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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 January 2018, Volume 26 Issue 1 Previous Issue    Next Issue
    Articles
    The Asymmetric Shock of Monetary Supply on Industry Economic Under the New Normal: Concurrently Discuss of Scenario Design and Analysis of the Shock Path
    LIU Han, HUANG Wei-ting, HE Yan-fei
    2018, 26 (1):  1-12.  doi: 10.16381/j.cnki.issn1003-207x.2018.01.001
    Abstract ( 1042 )   PDF (6082KB) ( 876 )   Save
    The asymmetric effects of monetary policy shocks to industrial output and price has great influence in the direction, intensity and rhythm of macroeconomic policy, and could improve the pertinency, flexibility and forward-ooking of monetary supply policy. The local projection is used to calculate the response of industrial output and price to monetary supply shocks under different regime of industrial output, price and money supply. The empirical results show that the influence of monetary supply shock to industrial output is uncertain, and has a neutral characteristic overall. The scenario analysis also confirms the above conclusion. There is an asymmetric impact of money supply on the industrial price, not only under different regime of the variables, but also before and after the new normal. The overall performance is that the shock has an effect on short-term, which is however invalid in a long-term. The results of scenario designing and analysis show that the use of monetary policy to stimulate normal under the new normal is not desirable, Its impact on the industrial output growth is uncertain and neutral, while it has a significantly positive influence on the industrial prices growth. The possible outcomes is industrial stagflation, which is the industrial output stagnated, while industrial prices soaring. Therefore, a new growth point and mechanism need to be found from the supply side of industrial, such as industrial upgrading, industrial technology innovation and other actions.
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    Research on Technological Innovation Resource Allocation Efficiency and Its Influencing Factors in High-end Equipment Manufacturing Industries——Based on the Empirical Analysis of the Two-stage StoNED-Tobit Model
    FAN De-cheng, DU Ming-yue
    2018, 26 (1):  13-24.  doi: 10.16381/j.cnki.issn1003-207x.2018.01.002
    Abstract ( 1282 )   PDF (1767KB) ( 777 )   Save
    Under the new normal, high-end equipment manufacturing industries are becoming more and more important in promoting the steady growth of the national economy, accelerating the transformation and updating of the traditional industries, and enhancing the core competence of the industry chain. However, the rationality and validity of the allocation of the technological innovation resource has become the main bottle-neck restrictions of the sustainable development of the industries. Based on the evalue chain theory, the technological innovation activities are divided into two stages from the perspective of input-output, including technology research and development and technology transformation. Then, a two-stage stoned model is constructed to measure and compare the technological innovation resource allocation efficiencg of high-end equipment manufacturing and industries by using the industry panel data covering the sample period of 2011-2014. Meanwhile, the tobit model is used to analyzing the key factors affecting the efficiency via the perspective of the industrial organization. The empirical results show that the total efficiencg and stage efficiency differ in degree and volatility among these sub-industries and the efficiency of technological research and development stage is so low that it limits the optimization of the total efficiency level. By identifying the above factors, it turns out that the enterprise's size has negative effect on the efficiency of the technology transformation stage. The government support has remarkably negative influence on both the total efficiency and two stage efficiencies. Based on the above analysis results, this paper puts forward some policy suggestions on dealing with present situation of the allocation of the technological innovation resources are provided.
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    Parameter Calibration and Estimation of Levy-LIBOR Market Models Based on Monte Carlo Simulation
    LIU Feng-qin, JIN Yu
    2018, 26 (1):  25-34.  doi: 10.16381/j.cnki.issn1003-207x.2018.01.003
    Abstract ( 1135 )   PDF (1921KB) ( 951 )   Save
    Nowadays, the standard LIBOR market model(LMM) is widely used to model the rate's stochastic process. But LMM shows much deficiencies. There will be a lot of improvement in the extensions of the standard model to make it better predict dynamic characteristics of forward rates. Based on analysis framework and applicable limitation of LMM with stochastic volatility (SV-LMM), furtherly, the Levy jump process is and intorduced, one kind of new multiple factor non standardized Libor market model (Levy-SVLMM) is set up in. Firstly, this paper calibration methods of the LIBOR market model are studied. Two common calibration tools interest-rate cap and swaption are introduced in the first place. Then traditional parametric methods and one new non-parametric method are used to calibrate model's instantaneous correlation matrix respectively. Thirdly, the parallel adaptive Markov Chain Monte Carlo method is employed to estimate parameters, and a parallel adaptive Metropolis-Hastings sampling algorithm is employed to improve the convergence efficiency. Lastly, the new Adaptive Markov Chain Monte Carlo method is used to estimate different Levy-LIBOR market model parameters and compared with normal one and the different paths of forward LIBOR rates are simulated and analysied.The empirical research conclusions are:empirical results that Levy jump stochastic volatility LIBOR model can more accurately describe the forward rate dynamic trend than standard LIBOR market model and stochastic volatility LIBOR market model. on long-term interest rate volatility calibration, segment-fixed structure is in line with market conditions. And for the calibration of correlation coefficient matrix, the non-parametric Monte Carlo method could get the minimum estimation error and the best market adaptability.
