Table of Content

    20 July 2019, Volume 27 Issue 7 Previous Issue    Next Issue
    Dynamic Portfolio Management Strategy with Adaptive Beta Coefficients
    GUO Fan-yong, PAN He-ping
    2019, 27 (7):  1-10.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.001
    Abstract ( 653 )   PDF (1268KB) ( 346 )   Save
    A new 2-level dynamic portfolio management strategy for stock investment is proposed in this paper. First of all, industrial sectors are selected according to their relative strength in terms of adaptive beta coefficients. Then stocks of the selected sectors are grouped into a stock portfolio which is managed through a dynamic multi-period mean-variance model. This dynamic model uses the classic mean-variance theory as the kernel, and the model parameters-the portfolio weights-are solved out using the data from the immediate preceding period with a certain length L. The portfolio with the solved weights is then held on for the immediate follow-up period with a certain length H. These two exogenous parameters (L, H) are optimized through historical data. This dynamic portfolio management strategy has been tested using historical data from the Chinese stock market, showing better performance than passive index-tracking investment strategies in three performance appraisal metrics (including annualized returns, risk-adjusted returns and prediction market return). In particular, the dynamic portfolio strategy can earn better excess risk-adjusted returns. The 2-level dynamic portfolio strategy provides a computationally feasible and operationally reliable stock portfolio management approach.
    All in all, a quantitative and dynamic asset management methodology for investors is proposed in this paper. On one hand, it verifies the Chinese stock market is ineffective; on the other hand, it can help investors decide how to allocate their wealth.
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    The Risk Hidden in Price Surge: Evidence from Chinese Stock Markets
    YE Yan-yi, GAO Hao-yu, YANG Xiao-guang
    2019, 27 (7):  11-22.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.002
    Abstract ( 469 )   PDF (4655KB) ( 223 )   Save
    Stock price surge intuitively generates higher profits and promotes the positive sentiment in the short run.Why it is regarded as risk? Prior literature has already done much researches on crash risk. However, there are few studies discussing the stock price surge.The features of stocks are analyzed with price surge, the future performance of these stocks is examined, and the empirical evidence on the potential risk of stock price surge is provided. A comprehensive database on Chinese stock market from 2006 to 2016 is used and the number of the trading days is counted that reached the positive price limit within a given period as a proxy for the intensity of price surge. To show potential risks behind the price surge, three outcome variables, i.e. the number of trading days that reached the negative price limit, the future cumulative abnormal returns (CAR) and stock return volatility, are introduced as risk measures.The data is compiled from CSMAR and WIND database.
    Our findings show that:(1)stocks with more price surges are associated with lower return on asset, higher market-to-book ratio, less institutional ownership, and less likelihood of being HS300-index stock; (2) these stocks exhibit lower long-runexcess returns, more stock price crashes and higher volatility in the future. Moreover, the cross-sectional heterogeneity across stocks is also explored in the risks hidden behind price surge. The interaction analyses find that the down-side risks turn to be significantly higher for firms with worse operation fundamentals, over-optimistic market sentiment, higher information asymmetry and worse corporate governance. These results are quite robust to alternative proxies for future performance and alternative model specifications. Our results suggest that the stock price surge is indeed a kind of risk because it results in severer future loss and higher uncertainty.This paperempirically illuminates the risk hidden behind price surge and add to the prior literatures discussing the extreme price risk.
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    Forecasting Financial Distress of Listed Companies with Textual Content of the Information Disclosure: A Study based MD&A in Chinese Annual Reports
    CHEN Yi-yun
    2019, 27 (7):  23-34.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.003
    Abstract ( 615 )   PDF (1768KB) ( 435 )   Save
    Traditionally the prediction of financial distress is based on the quantitative information such as accounting data and market trading data, which has been proved as inefficient with a series of debt crisis after the subprime mortgage crisis. Quantitative data reflect the financial position of the company directly, while the qualitative textual content in the information diclosure reports is an important supplement, which may provide new clues for the prediction of financial distress since the wording and style may change with the financial postion of the company.
