Loading...
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 August 2020, Volume 28 Issue 8 Previous Issue    Next Issue
    Articles
    A Review of Bank Risk Aggregation
    ZHU Xiao-qian, LI Jian-ping
    2020, 28 (8):  1-14.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.001
    Abstract ( 221 )   PDF (3019KB) ( 336 )   Save
    Banks face various types of risks, such as credit risk, market risk, and operational risk. These risks are closely related to each other, causing them to show a trend of enlargement or reduction, which significantly affects the accuracy of bank risk measurement results.Bank risk aggregation is committed to a more accurate measurement of bank risk based on full consideration of bank risk correlations. However, banks face many types of risks, the correlations between them are sophisticated and the lack of data problem is especially severe. For these reasons, there are still many challenges in the field of aggregated measurement of bank risks. This paper systemically reviews the researches on bank risk aggregation from three perspectives, i.e.aggregation objects, aggregation methods,and aggregation data. Firstly, the bank risks and the multiplecorrelations within them are analyzed.Then the complex characteristics of bank risk correlations are summarized. The bank risk aggregation methods are summarized and compared based on their abilities to capture these characteristics. Lastly, the ways to obtain the data for bank risk aggregation are also summed up.On this basis, the difficulties and future trends of bank risk aggregation research are further analyzed.
    References | Related Articles | Metrics
    Psychological Factors, Transaction Environment Change and Risk Measurement of Structured Products: A Review of Research
    WANG Zong-run, CHEN Xi
    2020, 28 (8):  15-29.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.002
    Abstract ( 179 )   PDF (1623KB) ( 150 )   Save
    With the rise of Internet finance, transaction environment has changed from offline counter to online platforms and the market of financial products has presented distinctive new features. Structured products have been more and more complex and developing rapidly, but there is a large risk behind their prosperity. Risk measurement and management are of crucial importance for the further development of structured product market. Studies have shown that psychological factors have an important impact on investors' beliefs and expectations. Moreover, transaction environment change can intensify investors' psychological biases and then lead them to irrational investment decisions and behaviors. This paper reviews the important literature related to demand and supply sides of structured products, individual psychological factors, transaction environment change, and risk measure theories and methods. Based on the existing research, it is proposed that further studies on the risk measurement of structured products on the Internet financial service platforms should take the transaction environment change and psychological factors into account, which helps to most effectively realize the risk assessment and management of the complex financial product market in the new Internet era.
    References | Related Articles | Metrics
    Research of Two-stage Insurance Contract Model with Bounties and Penalties and Pareto Improvement Under Adverse Selection
    MA Ben-jiang, YIN Peng-hua, CHEN Xiao-hong, XU Sai-xue
    2020, 28 (8):  30-41.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.003
    Abstract ( 208 )   PDF (2281KB) ( 59 )   Save
    In the markets of insurance, there extensively exists information asymmetry which causes the phenomenon of adverse selection, in order to avoid this phenomenon more effectively that influences the efficiency of insurance market, the two-stage insurance contract models with bounties and penalties were established according to the two and multiple risk types of insureds in this paper, which shows that bounties and penalties can be used to distinguish the risk types of policyholders for the first time. These models indicate that in the second period of insurance the insurers can give the insured bounties or penalties in terms of the claim or not by policyholders in the first period, the probability of obtaining penalties is far more greater than bounties in the second period if the insureds of high-risk choose the insurance contract designed for the low-risk, namely the high-risk policyholders are more afraid of penalties and thus the model meets Spence-Morris separation condition. This insurance contract model with expected profits of insurers still being zero, which does not lead to extra economic burden for insureds, can yet realize the strict Pareto improvement compare to the two-time repeat model of traditional partial insurance contract. Furthermore, the insurance contract model with bounties and penalties proves that as long as the insureds with each different risk type are incentive compatible to the policyholders of the highest risk type, they are incentive compatible to every risk type of insureds, which greatly simplifies the two-period insurance contract model under the conditions of various risk types. An example is given to illustrate the effectiveness of the model at last. In addition, our study not only presents a new screening tool, but also make a major step forward in the research of Multi-period dynamic insurance contract.
    References | Related Articles | Metrics
    An Enhanced Index Tracking Model based on Asymmetric Active Risk and Its Application
    MA Jing-yi, ZHANG Zhi-hao, WU Jia-bao, LEI Xue-fei
    2020, 28 (8):  42-51.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.004
    Abstract ( 186 )   PDF (1153KB) ( 53 )   Save
    Enhanced index tracking problem is a bi-objective optimization problem of selecting a portfolio outperforming the benchmark index while subjecting to a limited additional risk. It receives extensive attention from both theoretical researches and financial practices. Considering that asymmetric risks coincide more with the investors' perception of risks, an enhanced index tracking model is constructed based on the asymmetric active risks measure in this paper. The asymmetric active risk is gauged by the downside tracking error, and at the same time the short-sale constraint is adopted that is more consistent with the Chinese stock markets. By transform of the constraints on excess returns, our model is equivalent to the non-negative weighted lasso problem; hence, sparse portfolios can be built. Further, the generalized least angle regression (GLARS) algorithm is proposed to solve the model. GLARS algorithm is able to provide the solution of portfolio's coefficients which minimize the downside tracking error when excess returns change within a reasonable range and then the effective frontier can be derived, depicting the trade-off of the portfolio's excess return and downside tracking error.
    The empirical analysis is conducted by daily closing prices of Shanghai Stock Exchange (SSE) 50 index and its constituent stocks from Jan.4th to Dec.30th in 2016. Comparing our model with the existing enhanced index tracking strategy based on the excess return-tracking error model, the following results are reached. Controlling the number of stocks, the portfolio based on our model can obtain higher unit risk-return. Moreover, the downside median deviation and maximum drawdown of our portfolio' excess return are both lower and the excess return is more right-skewed. Under the requirement of sparseness, the portfolio based on our model is able to obtain a higher accumulated return than the benchmark index in terms of out-of-sample performance, which is of great value for the both institutional and individual investors and enriches the existing research of enhanced index tracking model.
    References | Related Articles | Metrics
    Optimal Pricing Decision in Finance-constrained Supply Chain Considering Deposits and Loans of the Bank Based on the Advance Payment
    CAO Bing-bing, FAN Zhi-ping, YOU Tian-hui, LIU Chun-yi
    2020, 28 (8):  52-64.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.005
    Abstract ( 209 )   PDF (1480KB) ( 96 )   Save
    In reality, supply chain members may confront with the fund shortage problem because of un-received payment, prepayment and inventory backlog, and need to apply for bank loan to ensure their benign operations. Supply chain members may deposit the idle fund for bank interest when they have the sufficient capital such as sales revenue and profit, for example, the retailer may deposit the sales revenue by the rate for fixed deposit by installments, the manufacturer may deposit the profit by the interest rate for benefit. The advance payment scheme refers to a way that the retailer transfers the payment to the manufacturer before the production process of the manufacturer. In addition, there are two supply chain power structures. Under the consideration of deposits and loans of the bank based on the advance payment scheme, how to determine the optimal policy of wholesale price and margin price for the different supply chain power structures in finance-constrained supply chain, it is a worthy and significant problem.
    In this paper, it is assumed that the supply chain comprises a manufacturer and a retailer, and one of them is finance-constrained or the leader of the supply chain. The following four situations are considered: the manufacturer is finance-constrained and the leader of the supply chain (MS-MC), the manufacturer is finance-constrained and the retailer is the leader of the supply chain (RS-MC), the retailer is finance-constrained and the manufacturer is the leader of the supply chain (MS-RC), the retailer is finance-constrained and the leader of the supply chain (RS-RC). Furthermore, the demand function and profit functions are built, and the optimal policies of supply chain members are determined for four situations. Then, the optimal wholesale price of the manufacturer and the optimal margin price of the retailer are analyzed for four situations, and the impacts of the bank rates, i.e., the rate for fixed deposit by installments, deposit interest and loan interest, on the optimal pricing policies and profits of the supply chain members are investigated. In addition, the comparison analysis for the following four cases is conducted: comparing the optimal policies and the impacts of bank rates on the optimal policies and profits of supply chain between situations MS-MC and RS-MC, MS-RC and RS-RC, MS-MC and MS-RC, RS-MC and RS-RC.
    Several important results are shown through the theoretical analysis. The rate for fixed deposit by installments, deposit interest and loan interest can affect the optimal policies and profits of supply chain members to varying degree for four situations MS-MC, RS-MC, MS-RC and RS-RC. The effect mechanism is related to the finance-constrained objectives and the supply chain power structures. Compared with the supply chain power structures, the effect mechanism is more related to the finance-constrained objectives. Furthermore, five useful managerial insights are obtained for guiding the decision-maker in practice. In addition, it is also shown that the advance payment can relieve the manufacturer's pressure on the finance, but intensifies the degree of the financial constraints of retailer.
    References | Related Articles | Metrics
    Optimal Dynamic Pricing of Consumer Referral Reward and Advertising Investment Based on Bass Model
    DUAN Yong-rui, YIN Jia
    2020, 28 (8):  65-75.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.006
    Abstract ( 243 )   PDF (2852KB) ( 170 )   Save
    With the rapid development of mobile internet, consumers are willing to share ideas about product, service or shopping experience and spread word of mouth on the internet. The consumer referral reward program (RRP) has been widely applied in online sales. There is no deny the fact that the company which has adopted the RRP does not stop advertising their products at the same time. In this paper, a product diffusion model is formulated which considers both the word-of-mouth effect and the advertising effect, and a dynamic pricing problem of the consumer referral reward and the advertising investment is studied. Assume the population size is 1. In our dynamic model, the state of the system is the cumulative sales, while the instantaneous sales rate has four resources: new consumers from innovation, advertisement, the WOM and reward referral. First, as for this optimal control problem, an optimal solution of the consumer referral reward and the advertising investment is obtained based on the Hamiltonian function and the maximum principle. It shows that the optimal trajectory for referral reward is decreased first and then increased, while the optimal trajectory for advertising investment is reduced gradually. Furthermore, numerical examples, comparing the coefficients from previous research, are provided, together with sensitivity analysis of the optimal solution with respect to major parameters. The consumer referral reward strategy and advertising investment strategy will be influenced by the reward efficiency, advertising efficiency, spontaneous purchase ratio and traditional word of mouth. (1) For high value products, it is advisable for enterprises to adopt a high-price-high-reward strategy. (2)When the referral is effective, the referral bonus and advertisement input should be higher. (3) It's better to sustain the high level of referral reward when the advertising doesn't work. (4)A high spontaneous purchase ratio means the product has advantages in quality, brand or something else. In such circumstance, it's wise to provide a lower referral reward and keep a lower advertisement density. (5)When traditional WOM efficiency is high, it's time to make the best use of WOM strength to sustain both referral reward and advertisement higher.
    References | Related Articles | Metrics
    Optimal Strategies and Coordination of Fresh E-commerce Supply Chain Considering Freshness-Keeping Effort and Value-Added Service
    LIU Mo-lin, DAN Bin, MA Song-xuan
    2020, 28 (8):  76-88.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.007
    Abstract ( 346 )   PDF (2724KB) ( 420 )   Save
    With the rapid development of the Internet and the quick popularization of E-commerce, more and more enterprises are involved in the field of fresh e-commerce. At the same time, as the consumption of fresh produce changes and upgrades, some fresh e-commerce companies choose to provide fresh produce as well as value-added service to meet customer demand. Besides, they have in-depth cooperation with suppliers, in which suppliers deliver fresh produce with freshness-keeping. In this context, both high level of freshness-keeping effort and value-added service can increase fresh produce demand. However, in such a fresh e-commerce supply chain, freshness-keeping effort and value-added service are respectively provided by different parties who may have free-rider behavior with relying on the other's effort. In addition, both parties aim to maximize their own profit, which may lead to deviation in the optimal strategies and thereby reduce supply chain performance. To solve this problem, the problem of optimal strategies and coordination of fresh e-commerce supply chain considering fresh-keeping effort and value-added service are studied.
    The main work in this paper includes the following four parts. First, the centralized and decentralized game models of fresh e-commerce supply chain considering freshness-keeping effort and value-added service level affecting the market demand of fresh produce are established, and the impacts of the elasticity of freshness and the elasticity of service on optimal strategies are analyzed, and the optimal strategies are compared in both models. Second, a revenue sharing-two way cost sharing contract is designed to achieve the perfect coordination and Pareto improvement of fresh e-commerce supply chain. Third, the changes in optimal strategies before and after coordination are analyzed. Finally, some conclusions are verified through numerical examples.
    The results show that, first, under the decentralized decision, with the increase of the elasticity of freshness, the fresh e-commerce always reduces the product price and the level of service, while the fresh supplier faces the choice of whether to improve freshness-keeping effort. When the elasticity of freshness is higher than a certain level, the fresh supplier will reduce freshness-keeping effort. Second, the revenue sharing-two way cost sharing contract can effectively coordinate the fresh e-commerce supply chain and realize Pareto improvement. Third, the product freshness and service level must be improved after supply chain coordination, but it could lead to a lower or higher price of fresh produce. When the elasticity of freshness and the elasticity of service are relatively low, the fresh e-commerce will make a relatively lower product price after coordination, and implement the strategy of "high-quality with low price". However, when the elasticity of freshness or the elasticity of service is higher than a certain level, the fresh e-commerce will make a relatively higher product price after coordination, and implement the strategy of "high-quality with high price".
    References | Related Articles | Metrics
    Pricing Policies and Offline to Online Channel Strategies with Asymmetric Information
    JIN Liang, ZHENG Ben-rong, SUN Lian-ke
    2020, 28 (8):  89-103.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.008
    Abstract ( 259 )   PDF (2199KB) ( 300 )   Save
    The Internet has made online shopping a global daily phenomenon. In 2018, online retail sales surpassed MYM2.5 trillion all over the world, while that of Chinese websites reached approximately RMB 9 trillion. Customers, however, cannot touch or feel a product before they purchase online. Indeed, product returns in Internet retailing have been shown to be, on average, as high as 22% of sales. This leads to much higher rates of customer returns in the online channel, which in turn leads to significant costs to retailers. In this context, the "offline evaluation, online purchase" mode has been increasingly viewed as an effective and novel way to provide information of the product to the customers and this mode can mitigate information gap exists in the supply chain. However, the existence of product return behavior and information asymmetry leads to incentive misalignment in the supply chain. To solve this problem, the optimal pricing policies and offline to online channel strategies are analyzed within a supply chain that consists of a manufacturer and an online retailer. Optimal pricing policies and the offline to online channel strategies and proposed, as well as the optimal contracts with consumer returns under full information and asymmetric information, respectively.
    The main work in this paper includes four parts. At first, optimal contracts are proposed and the optimal pricing strategies and contract design under full information and asymmetric information, respectively. Second, on this basis, the effects of the O2O channel strategies are analyzed on the equilibriums, and consequently the optimal pricing, demand and contract design of supply chain members are compared under different types of return cost. Third, the optimal decisions of both the manufacturer and online retailer, and the changing of consumer surplus are compared under full and asymmetric information. And the effect of different types of return cost and asymmetric information on willingness to share information and negotiation behaviors is presented. Finally, to address the value of O2O channel, the optimal decisions of both the manufacturer and online retailer, and the changing of profit of supply chain members and consumer surplus under before and after Introduces the O2O channel are compared.
    The results show that, the contracting scheme, composed of a wholesale price and a fixed payment, can coordinate the supply chain perfectly under symmetric information. The O2O channel strategies may not increase the retailer's expected profit, but it is favorable for the profit of manufacturer and the supply chain. The introduction of showroom can increase the consumers' surplus, but may not increase the consumers' surplus when evaluate products at showroom to identify their "best-fit" product but buy it at the online retailer. It's found that the online retailer may have an incentive to reveal the private information voluntarily and share the supply chain's profit with manufacture under certain condition.
    In summary, the value of O2O channel under asymmetric information is investigated. Moreover, the contracting mechanisms are used to coordinating the supply chain under asymmetric information, which offers a practical and a theoretical guidance to improve the value of online retail supply chain.
    References | Related Articles | Metrics
    Multi-party Behavior Game Research of Cross-border E-commerce Logistics Alliance Based on 4PL
    DU Zhi-ping, FU Shuai-shuai, MU Dong, WANG Dan-dan
    2020, 28 (8):  104-113.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.009
    Abstract ( 329 )   PDF (3867KB) ( 176 )   Save
    The rapid rise of cross-border e-commerce broadened the development space of cross-border e-commerce logistics. As a new logistics development model generated by the practice of the enterprises, the 4PL-based cross-border e-commerce logistics alliance can effectively satisfy consumers' comprehensive demand for cross-border e-commerce logistics. However, the cross-border e-commerce logistics alliance led by the cross-border e-commerce platform is a multi-member operation organization, and each member of which conducts multiple dynamic and complex games in the business operation. The game relationship between the members is crucial to the stable operation of the alliance. Therefore, the evolutionary game theory is used to analyze the dynamic game process between cross-border e-commerce platform, logistics service provider and merchants in the alliance, and the tripartite evolutionary game model is constructed. Based on the investigation of relevant enterprises, system dynamics is used to simulate and analyze the dynamic game process of the three-party strategy selection. The results show that: (1) In the process of alliance operation, the three parts of platform supervision, logistics enterprise efforts and merchant participation will eventually reach the equilibrium. And the merchant participation plays an important role in the stable operation of the alliance. At the same time, the platform supervision has a direct impact on the strategic choice of logistics enterprises. The platform should formulate scientific penalties and compensation rulings to improve the quality of logistics services and protect the interests of merchants. (2) Participants in the alliance have high sensitivity to their relevant exogenous variables, but the final strategy is influenced by multiple variables. For this reason, the platform needs to play the leading role and take various measures to stimulate the enthusiasm of logistics enterprises and merchants. The research in this paper provides a methodological guidance for multi-party operation management based on 4PL cross-border e-commerce logistics alliance, and has enlightening significance for the improvement of the alliance operational level.
    References | Related Articles | Metrics
    Research on the Dynamic Order Acceptance in Urban Delivery Considering Customer Choice of the Last-mile Delivery Modes and Time Slots
    QIU Han-guang, ZHOU Ji-xiang, LONG Yue
    2020, 28 (8):  114-126.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.010
    Abstract ( 197 )   PDF (3865KB) ( 98 )   Save
    To make the order acceptance or rejection decision efficiently in the context that the customer can choose the last-mile delivery modes and time slots, the framework of dynamic order acceptance in urbandelivery is constructed, which is composed of pre-routing,assessment of delivery requests, adjustment of order acceptance strategy and global optimization. An order valuation method based on the threshold of time window deviation is proposed. Then three different algorithms for adjustingorder acceptance strategy are designed including accepting all orders, allocating delivery modesstatically and allocating service options dynamically. The simulation results show that the dynamic allocation of service options could obtain higher profit than the other algorithms and spent less time especially in the example with more delivery requests; as the time slot range is increased, the revenue of reception box service and the total distance are gradually decreasing, however the revenue of attending home delivery service and the profit are increasing; the threshold of time window deviation has a significant effect on the profit of distribution service, but there is no trend; the threshold of time window deviation with higher revenue of attending home delivery often make a higher profit. The results may support the decisions of allocating the last-mile delivery modes and time slots in different distribution areas.
    References | Related Articles | Metrics
    Retailer's Demand Forecasting Information Sharing Based on Competing Manufacturers' Innovation Investment
    WANG Wen-long, WANG Cheng-jun
    2020, 28 (8):  127-138.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.011
    Abstract ( 231 )   PDF (2656KB) ( 113 )   Save
    Innovative practices carried out by an upstream player create value for other node enterprises, securing a supply chain which is free from the zero-sum game in terms of information sharing. Nevertheless, a competitor is likely to break the original balance and has a profound impact on the demand forecasting information sharing made by its retailer. Thus, it is necessary to study the problem of demand forecasting information sharing made by a retailer when the supply chain upstream is in horizontal competition by taking manufactures' innovation input in account. A decision model of supply chain which consists of two competing manufacturers making cost-reduction innovations and one retailer in the knowledge of the demand forecasting information has been considered and then analysis has been made on the equilibrium decisions in different information sharing scenarios. Afterwards, the impact of cost-reduction innovations made by manufacturers on the value of demand forecasting information sharing has been examined by comparing the ex ante profits of three players in different information sharing scenarios. A mechanism is figured out to motivate retailer to share demand forecasting information based on the innovation input by competing manufacturers, which leads to the Pareto improvement in the upstream competing supply chain. It finds:
    (1) The decision on innovation input made by a manufacturer depends on its competitor and the retailer in the knowledge of the demand forecasting information sharing. Suppose the demand in future market is positive: when innovation capability of a competing manufacturer is weakening, its largest innovation input can be seen if it is informed with the demand forecasting information as well as its competitor; when capability grows strong, being the only one informed of the two can ensure its largest innovation input.
    (2) Due to the innovative practices targeting at cost reduction conducted by two competing manufacturers, there is chance that the retailer might be benefited by sharing demand forecasting information. The more competitive upstream manufactures become, the more valuable the information sharing made by downstream retailer is.
    (3) When manufacturers are highly innovative, complete information sharing is not only their most favorable information state but also the dominant information sharing strategy for the retailer. Therefore, it can be considered as the most ideal information sharing state for the three players. And meanwhile manufacturers' innovation input is great. However, when manufacturers are less innovative, the retailer is reluctant to share the demand forecasting information with them. In this situation, the two competing manufacturers can motivate the downstream retailer to share its private demand information through paying information sharing expense. The range of information sharing expenses is widening as the innovation capability, upstream competition intensity, forecasting accuracy and stochastic demand volatility show an increase.
    These findings are of practical significance to manage supply chain made up by two competing manufactures and one retailer. This article provides insights into how a retailer shares demand forecasting information with manufacturers, how manufacturers determine their decisions on innovation input and motivate a retailer to share forecasting information.
    References | Related Articles | Metrics
    Research on New Energy Vehicle Manufacturers Pricing Decision Basis for Different Subsidy Bodies
    XIONG Yong-qing, LI Xiao-long, HUANG Tian-tian
    2020, 28 (8):  139-147.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.012
    Abstract ( 242 )   PDF (1786KB) ( 131 )   Save
    The New Energy Vehicle industry of China is still in the stage of "Technical and Commercial Demonstration", and government subsidy is an important way to promote the development of New Energy Vehicle industry. Based on the perspective of government intervention of different subsidy bodies,the research on the optimal pricing game strategy of New Energy Vehicle manufacturers can not only promote the government to play a more incentive role with limited financial resources, but also obtain the market operation mechanism under the circumstance of subsidies, so as to improve the development of New Energy Vehicle Industry. According to different subsidy bodies, this paper divides the subsidy policy into manufacturers' subsidy and consumers' subsidy. Assuming there exist price and quality substitute in the products produced by two New Energy Vehicle manufacturers with different technical levels, "price substitute rate" and "quality substitute rate" are introduced to depict the market competition environment. Stackelberg game model is established to describe the influence of government policy and consumer preference on the pricing decision of New Energy Vehicle manufacturers by numerical simulation, which helps get the manufacturer's Pareto optimal decision and propose policy recommendations.
    The results show that in the current stage of New Energy Vehicle industry, it's necessary to advocate government subsidies in terms of accelerating the development of New Energy Vehicle industry. Exposed to different subsidies, manufacturers can adopt different pricing strategies to cope with the changes in the market competition environment. Among all subsidies, manufacturers adopt different pricing strategies to cope with the changing competition environment of market. Among them, the quality competition is more conducive for the development of leading manufacturers, and so is price competition to the development of following manufacturers. However, the impact of price competition on manufacturer profits is obviously stronger than that of quality competition. And if consumers pay too much attention to price, it will lead to The Market for Lemons easily. The government should choose different subsidy bodies according to different policy goals. A subsidy for consumers is to raise the price of products so that manufacturers that are started late, smaller, and backward in technology will gain higher profits. It will promote more manufacturers to enter the new energy automotive industry to prevent monopoly. A subsidy for manufacturers is to reduce the product price, and the higher-quality manufacturers can obtain higher profits to encourage manufacturers to increase research and development in order to improve the product quality and guide more consumers to buy high-quality New Energy Vehicles, promoting the survival of the fittest of the New Energy Vehicle industry. The main body of government subsidies should gradually shift from consumers to manufacturers and increase investment, especially in research and development investment for leading New Energy Vehicle manufacturers. Policies can play a part on guiding manufacturers and consumers to attach great importance to improve the quality of New Energy Vehicles and reduce their sensitivity to price so as to promote the healthy development of New Energy Vehicle industry.
    References | Related Articles | Metrics
    Logistic Support for Post-earthquake Mountain Areas Power Distribution Systems Restoration
    LI Shuang-lin
    2020, 28 (8):  148-161.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.013
    Abstract ( 185 )   PDF (5062KB) ( 67 )   Save
    In recent years, though the number of natural disasters is decreasing, the cost of economic damages globally has seen an increase compared to the past two decades. One reason for higher economic losses is the consequence of disasters damaged the lifeline system, especially; the earthquake often has severe damaged to the power distribution system. An important issue faced by the local and federal authorities is the power distribution systems repair and restoration scheduling and logistic support. For the power distribution systems restoration scheduling problem, which includes the sequence for repairing the damaged components, i.e., buses, distribution lines, and assigning and routing for the repair crews? For the logistic support, which includes the materials allocation problem and the materials delivery problem? Specially, in determining the restoration schedule, it is important to consider the fact that the logistics support and geographical features. Therefore, a non-linear mixed integer programming model is first developed to maximize the utilities of restoration to describe the post-earthquake mountain areas power distribution systems restoration problem integrated with logistics support.
    According to the mathematical model, the MATPOWER 6.0 is used to control the constraint sets of the voltage of buses and the current of the distribution line. Since the scheduling and routing of the repair crews and the delivers is similar to the vehicle routing problem, which has been proved to be a NP-hard problem. In order to conquer this problem, the bacterial colony chemotaxis optimization algorithm (BCCOA) is introduced and improved by the strategy of chaos migration, the strategy of differential evolution, the strategy of precision self-adaption, and the strategy of normalizing the value of the objective function; the BCCOA with these strategies is referred as improved BCCOA. In addition, the A* algorithm is employed to calculate the required travel time between each pair of nodes to dismiss the impacts of the geographical features.
    Ultimately, the IEEE30, IEEE57, and IEEE118 buses system are employed to check the validation and utilizes of the improved BCCOA and the adopted strategies. The results show that: (1) The improved BCCOA has a good performance on the quality of solution and the CPU time when comparing with the enumerate method; (2) Only increase the capacity of restoration, the utilities of restoration increased 36.40% averagely, while only increase the capacity of materials supply support, due to limited of the capacity of restoration, the utilities of restoration only increased 7.99% averagely, but the delays of material supply support decreased 61.71%. When increasing the capacity of restoration and materials supply support simultaneously, the utilities of restoration be increased 38.23% averagely, the increased percentage nearly 209.14%. All of these results show that the logistic support is critical and practical to restore the power distribution system; and (3) The strategy of differential evolution is more powerful than the strategy of chaos migration, the strategy of chaos migration is more useful than the strategy of precision self-adaption, the strategy of normalizing the value of the objective function is dominated by the strategy of precision self-adaption, while the BCCOA is dominated by all of these strategies. These results indicate that the adopted strategies are really useful and helpful to improve the quality of strategy for restoring the post-earthquake mountain areas power distribution systems with the logistic support.
    References | Related Articles | Metrics
    The Model of Joint Relief Supplies Pre-positioning by the Governmentand Two Suppliers Based on Option Contractsand Suppliers' Profits Allocation Mechanism
    LIU Yang, TIAN Jun, FENG Gong-zhong, HU Zhong-quan
    2020, 28 (8):  162-171.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.014
    Abstract ( 250 )   PDF (1084KB) ( 96 )   Save
    The recent emergencies or natural disasters occurred across all corners of the whole world, such earthquakes, hurricanes, tsunamis, etc. Sudden disasters not only increase the demand of relief supplies, but also pose a serious security threat to people's health and life as well as property. The demand of relief supplies after a sudden disaster occurs will be an explosive growth. In real situations, in order to effectively guarantee the timeliness and availability of relief supplies, the government may urgently purchase relief supplies from multiple suppliers. However, the overwhelming majority of the existing studies assume that there only exists a single supplier in the relief supply chain, and few studies have been conducted with respect to the relief supply chain that consists of a single government and multiple suppliers. The number of agreement enterprises cooperated with the government, of course, should not be too many. Otherwise, it will increase the government's management cost and add difficulties tocoordinate each supplier's profit allocation.
    Therefore, the situation of joint relief supplies pre-positioning by the government and two suppliers is taken as an example, and the model of joint relief supplies pre-positioning is constructed. Considering relief supplies system as a relief supply chain, option contracts are introduced into the relief chain management. At the first stage, the government purchases a certain amount of real relief supplies and options from every supplier, which can be executed by the government at an execution price. At the second stage, the government decides how many relief supplies to purchase from suppliers 1 and 2 after the actual demand of relief supplies is realized. With some reasonable assumptions, the model of joint relief supplies pre-positioning by the government and two suppliers via option contracts is established.
    Next, the following critical questions are intended to be addressed. First, should the government select the government single pre-positioning model or the model of joint relief supplies pre-positioningby the government and two suppliers? Second, it is more profitable for the government to adapt the model of joint relief supplies pre-positioning, what are optimal pre-positioning strategies of the government and suppliers? Third, under what conditions will the government and suppliers will be better off? Finally, under which suppliers' profits allocation mechanism will the government make each supplier willing to conduct contracts?
    After derivation, there are several key findings associated with our study. First, it is found that the relief supply chain with the government and two suppliers can be coordinated via option contracts. Under cannel coordination, the model of joint relief supplies pre-positioning is superior to the government single pre-positioning model because it improves the total joint amount of relief supplies, as well as reduce the government's regular inventory level. Second, the conditions are presented which help the government and the suppliers achieve an all-win situation. Third, there exists a suppliers' profits allocation mechanism which makes each supplier willing to conduct contracts.