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    Optimal Credit Contract Design for a Capital-constrained Supply Chain Incorporating into Risk Aversion
    JIN Wei, LUO Jian-wen
    2018, 26 (1):  35-46.  doi: 10.16381/j.cnki.issn1003-207x.2018.01.004
    Abstract ( 1326 )   PDF (1901KB) ( 911 )   Save
    When facing capital constraints, a retailer fails to procure or order optimally, which not only significantly influences his own profitability, but also harms the competitiveness of the upstream supplier. Therefore, as a core firm of a supply chain, the supplier generally has an incentive to offer trade credit to alleviate the retailer's capital constraints problem. As a financing tool, trade credit has received extensive attention in supply chain finance area. However, the majority of extant literature focuses on the optimal trade credit contract decision by assuming that the credit-offer (i.e., supplier) is risk-neutral and the credit-receiver (i.e., retailer) only uses trade credit to finance inventory. In fact, the supplier may limit the retailer's credit line for the reason of controlling the potential loss risk. As a result, the capital-constrained retailer may adopt other financing tools such as bank credit besides trade credit to satisfy his financing need.
    Based on the practical background, two interesting questions arise, that is, how a risk-averse supplier designs a trade credit contract to alleviate the retailer' capital constraints and how the retailer's financing structure is influenced by the supplier's risk aversion. To answer the two questions, a two-echelon supply chain consisting of one risk-averse supplier and one capital-constrained retailer is considered. Based on the classical supply chain finance model, the financing decision model consisting of a supplier, a retailer and a bank is built. By adopting backward induction and non-linear optimization method, the retailer's optimal order decision is first solved and then the supplier's optimal trade credit contract design is analyzed. In addition, the bank's optimal interest rate can be determined on basis of competitively priced principle.
    The results show that:when the supplier's risk aversion is lower than a critical threshold value, he prefers to offer full credit to the retailer, and as a result, the retailer's financing structure is trade credit; however, when the supplier's risk aversion is higher than the threshold value, he prefers to offer partial credit to the retailer, and consequently, the retailer's financing structure is the portfolio of bank credit and trade credit. To examine the theoretical results, the data used in the existing literature is further used to simulate the corresponding conclusions. Our research can enrich the existing supply chain finance literature, and can provide decision support for the supply chain core enterprise and the bank.
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    Research on Credit Risk Mitigation Mechanisms of Peer-to-peer Lending Based on Social Network
    YANG Li, ZHAO Cui-cui, CHEN Xiao-hong
    2018, 26 (1):  47-56.  doi: 10.16381/j.cnki.issn1003-207x.2018.01.005
    Abstract ( 1418 )   PDF (1240KB) ( 859 )   Save
    Risk management is the core issue to determine the sustainable and healthy development of financial innovation. Based on the information economics and game theory, an information asymmetry mathematical model is set up to analyze the acting mechanism and working conditions of social network in mitigating P2P lending's credit risk. It is proved that with the introduction of social network, the credit risk of P2P lending can be mitigated by three mechanisms of social network, which are ex ante information acquisition mechanism, joint liability mechanism and ex post default constraint mechanism. Those constitute unique credit risk mitigation mechanisms of social network, which can effectively relieve adverse selection caused by imperfection of credit system as well as moral hazard caused by lack of effective monitoring mechanism and lack of default constraint mechanism in P2P lending market. Joint liability, dynamic incentive, the strength of supervision, sanctions, constraints of default intensity and the mining of social information are thedetermining factors to the risk mitigation level of social network. The theoretical frameworks are first proposed for credit risk mitigation of social network in P2P lending, including the developed social network theory and credit risk management theory,which provide new scientific evidence and theoretical support for risk control trial with social network in P2P platform. Great theoretical importance is provided to understand and grasp risk mitigation mechanisms of social network, as well as to use social network credit risk management.
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    Forecasting Realized volatility of Chinese Stock Index Futures based on Approved HAR Models with Median Realized Quarticity
    CHEN Sheng-Li, LI Yi-Jun, GUAN Tao
    2018, 26 (1):  57-71.  doi: 10.16381/j.cnki.issn1003-207x.2018.01.006
    Abstract ( 1481 )   PDF (6700KB) ( 631 )   Save
    Chinese stock index futures experienced an unusual bull and bear markets around 2015, but its volatility dynamic is a mystery for investors and regulators. Modeling and forecasting volatility is a feasible way to reveal volatility transmission process and track market risk. In this paper, 4 HAR-type models involving jumps, realized semivariances and signed jumps are established to forecast the realized volatility of CSI 300 index futures. Based on 4 basic HAR-type models, HARQ-type models and HARQF-type models are proposed by adding correction term of median realized quarticity (MedRQ). During the modeling process, two decompositions of realized volatility including continuous and jump variances, upside and downside realized semivariances are considered. To reduce the robustness of market microstructure noise, the optimal sampling frequency for calculating realized volatilities is determined by the minimum MSE criterion, the statistic Zmed of ADS jump test, realized semivariances and signed jump are revised based on realized kernel estimator. The newly MCS test is employed to evaluate the out-of-sample forecast performances. In-sample and out-of-sample analysis of forecast models are carried out on CSI 300 index futures, which shows important conclusions:1)Most of the predictable variation in realized volatility stems from continuous volatility rather than jump variance, and future realized volatility is more related to historical downside semivariances (bad volatility) than upside semivariances (good volatility); 2) Good volatility and bad volatility exhibit asymmetric impact effect that good (bad) volatility generate negative (positive) impact on future realized volatility; 3)Decomposition of upside and downside realized semivariances outperforms that of continuous and jump variances; 4) MedRQ can significantly enhance the forecast ability of HAR-type models, HARQF models outperform HARQ models on in-sample performances, while HARQ models achieve better out-of-sample forecast accuracy; 5) Signed jumps bear valuable information of both market volatility and directions, and HARQ-RV-SJ is the best model among all forecast models specified in our paper. Our findings have import implications for investors and policymakers to grasp the volatility and risk of Chinese stock index futures.
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    Investment Horizon, System Risk Value and the Sensitive Effect
    ZHAO Ning, YU Fang-kun, YOU Shen, WANG Zhen-shuang
    2018, 26 (1):  72-80.  doi: 10.16381/j.cnki.issn1003-207x.2018.01.007
    Abstract ( 1036 )   PDF (5048KB) ( 631 )   Save
    The effects of investment horizon on the estimate of the systematic risk are first investigated by Brennan et al,(2012). In general, the true investment horizon is unknown. The empirical work will overestimate the coefficient of the systematic risk based on the observed horizon. The copula Bayesian estimation approach is proposed to get the posterior distribution of the coefficients of the system risk beta and the investment horizon ratio gama in the Fama-French three factor model. The potent problem of the traditional Bayesian estimation is that the assumption of normal likelihood function ignores some fluctuations such as high peak and fat tail relative to kurtosis and skewness, which have been frequently, reported in financial data analyses. The copula Bayesian approach instead of the traditional Bayesian estimation is built to consider the pattern of the data with the strong correlation and the non-normal distributions. The reason why the copula function is chosen is to fit the pattern of the data. In the empirical work,the interaction of the system risk and the investment horizon is analyzed in 25 portfolios from 150 different data. Compared with the U.S. data, the correlation of the systemic risk and investment horizon is negative, and the frequency of the true horizon is higher than observed one in China. With the increase of the size of the company, the effect of the investment horizon is obviously magnified. And the appearance leads to the estimation bias of the systemic risk.
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    Optimal Pricing Model of Stock Loan-to-value Ratio Considering Liquidity Risk and Portfolio Rebalancing Risk
    SHI Yu-shan, LIU Hai-long, HU You-qun
    2018, 26 (1):  81-89.  doi: 10.16381/j.cnki.issn1003-207x.2018.01.008
    Abstract ( 427 )   PDF (2376KB) ( 741 )   Save
    The number that stock price is near or below the warning line in stock pledge business exceeds 300 times in 2015, which means the principal of pledge is difficult to fully recover. In this context, it is particularly important to set stock loan-to-value ratio reasonably and flexibly for reducing the risk of the pledgee effectively and suppress the market panic, which aims at avoiding similar extreme events.
    However, the stock loan-to-value ratio is often calculated simply based on the stock volatility in theory and practice, while ignoring that the impact of liquidity risk and portfolio rebalancing risk in terms of leverage and cross-shareholding. Given that, the influence of leverage and portfolio rebalancing on stock loan-to-value ratio is further researched based on the liquidity risk model of Obizhaeva(2008) and the study of leverage and portfolio rebalancing of Adrian et al.(2010) in the paper. It is revealed that the stock loan-to-value ratio is not only affected by the volatility, but also closely related to the liquidity risk and portfolio rebalancing risk. And the portfolio rebalancing risk is reflected in two aspects:the leveraged investor's leverage level and the portfolio structure between the leveraged investor and the pledgor. Finally, a pricing model of stock loan-to-value ratio considering volatility, liquidity and portfolio rebalancing is built.
    In order to obtain the numerical solution of the stock loan-to-value ratio, Monte Carlo method is used to simulate the movement path of the price of the underlying. The impact of two key parameters of the leverage and the liquidity shock on stock loan-to-value ratio is further analayzed. The results show that the stock loan-to-value ratio is significantly affected by leverage and liquidity shock. Compared with the traditional model which is based on forecasting volatility only, the stock loan-to-value ratio according to pricing model put forward in the paper is significantly lower than the former. It means that the proposed model can effectively solve the problem of adjusting stock loan-to-value ratio reasonably when high leverage exists in stock market.
