中国科学院科技战略咨询研究院

#### Table of Content

20 July 2020, Volume 28 Issue 7
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 )   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.
 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 )   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.
 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 )   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.
 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 )   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.
 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 )   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.
 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 )   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.
 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 )   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.
 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 )   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.
 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 )   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.
 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 )   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.
 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 )   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.
 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 )   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.
 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 )   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.
 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 )   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.
 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 )   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.
 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 )   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.