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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
   中国科学院科技战略咨询研究院

Table of Content

    20 February 2015, Volume 23 Issue 2 Previous Issue    Next Issue
    Articles
    A Study on the Effects of Adjusting Futures Margin Level on the Price Discovery of Chinese Steel Markets
    FANG Wen, FENG Geng-zhong, LU Feng-bin, WANG Shou-yang
    2015, 23 (2):  1-9.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.001
    Abstract ( 1938 )   PDF (2405KB) ( 1696 )   Save
    In recent years, China's steel prices often fluctuate violently. Shanghai Futures Exchange (SHFE) controls the price volatility risk by means of adjusting steel futures margin level. In Nov 29, 2010, SHFE increased the steel futures margin level from 8% to 12%, while decreased the margin level from 8% to 7% in May 2, 2012. Do these adjustment measures influence the price discovery of Chinese steel markets? The study of the effects of adjusting futures margin level on the steel price discovery is of great concern for researchers and market traders. Most previous studies have analyzed the price discovery of Chinese steel spot and futures market. However, steel traders nowadays can also trade in steel electronic market. Which market contributes more to the process of uncovering steel's full information or permanent value? Does their information contributions vary before and after the adjusting of steel futures margin level? Transaction costs are higher (lower) in the futures markets after the margin level increases (decreases). Given that the magnitude of the transaction costs determines whether a trader can profitably trade on a given piece of information, the adjustment of futures margin level should influence the price discovery of steel futures markets. Consequently, the steel price discovery process should be changed dynamically. The standard methodology to analyze price discovery is to estimate an vector error correction model. Applying this methodology to data on three steel markets are rare. The present paper contributes to this line of research. Steel futures price, steel electronic price and spot price over the period July 1st 2010-April 29th 2011 and June 7th 2011-March 21st 2013 are employed to analyze questions of price discovery of the three steel markets. Information share (IS) method based on three-dimension vector error correction model is used. Our results can be summaried as follows. The price discovery of steel futures market are enhanced by increasing of margin level whereas weakened by decreasing of margin level. Steel electronic market dominates the price discovery process when steel price flutuates violently. The dynamic of the price discovery of steel electronic market is different when futures margin level changes. This finding underpins the importance of taking the price discovery of steel electronic market explicitly into account. Important implications are provided in our results for the application of IS method to three commodity markets, and for the establishment of futures margin level in order to enhance the price discovery of Chinese steel futures market as well.
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    Investor Sentiment,Average Correlation and Stock Market Returns
    GAO Da-liang, LIU Zhi-feng, YANG Xiao-guang
    2015, 23 (2):  10-20.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.002
    Abstract ( 2188 )   PDF (1267KB) ( 2174 )   Save
    Pollet and Wilson said that the average correlation-return relation will be better than the mean-variance relation as proxy for the overall risk-return relation in the capital market. The correlation between investor sentiment and the average correlation-return relation is studied in this paper. After using data from 2001 to 2011 in the Chinese stock market to construct a investor sentiment index, the following empirical results are obtained. Compared with the stock market variance, the average correlation's ability is better than the stock market variance in forcasting earings, while in the low-sentiment periods, the average correlation-return relation is not significant, but during the high-sentiment periods, average correlation-return relation has been weakened significantly, even become a negative correlation. This shows that high sentiment will weaken the overall risk-return relationship. The conclusions' robustness has been proved in the subsequent robustness test, which shows a new mechanism of investor sentiment's influence on expected returns.
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    Description of the Typical Characteristics of Financial Asset's Yield Distribution and VaR Models Based on AEPD、AST and ALD Distribution
    LIU Pan, ZHOU Ruo-mei
    2015, 23 (2):  21-28.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.003
    Abstract ( 2716 )   PDF (1374KB) ( 1739 )   Save
    The financial asset's yield distribution has some typical characteristics such as "leptokurtic", "fat tail","skewed" and "Asymmetry", but the traditional normal distribution, t distribution, SKST distribution cannot fully describe these characteristics, which has influenced the efficiency of parameter method of VaR models based on them. In recent years, the theoretical circle has proposed AEPD, AST, ALD and other distributions to improve the description of the financial asset's yield distribution. The CSI 300 index is choosed to analysis and compare the description on the typical characteristics of financial asset's yield distribution and also the measurement differences of VaR models based on them. The empirical results show that the more typical characteristics of financial asset's yield distribution the model captures, the better to measure VaR. It only proves that the measurement effects of the VaR models based on AEPD, AST distribution are absolutely better than the model based on normal distribution, but have no obvious difference with model based SKST distribution; Model based on ALD performs even worse when measuring the short VaR but performs best when measuring the long VaR under the low quantile.