    In summary, there are two main contributions in the study. Firstly, the defect that the pricing model only considering the risk of volatility, while ignoring the risk of liquidity and portfolio rebalancing is made up. The model can effectively improve the pricing accuracy, especially in the situation that high leverage in the market. Secondly, the fact that the leveraged investor's leverage level and the liquidity shock are significantly related to stock loan-to-value ratio is further verified. When considering the negative impact caused by the phenomenon of price jump in financial market, the optimal stock loan-to-value ratio should be further reduced.
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    Study on Optimal Allocation of Issuance Amount of Local Government Bonds
    YIN Qi-hua, CHEN Zhi-bin
    2018, 26 (1):  90-97.  doi: 10.16381/j.cnki.issn1003-207x.2018.01.009
    Abstract ( 372 )   PDF (892KB) ( 115 )   Save
    Although the mode about issues and repayments by itself of local government bonds can effectively solve the problem about the non-conformance of the issue subject and the debt service subject, yet the high level government still faces great information asymmetry and moral hazard in the allocation of bond resources. Because China nation state carries on the quota management to debt balance of the local government, the provincial government is faced with the problem of how to allocate the new municipal government bonds under constraint conditions of ∑xtiA1.The ultimate goal is to minimize the probability of government debt default and maximize its benefits. In light of the Structure Model and the Contract Theory,the allocation decision model of local government bond issuance is constructed from the perspective of the high-ranking local government. A prerequisite is set as one of the constraint conditions on the minimum default risk or the maximum benefit of the government bond issuance, and approaches are stuied to be revealled to the realization of another goal. However, this depends on a reasonable determination of the weight of the two objectives. These two targets are used to give the corresponding weights by the weight coefficient transformation method. The multiple targets about the minimum default risk and the maximum benefit of the government bond issuance are synthesized into a single global target, and then an optimal solution set is sought by target optimization. Under the framework of the reasonable matching of income and risk, by using the genetic algorithm, into the bond configuration optimization scheme between the provincial government and municipal government based on the weighted dual objective. The results show that multi-objective optimization can realize the Pareto improvement of government bond resource allocation on the basis of the minimum default risk and the maximum benefit of the government bond issuance. A provincial government with 15 municipal cities included is taken as an example. The provincial government will distribute bond issuance amount based on the size of the assets of the municipal governments. This will be of great benefit to the study of debt risk dominances and the rational allocation of government bonds. Accordingly, it is conducive to the scientific management of China's increasingly serious debt risk of local governments.
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    Designing of Write-down Bond and Optimal Debt Structure of Bank Under Tax-rate Uncertainty
    LUO Peng-fei, GAN Liu, YANG Zhao-jun
    2018, 26 (1):  98-106.  doi: 10.16381/j.cnki.issn1003-207x.2018.01.010
    Abstract ( 371 )   PDF (2644KB) ( 100 )   Save
    In the recent financial crisis, many banks have experienced financial distress, under which they were not able to raise significant new funds from the market through a conventional approach. To solve such kind of problems, two new interesting classes of debt with loss-absorbing features, write-down debt and contingent convertibles (CoCos), have drawn much attention of researchers and regulators. According to the statistics, the 50 percent of debt with loss-absorbing features issued in Europe is write-down debt. For example, RaboBank issues 2.0bn USD write-down debt with perpetual term in November, 2011, Barclays issues 3.0bn USD write-down debt with ten years maturity in November, 2012 and Credit Suisse issues 2.5bn USD write-down debt with ten years maturity in December, 2013. The banks in China have stepped up issuance:from nothing in 2012 to RMB 385 bn yuan of the write-down debt with 10 years maturity by December 2014. The maturity of the write-down debt is long-term or perpetual, however, the tax rate will change during the maturity of debt. For example, the average of corporate statutory tax rates has fallen from 31.4% to 25.9% over the 1999-2008 period. So, the impact of tax-rate uncertainty on bank's financing policy is important. In this paper, the designing of write-down bond and the optimal debt structure of bank under tax-rate uncertainty are considered.
    It is assumed that the capital structure of bank is composed are considered equity, straight debt and a write-down debt. The before-tax cash flow x dynamics is described by the following geometric Brownian motion dXt=μXtdt+σXtdZt, where μ is the risk-adjusted drift parameter, and σ is the volatility rate.Zt denotes the Brownian motion under risk neutral measure.
    When the bank is alive, the straight debt has a coupon rate Cs and the write-down debt has a coupon rate Cw. Once the bank suffers from a credit event, the coupon of write-down debt is a automatically reduced by a fraction equal to δ. The write-down debt can be written down only once. When the bank defaults, two bondholders gain the remaining value of bank by equal priority rule. We assume that the tax rate follows a Poisson process. Given an initial tax rate τ0, at any short time interval dt there is a probability λdt that the tax rate changes to τ1. We examine how the bank chooses the optimal debt structure and the optimal write-down scale under tax-rate uncertainty.
    Firstly, according to the dynamic programming, the value of securities of bank under tax-rate uncertainty is provided analytically. Secondly, the optimal debt structure of bank is also conidered and the closed-form expression is given. Lastly, numerical analyses and implications are provided.
    In our numerical analyses, the base parameter values are similar to Andrikopoulos and Fedele et al(2011)based on empirical evidence. Our results show that the optimal coupon of straight bond is convex function of write-down scale,increases with the expected time to occur a tax cut, and a tax-rate cut reduces the optimal of straight bond. The optimal coupon of write-down bond first increases and decreases with write-down scale and the impact of the tax cut and the expected time to occur a tax cut on it is ambiguous. It is also found that the total value and the optimal leverage are first increases and decreases with write-down scale. The theory basis is provided for the feasibility of replacing the business tax with a value-added tax. What's more, reference about how the decision maker flexibly chooses the appropriate write-down scale is provided by maximizing total value and the effect of tax-rate.
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    Decisions and the Value of Government Compensation in Agricultural Supply Chain under Trade Credit and Uncertainty of Production Yield
    HUANG Jian-hui, YE Fei, ZHOU Guo-lin
    2018, 26 (1):  107-117.  doi: 10.16381/j.cnki.issn1003-207x.2018.01.011
    Abstract ( 417 )   PDF (1689KB) ( 203 )   Save
    Because of the high risk of agricultural supply chain financing and high cost of financing, the plight of agricultural supply chain financing becomes increasingly prominent, and seriously affects the development of agricultural modernization. To solve the supply chain financing difficulties of agricultural supply chain consisting of a capital-constrained farmer and an agribusiness firm, two different Stackelberg game models, in which the agribusiness firm as the leader and the farmer as the follower, are proposed respectively by considering bankruptcy risks of the farmer in supply chain financing under trade credit and uncertainty of production yield. In the meanwhile, the comparative analysis on the farmer's optimal decision making is performed, and the government compensation values for both the social welfare and the supply chain are discussed finally. The fingdings can be drawn as follows:(1) the smaller the input-output rate of the bad year is, the more favorable supply chain financing model, in which the farmer has the risk of bankruptcy, is to the farmer; (2) the government compensation policies can reduce the agribusiness firm's risk of advance payment and create more social welfare; (3) the government compensation policies can also motivate the farmer to design the proper input quantity of production to promote the supply chain efficiency, even to realize the optimal expected profit of centralized decision-making under certain conditions, and create more value for the capital-constrained supply chain. Finally, the numerical study is given to demonstrate the conclusions. Our research results not only provide some managerial insight to the decision-making of the farmer, but also help us have a new understanding of government compensation policies and recognize the importance of government compensation.
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    Recycling and Pricing Strategies of Closed-Loop Supply Chain by the Leader of Third-Party Recycler
    FENG Zhang-wei, XIAO Tiao-jun, CHAI Cai-chun
    2018, 26 (1):  118-127.  doi: 10.16381/j.cnki.issn1003-207x.2018.04.012
    Abstract ( 437 )   PDF (2539KB) ( 219 )   Save
    Many suppliers and manufacturers allow a third-party recycler to perform recycling operations of Waste Electrical and Electronic Equipment, then encourage the third-party recycler to disassemble these end-of-life products either for products remanufacturing or parts remanufacturing, which is of great importance in reducing environment pollution and promoting the reuse of resources. In this paper, recycling and pricing strategies of the third-party recycler are investigated in a closed-loop supply chain with two-echelon remanufacturing. Stackelberg game models of a closed-loop supply chain with two-echelon remanufacturing consisting of one supplier, one manufacturer, and one third-party recycler are developed. The returns price, effective recovery ratio, and recycling effort level are integrated within a modeling framework.The positive effect of two-echelon remanufacturing on effective utilization of the invalid parts,and its negative effect on the probability that the third-party recycler should handle the dismantling cost,are explicitly modeled. By the comparison of equilibrium decisions and profits under two remanufacturing strategies, it is found that (i) high quantity and the effective recovery ratio will contribute to the third-party recycler's profit; and (ii) remanufacturing strategies can reduce the wholesale price and sale price, and promote the demand, while the profits may not be improved; and (iii) when the effective recovery ratio under product remanufacturing is higher than that under two-echelon remanufacturing, recyclers' decisions and profit mainly depend on invalid parts' recycling price. Recyclers' decisions and profit under product remanufacturing turns better if the recycling price of invalid parts is sufficiently low. Otherwise, the recyclers' decisions and profit under two-echelon remanufacturing turns better. Moreover, numerical studies are employed to gain more intuitive insights. The field of two-echelon remanufacturing strategies are extended in the closed-loop supply chain and some new results are found. These new results may propose some constructive suggestions for the dominant third-party recycler in the reverse logistics.
