerical examples are executed to analyze the impact of different risk aversion levels and uncertainty degrees on retailer's inventory strategy and operational performance. The results show that, although the existence of uncertainty in supply and demand will lead to the loss of inventory performance, the loss is very limited. Specially, the robust inventory strategy derived from the model developed in this paper can ensure a preferable inventory performance for the retailer in most cases. In addition, although the retailer's inventory strategy and performance will deteriorate as the increasing of the risk averse levels and uncertainty degrees, the robust inventory strategy can still ensure the retailer obtain the ideal performance as the increasing of the uncertainty degree under the same risk averse level, which indicates that the model developed in this paper possesses well robustness in dealing with both supply and demand uncertainty.
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    Air Passenger Demand Forecasting Based on a Dual Decomposition Strategy and Fuzzy Time Series Model
    LIANG Xiao-zhen, WU Zhi-kun, YANG Ming-ge, WANG Shou-yang
    2020, 28 (12):  108-117.  doi: 10.16381/j.cnki.issn1003-207x.2019.1100
    Abstract ( 481 )   PDF (1985KB) ( 145 )   Save
    Improving the accuracy of air passenger demand forecasting plays a crucial role in the development of airlines and the whole air transport system,which is of great political and economic significance for all of society but is still a challenging task.In previous studies, individual decomposition strategy has been adopted generally to deal with the complex features inair passenger demand series, so as to improve the prediction performance of the hybrid model. However, the traditional decomposition strategy has some drawbacks such as incomplete feature extraction and the inherent defects in the decomposition method, which lead to the inadequate improvement of the prediction effect of the hybrid model.Therefore, a method for air passenger demand forecasting based on a dual decomposition strategy and a fuzzy time series modelis proposed.Firstly, a seasonal adjustment model (X12-ARIMA) is applied to decompose the original series into a seasonal component and a seasonally adjusted series. Then the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) is used to decompose the seasonally adjusted series into several intrinsic mode functions (IMFs) with different time scales and a residue.After that, the FTS model with fuzzy c-means algorithm (FCM) partitioning intervals is used to forecast each IMF component, the residue and the seasonal component. Finally, the prediction of air passenger traffic is obtained by integrating the above results.Case studies utilizing monthly air passenger demand data collected from Shanghai Pudong International Airport, Chengdu Shuangliu International Airport and Shenzhen Bao'an International Airport are employed as examples. The empirical results show that the dual decomposition strategy proposed in this paper is significantly better than the traditional decomposition strategy, and the proposed model outperforms all of the considered comparison models. The proposed model can be used to improve the accuracy of air passenger demand prediction.
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    Insecurity Information Analysis in Civil Aviation Safety Based on Bayesian Network
    XU Bao-guang, WANG Bei-bei, CHI Hong, SHAO Xue-yan, GAO Min-gang
    2020, 28 (12):  118-129.  doi: 10.16381/j.cnki.issn1003-207x.2020.12.012
    Abstract ( 366 )   PDF (2303KB) ( 149 )   Save
    In view of the unsafe events information collected in aviation safety, the data of the unsafe events found in the safety inspection is studied for the study. The problems found in the safety inspection are classified based on two classification principles, one of which is the factors related to data, and the other of which is related to human. The factors related to the human include training, supervision, staff deployment, information communication, knowledge, skills and several other aspects. The problem is divided into three categories:problems in the management of workflow, problems in the personnel management and problems in the equipment management. What's more, 10 basic reasons are summerized and the fault tree model of the civil aviation safety inspection is built. Besides, the fault tree model is used in the qualitative analysis of the minimum cut and structural importance. Then the NPC algorithm is used to infer the structure of the Bayesian network and study the parameters of the Bayesian network with the help of the EM algorithm. Combining the Bayesian network learning ability with the fault tree model, the Bayesian network model is presented for civil aviation safety inspection. Finally, based on the practical data collected from the airline security check, the impact of various factors is analyzed by use of the Bayesian network and come out with some conclusions. Individual factors, imperfect facilities and information communication are most likely to cause problems in the management of workflow. Management process and the deficiency of related knowledge and skills are most likely to cause problems in personnel management. Individual factors, training and equipment breakdowns are most likely to cause problems in device management. The research of this paper aims to provide an analytical method for the analysis and evaluation of aviation maintenance safety information. The Bayesian network model is constructed to solve the problem of civil aviation safety inspection in reality, which has pretty practical application value.
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    Pricing Strategy and Business Model Determination of Service Platform under Demand and Output Uncertainty
    ZHANG Xuan, CHEN Hong-min, ZHAO Dan
    2020, 28 (12):  130-139.  doi: 10.16381/j.cnki.issn1003-207x.2020.12.013
    Abstract ( 401 )   PDF (1508KB) ( 139 )   Save
    As the development of information and remote technologies, more and more offline service could be accessed. Someservice providers begun using online platforms to enable themselves to directly connect with customers, but sometend to be hired by platform. For the service provider, the platform like an online labor market now. To some service providers,they are not only using the platform but also being hired by the platform. Then, when the platform wants to drive the service providers to provide the desired outcome after their contract is signed, an ex-post problem arises. Meanwhile, the uncertainty of consumer side would also affect.
    Considering the cases that uncertainty on two sides, the service pricing, optimal incentive scheme, business model choosing and conduction of efficiency of platforms are analyzed. Unlike the usual platform that charges both sides a fixed fee, the online-hiring platform shares revenue with one sideaccording to service provider's performance. From equilibriums, it is shown that:(1) When the uncertainty of consumer side is high, pricing of consumer side is low. When the uncertainty of service provider side is high, pricing of consumer side is high. When the self-externality of consumer side is large, the effects of uncertainty of consumer side on service pricing is weakened. When the cross-externality of consumer side is large, the effects of uncertainty of consumer side on service pricing is strengthened. (2) When the uncertainty of consumer side or the uncertainty of service provider side is high, online service firm tend take more risk. (3) When the uncertainty of service provider side exists, the price of consumer side and the salary for service provider are both higher than ever before. And the variance on service provider side is larger than that of consumer side. The platform will take part of the efficiency loss and the amount of this efficiency loss it takes is positive with the cross-externality of consumer side.
    First, to see the uncertainty's impact on pricing in reality. Take online knowledge sharing industry for example. According to the reports of "China online knowledge sharing industry and consumer behavior investigation 2020", the main three platforms is Ximalaya FM, Zhihu and Dedao. And they have different business models, including OHP model where platform hire content provider, and Platform Model where platform is just a place for exchange. Although being the same business model, Ximalaya FM and Zhihu Live have different pricing strategy. With more restrictions and low uncertainty on consumer side, Zhihu Live's pricing on consumer side is higher than Ximalaya FM's pricing. Second, to see the uncertainty's impact on business model, a comparison between service industries is given. Household service with low uncertainty level have more cases signing contract directly with customers than that of knowledge sharing or online literature platform with high uncertainty level.
    Theoretically, by providing a new framework combining the two-sided market and principal-agent theory, the optimal pricing is given under the case of two-side uncertainty, and a conduction mechanism of efficiency loss is presented.In reality, it not only helps platform making pricing decision,but also explains why some kind of online service could not exist due to the heavy moral hazard problem. And, with more uncertainty on both sides, the platform should assume more risk. In more extreme situations, the platform should choose the B2C mode and assume all risks.
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    Optimization Model Analysis of New Order Agricultural Cooperation Model
    CUI Yu-quan, LIU Bing-jie, LIU Cong, QU Jing-jing
    2020, 28 (12):  140-150.  doi: 10.16381/j.cnki.issn1003-207x.2020.12.014
    Abstract ( 346 )   PDF (1001KB) ( 302 )   Save
    According to the current central poverty alleviation policy, taking the poverty alleviation method into consideration, a new cooperative mode of order agriculture is put forward and constructs a new order agriculture optimization model is constructed. First, according to the needs of regional economic development, an agricultural cooperative is established. The farmers took part in the shares in the proportion of land area. The total land area of the cooperative is S. The cooperative obtained profits by negotiating and signing the purchase contract with the agricultural products acquisition company and used part of the profits to pay dividends to the farmers.The cooperative employs professional managers to run the business. In addition, the cooperative will provide a fixed fee,Myuan per unit area, to the farmers according to their shares to ensure their income.The types and quantities of crops planted are determined by the cooperative, which grows a variety of crops and each crop yield is Qi (i=1,…N). At the same time, the cooperative needs to employ workers for planting. In order to improve the enthusiasm of workers, the wages of workers are positively correlated with the output of agricultural products planted. The coefficient is ci3, that is, the total wages of workers provided by the cooperative are $\sum\limits_{i = 1}^N {{c_{i3}}{Q_i}} $. Farmers can also apply to become workers to increase their income. Here it is assumed that the number of workers in the cooperative is a, in which the number of farmers is b. The cooperative and the acquiring corporation sign contracts in accordance with the principle of "guaranteeing the purchase price and following the market". That is, the acquiring price is max(wir,wi). According to the above content, a new three-level new order agricultural supply chain optimization model of "farmers + cooperatives+acquisition companies" was constructed:
    The profit function of the cooperative is:
    πe=ϕ$\sum\limits_{i = 1}^N {[{Q_i}\max (} w_i^r,{w_i}) - C({Q_i}) - {c_{i3}}{Q_i}] - MS$
    The profit function of farmers is:
    πf=(1-ϕ)$\sum\limits_{i = 1}^N {[{Q_i}\max (} w_i^r,{w_i}) - C({Q_i}) - {c_{i3}}{Q_i}] + MS + \frac{{b\sum\limits_{i = 1}^N {{c_{i3}}{Q_i}} }}{a}$
    Here,the C(Qi) is the cost function.
    Under the measurement criteria of conditional risk (CVaR), the specific benefits of cooperatives under different risk avoidance degrees are obtained.On the premise of ensuring the income of farmers and cooperatives, the corresponding constraint optimization model is established.Use the Lagrange function and the corresponding KKT conditions, then obtain the minimum land area that farmers can gain more benefits from joining the cooperative is
    ${S_1} = \frac{{\max ({w^r},w) - {c_1}}}{{2{c_2}q}}$
    And the minimum fixed fee that the cooperative provide for the farmers is
    $M > \frac{{q\phi (\max ({w^r},w) - {c_1})}}{2}$
    In the part of case analysis, specific values are assigned to these parameters and prove the correctness of the conclusion by formula calculation. These conclusions provide a theoretical basis for the establishment of cooperatives, and also provide solutions to the low fulfillment rate in agricultural contract.
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    Dynamic Routing-allocation Optimization of Post-disaster Emergency Resource Considering Heterogeneous Behaviors
    ZHU Li, CAO Jie, GU Jun, ZHENG Yi
    2020, 28 (12):  151-161.  doi: 10.16381/j.cnki.issn1003-207x.2020.12.015
    Abstract ( 443 )   PDF (2373KB) ( 126 )   Save
    In recent years, various frequently-occurred disasters has brought severe threats to human life and property security. As for the humanitarian-based emergency relief operations, in addition to the efficiency, effectiveness and equity issues, the impact of heterogeneous behaviors of emergency participants on the entire humanitarian relief decision-makings also draws much attention, such as the differentiated psychological pains or negative emotions suffered by victims in the face of disasters, or the diverse decision preferences shown by various decision-makers, etc.
