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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 July 2020, Volume 28 Issue 7 Previous Issue    Next Issue
    Articles
    Research on The Self-exciting Effect of Chinese Stock Market Considering Investor Sentiment
    TANG Zhen-peng, WU Jun-chuan, RAN Meng, ZHANG Ting-ting
    2020, 28 (7):  1-12.  doi: 10.16381/j.cnki.issn1003-207x.2018.1001
    Abstract ( 421 )   PDF (3586KB) ( 347 )   Save
    In recent years, extreme events such as continuous soaring and plummeting have occurred frequently in Chinese stock market, and the management of extreme risks in the stock market has been severely challenged. In order to explore the relationship between extreme events and the impact of Investor Sentiment on the extreme returns of the stock market. In this paper, the Process of the Marked Self-exciting Point Process (MSEPP) is used to describe the clustering and short-term dependence of the extreme return series of stock index, and the homogeneous Poisson process with fixed intensity λ described by the traditional Peaks Over Threshold(POT) model is extended to the non-homogeneous Poisson process with time-varying intensity function λ(·). Using the method of risk preference index, the Equity Market Sentiment Index(EMSI) of Chinese stock market is synthesized based on the CSI300 Index Components. Taking EMSI as one of the explanatory variables of the strength function λ(·), the MSE PP-EMSI model is further constructed to predict the extreme risk Outbreak Probability of CSI 300 index, Shanghai composite index and Shenzhen component index during the stock market crash in 2015, and to measure the dynamic Expectd Shortfall(ES) risk of these indexes from June 9, 2017 to March 30, 2018. The empirical results show that the stock indexes of Shanghai and Shenzhen stock markets have plummeted continuously in the short term, and investors' extreme negative emotions will aggravate the violent turbulence of the stock market. When considering the impact of investors' emotions on extreme risks, MSEPP-EMSI model can effectively improve the probability prediction accuracy and ES prediction accuracy of extreme risks. The conclusion of this study reveals the Self-exciting effect of extreme risks in Chinese stock market, and explores the impact of investor sentiment on stock market returns, expanding the research in related behavioral finance fields. At the same time, it can effectively guide the trading behavior of stock market participants, enhance the risk management level of institutional investors in the face of extreme risks, and provide a basis for government regulatory authorities to formulate policies.
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    Under the Macroscopic Stress Test Commercial Bank Retail Credit Products PD Model Prediction Research
    XIONG Yi-peng, XIONG Zheng-de, YAO Zhu
    2020, 28 (7):  13-22.  doi: 10.16381/j.cnki.issn1003-207x.2020.07.002
    Abstract ( 277 )   PDF (1262KB) ( 95 )   Save
    Stress testing is designated by the Basel Committee as an important tool for identifying, measuring and controlling liquidity risk and is an important part of the enterprise risk management framework. The China Banking Regulatory Commission also requires banks to establish a stress testing framework to effectively manage capital so that they hold sufficient capital to withstand risks at all stages of the economic cycle and assess potential losses in relatively extreme scenarios. However, the domestic retail banking stress test method has not yet fully unified the standard. The applicability of various measurement models under different scenarios needs further testing, and the study of the credit risk of retail banks is also discussed in combination with domestic macroeconomic variables. Based on Chinese macroeconomic operation rules, a bank's retail credit product policy and business operation mode are combined, as well as the availability of relevant historical data, to design a stress test plan for the retail credit portfolio. The stress test program has good operability and good decision-making reference value, which is extended to other similar retail banks to help modern retail banks strengthen risk management.The data of the housing mortgage default probability index are from the data of Bank A from 2012 to 2016, and the macro factor indicator data are from the data of China National Bureau of Statistics website from 2006 to 2016. By using house mortgage loan data collected from a commercial bank, a prediction model for probability of default is constructed based on macroeconomic indicators. Economic indicators that proved to be significant predictors to default probability are trained by value at risk model, including gross domestic product (GDP), consumer price index(CPI) and Herrick Payoff Index(HPI). Through observing the AICC value of the VAR model of different lag order combinations, the high order items of those indicators are used to build the regression equation and to do the stress test. The results show that the probability of default begin to increase slowly from the stressing point, and the largest increase occurs under the condition of severe stress. It is indicated that the factorial of macroeconomic factors can better capture the above characteristics, and the PD prediction model can accurately describe the risk conduction process, which can be a strong support to commercial bank for the risk management in retail businesses.
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    The Impact of Investor Attention on Market Volatility Based on the LSTHAR Model
    QU Hui, SHEN Wei
    2020, 28 (7):  23-34.  doi: 10.16381/j.cnki.issn1003-207x.2020.07.003
    Abstract ( 296 )   PDF (1588KB) ( 106 )   Save
    Limited attention theory points out that investors have limited attention and can't possess all the information in the financial market. This will cause temporarily mispricing of stocks which generates volatility in the market, thus investor attention may include valuable information about future volatility.
    Since the Baidu index can well measure active investor attention in China, the logistic smooth transition structure is incorporated in the heterogeneous autoregressive (HAR) models of realized volatility, with the Baidu index being the transition variable, which can characterize the nonlinear influence of investor attention variation on future volatility. Three HAR models are considered as the benchmark model, that is, the basic HAR-RV model, the HAR-RV-J model which includes jumps and the HAR-RV-CJ model with separates the contribution of continuous volatility and jumps.