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    Supplier Matching Method Based on Ontology and Fuzzy QoS in Cloud Manufacturing Environments
    SUN Xiao-lin, JIN Chun, MA Lin, WANG Wen-bo
    2018, 26 (1):  128-138.  doi: 10.16381/j.cnki.issn1003-207x.2018.01.013
    Abstract ( 378 )   PDF (5867KB) ( 116 )   Save
    For the supplier selection of manufacturing enterprise in cloud manufacturing environment, a larger range of choices and the wide distribution of manufacturing resources are highly shared compared with the traditional manufacturing environment. Moreover, the fuzzy features of QoS bring new challenges for the supplier selection in cloud manufacturing environment. Therefore, large quantity of resource, semantic information asymmetry, and fuzzy of QoS become the key problems in supplier service matching.
    On a cloud manufacturing platform, the suppliers as services can be described by functional information and QoS information. Functional information is composed of concepts, numerical and interval. QoS information is represented by fuzzy language. Because of the large number of suppliers, functional information of supplier s1 and supplier s2 are probably the same, but they almost have different QoS information. Accurate matching results can be obtained by matching the two kinds of information in two services.
    In this paper, a three-phase service matching model is proposed based on ontology and fuzzy QoS clustering. Firstly, a description models of service description and ontology is established with semantic ontology in order to eliminate the asymmetry of information and increase the integrity of the semantic information. Secondly, the multiple attributes of QoS based on the triangular fuzzy number are established by combine with fuzzy preference and optimize fuzzy c-means clustering algorithm (FCM), greatly improve the speed and efficiency of convergence. Finally, the experiment is conducted according to real automobile supplier data and expert opinions, and the results from the actual experiment have shown that this method can achieve higher precision and adaptability compared with the traditional methods. In this study, new idea,whinch is about how to solve the problem of service matching in cloud manufacturing environment is put forward.
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    Research on Dominant Models of E-CLSC Based on Network Sale and Recycle Considering Fairness Concern
    WANG Yu-yan, LI Jing
    2018, 26 (1):  139-151.  doi: 10.16381/j.cnki.issn1003-207x.2018.01.014
    Abstract ( 463 )   PDF (2004KB) ( 141 )   Save
    With the rapid development of the Internet, more and more manufacturers prefer to choose the E-closed loop supply chain system which has more opportunities and a larger market. However, with the growth of consumers' purchasing power and awareness of rights in online-shopping, a large number of customers require a network platform to be fairer, making fairness concern to be a key of E-closed loop supply chain's development.
    Based on the E-closed loop supply chain which consists of a manufacturer and, third-party network platform, four kinds of decision-making models including are constructed:E-CLSC dominated by manufacturer without fairness concern, E-CLSC dominated by network platform without fairness concern, E-CLSC dominated by manufacturer with fairness concern, E-CLSC dominated by network platform with fairness concern.
    In these four models,The profit function of manufacturer is:
    πM=(p-cn)(Q-Qo)+(p-co-po)Qo-ρpQ-λQo
    The profit function of network platform is:
    πN=ρpQ+λQo-ks2/2
    In these functions, cn is the cost of manufacturer producing new productions; co is the cost of manufacturer using wasted products to make recycled goods; p is sales price; po is recycling price; s is network platform's service level provided to selling and recycling (assuming the cost of service is ρ(0<ρ<1)); p > cn > co+po > po > 0 is market demand; Qo is market recovery amount; ρ(0<ρ<1)represents commission rate of unit sales charged by network platform; Q(p)=α-βp+γs is commission of unit recycling of wasted goods.
    According to the profit functions of manufacturer and network platform, by using Stackelberg Game, the sale price, service level, recycling price and profit of each model are calculated and analyzed.
    The findings can be drawn that:(1) Whether or not network platform concerned fairness, the sales price, the service level and the manufacturer's profit are all higher with dominant manufacturer than the dominant network platform. (2)The recycling price in CLSC is only influenced by the production cost, the recycling cost and the recycling commission charged by network platform.(3)The fairness concern could decrease the sales price, service level and manufacturer's profit.(4)When the fairness concern's degree is lower, the profit of network platform is higher with the dominant network platform than dominant manufacturer. But when the fairness concern's degree is higher, the profit of network platform is lower with the dominant network platform than dominant manufacturer. (5)When the manufacturer is dominated, the profit of network platform increases firstly and then decreases with the growth of fairness concern's degree. (6) In reality, the network platform would not consider fairness forwardly when it is dominated. However, when the manufacturer is dominated, the network platform would consider fairness.Moreover, because of the pressure of consumer's trust, government's requirement and the competition between enterprises, the network platform has to consider fairness.
    The conclusion of this article further enriched the theoretical foundation of E-closed loop supply chain.
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    Low-carbon Technology Selection for Supply Chain under Cap and Trade Mechanism with Low-carbon Preference
    LIU Ming-wu, WAN Mi-yu, FU Hong
    2018, 26 (1):  152-162.  doi: 10.16381/j.cnki.issn1003-207x.2018.01.015
    Abstract ( 437 )   PDF (5115KB) ( 176 )   Save
    In this paper,the problem of choosing low-carbon technologies under carbon trading market mechanism is investigated by dividing the carbon emissions of a product into the manufacturing stage and the usage stage. It is we assumed that the supplier can make efforts to reduce the carbon emission in each of the two stages and the efficiencies in terms of reducing the carbon emission in the two stages by the supplier's efforts are different. It is Further assumed that consumers prefer to low-carbon products.The technology characteristics of low carbon with cost and efficiency are analyzed and a dynamic supply chain optimization model with low carbon technology investment and cooperation is set up. The optimal decision for the supplier (i.e., the efforts that made in two carbon emission stages) is derived and obtain the corresponding profits of the chain members are obtained by solving a Hamilton Jacobi Bellman Equation. The optimal trajectory of product carbon emission is obtained. In view of the limited choice about technical features in practice and the willing cooperation level of the retailer, the market condition for promoting the retailer cooperation is derived. The study shows that:(1) In the short term, the margin profit of emission reduction can improve both emission and profit; while in the long term, if the efforts are selected properly in the two carbon emission stages, a win-win result can be achieved. (2) The revenue from the market is crucial to cooperation, and has a positive impact on the cooperation between the two chain members. (3) Dividing emissions in the two carbon emission stages under carbon trading market can encourage carbon reduction efforts. Additionally, numerical experiments are used to analyze the influence of critical factors. In this paper, the question about which kind of technologies should be adopted is answered and a basic idea and framework is provided for supply chain carbon emission reducing.
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    Research on Quality Assurance Strategy of E-commerce Platform Considering Bilateral Effort
    GUI Yun-miao, GONG Ben-gang, CHENG Yong-hong
    2018, 26 (1):  163-169.  doi: 10.16381/j.cnki.issn1003-207x.2018.01.016
    Abstract ( 503 )   PDF (663KB) ( 224 )   Save
    In the electronic commerce, consumers are more difficult to perceive the product quality and trust the quality of online goods compared with the traditional business mode. Quality assurance strategy has become one of the important means to win the trust of consumers and improve the competitive advantage of the electronic commerce platform. Relatively few researchers analyze the problem of quality assurance decision from the perspective of two-sided markets. So in this paper, the characteristics of three types of e-business platform modes, including platform mode, reseller mode and hybrid mode, are analyzed bilateral quality assurance efforts of supplier and electronic commerce enterprises as well as product quality impact on demand function are studied, and their quality assurance strategy game model is developed based on two-sided markets. Through comparing their results, it is showed that the hybrid mode is preferred both to reseller mode and platform mode, the optimal quality efforts of e-business enterprise under platform mode is lower than reseller modes, and the optimal quality efforts of supplies is higher than reseller modes. If suppliers' moral hazard is more important than e-commerce enterprises' moral hazard, the platform mode is better than the reseller mode, and the optimal quality under the platform mode is higher than reseller mode. Lastly, three operating modes are analyzed considering internal competitive. It is found that the platform mode is superior to the hybrid mode; the hybrid mode is superior to the reseller mode if single homing percentage of suppliers and quality efforts satisfies some conditions, and internal competition is conducive to the development of the platform mode. The conclusions of this paper offer a theoretical reference for the quality management decision of e-commerce enterprises.
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    Count Judgment Decision Support System Based on Text-mining and Machine Learning
    ZHU Qing, WEI Ke-zhen, DING Lan-lin, LI Jian-qiang
    2018, 26 (1):  170-178.  doi: 10.16381/j.cnki.issn1003-207x.2018.01.017
    Abstract ( 493 )   PDF (5482KB) ( 223 )   Save
    In many other countries with the continental legal system, the constant generation of new legal relationships makes, the defect of statute law which is unable to be timely formulate and modify gradually become obvious. As the number of dispute lawsuit rapidly grows, many countries in the world face the problem how to improve the efficiency of the judicial system under the premise of guaranteeing the quality of the trial. Therefore, in addition to reforming the system, the decision support system will effectively improve judicial decisions.
    In this paper, medical damage judgment documents in China are taken as example, and a court judgment decision support system (CJ-DSS) is proposed based on text mining and the automatic classification technology. The system can predict the trail results of the new lawsuit texts according to the previous cases verdict:rejected and no rejected. By combining different feature extraction methods (DF, Chi-square and DF-CHI feature combination extraction method) and classifiers (SVM, ANN and KNN), multiple combinations that meet the expected performance as the base learning machines are selected. Based on the theory of Delphi Method, integrated learning is used to predict new cases. Integrated learning refers to constructing a new model and using the prediction result of base learning machines that have met expectations as input after proper training, and finally outputting a prediction result with maximum probability through linear or non-linear calculations.
    At the same time, by combining with real cases, it is found that the combination feature extraction method can indeed improve the classifier's performance, especially for SVM, ANN and KNN classifiers. In addition, the system classification performance became more consistent after integrated learning. The best performance reached 93.3%, which significantly increased system accuracy.