    The impact of heterogeneous behaviors on emergency relief operations is explored from two perspectives. On one hand, we focus on the psychological sufferings of different levels resulted from the unmet resource needs in time in the multi-stage emergency relief. By using the deprivation cost as economic loss valuation of the psychological sufferings, we quantitatively characterize diverse victims' pains or differentiated trauma and incorporate its effect into the social cost, i.e., the decision-making goal in emergency relief operations. On the other hand, in the decision-making process of post-disaster emergency resourcerouting-allocation, the joint chance-constrained programming is used to characterize decision-makers' requirements for the balance of multi-stage rescue supply and demand. By means of different confidence levels, we pay attention to different relief attitudes of decision-makers with heterogeneous preferences in post-disaster operational decisions. Combining with the dynamic balance constraints between supply and demand captured by the joint chance-constrained programming, a multi-stage post-disaster routing-allocation optimization model is built considering heterogeneous behaviors of victims and decision-makers, for minimizing the social costs composed of emergency transportation cost and heterogeneous psychological cost of victims.By taking 2008 WenChuan earthquake as a case, a genetic algorithm is applied for model solution. By combining real data with some set parameters, our model is compared with traditional emergency routing-allocation solutions without considering heterogeneous behaviors. Based on the analytical results, the effectiveness of our model and algorithm is verified. Besides, sensitivity analysis of key parameters is also performed, including relief frequency, number of rescue points, the waiting-time period of relief service, and heterogeneous preference of decision-makers.
    Through model solving and parameter analysis, the following conclusions are demonstrated:(1) The traditional emergency decision-making models that do not consider the heterogeneous psychological sufferings of victims may only be suitable for the fast and efficient emergency relief operations.If the relief frequency is not fast enough, the impact of the victims' heterogeneous psychological sufferings cannot be ignored. (2) Compared with the traditional fixed penalty (FP) model, our routing and allocation (RAP)model has more advantages in rescue investment, rescue in time, and relief demand satisfaction.In particular, our emergency decision-making can give priority to rescue in severe disaster areas, mainly due to our consideration of the psychological sufferings of victims who have not been rescued in a timely manner.(3) In order to improve the efficiency in emergency relief operations, it is necessary to emphasize some prevention and control measures, such as increasing emergency resource investment and strengthening regional disaster-resistant capacityin the normal state of emergency management.As long as sufficient resources are available,the emergency needs can be met within a certain time limit.However, decision-makers still need to comprehensively think about whether it is worth investing in emergency resource, according to the marginal efficiency of resource investment in emergency relief decision-makings.Our research results provide some managerial suggestions for establishing an effective and efficient emergency relief system.
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    An Optimization Model for Emergency Shelter Location and Relief Materials Allocation Considering Human Suffering
    WANG Xi-hui, ZHANG Wen-xin, YU Yu-gang, LIU Bing-bing
    2020, 28 (12):  162-172.  doi: 10.16381/j.cnki.issn1003-207x.2019.2006
    Abstract ( 403 )   PDF (2166KB) ( 396 )   Save
    The large-scale disasters have seriously destroyed or collapsed the original social and economic systems in the affected areas. After the disaster, the currency could not circulate, the infrastructure is damaged and the supply chain of economic market is disrupted. These problems often lead to the shortage of emergency supplies. Furthermore, the lack of basic survival and living materials will lead to the discomfort of individuals and bring anxiety and pain to the affected people. To reduce the human suffering and conduct the relief operation effectively, it is urgent for decision makers to incorporate beneficiaries' perception into total cost of emergency relief. In this paper, a numerical rating scale (NRS) is designed to construct a human suffering function, which can describe the suffering perception cost of the beneficiaries.According to the principles in welfare economics, the concept of social cost is first proposed in emergency management. It refers to the sum of logistics cost and suffering perception cost. An integrated optimization model is proposed to combine evacuation and resettlement of the affected people, location of temporary shelters and distribution of relief materials, whose objective is to minimize total social cost. The classical mixed integer programming method and improved genetic algorithm are designed to solve the model effectively. Finally, the performance of the two methods is compared by numerical simulation.Comparisons of three simulation scenarios indicate that the number of transferrable population obtained by using genetic algorithm is larger and the total social cost is smaller as the increase of the maximum rescue time. The model and algorithm are applied to the case of 2014 typhoon rammasun in Hainan province in China. The results further show that in order to maximize the rescue effectiveness, more shelters need to be built and sites should be located near the affected areas.In addition, each shelter needs more transport vehicles to evacuate more people in a shorter rescue time. It provides an effective suggestion to help post-disaster managers to enhance the effectiveness of emergency rescue operations.
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    The Impact of Urban Low-carbon Transportation System on the Improvement of The Structure of Energy Consumption——Evidence from 14 Cities in China
    ZHANG Xue-feng, SONG Ge, YAN Yong
    2020, 28 (12):  173-183.  doi: 10.16381/j.cnki.issn1003-207x.2020.12.017
    Abstract ( 369 )   PDF (1357KB) ( 189 )   Save
    In order to achieve the international goal of energy conservation and carbon reduction, China has actively improved the urban public transport system to control carbon emissions. The urban low-carbon transport system development's influence on the energy consumption structure was discussed by this essay. A random effect variable coefficient model that contains 14 Chinese city's panel data from 2006 to 2016 has been built. It is found that the government can change the demand structure of residents' transportation through public transportation pricing, so as to optimize the energy consumption structure. In urban low-carbon transportation system, railway system plays an improved role in optimizing energy consumption structure. The increase in private car ownership will hinder the optimization of energy consumption structure. The impact of bus on energy consumption structure will vary with the degree of urban development. Improving the urban low-carbon transportation system can optimize the energy consumption structure. The government should expand the fiscal expenditure, improve railway system and make reasonable bus (electric) operation system. In addition, appropriate restrictions should be put on the purchase of private cars with fuel. Meanwhile, preferential policies for public transport and new energy vehicles should be improved.
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    Multi-attribute Auctions for Online Services Procurement Considering Renegotiation
    LI Zhi-peng, HUANG He
    2020, 28 (12):  184-195.  doi: 10.16381/j.cnki.issn1003-207x.2020.12.018
    Abstract ( 323 )   PDF (1144KB) ( 48 )   Save
    Motivated by the rapid growth of the online outsourcing market, a multi-attribute auction model for online service outsourcing is studied, in which multiple potential suppliers bid service quality and service price, and renegotiation may take place after the determination of auction winner. To investigate the effects of service content renegotiation on the players' decisions and expected profits, both a scenario without renegotiation and one with renegotiation are examined and compared. Results show that, without renegotiation, the suppliers' service quality and information rent are increasing inthe initial service contentannounced by the buyer. However, in the scenario withrenegotiation, although the buyer's weighting of service quality increases inthe initial service content, the suppliers' service quality, information rent and buyer's expected profits are not affected by the initial service content. In other words, the regulation function of the initial service content is completely substituted by renegotiation. Furthermore, comparisons show that the renegotiation option leads to higher service quality and higher ex post service content, and it makes the buyer, the winning supplier and the platform better off. The study contributes to the literature by providing a buyer-determined auction model for online service outsourcing considering renegotiations, and it provides insights on the value of renegotiation for online service providers, buyers and transaction platforms.
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    The Impacts of Privacy Concerns on Social Login
    CHENG Yan, MEI Shu-e, ZHONG Wei-jun
    2020, 28 (12):  196-207.  doi: 10.16381/j.cnki.issn1003-207x.2020.0052
    Abstract ( 338 )   PDF (1388KB) ( 89 )   Save
    By introducing social login, the platform can attract internet users to log in. Meanwhile, "social login" can improve the platform's advertising targeting ability because of sharing users' personal data. However, because of users' privacy concerns, social login may cause users not willing to use the platform. Hence, it is important to study the effects of internet users' privacy concerns on social login to help the platform make its social login strategy. So far, the existing literatures have not solved the impacts of user's choice of social login on the platform/enterprise's social login provision, and the literatures on platform/enterprise's choice of social login has not considered the influence of user's privacy concerns.
    In this paper, the effects of Social Login on the platform's targeted targeting strategy are studied in a monopoly market. There are two types of Internet users on one side of the platform, the first type whoare called "privacy sensitive users" with high privacy concerns andthe second type who are called "privacy neutral users" with low privacy concerns.Meanwhile, there are plenty of advertisers on the other side of the platform. These advertisers choose to targeted advertise by measuring the platform's targeting ability, which is determined by advertising targeting capability and the number of Internet users on the platform. A four stage game-theoretic modelis constructed:In the first stage, the platform determines whether to open Social Login. In the second stage, the platform determines its advertising targeting capability. In the third stage, advertises determined whether to targeted advertise on the platform or not. In the fourth stage, Internet users determine whether to login the platform or not and further choose the way to login, using Social Login or Platform Account Login.