    50 ETF high-frequency data and the Baidu index from January 2, 2014 to November 30, 2017 are used as empirical data. For the out-of-sample forecast comparison, we not only compare the average losses, but also perform the Diebold-Mariano test and the model confidence set test to evaluate the statistical significance of the models' forecasting performance difference. Empirical results show that, the new models are significantly superior to the original heterogeneous autoregressive models both in-sample and out-of-sample, indicating that the nonlinear introduction of investor attention has significant contribution to volatility forecasting. In addition, compared to introducing the total index and the mobile index, introducing the PC oriented index contributes to volatility forecasting more significantly, showing that the investor attention represented by the PC oriented index impacts the market volatility more significantly.
    The volatility forecasting capability is effectively improved by the nonlinear introduction of investor attention, and the appropriate choice of investor attention proxy is illuminated. Meanwhile, it provides practical guides for investor risk management and investment decision-making.
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    A Study on Default Risk and Prevention Mechanism of China Shadow Banking——Evidence from Entrusted Loans of Listed Firm
    QIAN Xue-song, QU Shen, KANG Jin, DU Li
    2020, 28 (7):  35-44.  doi: 10.16381/j.cnki.issn1003-207x.2020.07.004
    Abstract ( 236 )   PDF (1025KB) ( 122 )   Save
    In recent years, the scale of shadow banking has grown rapidly in China. At the same time, the Chinese government repeatedly highlights the importance of preventing systemic financial risk. Since the shadow banking activity is outside the regulatory system, the risk of shadow banking is widely concerned. However, limited by the availability of micro-data, few papers empirically examine the risk of shadow banking. Fortunately, the Chinese listed companies disclosed the information of entrusted loans, which is a typical shadow banking mechanism. Using entrusted loans data of listed companies in China from 2004 to 2015, the risk of shadow banking in China is empirically examined in this paper. The data show that the default rate of entrusted loans is 10.09%, which is much higher than the non-performing loan ratio of banking financial institutions in the same period(1.94%). Moreover, the default of entrusted loans is more obvious for the real estate industry or in central and western China. Further, multiple regression methods are used to examine shadow banking riskfrom the perspective of collateral and distance. The results indicate that both the collateral and the distance affect the default rate of the entrusted loan. First, the collateral and the loan default rate are significantly positively correlated. This shows that in order to prevent the moral hazard problem, the lender will ask the borrower to provide collateral. Second, the distance between the lender and borrower is significantly and positively related to the default rate, which means that the farther the distance is, the harder it is for the lender to distinguish and supervise the borrower, thus pushing up the default ratio of entrusted loans. This study not only provides direct empirical evidence for the default risk of the shadow banking system in China, but also has important implications for shadowing banking participants and supervision.
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    Specification Test of Volatility Functions in Jump Diffusion Processes using Nearest Neighbor Truncation
    CHEN Qiang, GONG Yu-ting
    2020, 28 (7):  45-56.  doi: 10.16381/j.cnki.issn1003-207x.2020.07.005
    Abstract ( 206 )   PDF (1106KB) ( 56 )   Save
    Since the volatility function testing is sensitive to jumps in high frequency data, based on nearest neighbor truncation approach,new tests for volatility function form of jump diffusion models are constructed by thepartial sum residual processes. The tests approximating asymptotic properties and their bootstrap methods are investigated. The test statistics are asymptotically robust to the drift and jump terms in jump diffusions. Monte Carlo simulations show that the tests are robust to jumps, and have reasonable size and power performances. The proposed tests are applied to the data of Shanghai Interbank Offered Rate (Shibor), it is found that the jump robust tests can distinguish models better than non-robust tests.
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    Liquidity Provision and Intraday Price Efficiency——Evidence on Chinese Stock Market
    MA Dan, WANG Chun-feng, FANG Zhen-ming
    2020, 28 (7):  57-67.  doi: 10.16381/j.cnki.issn1003-207x.2020.07.006
    Abstract ( 252 )   PDF (1542KB) ( 109 )   Save
    In recent years, financial markets have experienced several crisis events. The US stock market crashed on May 6, 2010. The Chinese stock market suffered the price collapse in June 2015. The occurrence of these events due to the exhausted liquidity. Hence, liquidity supply is an important factor affecting market price efficiency. A sufficient and stable supply of liquidity can ensure the sustainability of the market price discovery process, while the lack of liquidity supply will hinder the transaction process, even result in price deviations and abnormal fluctuations. Although existing researches point out the importance of liquidity to price efficiency and the harm of liquidity shortage, there is barely literature concerning on the relationship between liquidity supply and price efficiency in Chinese stock market.
    In the perspective of market microstructure, effective ways are explored to improve intraday price efficiency using the contrarian trading ratio as the intraday liquidity provision. Considering the informed trading and market conditions, the moderating effect of institutional trading and price fluctuation is investigated to liquidity provision and price efficiency.
    In the conclusions of this paper, liquidity supply is an important factor affecting intraday price efficiency, and higher liquidity supply can significantly improve price efficiency. In terms of information trading, institutions are strategic and informed traders. Increasing the proportion of institutional transactions is positively promoting the relationship between liquidity supply and price efficiency. In terms of market status, stock price fluctuations measure the heterogeneous beliefs of the market to some extent. When the fluctuation is large, it is not conducive to the integration of market information and the effective recovery of price. Therefore, the lower price fluctuation has a positive effect on the relationship between liquidity supply and price efficiency.