    With various studies on the automatic textual analysis in the field of corporate finance, mainly on the stock market related issues, bag of words methods are applied to measure the management tone reflected in the Management Discussion & Analysis (MD&A) of Chinese annual reports, and test whether the management tone can provide additional information for financial distress prediction empirically. With different dictionaries, word segmentation tools and term weighting methods, a series of management tone variables are created, and added to various traditional financial distress prediction models.
    Taking the special treatment (ST) as the symbol of financial distress, a sample of 2024 Chinese listed companies is selected.The emprical results from estimations with discrete-time hazard model, information content tests, in-sample and out-of-sample forecasting indicate:(1) management tone can provide new information for the financial distress prediction, and improve the fitness and predictive power of the financial distress prediction models; (2) management tone is an important supplement to the quantitative financial data, which have not been fully reflected in the market price; (3) the negative tone can provide more information than the net tone reflected in the textual content; (4) the tone or sentiment analysis of financial text should be based on the dictionaries created on similar text, but not the list of words from other non financial fields.
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    The Research on the Relationship between the Interest Rate And Volume in the P2P Lending Market——An Empirical Analysis Based on Data in Different Regulatory Periods
    TANG Yong, ZHU Peng-fei
    2019, 27 (7):  35-45.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.004
    Abstract ( 374 )   PDF (1417KB) ( 126 )   Save
    The relationship between volume and price is the key to understand the complexity of financial markets. With the coming of period of comprehensive and strict supervision on Internet finance, is there some significant change on the volume-price relationship of the online P2P market compared with the previous loose supervision period? The average comprehensive interest rate and total trading volume of P2P market are taken as the research object in this paper, where data of loose supervision period is selected from 2015-5-13 to 2016-10-12 and strict supervision period is selected from 2016-10-13 to 2018-1-3. Based on fractal perspective, the DCCA coefficient, DCCA based on time delay and MF-DCCA methods are adopted in this paper to investigate the evolution and complexity of the relationship between trading volume and interest rate in online P2P Market. During the investigation, there is a comparison on the correlation level, conduction direction and multi-fractal characteristics of the volume-price relationship in the online P2P market during the two periods of loose and strict supervision. The empirical results show that, first, there is a multi-time scale cross-correlation between interest rate and volume in both two periods, and different from the gradually decaying correlation during the loose supervision period, the volume and price on each scale of the strict supervision period always show a high correlation level. Second, during the loose supervision period, the transaction volume and interest rate alternately dominate the volume-price transmission process, while the volume of the strict supervision period always dominates the transmission process. Finally, compared to the loose supervision period, the cross risk between the interest rate and the volume of the online P2P market during the strict supervision period is significantly reduced, but the improvement in the effectiveness level is not significant. A new perspective for online P2P market regulators is provided to gain insight into the micro-market structure and broadens the discussion scope of the complexity of the online P2P market.
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    A Study of Risk Measurements of Chinese Gold Market based on Bootstraped Filtered Historical Simulation Approaches
    LYU Yong-jian, FU Ting-luan, HU Ying-yi, DAI Dan-miao
    2019, 27 (7):  46-55.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.005
    Abstract ( 501 )   PDF (1091KB) ( 120 )   Save
    Traditional Historical Simulation and Filtered Historical Simulation are the most used risk measurements among international commercial banks. Another filtered historical simulation approach——BHW is presented in this paper, which is constructed by Hull and White (1998) and bootstrap methods. Then the spot trading of gold price is taken as samples, and the accuracy of the BHW method and other popular methods, such as traditional historical simulation methods, BRW methods, Hull and White(1998) methods and parametrical GARCH methods are backtested. Since Dumitrescu et al. (2012) pointed out that there's none backtesting method have absolute advantage on others, and suggest that take more backtesting methods as possible, six different methods are taken. The conclusions include:(1) