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Table of Content

    20 February 2017, Volume 25 Issue 2 Previous Issue    Next Issue
    Articles
    High-dimensional Portfolio Risk Measurement Based on M-Copula-SV-t Model
    LIU Xiang-dong, FAN Bin, Yang Yi-ming, LIU Cheng
    2017, 25 (2):  1-9.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.001
    Abstract ( 1109 )   PDF (7676KB) ( 1138 )   Save
    The return of financial asset usually has a characteristic of fluctuation clustering with sharp peaks and fat tails, not complying with the normal distribution. Therefore, the nonlinear correlation should be considered when measuring the risk of an investment portfolio. In this respect, copula functions provide a fairly new approach for connecting the marginal distributions of nonlinear series in the high-dimensional risk assessment of portfolio. However, it is noteworthy that two challenging problems exist in this field:one is how to choose or construct an appropriate copula function, the other is how to estimate model parameters. To address these issues, a novel M-Copula-SV-t model is proposed in this paper. Specifically, SV-t model is first employed to fit the marginal distributions of financial time series, where MCMC method with Gibbs sampling are used to estimate marginal parameters; then an M-Copula function consisted of linearly combined Archimedean Copulas is designed to jointly connect these marginals. where joint model parameters are estimated by MLE and BFGS algorithm; afterwards Monte Carlo technique is adopted to simulate optimal portfolios under minimal values of VaR and CVaR. The model feasibility and effectiveness is fruther vertified by taking an example of four exchange rates, where the empirical results indicate that our mixture modeling outperforms other individual Archimedean Copula modeling in dealing with the issue of dimensionality curse, and capturing asymmetry and tailed fatness of portfolio analysis. Therefore, our proposed model contributes to the literature of intra-market portfolio management, and provides valuable suggestions for international investors with respect to short-term decisions.
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    Risk analysis of Foreign Exchange Portfolios Based on High-dimensional Dynamic Vine Copula
    HAN Chao, YAN Tai-hua
    2017, 25 (2):  10-20.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.002
    Abstract ( 1132 )   PDF (2009KB) ( 1030 )   Save
    The structure of high-dimensional dynamic vine copula can overcome ‘dimensional curse’ faced by bivariate Copula and dynamically describe nonlinear dependence between multi-variables, and represents the academic frontier. Five kinds of foreign exchange log-returns, including USD, EUR, JPY, HKD and GBP, are selected to make empirical analysis, Time series are fitted with AR-GJR-GARCH and GPD models. After probability integral transform, high-dimensional dynamic C and D vine copulas are modelled. Then, portfolio VaR sets are got by Monte-Carlo method, tested by UC back testing, and compared to the corresponding static research. The results show that VaR based on high-dimensional dynamic C vine copula performs the best, and marginal risk of USD is considered as the least by VaR decomposition, the more USD the lest risk. The conclusions provide a new model and method to quantify risk, reasonably allocate asset portfolio, and for authorities to regulate risk.
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    Research ofIPO Underpricing Decomposition Based on Two-tiered Stochastic Frontier Model: Evidence from Chinese Growth Enterprises Market
    HUANG Shun-wu, JIA Jie, WANG Wen-jun
    2017, 25 (2):  21-29.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.003
    Abstract ( 1203 )   PDF (1072KB) ( 970 )   Save
    IPO underpricing is one of financial anomalies, and it has always been the concerns of stock market. Especially, there is singularly high IPO underpricing in China stock market. The classic theories in related field consider that IPO underpricing is derived from intentional discount in primary market and emotional premium in secondary market. Although domestic correlated researches indicate that intentional discount in primary market is not existent in Chinese stock market, it cannot be denied that IPO underpricing is assuredly derived from offering price in primary market and exchanging price in secondary market. Based on this thoughtfulness, the article firstly uses stochastic frontier model to analyze offering price and exchanging price of stocks in growth enterprise market in China. The results find that whether offering price or exchanging price has not been underestimated, and, on the contrary, they both have price premium in different degrees. According to the general formula of IPO underpricing, the article discovers that the price premium from offering price can comparatively cause the declining of IPO underpricing, and, on the contrary, the price premium from exchanging price can comparatively cause the increasing of IPO underpricing. In accordance with the above discovery, two-tier stochastic frontier model iscreatively applied to the study of IPO underpricing, and a new IPO underpricing decomposition model is created. In the new model, IPO underpricing is successfully decomposed into discount effect from primary market and premium effect from secondary market. Then, sample data is employed to study IPO underpricing. The results indicate that, relative to discount effect from primary market, the premium effect from secondary market is the major reason of IPO underpricing of sample stocks. The robustness test also proves that, no matter different periods, different industries or different growth firms, premium effect from secondary market is larger than discount effect from primary market. Our sample includes 377 stocks listed on growth enterprise market over the period from October.30, 2009 through March.26, 2015. Except for underwriter's income and financial performance indicators collected from the prospectuses, other data is downloaded from Wind Database. All data is standardized and winsorized in order to control the effect of extreme values. It is the mainly contribution that a new IPO underpricing decomposition model is proposed based on two-tier stochastic frontier model. Therefore, it affords a new idea or paradigm to follow-up study on IPO underpricing.