    A new perspective for improving intraday price efficiency is provided, benefit to policy-making and investment decision. A certain contrarian trading ratio guarantees the liquidity supply of the market, while the continuous and stable liquidity supply helps not only the market price efficiency during the normal trading period, but also the extreme liquidity demand during the crisis period, thus improving the market quality. At the same time, high-frequency traders can capture short-term momentum or reverse earnings by capturing the imbalance of intraday trading and developing a homeopathic or contrarian trading strategy as needed.
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    Identification and Measurement of Leverage Effects Using Local Correlation and Truncated Distorted Mix Copula Constructing
    SHEN Gen-xiang, ZOU Xin-yue
    2020, 28 (7):  68-76.  doi: 10.16381/j.cnki.issn1003-207x.2018.1833
    Abstract ( 199 )   PDF (2281KB) ( 102 )   Save
    It is found the empirical evidence in China stock market that the dependence structure between the asset's return and its volatility measured by realized volatility, so-called the leverage effect, have a special correlation pattern in terms of local correlation, which is not consistent with that implied by typical leverage effect assumption,but consistent with the findings about American equity market in Chen and Ghysels (2011). The distortion mixture method of Li et al. (2014) is employed to construct Copulas to capture the tail dependence in real data, and tailor the quadratic distortion functions by truncation to mitigate the confounding of the components Copula in the mixture. The closeness of the local correlation pattern of the estimated local correlations using simulated data from the constructed Copulas to that of real data shows that the Copulas proposed in this paper capture the correlation features in real data well, and the nonparametric goodness-of-fit test confirms the validity of the Copula further.
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    The Spillover Effects of China's Monetary Policy on the United States——An Analysis based on the Two Countries' Open DSGE Model
    ZHAO Xing, CUI Bai-sheng
    2020, 28 (7):  77-88.  doi: 10.16381/j.cnki.issn1003-207x.2020.07.008
    Abstract ( 266 )   PDF (3973KB) ( 99 )   Save
    In recent years, with China becoming one of the world's major economies, the spillover effect of China's monetary policy on other countries has become a new topic. The open new Keynesian DSGE model is built to analyze the Chinese monetary spillover effects on the United Sates. The model includes three departments which are family, firm and monetary authority. Bayesian estimation method is used to estimate the dynamic parameters. There are two monetary policy rules used by the monetary authority. One is the interest rate rules. The other is the money supply rule. The results show that the monetary policy of China under the two monetary rules has the same direction of spillover to the economic variables of the United States, but there are still differences in the size of spillover effect. The spillover effect of interest rate reduction in China's money supply to the United States interest rate is obviously greater than the spillover effect of interest rate directly on interest rate. China's money supply policy is not as good as the smoothness of the interest rate policy. China pays more attention to inflation, output and exchange rate under the interest rate rules than it does under the rule of money supply. Therefore, from the perspective of China's domestic objectives of monetary policy and the coordination of international monetary policy, Taylor's rule is more suitable for China's current economic situation, and can reduce the impact on US macroeconomic variables while achieving the domestic objectives of stabilizing prices and economic growth.
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    Robust Decision to Reverse Factoring Supply Chain with Demand Disturbance
    CHEN Zhong-jie, YU Hui
    2020, 28 (7):  89-101.  doi: 10.16381/j.cnki.issn1003-207x.2020.07.009
    Abstract ( 274 )   PDF (2797KB) ( 123 )   Save
    Reverse factoring solves the seller's financing difficulty by using the good reputation of the buyer. In practice, core enterprises such as Xiaomi and Haier carry out the strategic cooperation on reverse factoring with financial institutions to alleviate supplier's financial difficulties and reduce the risk of supply disruptions.Previous studies have generally explored the impact of financial-oriented reverse factoring on supply-side operations. However, due to the transformation of commercial credit into bank credit, core enterprises are facing credit risk but not getting financing,does the credit risk affect the decision-making of core enterprises? In addition, demand disturbances often occur in reality, and demand uncertainty will inevitably lead to operational risk of supply chain and affect the repayment ability of reverse factoring, how should supply chain make decisions?
    The decision-making and operation rules of supply chain with reverse factoring are studied when only the mean and variance are known. A two-level supply chain consisting of a supplier and a retailers is constructed. A game model of supply chain based on wholesale price contract is established by using minimax method. Decision-making goals of the retailer and the supplier are $\begin{array}{*{20}{c}} {\mathop {\max }\limits_{q \ge 0} }&{\mathop {\min }\limits_{F \in {\Gamma _+ }\left({\mu,{\sigma ^2}} \right)} }&{E\left[{{\pi _r}\left({q,D} \right)} \right]} \end{array}$ and maxE[πs(w)].By solving the Stackelberg game model inversely, the quantitative decision of reverse factoring in supply chain is proposed:the optimum order quantity is ${q^*}=\mu + \frac{\sigma }{2} \cdot \frac{{P-W}}{{\sqrt {PW} }}$, and the optimal wholesale price w* meets with $\frac{{G{{\left({p-s} \right)}^2}}}{{{{\left({PW} \right)}^{1.5}}}}-\frac{{2\left({P-W} \right)}}{{{{\left({PW} \right)}^{0.5}}}}=\frac{{4\mu }}{\sigma }$. there $P=p-\left({w + \frac{{cl}}{A}} \right)$ (l is the credit risk loss coefficient),$W=\left({w + cl/A} \right)-s,G=w-c\left({1 + r} \right)$,they three represent the retailer's unit profit and unit unsalable loss, as well as the supplier's unit profit. The numerical expressions mean that the optimal wholesale price is the result of the trade-off between suppliers and retailers,and the optimal order quantity fluctuates in the mean value, which is affected by the relationship between retailers' profitability and unsalable loss. Combined with numerical simulation, the research shows that robust decision-making can provide effective and robust decision-making for missing information supply chain in reverse factoring; and the reverse factoring based on the supply chain relationship strengthens the supply chain cooperation; once the interest rate is determined, the profit of retailer will not be reduced because of the loss of the supplier's reputation, which eliminates the buyer's concerns on risk-taking of financing. Thus the research enriches the theory of interaction between finance and operation.