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    Models and Empirical Research of Term Structure of Interest Rates in China: Based on No-Arbitrage DNS Model and DNS Model
    GE Jing, TIAN Xin-shi
    2015, 23 (2):  29-38.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.004
    Abstract ( 1986 )   PDF (1873KB) ( 1867 )   Save
    With the deep development of Chinese interest rate marketization and the diversification of the interest rate derivatives,how to predict interest rate effectively,as one of the kernel variables in securities pricing, has become a key work. The no-arbitrage DNS model is developed on the basis of DNS model, and theoretical studies show that it is a constrained affine Gauss process. With the term structure of yields implied in monthly bonds price from 2005 to 2012 in Shanghai Stock Exchange (SSE), the no-arbitrage DNS model and the DNS model are studied empirically using the method of quasi-maximum likelihood. Are the results show that the no-arbitrage DNS model keeps the no arbitrage condition of affine term structure model and good empirical results of DNS model; and also it keeps the forecast advantage of DNS model, because prediction errors of all term structures in both two models are within 1.5 basis points; and also the characteristics of constant adjustment item show that the value is increasing with the extension of maturities.
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    Research on Optimized Allocating the Unified Credit Line of Group Customer of Commercial Bank
    CHEN Lin, ZHOU Zong-fang
    2015, 23 (2):  39-43.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.005
    Abstract ( 1767 )   PDF (868KB) ( 2034 )   Save
    The enterprise group is the chief loan customer of commercial bank, and this situation lead up to that the default risk of enterprise group is particularly prominent for commercial bank. According to the structural model and the constraint of unified credit line, and based on multi-objective decision-making on management of default risk and loan revenue, a model of optimized allocating the unified credit line to the group customer of commercial bank under unification principle is put forward. A case analysis shows that it can get the optimized allocating unified credit line for each members of enterprise group by genetic algorithm under condition of setting different importance of each target. This method may help commercial banks to actively prevent credit risk of enterprise group.
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    The Adaptive Research of the Time-varying O-U Model in the Pricing of Weather Derivatives-A Case Study of Beijing
    WANG Ming-liang, HE Jian-min, CHEN Bai-shuo, CAO Jie
    2015, 23 (2):  44-49.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.006
    Abstract ( 1703 )   PDF (1141KB) ( 1548 )   Save
    How to accurately price the weather derivatives,which as a sort of weather risk-hedging financial derivatives, has always been the focus of academic debate. Based on the O-U model of monthly volatility presented by Alaton[5], the speed of mean reversion is considered in this paper,which is a constant in the original model as a time-dependent variable. Then the time sequence of the speed of mean reversion is analyied by ARMA(p, q) model and establish the time-varying O-U model. Based on Beijing's daily average temperature data from 1951, three years of daily average temperature from 2010 to 2012 are simulated respectirely, and compared with its true value. After the comparison,it is found that: the residual sum of squares of the improved model are smaller, meanwhile the bias proportion, the variance proportion and the covariance proportion also show the improved model obtains a better temperature prediction. Finally, the CDDs are calculated and HDDs are calculated according to Beijing's daily average temperature data by Monte Carlo simulation, and then price the related futures contract to further validate the adaptability of improved model.
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    VaR Forecast Comparison between Realized Volatility ARFI and CAViaR Models
    YU Bai-min, WU Wei-xing
    2015, 23 (2):  50-58.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.007
    Abstract ( 2159 )   PDF (1080KB) ( 1737 )   Save
    The models for calculating and forecasting VaR can be classified into two broad categories: indirect-VaR and direct-VaR approaches.The VaR forecast performances between models taken from these two approaches respectively are compared. One is ARFI-VaR forecast model the indirect-VaR approach based on "realized volatility" obtained by high frequency data. Another two are CAViaR-based models, which are the representatives of direct-VaR approach. By the various backtests that are extensively used for VaR performance evaluation, using 5-min high frequency data of CSI 300 Index, SSE Composite Index and SZSE Component Index, the empirical evidence shows the CAViaR-based models perform better than realized volatility-based ARFI model.
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    Study of Inventory Policy in a Dual-channel Supply Chain with Learning Effects
    BAI Qing-guo, XU Xian-hao
    2015, 23 (2):  59-69.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.008
    Abstract ( 1931 )   PDF (1104KB) ( 2235 )   Save
    The optimal inventory policy for a dual-channel supply chain problem with learning effects is considered in this paper. Distributor satisfies the downstream customer's demands of both traditional channel and internet channel in a finite planning horizon. The sell price of each channel is assumed to be a non-decreasing linear function of time. When learning effect of fixed set-up cost is incorporated into a supply chain system with a constant probability,a mixed-integer constraint optimization model for non-perishable items and a unconstrained optimization model for perishable items are established. The objectives of two models are maximizing the total profits. By analyzing the optimal properties for each model,it is proved that the optimal inventory policy is unique by using the technique of relaxing the number of replenishments to continuous variable. In addition,the solving method of the optimal inventory policy for each model is proposed and both of these models are compared. Finally,some numerical examples are provided to illustrate above theoretical models and the numerical results also show that more profit can be obtained when learning effect is incorporated into the supply chain system.
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    Retailer Transshipment Policy with Supply Disruption in a Two Stage Supply Chain
    WANG Chuan-xu, XU Chang-yan
    2015, 23 (2):  70-79.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.009
    Abstract ( 1776 )   PDF (3240KB) ( 1920 )   Save
    Many supply chain risks result from supply risk. Once supply disruption occurs, a retailer with stock out usually transships product from other retailers with surplus product to meet the demand. Therefore, retailer transshipment policy with supply disruption in a supply chain is studied in this paper. Considering a two-stage supply chain consisting of two suppliers and two retailers with supply disruption, jointly considering four cases of supply disruption, retailers' order quantity decision models with product two-direction transshipment, one-direction transshipment and non-transshipment are developed. Order quantity and profit under three different transshipment policies are compared, and impact of transshipment price and transshipment cost on retailers' order quantity and profit are analyzed. A numerical example is given to demonstrate the effectiveness of proposed model, and analyze the impact of supply disruption probability and other parameters on retailers' optimal order quantity and profits. It is shown that the profits of retailers with two-direction transshipment are greater than those with one-direction transshipment, and the profits of retailers with one-direction transshipment are greater than those with non-transshipment. For the retailer who transship out the product under one-direction transshipment policy, the order quantity with one-direction transshipment is greater than that with non-transshipment, and the order quantity with non-transshipment is greater than that with two-direction transshipment. For the retailer who transship in the product under one-direction transshipment policy, the order quantity with non-transshipment is greater than that with two-direction transshipment, and the order quantity with two-direction transshipment is greater than that with one-direction transshipment. The contribution of this paper lies in three aspects. Firstly, previous research doesn't jointly consider the supply disruption and product transshipment, while four different cases of supply disruption and three different transshipment policies of retailers are considered in this paper. Secondly, previous research mostly studies the transshipment policy of retailers with one supplier, whereas the transshipment policies of retailers with two suppliers are investigated in this paper. Thirdly, previous research mostly only considers one-direction transshipment or two-direction transshipment; however, not only one-direction transshipment but also two-direction transshipment are studied in this paper, and performs comparison analysis between them are carried out.
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    Decision Models for Supply Chain Based on CVaR and Buyback Contract under Strategic Consumer Behavior
    ZHANG Xin-xin, HOU Wen-hua, SHEN Cheng-lin
    2015, 23 (2):  80-91.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.010
    Abstract ( 1995 )   PDF (1561KB) ( 2117 )   Save
    In CVaR framework, decision models for supply chain are proposed based on buyback contract and strategic consumer behavior. Decision behaviors of risk-averse members in both centralized and decentralized supply chain are investigated. In addition, the interactions among strategic consumer behavior, members' risk-aversion and buyback contract are discussed by theoretical analysis and numerical study. The main results are as follows: First, the price commitment can become a perfect strategy to reduce the negative impacts of strategic customer behavior when supplier and retailer are both risk-averse. Second, the optimal buyback price is influenced by members' risk-aversion and the optimal ordering quantity increases with the growth of the buyback price under the decentralized supply chain. Third, buyback contract can coordinate the supply chain perfectly if and only if retailer's risk-averse factor equals to supplier's risk-averse factor. Otherwise, the profit cannot be allocated arbitrarily between supply chain members based on buyback contract. Finally, when retailer's risk-averse factor does not equal to supplier's risk-averse factor, retailer's profit-sharing will increases with the rising of consumers' valuation, and the player with lower risk-aversion has to give a part of profit to the one with higher risk-aversion so as to guarantee the implement of the contract.
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    On Contracts with Risk Share for VMI Program Under Replenishment Strategy
    FAN Chen, WANG Xiao-li, DING Chao, SU Qiang
    2015, 23 (2):  92-98.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.011
    Abstract ( 1858 )   PDF (1123KB) ( 1429 )   Save
    This paper deals with the problem of contracts designing for supply chain under VMI(Vendor Managed Inventory) program. Inventory replenishing policies are also taken into consideration. A single supplier and single retailer module are considered under "vendor with owner ship" and discrete demand. Based on risk sharing, 2 contract forms are proposed: Design1: Supplier pays fix amount fee to retailer as the lost sales compensation, while retailer shares the occurred holding cost of supplier. Desing2: Retailer pays fix amount fee to supplier and supplier bears the occurred lost sale penalty while retailer shares the occurred holding cost of supplier. Based on Zheng and Federgruen's (r,Q) and (s,S) model, the 2 contracts' performances are studied under the 2 inventory replenishing policies. The result indicates that the efficiency of supply chain under the 2 contracts is satisfactory. And with proper contract parameters' designing, supply chain coordination is also possible. Meanwhile, the result is compared with revenue share contract,which shows that contracts with risk share can achieve higher supply chain efficiency. The later simulation proofs our result. The study shows that one contract performs differently under different supply chain environment; the inventory replenishing policy has impact on contracts performance. It is found that under certain circumstance, supply chain can benefit from sharing risk rather than sharing revenue.
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    Analysis of R&D Project Schedule Risk Based on the Organization-task Network: With the Organization Failure as a Risk Factor
    ZHANG Yan-lu, YANG Nai-ding
    2015, 23 (2):  99-107.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.012
    Abstract ( 1830 )   PDF (1839KB) ( 1886 )   Save
    In modern society, facing the complexity of technology, scarcity of resources and dynamic of market demand, it has become an effective mode for R&D project to form a network composed of many organizations. However, duration delay has been a common phenomenon in R&D project due to the great amount of sub-organizations and sub-tasks, high complexity of technology and uncertainty of external environment. Research studies also show that schedule problem has been one major cause of many risk events, and become a big challenge faced by managers. Therefore, it has become essential to analyze the schedule risk of R&D project under the context of networking R&D.According to literature review, many studies focus on analyzing the project schedule risk from the view of uncertain task by adopting Gannt Chart, Work Breakdown Structure, Critical Path Method, Program Evaluation and Review Technology, Graphical Evaluation and Review Technology, etc. However, few studies focus on the schedule risk from the organization failure that implements the project task. In fact, project organization is an important factor of schedule risk by allocating materials, human and budget that are necessary for project tasks. In this sense, the failure of a few organizations in R&D project will cause many neighboring organizations to fail, and then influences the durations of some tasks that are implemented by those organizations. Therefore, this paper adopts the coupled map lattice model to describe how the failure of some organization influences the duration of R&D project, which can provide a new insight into managing the schedule risk of R&D project under the context of networking.Firstly, this paper establishes the organization-task network model of R&D project, where organization network has the characteristics of scale-free network based on referring to the conclusions from many scholars, and task network includes three modes of sequence relationships of tasks, finally the execution relationships from organizations to tasks is established based on the organization network and task network.Secondly, based on the established organization-task network, this paper proposes the risk analysis model of R&D project with the organization failure as the factor of R&D project schedule risk. In this model, this paper adopts the coupled map lattice model of cascading failure theory to describe the cascading failure process of organizations in R&D projects, which is shown as below: 