    At last, all conclusions are validated by a numerical example. Our findings contribute to provide managerial insights for the government's decisions of relief supplies pre-positioning.
    References | Related Articles | Metrics
    The Researchon the Analysis and Prediction of Mass Incidentsin Multi-dimensional Scenario Space Based on Deep Learning
    ZHANG Ding-hua, LI Wei-jun, LI Cheng, SHEN Shi-fei
    2020, 28 (8):  172-180.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.015
    Abstract ( 297 )   PDF (2383KB) ( 274 )   Save
    The increasing mass incidents have greatly affected the harmony and stability of the society in the context of social transformation. A multi-dimensional scenario space model is constructed by using the "Scenario-Sub-Scenario-Object-Factor" model to decompose of all kinds of mass incidents and extract related influential factors. Based on multi-dimensional scenario space model, the convolutional neural network model is applied to mass incidents prediction, its principle is explained in detail and practical applications are discussed. A data set, formed by encoding a group of mass incidents' cases based on the multidimensional scenario space model is used to train (test) the predictive model and evaluat its validity via Area Under Curve (AUC). Furthermore, the effect of different factors on the prediction of mass incidents is analyzed and the direction of emergency management is indicated.
    References | Related Articles | Metrics
    Optimization of the Choice of Contra-flow Links Considering the Influence of Intersections
    GAO Ming-xia, FAN Bei-lin, WANG Rong
    2020, 28 (8):  181-187.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.016
    Abstract ( 144 )   PDF (787KB) ( 59 )   Save
    A reversible roadway (contra-flow) is one in which the direction of traffic flow in one or more lanes is reversed to the opposing direction for some period of time. Reversible lanes have been widely used, especially in recent years, for the evacuation of major metropolitan regions threatened by hurricanes etc. One important problem in the practice of evacuation traffic organization is to choose right road links for contra-flow. Most research on the choice of contra-flow links does not consider the influence of intersections, which may lead to overestimation of evacuation capacity especially in congested urban road networks. An evacuation road network is abstracted as a special network with directional node-weights by considering the capacity of intersection movements as directional weights of nodes. The critical edge for increasing the maximum flow value of such network is defined as the one that can maximize the range of flow value increase by increasing its capacity. Alternative links for contra-flow can be got by searching critical edges in such network. A modified algorithm is presented to find such critical edges on the basis of the maximal capacity path algorithm for the classical maximum flow problem. A numerical example is given and the effects are tested through traffic simulation. It is shown that the results when considering the influence of intersections are more reasonable. The total evacuation time can be compressed more effectively by increasing the capacity of road links when considering the influence of intersections.
    References | Related Articles | Metrics
    Multi-manufacturing Cells Collaborative Scheduling Based on Parallel Manufacturing
    ZHAO Dong-fang, ZHANG Xiao-dong, ZHOU Hong-li
    2020, 28 (8):  188-195.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.017
    Abstract ( 191 )   PDF (2788KB) ( 66 )   Save
    Production is becoming more and more complex with the manufacturing system changing from mass manufacturing to multi-varieties and small-batch production. A better way to improve production efficiency is considering processing and assembly in multi-step and multi-cells within the production process. However, the present researches in discrete manufacturing systems focused on workshop or multi manufacturing cells scheduling, but rarely on the parallel collaborative scheduling of multi manufacturing cells. Moreover, the transport time, changeover time, and debugging time were ignored, which resulted in deviations between scheduling results and actually machining. In fact, changeover time, and debugging time, transport time between cells during product switching have taken place in the discrete numerical controlled manufacturing cell all the time. And the production time of spare parts fabricated in the product could not satisfy the assembly requirement. As a result, parallel collaborative scheduling when processing and assembling multi manufacturing cells workpieces for multi products is a proper way to improve the production efficiency.
    To promote the performance of production, multi-manufacturing cells are regarded as a manufacturing system (MS) proposed a collaborative scheduling method based on parallel manufacturing, then a parallel collaborative scheduling model is presented by considering the transport time, changeover time, and debugging time, In order to solve the efficiently of the model, parallel collaborative genetic algorithm (GA) is also proposed. Based on this, the method is tested in a complex electromechanical products workshop which has multi- manufacturing cells, and then a comparative variable batch scheduling model and equal batch was conducted. Through the studies,the parallel collaborative scheduling can significantly reduce the production cycle and promote the performance of machine.
    The research shows that parallel collaborative scheduling can make the tasks reasonably assigned to machines, shorten the assembly waiting time and the time of the tooling changing, installment and testing within aitifact swithing, so as to increase the availability of machine and shorten the production cycle. It can be seen that the parallel collaborative scheduling can significantly reduce the production cycle and promote the machine performance.
    References | Related Articles | Metrics
    Prediction of Inter-industry Carbon Emissions Transfer Network in China Based on Grey Quantum Particle Swarm Optimizing General Vector Machine
    LV Kang-juan, HU Ying
    2020, 28 (8):  196-208.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.018
    Abstract ( 150 )   PDF (3278KB) ( 68 )   Save
    The state attaches great importance to the carbon emissions reduction of industries. It is shown that the key industries of carbon emissions reduction can be identified by analyzing the carbon emissions transfer network formed by the exchange of intermediate products in industries. Therefore, it is of great significance to establish the forecasting model of carbon emissions transfer between industries and forecast the carbon emissions transfer network.Previous studies have been mainly focused on the prediction oftotal carbon emissions time series, which has a signicantincreasing trend year by year. However, the time series ofinterindustry carbon emissions transfer in China has the characteristicsof small sample, nonlinear, nonmonotoney, volatility and randomness,According to the data characteristics,a hybrid forecasting model of grey quantum particle swarm optimization general vector machine forsmall sample random oscillation sequence(ROGM-QPSO-GVM)is proposed.Firstly, the ROGM (1,1) model is used to obtain the prediction sequence and residual sequence of carbon emissions transfer between different industries. Then a new quantum particle swarm optimization (QPSO) algorithm is proposed to optimize the network parameters of GVM model, and the QPSO-GVM model is constructed to modify the residual sequence, then the prediction values of the two parts are added together to obtain the prediction values of inter-industry carbon emissions transfer network. Finally, an inter-industry carbon emissions transfer network is constructed based on all the predicted values.Empirical analysis is made on the data of carbon emission transfer between 28 industries in China from 1997 to 2017. The results show that the ROGM-QPSO-GVM model has better prediction effect than other models, and China's inter-industry carbon emissions transfer network in 2020, 2025 and 2030 is predicted by this model and the trend is analyzed. It provides a reference for the national policy intervention on industry carbon emissions reduction, and lays a foundation for further clarifying the responsibility of each industry.
    References | Related Articles | Metrics
    Policy Modeling and Simulation on Ecological Civilization Construction in China Based on System Dynamics
    LIU Kai-di, YANG Duo-gui, WANG Guang-hui, ZHOU Zhi-tian
    2020, 28 (8):  209-220.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.019
    Abstract ( 258 )   PDF (3644KB) ( 153 )   Save
    Ecological civilization construction in China is a complex dynamic process, regarded as crucial as the construction of economy, politics, culture and society, evolving issues including ecological and environmental protection, resource conservation and environmental governance. Existing studies on ecological civilization construction can be divided into two groups: qualitative analysis and quantitative analysis. The former ones focus more on the concept, connotation and realization path, while the latter ones on performance evaluation. Also, ecological civilization construction includes multiple factors such as economy, science and technology (S&T), education, policy, and environmental governance, changes of which will affect other factors and further the entire system.However, interdisciplinary studies are rarely conducted in this field, especially from the perspective of system science.Besides, fewer of the quantitative havenoticed the path and impact of different policies on ecological civilization construction.Therefore, investigating policy simulations of ecological civilization construction in China based on a systematic approach is of great significance.
    For this purpose, a dynamic model of the ecological civilization construction system in China is built in this study based on systematic analysis of this process. Simulation period isfrom 2005 to 2030, during which period 2005-2017 is taken as the simulation interval and period 2018-2030 the simulation forecast interval. Four types of policy driving factors (i.e., birth, education, S&T, environmental governance) are set. 11 types of simulation policy scenarios in 3 categories are further constructedfor investigating the effects of differentpolicies and policy combinations on ecological civilization construction.Results show that: (1) Under current development mode,level of ecological civilization construction in China will continue to be enhanced,with the greatestprogress in the field of resource conservation. (2) Under single policy scenarios,S&T policywill promote the development of ecological civilizationto the greatest extent. The promotion effectiveness of birth policy is higher than the benchmark scenario, but weaker than that of education policy and environmental governance policy. (3) Under the combination policy scenarios,the combination of S&T and environmental governance policypromotesecological protectionmost powerfully. The combination of education and S&T policy can achieve the highest resource utilization efficiency.Yet choosing policy combination to improve the level of ecological civilization construction should also be combined with the long and short term of environmental governance.The former combination can help achieve the goal faster, while the latter combination promises a more stable progress. (4)S&T has become an important policy factor in both single policy scenarios and combined policy scenarios,indicating its significant role in ecological civilization construction.This study provides a reference for policy formulation and implementation as well as decision-making for promoting the efficiency and performance of China's ecological civilization construction.
    References | Related Articles | Metrics
    Research on Growth Optimal Path For Wind Power Technical Talents
    LIU Lin, YANG Wen-yin, HUANG Lin-hua
    2020, 28 (8):  221-230.  doi: 10.16381/j.cnki.issn1003-207x.2020.08.020
    Abstract ( 152 )   PDF (2798KB) ( 112 )   Save
    The sustainable development of talents is necessary for the development of wind power.As a multidisciplinary emerging industry, the training and accumulation of Wind power Technical talents takes a very long time period.Therefore, how to effectively improve the speed and quality of wind power talentsgrowth is essential.Based on the analysis of the characteristics of the growth network of technical talents, the relationship between different growth states of the quantified scale of growth cost function and a model of wind power talents growth are proposed, and then the improved Floyd algorithm is used to find the optimal path of wind power talents growth according to the transfer cost function.Finally, Through the simulation experiment verifies that this method can effectively improve the speed and accuracy of calculation and reduce the time complexity. It provides a quantitative method to support the growth speed and quality of new energy wind power talents.
    References | Related Articles | Metrics