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    Research on Robust Optimization of Emergency Resource Allocation Based on Supplier Participation Mechanism under Uncertain Demand
    ZHANG Meng-ling, WANG Jing, HUANG Jun
    2020, 28 (7):  102-111.  doi: 10.16381/j.cnki.issn1003-207x.2019.0686
    Abstract ( 277 )   PDF (1550KB) ( 245 )   Save
    With the deepening of research of emergency management, the emergency resource optimization configuration in the emergency preparation stage is the prerequisite and basic guarantee for the effective implementation of rescue work after emergency. Based on the research of domestic and foreign related research, the emergency resource security strategy considering supplier participation mechanism is proposed in facing earthquake disasters. During the pre-disaster phase, the cooperation mechanism between government and suppliers is established by selecting suppliers to achieve the selection and resource allocation of government reserve warehouses. After disasters strike, the time-phase demand for emergency resources during rescue are either dispatched from the government reserve warehouses or supplier production capacity, with a view to coordinating the ratio of suppliers to government reserves, pre-disaster physical procurement and procurement of post-disaster production capacity. Therefore, the cost of the emergency resource security system is reduced while ensuring rescue efficiency.
    In this paper, with earthquake disasters being characterized by the uncertainty of demand, a robust optimization model for two-stage decision-making of disaster preparedness and disaster rescue with a set of uncertainty defined by the L1 -norm is equal to a solvable formulation. The duality theory and uncertainty sets are adopted to transform the robust model into a deterministic model that can be solved by CPLEX. Finally, a case study focused on the 2010 earthquake at Yushu County in Qinghai Province of China illustrates the application of the proposed model. The advantage of the robust model is demonstrated through comparison the stochastic model and deterministic model for the same problem. Sensitivity analysis shows the impact of minimum agreement amount, maximum order quantity and production capacity on total cost, which provides a good reference for actual decision makers offers managerial insights for government agencies.
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    Dual-channel Manufacturer's Referral Strategies Based on Risk Aversion
    LI Zeng-lu, GUO Qiang, NIE Jia-jia
    2020, 28 (7):  112-121.  doi: 10.16381/j.cnki.issn1003-207x.2020.07.011
    Abstract ( 280 )   PDF (1173KB) ( 138 )   Save
    With the development of internet, more and more manufacturers have launched direct channel, such as Huawei, Haier, and Lenovo. If the consumers search for a certain brand name, they are oftentimes led to manufacturer websites. You can browse the product information on its homepage, and then buy the product that you are interested in through the manufacture's referral channel, which called "manufacturer referral". There are two kinds of manufacturer referral strategies:1) referring the customers visiting his homepage to official store (OS); 2) referring the customers to official store and retailers (ORS). It is an amusing question for us to consider which referral strategy is better. Motived by this, we explore the referral strategies of dual-channel manufacturer.
    A supply chain consisted of a dual-channel manufacturer and a retailer is investigated. The consumers are grouped into two independent market segments:the traditional market and the referral market. The consumer in the traditional market know both official store and retailer of the manufacture, they purchase a certain product at the retailer or the official store directly. In the referral market, the consumers visit manufacture' websites, then purchase the product by the manufacture's referral channel. The scale of the consumer market is fluctuant in real life due to price, the degree of consumer concern, word of mouth effect, etc. So the following assumptions are proposed:1) the traditional market size is a random variable; 2) both manufacturer and retailer are risk aversion. It is assumed that the manufacturer set the wholesale price and the direct selling price firstly, and then the retailer as a follower decides the retailing price. The decision modes of the manufacturer and the retailer under different scenarios are developed respectively. Then the equilibrium outcomes of the decision models are derived by Stackelberg dynamic game theory.
    It is found from the result that:In the benchmark model without risk aversion, when the size of referral market size is small, the manufacturer refers the consumers to official store (OS), but if the referral market size is large, the manufacturer refers the consumers to official store and retailers (ORS). In the case where the retailer is risk aversion, compared with the benchmark, when the referral market size is mediate, if the competitive intensity is weak, with the increase of the retailer' risk aversion degree the referral strategies from OS changing to ORS; if the competitive intensity is large, with the increase of the retailer' risk aversion degree the referral strategies from ORS changing to OS. Under different scenario where the manufacturer is risk aversion, if the referral market size is mediate, with the increasing of risk aversion degree of the manufacturer, the referral strategies is changed from OS to ORS. Finally, the refer strategies are researched under all the supply chain members are risk aversion by numerical example. The paper can enrich and perfect the relevant theories of dual-channel supply chain, and provide some useful guidance for the manufacturer and retailer.