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    Bayesian Evaluation and Selection Strategies in Venture Project Portfolio Decision Analysis
    HU Zhi-jun, PENG Fei, LI Zhi-xia
    2017, 25 (2):  30-39.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.004
    Abstract ( 1264 )   PDF (1251KB) ( 1397 )   Save
    The venture capital market plays a significant role in providing capital to a new feasible business idea(new product, service, or retail concept) and businesses of different type. Project portfolio selection is an important decision in many venture capital companies, and practically all venture capitalists(VC) seek to creat value by selecting and executing portfolios of venture projects that consume resourse, and behavioral factors of the VC directly influences the result of the optimal portfolio selection. Most studies on project portfolio selection focus on identifying the "right" project portfolio under various criteria, such as reward and risk.
    In this paper a portfolio approach is taken to analyze the investment strategy of aVC. Considering the psych-ological characteristics of VC's loss aversion from the perspective of prospect theory, a more practical portfolio optimization model that maximizes the expected utility of VC is constructed, and the model is transformed into a linear mixed integer programming problem by the Monte Carlo simulation method.
    Typically, the value of venture capital project is uncertain,and thus venture capitalist must take decisions based on ex ante estimates about what this future value will be. Due to estimation uncertainties, it is difficult to identify the truly best projects, whereby the selected portfolio is typically suboptimal. Furthermore, it can be shown that the value of the selected portfolio is systematically overestimated, causing the VC to experience post-decision disappointment. The phenomenon underlying post-decision disappointment is, in short, that the more the value of a project has been overestimated, the more probable it is that this project will be selected. In this paper, a Bayesian model framework to account for value uncertainties in project portfolio selection is developed. Our analytical and simulation results show that, in comparison with the straightforward portfolio selection based on ex ante value estimates, the explicit Bayesian modeling of estimation uncertainties tends to give more accurate project value estimates, resulting in a higher expected portfolio utility value, and eliminate the expected gap between the realized ex post portfolio utility value and the estimated ex ante portfolio utility value. Moreover, our results have shown that the Bayesian revision of value estimates decrease the level of disappointment that the VC can expect to experience.
    With the proposed Bayesian framework VC can gather more precise information about projects' value and mitigate the experienced post-decision disappointment. Apart from the debiasing of value estimates, our frame-work could be extended by developing a model that accounts both value and cost uncertainties. This way number of targets of application could be substantially increased.
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    CVaR Based High Dimensional Portfolio Selection under Norm Constraints
    XU Qi-fa, ZHOU Ying-ying, JIANG Cui-xia
    2017, 25 (2):  40-49.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.005
    Abstract ( 923 )   PDF (1693KB) ( 998 )   Save
    In practice, monitoring and managing a portfolio with many assets is not only time consuming but also expensive. It is therefore ideal to pick a reasonable number of stocks to address these two issues. However, this has not been considered in traditional portfolio methods. In addition, the traditional portfolio methods often cause too extreme long and short positions, which implies a high trading cost. To this end, a new method of portfolio selection through adding norm constraints is proposed to the standard CVaR portfolio investment selection model. The basic idea of our method comes from variable selection procedure like LASSO in statistics and contains three important aspects. First, it is illustrated that the process of solving the CVaR portfolio selection model is equivalent to a classical quantile regression problem. As we all know, quantile regression approach is efficient to describe the behavior of a financial asset across quantiles, which is corresponding to a CVaR value. Second, the CVaR portfolio selection model with norm constraints is solved through LASSO quantile regression approach. Third, selection criterions for optimal number of financial assets are compared through Monte Carlo numerical simulations considering two cases:n>p and np and n p case. For illustration, we also do empirical analysis on Shanghai and Shenzhen 300 (HS300) index. The sample period spans from Apr 11, 2011 to Nov 11, 2013. Note that the 300 constituent stocks in HS300 are always changing in the sample period since the sample is adjusted every half year. Those stocks are intersected and ultimately 230 constituent stocks are kept for a portfolio candidate. It shows that with norm constraints, our method avoids two extreme positions effectively. Moreover, our method is efficient for solving high dimension portfolio selection and outperforms some popular method like L1-Variance model in dispersing tail risk of portfolio only using a small amount of financial assets. For example, our method reduces the VaR by 30.28% in sample and 0.69% out of sample, while reduces the CVaR by 44.92% in sample and 10.42% out of sample. To sum up, our new method is a general one that includes the standard CVaR-based portfolio selection model as a special case. It is certainly that our method can be improved by utilizing some alternative constraints like SCAD (Softly Clipped Absolute Deviation) penalty. This penalty will bring an unbiased results, which does not have in our current method. This is left for future research.