    The equilibriums are derived through backward induction method. By analyzing the equilibriums, propositions were given from three thresholds. Firstly, due to the existence of user privacy concerns, it is suggested thatthe platform maynot provide social login. If the proportion of privacy sensitive users is relatively high, whensocial login brings a higher targeting promotion to the platform, providing social login will reduce the platform's revenue.Secondly, it also indicated that ifthe platform provides social login, social login has the following effects on the platform's advertising targeting capabilitywhen there are more privacy sensitive users in the market:the platform's advertising targeting capabilityincreases first and then decreases with the increase of targeting promotion. When there are more privacy neutral users in the market, strengthening targeting promotion discouragesthe platform from increasingadvertising targeting capability. In addition, with the strengthening targeting promotion, the platform's profit is concave intargeting promotion. Thirdly, it is shown that when targeting promotion brought by social login is low, social login cannot help the platform attract more users.
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    Dynamic Evaluation Method Based on Vertical Projection Method
    LI Mei-juan, YUAN Ning, XU Lin-ming
    2020, 28 (12):  208-219.  doi: 10.16381/j.cnki.issn1003-207x.2019.1564
    Abstract ( 357 )   PDF (1633KB) ( 93 )   Save
    In order to evaluate multiple systems at different times, this paper proposes a new dynamic evaluation method. Firstly, on the basis of the traditional ideal solution, a Vertical Projection Method is proposed to measure the degree of closeness to the ideal solution by using "Vertical Distance" instead of "Euclid Distance". Then the two-dimensional data with time series data is extended to three-dimensional data to construct a dynamic evaluation method based on vertical projection method. The difference degree and the values growth degree of evaluation index values are both considered by this model. Finally, the values and sequencing results of the evaluation objects are calculated by quadratic-weighted method. The values and sequencing results of the evaluation objects at a certain time and the overall evaluation values and sequencing results of the evaluation objects at a period of time are both obtained by this method. In order to prove the stability and effectiveness of the model in this paper,this dynamic evaluation method is used to evaluate the innovation capability of eight comprehensive economic zones in China.The data on the index system for the evaluation of innovation ability comes from China statistical yearbook, China statistical yearbook on science and technology, and the website of People's Bank of China,meanwhile, the sensitivity analysis of preference parameters to the ranking results and the comparison of other dynamic evaluation methods are discussed with this examples.The research of this paper contributes to enrich the theory and application of dynamic evaluation method.
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    A Possibility Degree Model for Ranking Interval Numbers under Non-uniform Distribution and its Application
    Gong Ri-zhao, Pan Fen-ping
    2020, 28 (12):  220-230.  doi: 10.16381/j.cnki.issn1003-207x.2020.12.021
    Abstract ( 324 )   PDF (1164KB) ( 70 )   Save
    For any two interval numbers a=[a-,a+] and b=[b-,b+] from different sources, comparing their sizes is one of the basic problems that the academic circles have been exploring continuously.In this paper, the possibility degree of interval number a=[a-,a+] larger than interval number b=[b-,b+] is defined as P{a>b}$ \buildrel \Delta \over=$P{(x,y):x>y,xa,y∈b}. Under the assumption that the values in interval[a-,a+] and[b-,b+] obey the general distribution, a new probability calculation model of interval number ranking is constructed by using the definition of two-dimensional probability space distribution. The calculation model constructed by previous scholars is revised and generalized.Based on the new calculating model of possibility degree, the previous definitions of the equality of two interval numbers are revised, and the concepts of interval number shape and so on are put forward. At the same time, the reflexivity condition of possibility degree and the comprehensive ranking method of interval numbers are further revised. The theory is applied to the multiple attribute decision making problem, and the basic decision process is given. The feasibility and rationality of the new theory and method are presented by calculating the case decision-making problem, which has a good application value.
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