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    Study on the Outsourcing of Fresh Agricultural Products under Partial Information
    ZHOU Ji-xiang, WANG Yong, QIU Han-guang
    2020, 28 (7):  122-131.  doi: 10.16381/j.cnki.issn1003-207x.2020.07.012
    Abstract ( 292 )   PDF (1072KB) ( 152 )   Save
    In the absence of market demand information, the inherent properties of metamorphism, short life cycle and small residual value of fresh agricultural products bring great risk to retailers who sell fresh agricultural products. Retailers outsource procurement business to third-party logistics companies with close business relations therewith. It can not only transfer its procurement risk, but also make 3PL obtain certain business. Based on this, a game model between retailers and 3PL is established, to compare and analyze the influence of 3PL purchasing and retailer purchasing on the optimal decision and profit of retailer and 3PL as well as the profit of supply chain system under partial demand information. The results show that the judgment of the actual demand of 3PL on fresh agricultural products is more accurate when the forward direction demand risk is high. When the demand risk is small, the judgment of the actual demand of retailers on fresh agricultural products is more accurate. It is also found that in most cases, 3PL procurement is unfavorable to the supply chain system. Only when the forward direction demand risk is very high, or the consumption rate of fresh agricultural products is very large, or the loss sharing ratio is very high, can the 3PL procurement increase the profit of the supply chain system. However, the profit of 3PL is lower than that of retailer under the condition that the procurement increases the profit of supply chain system. It is suggested that retailers should adopt the method of returning 3PL profits to encourage 3PL to participate in purchasing management, so as to increase the profits of retailers, 3PL and supply chain system and improve the competitiveness of supply chain.
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    Two-period Pricing and Contract Design of Supply Chain Considering Consumers' Strategic Behavior
    ZHANG Xu-mei, WANG Da-fei, REN Ting-hai, GUAN Zi-li, DAN Bin
    2020, 28 (7):  132-145.  doi: 10.16381/j.cnki.issn1003-207x.2020.07.013
    Abstract ( 339 )   PDF (2293KB) ( 195 )   Save
    With the rapid development of information technology and internet, it is more and more convenient for consumers to obtain product information. As a result, consumers are becoming more and more rational. Consumers can strategically choose the time for purchase to maximize their utility. Because of the perishability of products and the fierce market competition, the firms often use markdown promotion to increase sales. Although the sales revenue can be quickly realized by markdown promotion, it will induce more consumers to choose to purchase at the markdown sales stage. This may lead to a reduction in demand at the normal sales stage, which is not benefit for the firms to obtain the high profit. In addition, the reduction in demand during the normal sales stage will lead to a reduction in the order quantity, which will adversely affect the upstream manufacturers. Therefore, according to the strategic purchase behavior of consumers, how to set the price in the normal sales and promotion stage and how to design effective contracts to coordinate the supply chain are researched in this paper.
    Considering a supply chain consists of a manufacturer and a retailer in which consumers' strategic purchase behavior exists, a two-period dynamic game model is established to analyze the effects of strategic degree of consumers' purchase behavior on the two-period equilibrium results, consumer surplus and social welfare. The optimal two-period dynamic pricing of the manufacturer and the retailer is studied. Further, the equilibrium results under the decentralized decision are compared with those under the centralized decision. Moreover, a two-period revenue sharing contract and a two-period revenue sharing contract combined with a transfer payment are proposed, which are related to the consumers' strategic degree.
    The results show that:(1) When the consumers' strategic degree is high, both the manufacturer and the retailer should decrease the price of the first period and increase the price of the second period, the total profit of the manufacturer and the retailer for two periods will decrease, the consumer surplus and social welfare will increase. (2) Under some cases, the consumers' strategic degree will weaken the price distortion in the two periods of decentralized decision, but the differences between the decentralized and the centralized system profits will increase with the consumers' strategic degree. (3) When the consumers' strategic degree is below a certain threshold, the two-period revenue-sharing contract can not only achieve supply chain perfect coordination but also improve consumer surplus and social welfare. (4) When the consumers' strategic degree is not below a certain threshold, the two-period revenue sharing combined with a transfer payment contract can achieve supply chain perfect coordination. However, the increase of consumers' strategic degree is not always able to improve consumer surplus or social welfare in this case.
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    Probabilistic Selling Policy Based on Consumers' Loss Utility
    YANG Guang, LIU Xin-wang, QIN Jin-dong
    2020, 28 (7):  146-155.  doi: 10.16381/j.cnki.issn1003-207x.2020.07.014
    Abstract ( 250 )   PDF (3488KB) ( 144 )   Save
    With rapid development of information technology, probabilistic selling, as a novel sales strategy, has been used widely in travel industry. The consumers' anticipated loss and its role are explored in a competitive market consisted of a vertical random product and its transparent rival. In our two-firm model, one firm (Firm H) provides a product with high quality (product H) and sells it transparently. The other firm (Firm R) provides two products with lower and different qualities (products M and L) and can mix them to create any possible random products, in addition to transparent products M and L. It starts with the benchmark case in which consumers have loss neutrality. It is shown that Firm R offers the random product only when the quality of product H is intermediate. When product H's quality is too high, Firm R offers product M because the product differentiation is large enough and it can extract more surplus from the consumers who value quality without worrying much about competition. When product H's quality is too low, Firm R will only offer product L to maximize differentiation from product H. Therefore, when the quality of product H is intermediate, a random product that mixes M and L should be offered to better balance surplus extraction and product differentiation by adjusting the probability of obtaining L. The case is then explored in which consumers can anticipate the potential-post purchase loss. Our results suggest that the consumers' anticipated loss can actually incentivize the firm to adopt probabilistic selling, depending on the relative magnitude of consumers' sensitivity to purchase loss and selection loss. Furthermore, even when consumers are extremely averse to selection loss, the random product should still be provided because of the benefits from the "reverse quality discrimination." Moreover, numerical application results and some parameters sensitivity analysis are given. Finally, some feasible and practical management insights are gotten.