    (1)
    Where si(t) means the state of organization i at time t, bij(t) means the state whether organization i is linked to j or not at time t, ki(t) means the node degree of organization i at time t, tunable parameter ε∈(0,1) means the coupling degree between organizations. At time m, an external disturbance R is imposed on organization c and then causes this organization to fail. Then, all the other organizations' states will be calculated again according to the equation (1). In this way, the cascading failure process of nodes spreads in the organization networks.Thirdly, this paper proposes the influencing mechanism of how the actual duration of task i is affected by the failure of organizations that implement this task. More specifically, this paper proposes that the actual duration ti' of task i is affected by three elements, which are the planned duration ti of task i, the proportion of failed organizations against all organizations, the influencing degree of organization failure on the actual duration. Therefore, the actual duration of task i is calculated according to the following equation: 
                                           (2)
    Where Ψi means the set of failed organizations that implement task i, ω means the influencing degree of organization failure on the actual duration.Finally, this paper explores how the organization failure influences the schedule risk of R&D project throughnumerical simulation under different elements, which are tunable parameter R and ε, average degree of network 〈k〉, attack strategy. The results show that the external disturbance R that is imposed on one organization node can eventually cause the duration delay of R&D project badly only when it reaches a certain threshold, i.e. critical disturbance threshold; This threshold has the negative correlation with the degree of coupling among the organizations, and has the positive correlation with the average degree of organization network; highest-degree attack can more easily lead to the occurrence of schedule risk than random attack and lowest-degree attack, and the gap between their consequences is becoming much larger with the coupling degree among the organizations being smaller.Takes the organization failure is taken as the element of schedule risk of R&D project, and analyzes how the organization failure influences the schedule risk of R&D project through numerical simulation is analyzed. The research work of this paper will provide a new view for R&D project schedule risk management under the context of networking.
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    Optimal Quality and Pricein Two-Period Management of Software Release——Analysis under Uncertainty of Customers' Requirements
    LI Wei, LI Min-qiang, CHEN Fu-zan
    2015, 23 (2):  108-115.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.013
    Abstract ( 1658 )   PDF (2269KB) ( 1536 )   Save
    Multi-period release is a widely adopted practice followed by software providers to cope with the uncertain customers' requirements. In order to examine the impact of the requirement uncertainty on software providers' decisions, a two-period framework is considered with a monopoly software firm releasing software products to heterogeneous customers. The monopolist releases the initial product with lower quality in the first period, making the uncertain requirements more specific through the interaction between the customers and the initial product. In the second period, the monopolist releases the upgrading product to meet those requirements. The monopolist's decisions as an optimization model impacted by requirements uncertainty are formulated, taking the quality of initial product and the prices of initial and upgrading product as decision variables. The numerical results illustrate that, both the optimal quality of the initial product and the optimal prices of the initial and upgrading products decrease in the requirements uncertainty. In addition, it is optimal for the monopolist not to release the initial product in the first period when the market satisfies following conditions simultaneously: Firstly, the uncertainty of customers' requirements is sufficiently high, and secondly, the intensity of the negative word-of-mouth effect is higher than that of positive word-of-mouth effect. Some supports are offered in our work to the optimal decisions in the context when the information goods providers can not capture correct requirements of the customers.
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    DEA Cross-Efficiency Evaluation Model by the Solution Strategy Referring to the Ideal DMU
    LI Chun-hao, SU Hang, TONG Yi-jie, SUN Yong-he
    2015, 23 (2):  116-122.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.014
    Abstract ( 1898 )   PDF (895KB) ( 1744 )   Save
    Among the existing DEA cross-efficiency models, aggressive model and benevolent model may lead to inconsistent ranking results which make it hard for decision maker to choose between them.Although neutral model formally solves the problem above, there is obviously a theoretical flaw in it. In view of the above questions, a new DEA cross-efficiency model, DEA cross-efficiency evaluation model by the solution strategy referring to the ideal DMU is proposed in this paper. The new model cannot only keep the decision maker from the dilimma of choosing, but also is better to stick to the DEA basis principle which is in favour of the evaluated DMU by comparing with existing models. Numerical simulation shows that the new model is more applicable to real world decisions.
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    A Study on Revisiting Multi-Attribute Decision Targets Based on Psychological Threshold
    LIU Jian, LIU Si-feng, MA Yi-zhong, WANG Jian-jun
    2015, 23 (2):  123-130.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.015
    Abstract ( 1858 )   PDF (1027KB) ( 1815 )   Save
    Decision maker's utility or value may not depend on the levels of performance on different criteria, but instead on whether the levels meet a target or threshold on one or more criteria. In this paper, based on this psychological threshold, a new decision analysis method is proposed. First, three criteria satisfaction functions are constructed corresponding to three different types of criteria, respectively. Second, the decision targets according to the satisfaction degrees of the decision makers are revised. Using the selected alternatives and criteria, a new decision table is constructed. Third, a new method is proposed to obtain the criteria and aggregate the information based on the satisfaction degree of the decision makers. Finally, an example is used to demonstrate that the method is scientific and effective as well as feasible.
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    An Approach to Multiple Attribute Group Decision Making Based on Uncertain Pure Linguistic Hybrid Harmonic Averaging Operator
    PENG Bo, YE Chun-ming
    2015, 23 (2):  131-138.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.016
    Abstract ( 2715 )   PDF (924KB) ( 1624 )   Save
    In the real life, due to people's limited expertise related to the problem domain, time pressure and so on, the decision information is expressed in the form of uncertain pure linguistic variables, in which all expert weights, attribute weights and attribute values take the form of linguistic labels. In this paper, the multiple attribute group decision making (MAGDM) problems under uncertain pure linguistic information are studied. Aggregation operators including the uncertain pure linguistic ordered weighed harmonic averaging (UPLOWHA) operator and the uncertain pure linguistic hybrid harmonic averaging (UPLHHA) operator are proposed. Also, an approach based on the proposed operators for MAGDM is developed. The prominent characteristic of the approach is straightforward and does not produce any loss of information. Moreover, the approach is applied to the partner selection of virtual enterprises. And finally, the effectiveness of the developed approach is shown by comparison with other methods.
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    Heterogeneous Environments' Influence on Housing Supply Regulation
    LI Bin, ZHANG Suo-di
    2015, 23 (2):  139-147.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.017
    Abstract ( 1657 )   PDF (982KB) ( 1269 )   Save
    On the basis of housing stock adjustment model, policy implementation environments and policy instruments are introduced into analytical framework for housing supply in this paper, and the dynamic model of commercial housing supply regulation is estiblished based on heterogeneous environments.And two types of micro-environmental factors--expectation and city are set, and empirical analysis of the macro-policies' performance on commercial housing supply from 1999 to 2010 in 35 cities of China are carried out. The results show that: in heterogeneous expectation environment, the same policy instrument has different effects on commercial housing supply; the presence of expectation not only has direct influence on housing supply, but also weakens the implementation effects of monetary policy and land policy; in the heterogeneous city environment, there are also significant differences in the same policy instrument's effects on commercial housing supply. From the perspective of heterogeneous environments, new interpretation and solution to inefficiency of housing regulation in reality are given.
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    Study on Parent-subsidiary Corporation Governance of Enterprise Groups Based on Evolutionary Game
    ZENG Jiang-hong, CUI Xiao-yun
    2015, 23 (2):  148-153.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.018
    Abstract ( 1662 )   PDF (1103KB) ( 1883 )   Save
    With the development of information & knowledge economy and the deepening of economic globalization, Chinese businesses are facing increasingly competitive pressure from the world. Construction of large enterprise groups is becoming a trend. At the same time, with the increase of mergers and acquisitions, and the further expansion of multinational corporations, governance problem brought by the complexity of the enterprise groups is urgent to be solved. Corporate governance should span a single corporate governance boundary, to expand enterprise dimensions, implementation from "Corporate "governance to "group" governance breakthrough.Parent-subsidiary corporate governance is the core issue of corporate governance, parent companies and subsidiaries within the group interconnected and relatively independent relationship has produced a new governance issue, become a problem that influence enterprise groups to exert the overall advantages. In this paper, by using evolutionary game analysis model, and fully considering the dynamic nature of governance and its subsidiary initiative on governance, the mechanism of interaction between supervision strategy of the subsidiary to the parent company and the strategy selection strategy of subsidiary is studied, and the important factors affecting the evolution stability of the system were analyzed.The corporate governance theory is enriched, and a new idea to solve the principal-agent problem between the parent and subsidiary is offered.The results show that the process of the game existed evolutionary stable strategy in 3 cases, but there is no optimal stable strategy. The strategy choices depend on each other's strategy selection probability, the final equilibrium state depends on the parent company learning adjustment speed. Through the design of a reasonable incentive mechanism, such as the introduction of the percentage ratio α that positively related to the income created by the subsidiaries of the group, to increase penalties, take regular or irregular spot checks and other means, the parent-subsidiary company strategy adjustment speed can be affected, the game will turn to the strategy evolution evolution that group profit is the biggest change, or that there is no supervision.And a good relations of mutual trust and benefit between parent company and subsidiary is promoted, the group overall income is increased, the overall superiority of enterprise groups will be strengthen.