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    Advance Sellingin the Presence of Uncertainty Market Size
    LI Hui, QI Er-shi
    2017, 25 (2):  50-56.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.006
    Abstract ( 1086 )   PDF (873KB) ( 1110 )   Save
    Advance selling is the sale of a product before it is released. This strategy can help the retailer to better forecast the demand through reducing the uncertainty of demand. In this paper, the conditions that a retailer can implement advance selling strategy are examined in the case of uncertain market size. Based on the behavior properties of strategic consumers, the newsvendor model is established to take the comparative study between the strategies of advance selling and no advance selling, and the optimal advance price and order quantity are obtained through establishing the profit functions of the two sales strategies. It is fourd that when the consumers' expected valuation of the product is high or when the unit order cost is low, advance selling may bring more profit to the retailer. Otherwise, the retailer may be inclined to prefer no advance selling strategy. When the retailer applies advance selling strategy, the advance price is not always smaller than spot price. In order to avoid the risk of stock-out in spot period, under some certain situations, the consumers are likely to pay a higher price to buy in advance period. Under this situation, the advance price may be higher than the spot price.
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    Multi-product Newsvendor Model with Multivariate Markovian Demand
    CHEN Jie, TANG Ping, GAO Teng
    2017, 25 (2):  57-67.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.007
    Abstract ( 1011 )   PDF (1117KB) ( 1087 )   Save
    In practice, many companies have more than one product in inventory, and multi-product inventory control problem is more complicated than single product inventory control problem. At present, the multi-product inventory problem has aroused widespread attention, However, most authors only consider independently demands, little attention has been paid to the inventory with dependent demands. In fact, some multiple data sequences of the demands are correlated to each other, and these correlations impact on the optimal policy for multiple products inventory system. To explore the relationships among the demands and characterize the statistical law of inner movement for the demands of multiple products, these multiple data sequences are modelled by using multivariate Markov processes, and the multi-product newsvendor model with multivariate Markovian demand is proposed according to the movement characteristics of the demands. Under the theoretical framework of the new multi-product newsvendor model, the optimal ordering policy for the multi-product inventory system is studied, and the properties of the solution for model are analyzed through the truncated probability, dual factors and strength of relationships among the demands. The conclusion demonstrates that the optimality of ordering policy has a positive correlation with expected profit related to the truncated probability and a paradoxical relation with the dual factors; there is a unique advantage on the new model compare with the conventional multi-product newsvendor model, that is the strength of the demand correlation impact on the optimal ordering policy is fully considered. Moreover, the feasibleness and effectiveness for the model are verified through the numerical example, and some important management implications of the model are given for the optimization and control in the inventory system. From the new model, the relationships among competitive products are modeled, and decision-maker can obtain the information for the correlations of demands impact on the optimal ordering policy.