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    The Optimal Production Decision with By-Product Synergy and Bargaining
    ZHOU Pin, XU He, LU Fen
    2020, 28 (7):  156-163.  doi: 10.16381/j.cnki.issn1003-207x.2020.07.015
    Abstract ( 197 )   PDF (1421KB) ( 92 )   Save
    A two-tier supply chain structure composed of a upstream manufacturer with environmental concern and a downstream processing plant is considered. The manufacturer produces the prime product and generates valuable wastes. The plant may produce the by-product based on the wastes (material) from the manufacturer. Based on different bargaining powers in the supply chain, the by-product synergy production mode is investigated, in which the manufacturer sells wastes to the plant and the plant converts the wastes into a new by-product. The manufacturer's optimal production decision is derived, the optimal trading price of wastes (between manufacturer and the plant) and the manufacturer's optimal waste-disposal strategy. The results show that by-product synergy production is not always better for manufacturer, which is determined by the customer's quantity sensitivity to the by-product. When this sensitivity is high, the manufacturer is more prone to disposing wastes by himself. However, if the customer is less sensitive, the manufacturer will choose the by-product synergy strategy. Meanwhile, as the increase of the manufacturer's bargaining power, the manufacturer's equilibrium profit increases and the plant's profit decreases, respectively. Finally,it is verified that our main results are still robust in random yield scenario.
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    How to Generate Channel Agility through Information Technology Governance
    CHI Mao-mao, LI Yan-hui, WANG Wei-jun, LU Xin-yuan
    2020, 28 (7):  164-173.  doi: 10.16381/j.cnki.issn1003-207x.2020.07.016
    Abstract ( 224 )   PDF (1121KB) ( 71 )   Save
    Today's marketplace is characterized by intense competitive pressures and high levels of turbulence and uncertainty. Firms require agility in their supply chains to provide competitive advantage. How to supply chain agility (i.e., channel agility) has attracted both researchers and practitioners. However, prior literature focuses on the following antecedents of supply chain agility, i.e., flexibility of the supply chain processes or IT flexibility, ignoring the effects of the governance factors on the channel agility. Based on IT governance and IT-business strategic alignment, the mediation model is studied, and explores the effect of IT governance, inter-firm e-business strategic alignment (including intellectual and operational alignment) and environmental turbulence on the channel agility are explord. Using data from a survey of IT or business executives in 209 firms, it is uncovered that IT governance has a positive effect on channel agility through intellectual and operational alignment. In addition, the mediating effect of operational alignment is more positive when higher level of environmental turbulence. Although there is no the moderated mediator effect in the path of IT governance-intellectual alignment-supply chain agile, the environmental turbulence has a negative moderated effect between IT governance and intellectual alignment, and has a positive moderated effect between intellectual alignment and channel agility. Through integrating IT governance and IT-business strategic alignment, it is revealed the effect mechanisms of IT governance and channel agility, and the theory of the generation of supply chain agility is also contributed.
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    The Evolution and Simulation of Product Quality Supervision in Enterprise Clusters
    KONG Qing-shan, ZHANG Qin, YANG Hui-xin, SHI Jian-gang
    2020, 28 (7):  174-183.  doi: 10.16381/j.cnki.issn1003-207x.2018.1385
    Abstract ( 234 )   PDF (3607KB) ( 108 )   Save
    The product quality fraud emerges in endlessly, quality supervision departments have to face the challenge of how to supervise the quality of a large number of enterprises' products. Different from making sampling plan by enterprise-scale (small medium and large according to certain ratio respectively), a supervision model of enterprise clusters supervision is proposed then the sampling strategy and punishment mechanism are discussed. The product quality evolution of enterprise clusters is also analyzed in four sampling strategy, namely free sampling, full sampling, global cluster sampling and stratified cluster sampling. In free sampling, quality punishment not be credible with the emergence of "regulation failure", all the enterprise clusters evolve to quality fraud strategy; In full sampling, the evolution of enterprise clusters depends on whether quality punishment cover cost reducing in quality fraud; In global cluster sampling and stratified cluster sampling, the ascension path of quality punishment and sampling probability is gotten besides enterprise clusters evolution path, the enterprise clusters evolve to standard quality when quality punishment according to the maximal cost reducing and competitive profit, the lower the quality punishment, the higher the sampling probability, the stratified cluster sampling can reduce the overall sampling probability. Our work provides theoretical support and decision reference for product quality supervision model. The enterprise clusters supervision model is hoped to play a role in practice of product quality supervision.