    This paper's data source is the "BeiDaFaBao" legal database. "Medical malpractice" is used as the keyword and more than 300 court verdict and mediation documents from 2013 are retrieved. Due to the short format of mediation documents and its brief case explanations, they are eliminated from the study. The rest of the documents are trained and tested after preprocessing.
    In previous studies, the accuracy of text classification system has been greatly influenced by the training set size:the larger the training set data, the better the performance. This paper has a reference value for constructing structured high-performance system based on a small sample training set in the future. Meanwhile, since the process of labelling documents is costly, therefore, the study and model construction for unlabeled text should be the focus of future research for data scientists.
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    Research of Knowledge Sharing Partner Selection in Cluster Enterprises Based on Invisible Contract
    HAN Ying, CHEN Guo-hong
    2018, 26 (1):  179-185.  doi: 10.16381/j.cnki.issn1003-207x.2018.01.018
    Abstract ( 385 )   PDF (1983KB) ( 169 )   Save
    The existence of cluster invisible contracts control the opportunism behavior occurring in the cooperation of industrial cluster enterprises, and make the knowledge sharing cooperation between cluster enterprises be more stability than the other general enterprises. Due to the industrial cluster invisible contract, the enterprises which betray the original knowledge sharing partners will get punishment. In this paper, based on the cluster invisible contract background, a Hoteling game model is constructed to analyze the mechanism of industrial cluster invisible contract to the partner selection of cluster enterprise knowledge sharing behavior. The model is divided into two stages to explore the cluster enterprise knowledge sharing partner selection in decision-making behavior. Specifically, in the first stage, the cluster enterprises can choose the knowledge sharing partners arbitrary, but in the second stage, without the continuation of the first phase of the choice, the cluster enterprise will receive the punishment of the invisible contract in industrial cluster. The results shown that (1) building a broader knowledge sharing partnership in the early stage is good for the long-term development of enterprise, so for the new enterprises into the cluster, establish quality and extensive network connections should be in the first place; (2)the cluster enterprises always prefer to establish knowledge sharing relations with the enterprises which have the greater cluster power. Therefore, when the cluster enterprises establish a new contact with other nodes, they can give priority to the core enterprises in the cluster, and the local government should also strengthen for the cultivation of cluster core enterprise; (3) the invisible contract constraint is helpful to establish a more stable relationship about knowledge sharing network of industrial cluster, which can improve the knowledge revenue of cluster enterprise, and contribute the benign development of industrial cluster.So in the development of the cluster, the invisible contract of industry cluster should be consoidated and developed. For the specialty of industrial cluster, the influence of cluster invisible contract on cluster enterprise knowledge sharing activities, and beneficial enlightenment is provied for industrial cluster knowledge management practice.
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    Analysis of Key Variables Correlation Feedback Loop of the Development Countermeasures of the System of Debang Scale Breeding and Cultivating
    JIA Wei-qiang, WANG Wen, JIA Ren-an
    2018, 26 (1):  186-196.  doi: 10.16381/j.cnki.issn1003-207x.2018.01.019
    Abstract ( 351 )   PDF (5023KB) ( 93 )   Save
    The feedback loop structure is and the core structure of dynamic changes in complex systems,and the analysis based on the feedback loop structure is the key to the specific management countermeasures of such systems. How to analyze the feedback loop structure and realize the effective feedback loop development management is an important problem to be studied deeply. In order to solve the above problems, a four-step analysis method of key variable correlation feedback loop is proposed:Firstly, the flow rate is established into the basic tree model of the complex systems by using the new branch vector determinant algorithm of system dynamics. Secondly, on the basis of the system development goal, the key variables are determined. Thirdly, the total feedback loop of the system is calculated by using the vector Algorithm, key variables associative feedback loop structure flow diagram are constructed, and determines the associative feedback loop structure flow diagram's dominant feedback loop is determined. Finally, according to the key variables leading feedback loop analysis, the management strategy is determined. By taking the system of Debang scale breeding and cultivating for example, the basic tree model of the flow rate of six trees is established including. According to the three major goals of system development, the three key variables including:aquaculture profit, annual application amount of organic fertilizer application, household pig manure annual output of biogas slurry are determined. Based on the construction of three key variables associated with the feedback loop structure, according to the development of Debang scale breeding system, combined with historical data of Debang aquaculture industry, biogas slurry development, household biogas digesters construction, the dominant feedback loop of three associated feedback loop structures is determined. Finally, according to the analysis of the dominant feedback loop, the three management strategies of the system development are determined. During the Practice of Management Countermeasures of Debon Scale Breeding System, the effectiveness of the three management strategies is verified, and the feasibility of this method in determining the complex system management countermeasures is verified. The four-step analysis method of key variable correlation feedback loop provides a normative method for feedback loop structure analysis, and also provide an operational process for the development of complex systems development management strategies.
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