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    Closed-Loop Supply Chain Coordination Mechanism Based on Mean-CVaR
    CHEN Yu-ke, XIONG Long, DONG Jing-rong
    2017, 25 (2):  68-77.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.008
    Abstract ( 961 )   PDF (1611KB) ( 875 )   Save
    In the paper, a three-stage close-loop supply chain system including a risk-aversion retailer, a risk-neutral manufacturer and a risk-neutral recycler is studied. A mean-CVaR close-loop supply chain model is established with mathematical methods. It analyzes the optimal decision of the close-loop supply chain members in decentralized decision-making situation and joint decision-making situation respectively. It is paper proved that the mean-CVaR criterion can help to improve order quantity and profits. It is indicated that profit sharing-cost sharing contract can not only coordinate close-loop supply chain members, but also can improve the recycling quantity of worn-out products. Moreover, how λ and η influence the close-loop supply chain decision maker's profit and the profit of the whole system is analyzed.
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    The Study of Emission Reduction Model for Supply Chain Considering Transportation
    LI Jian, SU Qin
    2017, 25 (2):  78-86.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.009
    Abstract ( 966 )   PDF (1797KB) ( 983 )   Save
    Based on two-stage supply chain system for retailer-and-manufacturer, considering transportation process of including carbon tax cost, a carbon trading model that take into account investment for reducing emission is established in the paper, and model under carbon policy is compared to that under no policy. By this, the influence mechanism of carbon policies on supply chain is studied. The results show:under the constraint of the ratio of transportation and cost for retailer, carbon tax raises the price of energy and reduces emissions; under the constraint of the strict cap, carbon trading policy including investment for emissions reduction can realize the dual optimization of the manufacturer cost and emissions; manufacturer taking the partial transportation can achieve the coordination of supply chain, and the multiple carbon policies can reduce coordination cost. Finally, the models are verified and analyzed by a numerical example.
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    Cost and Revenue Optimization for Supply Chain Network of Dairy Products with Short-Life-Cycle
    GUO Chuan-hao, CHEN Fang, SHAN Er-fang
    2017, 25 (2):  87-97.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.010
    Abstract ( 1155 )   PDF (2278KB) ( 967 )   Save
    Compared with the developed countries, the cold chain logistics started relatively late in China. Nowadays, there still exists some problems in cold chain logistics in China. For instance, facilities are not complete, cold chain management is not perfect, cost is high, profits are low, and so on. Especially, the supply chain network of dairy products with short-life-cycle is a special class of cold chain logistics. Since the dairy products with short-life-cycle are perishable, we need not only to make sure of the quality of dairy products, but also to send them to the right place in the fastest way, in the shortest possible time. Meanwhile, the dairy products with short-life-cycle have some characteristics. For example, the customer demand is uncertain and difficult to predict, product variety, the small amount of product's order, etc. Thus, the requirements for dairy products supply chain network management are higher, and subsequently, the corresponding cost is relatively high.One of the goals of researches on supply chain network is to minimize the total cost and maximize the total revenue at the same time under the condition of the whole supply chain network satisfying the customers certain demand. In this paper, for short-life-cycle dairy products which have many varieties and are difficult to store as well as have some special requirements in the process of transportation, the related cost and revenue optimization problems for the four levels of dairy products supply chain network with "supplier-manufacture-distributioncenter-retailer" are studied. Under the condition of satisfying the customers demand for some products, a double-objective mixed-integer programming model is established, which can ensure that the cost and the revenue of the dairy products supply chain network could obtain the optimal value at the same time. Moreover, in order to describe the product's practical inventory for retailers effectively, a new nonlinear function is introduced in this paper to define the dairy product's inventory. By making use of the structure characteristics of the proposed model, a new augmented ε-constraint method is designed to solve the model. The empirical analysis results show that the proposed model could not only provide optimal decision-making scheme such that the cost and the revenue of the whole supply chain network could achieve the optimal value at the same time, also give the related optimal decision schemes for the products production, transportation and so on. Furthermore, the designed method is more promising than the standard ε-constraint method. The related research results have important potential guiding significance for studying how to optimize the cost and the revenue of supply chain and improve the customer's satisfaction, solving the general double-objective optimization problems and so on.
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    Coordinating a Group Purchasing Supply Chain under Economies of Scale and Competition
    ZHOU Mao-sen, DAN Bin
    2017, 25 (2):  98-110.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.011
    Abstract ( 3808 )   PDF (2170KB) ( 1035 )   Save
    In the current context of variety and small batch production, group purchasing has been increasingly viewed as an effective tool to save cost and improve performance in manufacturing. Through group purchasing, manufacturers can realize economies of scale by aggregating their purchasing volume. However, in many cases, due to incentive misalignment, group purchasing may create less value than individual purchasing, which makes group purchasing infeasible. To study the value-creating and incentive issues with group purchasing, a supply chain that consists of one group purchasing organization (GPO) and two manufacturers competing in quantity is investigated. The GPO purchases a common component from vendors at a price given by a quantity discount function, and then provides the component for the manufacturers at a transfer price. The manufacturers further process the component to make imperfectly substitutable products. A two-stage Stackelberg game model is used to study the equilibrium decisions. In the first stage, the GPO sets a unified wholesale price of the component for the manufacturers. In the second stage, upon learning the wholesale price, each manufacturer decides his order quantity.