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    Method for Multiple-Attributes Trade Matching Considering Evaluations of the Third-Party in E-Brokerage
    LI Yong-hai, FAN Zhi-ping
    2020, 28 (7):  184-195.  doi: 10.16381/j.cnki.issn1003-207x.2020.07.018
    Abstract ( 184 )   PDF (1304KB) ( 137 )   Save
    With advances in information technology and Internet, posting product reviews is getting easier and it has become a habit for most people. These reviews, which can be seen in various websites easily, contain a wealth of information, such as customers' concerns, sentiments and opinions. The existing research results have shown that these reviews, as a third-party evaluation information, have significant impact on consumers' purchase decisions. Especially in multi-attributes trade led by e-Brokerage, the buyers have become increasingly dependent on these reviews (i.e., third-party evaluation information). With the consideration of the dependence on the third-party's evaluations in multi-attributes trade, a method for multiple-attributes trade matching considering evaluations of the third-party in e-Brokerage is proposed, and the probability and statistics theories are employed to deal with evaluation or feedback information provided by the third-party. First, the supply and demand information in multiple forms provided by supplies and buyers is transformed into the uniform one with cumulative distribution function. Second, the evaluation or feedback information of the third-party in multiple forms is also transformed into the uniform one with cumulative distribution function. On the basis of this, overall matching degrees of the supplies and buyers with respect to opposite sides are measured with the consideration of third-party's evaluation or feedback information, and a multi-objective optimization model is formulated to maximize the overall matching degree of the supplies and buyers, as well as to maximize earnings of the e-Brokerage. Furthermore, the weighting sum method based on membership function is employed to transform the multi-objective optimization model into single-objective optimization model. The optimal matching pairs can be determined by solving the single-objective optimization model. To illustrate the performance of the proposed method, a case study is conducted. The data of the case are derived from the related references and websites. The results of the case study show that the third-party evaluations on products can play an important role in multiple-attributes trade. The use of the proposed method will help in obtaining more objective and accepted matching results. It can not only promote buyers to get the desirable products, but also supervise and urge suppliers to pay more attention to their products and words of mouth.
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    Cost Control,Ratchet Effect and Optimal Incentive Contract
    CUI Jian-bo, LUO Zheng-ying
    2020, 28 (7):  196-203.  doi: 10.16381/j.cnki.issn1003-207x.2020.07.019
    Abstract ( 280 )   PDF (1266KB) ( 97 )   Save
    In 2015, the government-imposed pay curbs in state-owned enterprises (SOEs) came into force, involving the principals of central enterprises down to the SOEs at different levels. Even though reducing the remuneration using a "one-size-fits-all" approach can save the cost of executives'salaries apparently, it can't compensate for the loss caused by managers' negative attitude toward work. Cost control has the potential which leads to the use of incentive schemes under asymmetric information. As time goes by, the principal (headquarters of SOEs) will take the agent's performance of cost control into consideration when modifying the scheme, which induces agent to be slack to avoid more demanding schedules in the future-the ratchet effect. The principal has to pay high rent to induce the agent to reveal its real type to weaken effect. However, the pay curbs may prevent it. A two-period game model is built and turns the equilibrium game model between the headquarters and production unit is turned into a perfect Bayesian equilibrium. As the starting point, the effect about incomplete information on effort in a static framework is researched. In the beginning, there are some given assumptions, such as impossible to promise the intertemporal incentive scheme, sequential selection of the rewarding programme and realizing cost, the incentive scheme revised dynamically. Research results show that the managers of high-efficiency production unit can always imitate the low-efficiency ones in low cost. When the probability distribution is poor, the agent has the incentive to persuade the principal that they are low efficiency. More importantly, the incentive scheme, which can achieve the separating equilibrium, is better in order to maximize utility. And there is trade-off between information rent and effort level in the optimal value. Under quasi-separating equilibrium or pool equilibrium, there exists stronger incentives than in static model due to ratchet effect. In summary, the paper explores the ratchet effect caused by asymmetric information as well as the balance between the incentives of optimal contract and rent extraction. Under given conditions, the separating equilibrium can strike an average between information rent and effort efficiency, weaken the ratchet effect and optimize the utility of headquarters of SOEs. The study and its conclusion provide theoretical direction for the formulation and implement of government-imposed pay curbs.
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    Improved Multi-Strategy Grouping Genetic Algorithm for the Pickup and Delivery Problem with Time Windows
    GUO Dong-wei, DING Gen-hong, LIU Wei
    2020, 28 (7):  204-211.  doi: 10.16381/j.cnki.issn1003-207x.2020.07.020
    Abstract ( 261 )   PDF (1587KB) ( 85 )   Save
    The Pickup and Delivery Problem with Time Windows (PDPTW) is a generalization of the Vehicle Routing Problem with Time Windows (VRPTW). Since the Pickup and Delivery Problem with Time Windows is an NP-hard problem, it is difficult to obtain an optimal solution. PDPTW refers to arranging service paths for a given fleet of vehicles to meet the customers' loading and unloading needs. Each demand task consists of two demand points (customer points):one pickup location (origin) and one delivery location (destination). For each pickup and delivery location, the size of the load has to be transported from the origin to the destination by exactly one vehicle. Each demand point has a time window, that is, the earliest start time and the latest start time for loading or unloading at the point. There are enough vehicles, each with the same maximum loading capacity. Each vehicle starts from the depot and returns to the depot after completing the distribution task.
    Firstly, the mathematical model of the PDPTW is established. Then, by comparing the optimal solution obtained from the test with the sub-optimal solution, it is found that the vehicle routing is more or less the same, only the location of some customers in a single vehicle needs to be adjusted, or the requests in two paths need to be changed. In order to improve the Multi-Strategy Grouping Genetic Algorithm for solving the PDPTW, a translocation combination crossover operator and two path adjustment strategies are presented:single-vehicle path rearrangement strategy and requests exchange strategy. Compared with the combination crossover operator presented by Pankratz G, the translocation combination crossover operator can accelerate the optimization of the number of vehicles used. The single-vehicle path rearrangement strategy is based on the full arrangement of some customer points selected. Requests exchange strategy refers to exchanging the requests of two paths in an individual.