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    Research on Algorithm of Post-processing Association Rules Based on Clustering and Domain Knowledge
    ZHANG Ling-ling, ZHOU Quan-liang, TANG Guang-wen, LI Xing-sen, SHI Yong
    2015, 23 (2):  154-161.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.019
    Abstract ( 1756 )   PDF (1278KB) ( 2483 )   Save
    Second mining of the result of association rule mining is proposed in solution of the large numbers of redundant rules in the traditional association rules mining algorithm, and the algorithm for clustering of association rules is designed, then the novelty of the association rules is assessed after clustering based on the existing domain knowledge. It is insited that the association rules with more novelty and higher value can be stored in the domain knowledge base, and can be used for the decision or mining again. The algorithm proposed in this paper is effective to reduce the number of rules and also help to improve the novelty and precision of rule, which has a very high value for business applications. Finally the open source data from UCI is used to carry on the experiment to verify the effectiveness of the algorithm.
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    Studyon the Relationship among the Financial Development, Technological Innovation and Economic Growth Based on China's Provincial Panel Data
    LI Miao-miao, XIAO Hong-jun, ZHAO Shuang
    2015, 23 (2):  162-169.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.020
    Abstract ( 2014 )   PDF (1067KB) ( 2709 )   Save
    The purpose of this paper is to explore the relationships among financial development, technological innovation and economic growth, by the unit root test, co-integration test, vector auto-regression (VAR) and causal directed acyclic graphs (DAG), and based on the panel data of China's 31 provinces and cities from 2000 to 2011,which is from the related statistical yearbook and statistical bulletin.This study shows that: firstly, a long equilibrium co-integration relationship between any two of financial development, technological innovation and economic growth is proved.Secondly, technological innovation is directly caused by financial development, that is, there is a strong positive relationship between domestic financial development and R&D investment, while the bank-dominated financial development is not conducive to R&D investment.Thirdly, economic growth is significantly promoted and directly caused by technological innovation.Finally, financial development is the direct and indirect reason of economic growth. The structure of financial development has a significantly positive effect on economic growth in the low level of development countries, while the scale of financial development has a significantly and directly negative effect on economic growth, and it also can indirectly promote economic growth by the promotion of R&D investment.
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    Research on The Dynamic Evolution Pathes of Risks Trasmission for Network Organization
    SUN Guo-qiang, QIU Yu-xia, LI Jun-mei
    2015, 23 (2):  170-176.  doi: 10.16381/j.cnki.issn1003-207x.2015.02.021
    Abstract ( 1689 )   PDF (1119KB) ( 1987 )   Save
    Network organization is a crossing complex systems of highly sensitive to risks. On one hand, risks are objective and necessary; on the other hand, it is easy for risks of network organization to conduct within the organization, various risks will rapidly expand under the interaction of the internal and external forces. Therefore, risk conduction mechanism and the dynamic evolution pathes of such a system have become the key if synergies can be achieved. In this paper, the conduction of network organization risks has path dependence.The conductive process of risks for network organization is deduced by functional analysis from the time dimension, and the model of risks conduction for the network is constructed, and the results are verified by numerical example, which has the typical characteristics of network organization, in order to provide a new insight to control the risk for network organization, explore dredge channels, and achieve efficient allocation of resources.
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