    The main work in this paper includes four parts. At first, two benchmark models are established to investigate the scenarios of centralized decision and individual purchasing, respectively, and the feasible condition of group purchasing is analyzed. Secondly, the decentralized decision model of group purchasing with wholesale price contracts is constructed, and by analyzing the impacts of economies of scale, competition intensity and component value on the equilibrium results, the incentive issues for the manufacturers to participate in group purchasing are raised. Thirdly, to address the incentive issues of group purchasing, two contracting schemes for supply chain coordination are presented, and their participation conditions are also checked to show their applicability. Finally, a numerical example is given to illuminate the impacts of the environment parameters on the quantities and the profits under different scenarios.
    The results indicate that group purchasing can be feasible relative to individual purchasing only under certain conditions, especially when the component value is higher or the competition is more intense. Group purchasing with wholesale price contracts will not only decrease the value of group purchasing, but also reduce the motivation of the manufacturers to participate in group purchasing, thus they make group purchasing more difficult to be feasible. Although a revenue sharing contracting scheme can achieve the first best value of group purchasing, it cannot satisfy the manufacturers' participation conditions in some cases, especially when the scale economy is lower and the competition is more intense. Instead, a two-part tariff contracting scheme, composed of a membership fee and a trade commission, can not only achieve the first best value of group purchasing, but also satisfy the manufacturers' participation conditions in all cases, thus it can coordinate the supply chain under group purchasing perfectly.
    In summary, the value of group purchasing under economies of scale and competition is investigated, which provides a new insight on the incentive issues of group purchasing. Moreover, contracting mechanisms are used to coordinate the supply chain under group purchasing, which offers a practical and a theoretical guidance to improve the value of group purchasing.
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    A Multi-player Game Model about Product Quality Regulation Based on Incomplete Information
    ZHAO Ying-mei, GUO Ben-hai, LIU Si-feng
    2017, 25 (2):  111-120.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.012
    Abstract ( 991 )   PDF (968KB) ( 1227 )   Save
    LongAbstract:In view of the domestic product quality and safety accidents in recent years,a topic about product quality regulation is involved in this paper.What causes the frequent occurrence of product quality and safety accidents is the information asymmetry in the product quality supervision.Owing to the complexity during the production process and the non disclosure information existed in the quality formation,those businesses who are in a strong position seek improper interest wantonly with their information superiority.While the right to be informed and other related rights and interests of the weak ones can't get the guarantee.Based on this,a three party static game model involving manufactures,dealers and government supervision department is constructed in this paper.It strengthens the rationality of the three subjects to crack the dilemma in the procedure of the product quality supervision with the interest realization mechanism.By constructing and analyzing the game model, the result shows whether these three subjects will regulate their own behavior strictly or not mainly depends on the supervision of their own,direct supervision cost and the opportunity cost of the regulation.Hence,a few of conclusion are drawn based on the research.If we want to handle the product quality issues and regulate government and enterprises behavior effectively,these three measures are supposed to be taken at the same time.Firstly,it is wise to decrease the government supervision cost by improving regulatory processes and optimizing information structure.Secondly,it is supposed to put pressure on the government and enhance government motive power to promote it to pay more attention to the product quality by using law and administrative means comprehensively.In addition,containing the local protectionism by strengthening the third party supervision is the priority among priorities.
    These conclusions make a supplement to the early researches involving product quality regulation by other researchers.Besides,it makes the benefit mechanism more effectively by introducing the third variable-government.The results drawn in the research can help manufactures,dealers and government play their role better in the supervision system.