    The algorithm is tested by using Li & Lim's Pickup and Delivery Benchmark 400-Customer Problems. There are 60 examples in the case set, each of which has at least 400 customer points. In comparison to the best results published, the best results of the IMSGGA are better with respect to total travel distance in 4 cases and the same in 14 cases. Finding the appropriate path adjustment strategy will further optimize the algorithm.
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    Critical Chain Buffer Sizing Based on the Schedule Fractal Dimension
    ZHANG Jun-guang, LI Kai
    2020, 28 (7):  212-219.  doi: 10.16381/j.cnki.issn1003-207x.2020.07.021
    Abstract ( 176 )   PDF (2037KB) ( 72 )   Save
    The large-scale projects always have an enormous number of data and tasks, and that makes the project manager easier to unconsciously ignore some important information. The traditional buffer sizing methods adopted by the project manager only consider the information of the activities on the critical chain, which usually cause an inaccurate buffer size for lacking of information of non-critical activities. What is more, the project manager and workers always have a game on striving for the report time, which results in large amount of time waste. Hence, a new buffer sizing method is proposed by considering the schedule fractal dimension, the project link activities and the correlation between different levels of activity chains.Firstly,the complexity of projects and the correlation of the different level of activity paths are described based on the Fractal Dimension theory. Secondly, considering the project manager's decision-making power and risk adverse index, a balanced time-cut position between the manager and workers is identified based on the game theory. Finally, the aforementioned information is incorporated to the logistic growth model and the buffer size of each dimension chain is calculated.One of the advantages of the logistic growth model is that it sets anupper limit for the buffer size, overcoming the problem of liner increasing as the scale of the project grows and the number of activities increases. The improved project buffer size is reasonably calculated by the growth function $f\left(C \right)=\frac{K}{{1 + \left({\frac{K}{{{f_0}}}-1} \right){e^{-pC}}}}$, where F(C) represents the needed buffer, f0 denotes the initial buffer size, K is the most optimistic buffer size, p represents the speed of buffer increasing and the C is the schedule fractal dimension.
    To validate the proposed method, the management processis simulated by Matlab software and compare the experiment results with three classic methods(C&PM, RSEM and APD). The results indicate that the proposed method can effectively shorten the project duration (4.7%) and reduce the total cost of the project (34.9%).Our research has filled gaps in the critical chain field by determining the buffer with an in-depth analysis of the schedule fractal dimension of the project network. In practice,the model constructed in this study can be revised and improved to provide a decision support in solving complicated problems about buffer decision inlink information missing and multi-loop network projects, making a contribution to the studies of critical chain project management (CCPM) by providing a more reasonable buffer size.
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    Proactive Project Scheduling Optimization Based on Flexible Resource Constraint
    MA Yong, HE Zheng-wen, ZHENG Wei-bo
    2020, 28 (7):  220-230.  doi: 10.16381/j.cnki.issn1003-207x.2020.07.022
    Abstract ( 240 )   PDF (1882KB) ( 126 )   Save
    With the increasingly fierce market competition and diversified customer needs, in order to quickly adapt to market changes, companies need to complete customized production and provide personalized services within a certain period of time. This requires the ability of companies to achieve smart manufacturing and resource flexibility plays an important role in it. Two typical examples of flexible resources are industrial robots and multi-skilled human resources. At the same time, projects are executed in a complex and dynamic environment, facing considerable uncertainties:activities may take more or less time than originally estimated, resource may become unavailable, etc. These uncertainties may lead to schedule disruptions or even failures. Therefore, it is important to develop a schedule that is protected as well as possible against schedule disruptions caused by uncertainties. Based on the above theory and facts, this paper studies the proactive project scheduling problem with stochastic activity durations and flexible resource constraints. The objective is to schedule the starting times of the activities in a reasonable way so as to maximize the robustness of the project schedule under the constraints of precedence, flexible resources and project deadline.
    Firstly, the research problem is defined, where the activity duration is a random variable with known mean value and standard deviation.Flexible resources are defined as renewable resources with multiple skills, but only one skill can be selected for use before project execution and each resource must be used as a whole. The robustness of the project schedule is defined as the sum of the products of time buffers and the weight coefficients of all the activities. Then the optimization model is constructed.Based on the NP-hardness attribute of the problem and the characteristics of the model, a two-layer nested tabu search heuristic algorithm is developed to obtain satisfactory solutions. The outer loop of the algorithm aims to find a feasible resource skill allocation plan and the inner loop searches for the project schedule with maximum robustness under the constraint of resource skill allocation plan. At last, a practical project is introduced to illustrate the research problem, for which the satisfactory solutions obtained under the constraints of inflexible resources and flexible resources are compared and analyzed. The research results indicate that, compared with the project schedule developed under the condition of inflexible resources, the robustness of the project schedule obtained with flexible resources has increased from 3.76 to 7.42, i.e., an increase of 97.34%, which improves the anti-interference ability of the project and ensures a more stable project implementation. Besides, the influences of the key parameters, including project deadline, resource availability and resources flexibility, on the robustness of the project schedule, are analyzed.The following conclusions are drawn:with the extension of project deadline, the increase of resource availability or resource flexibility, the robustness of the project schedule increases respectively.
    The research in this paper extends the flexible resource constrained project scheduling to the robust project scheduling field,which can provide reference for relevant research.
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