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    Co-op Advertising and Emission Reduction Cost Sharing Contract and Coordination in Low-carbon Supply Chain Based on Fairness Concerns
    ZHOU Yan-ju, BAO Mao-jing, CHEN Xiao-hong, XU Xuan-hua
    2017, 25 (2):  121-129.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.013
    Abstract ( 1146 )   PDF (948KB) ( 1432 )   Save
    Governments' energy-saving emission reduction policies and consumers' low-carbon preference have important implications for an enterprise's production operations. Implementing processes that save energy and reduce carbon emissions always increases a company's operation costs. In response to the consumers who has low-carbon preference, companies often adopt advertising campaigns to increase product sales, which further increases the sales cost. The increase of production and sale costs bring down the market performance of supply chain. In this paper, a low-carbon supply chain channel with one manufacturer and one retailer is considered and how to optimize the low-carbon supply chain management decision is shown and the supply chain performance is improved through contract design. In this paper the co-op advertising (CA) contract and the co-op advertising and emission reduction cost sharing (CA-ERCS) contracts how to impact the low-carbon supply chain's optimal decision and coordination are analyzed. How the optimal decision and coordination change when a retailer has fairness concerns is also explored. There are several findings. First, regardless of whether or not the retailer has fairness concerns, a co-op advertising contract cannot achieve channel coordination, but can enhance channel effectiveness; Second, when the retailer does not have fairness concerns, the co-op advertising and emission reduction cost sharing contracts can achieve channel coordination and achieve win-win situation under certain conditions; Third, the retailer's fairness concerns can change the co-op advertising and emission reduction cost sharing contracts' coordination in some cases:when the retailer feels general equality, the channel can be coordinated; when the retailer feels disadvantageous inequality, the channel can be coordinated only when the marginal profits of the manufacturer and the retailer within a certain proportion; but when the retailer feels advantageous inequality, the channel cannot be coordinated. So the retailer's fairness concerns can change the contract's coordination under certain conditions. Our study contributes to the theoretical basis for the design of low-carbon supply chain cooperation contracts, especially in cases where the retailer has fairness concerns.
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    A Game Analysis of Optimal Advertising Efforts and Direct Price Discount Strategy for the Two-level Supply Chain
    HE Li-hong, LIAO Xi, LIU Meng-meng, YUAN Chun
    2017, 25 (2):  130-138.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.014
    Abstract ( 1036 )   PDF (1574KB) ( 978 )   Save
    When the market demand is sensitive to sales price and the advertising efforts, both manufacturer and retailer in a supply chain must make decisions on their advertising effort levels and price discount. Based on the new demand function which is simultaneously affected by advertising efforts and direct price discount offered by the manufacturer to consumers, the optimal advertising efforts strategy of the supply chain and direct price discount of the manufacturer are mainly discussed by comparing four game models, which are Nash Equilibrium, Stackelberg game model in which the manufacturer is leader, Stackelberg game model in which the retailer is leader and cooperative game. The study finds that only when price elasticity meets a certain level, the manufacturer is willing to offer direct discount to consumers. Besides, the greater the price elasticity is, the more discount will be given and consumers can get the maximum discount in cooperative model. Once the manufacturer gives consumers the optimal price discount, the advertising efforts of both the manufacturer and the retailer are found to be positively correlated with the price elasticity. In addition, there is a certain proportion between their advertising costs. One player can estimate the other's cost of advertisement in accordance with its own advertising cost. In comparison of the optimal strategies in above four models, the results reveal that the advertising efforts by both manufacturer and retailer in cooperative model, as well as price discount the manufacturer providing to the consumers, are greater than those in the other models; thus, the maximal profit of a supply chain can be obtained using cooperative strategy. Finally, Pareto improvement is used to coordinate the cooperative game model to realize the multi-wins situation of both players of supply chain and consumers. All findings above can guide players to make optimal selection of cooperative models, advertising efforts strategy and price discount strategy.
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    How User Control Affects the Effectiveness of Video Advertising?
    YI Cheng, ZHOU Mi
    2017, 25 (2):  139-146.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.015
    Abstract ( 1251 )   PDF (1588KB) ( 906 )   Save
    Video advertising, a widely used online advertising format, has become the major source of revenue for video-viewing websites. However, video ads often interrupt users' video viewing experience, leading to increased annoyance and even negative attitudes towards the advertising brands. In view of the lack of research on the effectiveness of video advertising design and online users' interaction with ads in particular, the current research investigates the effects of users' skipping control over video ads on their attention to and memory of the ads content, as well as their brand attitudes. Furthermore, the moderating role of users' online information task type (i.e., searching versus browsing) is also examined. Drawing on information control and online information task literature, it is proposed that for information browsers, providing skipping control over video ads will lead to increased memory of the ads content and enhanced brand attitudes, whereas the reverse will happen for information searchers.
    A 2 (ads control:skippable vs. non-skippable)×2 (task:searching vs. browsing) laboratory experiment is conducted to test the hypotheses. Video viewing platforms with different advertising skipping control are created, and 90 college student participants are randomly assigned to one of the experimental groups. Both questionnaire and eye-tracking data are collected from the participants. The experimental results largely confirm the hypotheses. This research contributes to the literature of online advertising design and effectiveness, and provides practical guidance in terms of how to improve video ads effectiveness through designing for user interactions.
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    A Two-stage Method for Mega Projects Bidding System Based on Fuzzy Analytic Hierarchy Processand Gale-shapley Strategy
    DING Xiao, SHENG Zhao-han, LIU Hui-min
    2017, 25 (2):  147-154.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.016
    Abstract ( 1077 )   PDF (1490KB) ( 866 )   Save
    At present,China's bidding system is mainly used in the field of construction projects such as engineering survey,turnkey,design and supervision.Fault in bidding stage contributes to the late part of projects.It is proposed that there is a resource deployment optimization problem in bidding system of mega.Based on the theory of fuzzy analytic hierarchy process(FAHP)and Gale-Shapley(G-S) strategy, a two-phase bidding system is proposed.N_M bidding enterprises are eliminated by FAHP in the first phase.FAHP proposed by T.L.Satty is a quantitative method for uncertain problem. In the second phase. a Two-sided match is given through G-S strategy.To maximize the system utility, the exchange condition is changed from comparing individual preferences into system preferences.The final comparison examples show that new method is effective at promoting system utility.The existence of optimal solution and Pareto optimality proves its feasibility.Based on the result of CPU time and the number of iterations, our method can be further extended to the common two-sided match problem.
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    Geopolinomic Analysis of Industrial Structural Changes of Countries based on a Multiple-country-sector General-Equilibrium Model
    HU Min, WANG Zheng, GU Gao-xiang
    2017, 25 (2):  155-164.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.017
    Abstract ( 1027 )   PDF (3679KB) ( 797 )   Save
    Based on a multiple-country-sector general-equilibrium model, the development and industrial structural changes of several main countries or regions are analyzed. Taking geographic interaction into account, the world in this paper is divided into 10 countries and regions, and every country or region has 12 industrial sectors. And different investment structures are also made to analyze the changes of industrial structure. The results show that if China strengthen the development of the service sector, the development of China's and global economy will be better. If the USA and Japan strengthen the development of second industry, the economy of them will get bad influence, and this will also be bad to the economy of global economy.
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    A Dynamic Combined Evaluation Method Based on Fuzzy Borda and Its Application
    XU Lin-ming, LIN Zhi-bing, LI Mei-juan, WU Song-qiang
    2017, 25 (2):  165-173.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.018
    Abstract ( 1088 )   PDF (919KB) ( 859 )   Save
    A dynamic combined evaluation method based on fuzzy Borda is proposed, in order to get rid of the inconsistency among evaluation results from different dynamic evaluation methods. The two-dimensional data with time series data is extended to three-dimensional data. The dynamic combined evaluation method based on fuzzy Borda combines the comprehensive evaluation values and sorting results from different dynamic evaluation methods in dynamic compatible methods set. In order to grasp the overall situation and development trend for regional collaborative innovation capabilities, need for dynamic evaluation. The source data of the evaluation indicators for the regional collaborative innovation capacities come from China Statistical Yearbook, China Statistical Yearbook on Science and Technology, China Statistical Yearbook on Regional Economics. The collaborative innovation capabilities of the provinces in China are evaluated using the dynamic evaluation methods, but the evaluation results from different dynamic evaluation methods are inconsistent, therefore the evaluation results are combined using the dynamic combined evaluation method based on fuzzy Borda. The research shows that regional collaborative innovation capabilities in Chinese provinces and autonomous regions are different from 2009 to 2013. Viewing from their rankings, the regional collaborative innovation capabilities of the eastern coastal areas are at the highest level, those of the northeast and central regions at the middle, and those of the western regions at the lowest. Such an evaluation, as an instance, shows that the findings of this work are practically effective. The consistency evaluation results of the evaluation objects at a certain time and the overall evaluation results of the evaluation objects at a period of time are both obtained by this method. The method proposed in this study provides an idea in dealing with dynamic evaluation and the inconsistency among dynamic evaluation results, helpfully complements the comprehensive evaluation method, and facilitates the researches in related fields.
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    Performance Evaluation of Portfolios with Cardinality Constraints
    ZHOU Zhong-bao, JIN Qian-ying, ZENG Xi-mei, WU Qian, LIU Wen-bin
    2017, 25 (2):  174-179.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.019
    Abstract ( 1188 )   PDF (1523KB) ( 1066 )   Save
    Using Data Envelopment Analysis (DEA) to evaluate the performance of portfolios requires that the portfolio efficient frontier is continuous and concave. However, the efficient frontier on considering cardinality constraints may not be continuous or concave. Obviously, the direct use of DEA to evaluate the performance of portfolios with cardinality constraints is not reasonable. In this case, the definition of portfolio efficiencyis provided. Since the efficient frontier with cardinality constraints is a piecewise concave function, a numerical searching algorithm is put forward to obtain the sample segment points, which are used to group portfolios under cardinality constraints. The DEA model is then used to evaluate the performance of portfolios in each group. The simulation example indicates that, with the increase of sample size, the sample segment points converge to the real segment points, the DEA frontiers converge to the efficient frontier with cardinality constraints, the correlations between DEA efficiencies and portfolio efficiencies are becoming larger, which all indicate the feasibility and effectiveness of the proposed approach.
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    Variable Precision Rough Set Model and Application Based on Dominance Grey Degree
    LIU Yong, Jeffrey Forrest, XIONG Xiao-xuan, LIU Si-feng
    2017, 25 (2):  180-186.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.020
    Abstract ( 1075 )   PDF (919KB) ( 1124 )   Save
    Due to the complexity and uncertainty of the physical world, as well as the limitation of human ability to comprehend, it is very difficult for the traditional rough set to effectively deal with the real decision making information system consisted of a lot of preference information, grey information and noise data. In view of this, the thought and method of the grey system is used to construct the variable precision rough set model based on dominance grey degree in the paper. The method, to begin with, based on the new results of the grey number and grey degree, the concept of dominance grey degree is proposed to determine the dominance relationship between objects, so that it is used to substitute for the indiscernibility relationship of variable precision rough set, and then the variable precision rough set model based on dominance grey degree is established, and then its natures are discussed, finally an examples is used to validate the effectiveness and applicability of the model. The result shows that the proposed model has a certain tolerant ability by adjusting the threshold parameter, and then it can realize the scientific decision-making by effectively extracting decision rules.
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    Strategy of Entering into Networks of Transfer Enterprise, Network Structure and Level of Knowledge
    MA Yong-hong, ZHANG Fan
    2017, 25 (2):  187-196.  doi: 10.16381/j.cnki.issn1003-207x.2017.02.021
    Abstract ( 1045 )   PDF (13674KB) ( 942 )   Save
    A large number of enterprises enter industrial cluster by the way of cluster transfer, and realize the common growth between themselves and local companies through the netting cooperation with local companies. The speciality of netting strategy will effect the cluster network structure and knowledge level. The strategy of entering into networks of transfer enterprise is definited based on environmental uncertainty, and the dynamic simulation model of cooperative innovation of transfer enterprise and local enterprise is constructed by multi-agent simulation methods. Then three network structures are compared by following three kinds of networks which take shape after cooperative innovation by transfer enterprise and local enterprise. On this basis, the level of knowledge of cluster under three kinds of environments is compared, and the mechanism of the simulation results is explored. The results show that:under the condition of environmental difference the network structure and knowledge level of clusters present a different changing rule. Risk cluster has the feather of high connectivity and high knowledge level. Partial transfer of business in Shackle cluster are failure to cooperate with local enterprise. And the knowledge width of Shackle cluster has many zero growth. The risk environment is more suitable for transfer enterprise to local embedded in the long run. Risk environment is more suitable for the cluster environment of transfer of enterprise of the local embedding netting, and it accelerates the transfer of promoting enterprise to enhance the cluster knowledge level of the cluster. The research perspective of transfer enterprise netting strategy is expanded into the environmental uncertainty. In a certain sense,it reveals the influence of transfer enterprise netting strategy on the cluster innovation network structure and knowledge level under the condition of environmental difference, and provides certain reference basis for the administrator to develop system and improve the cluster environment.
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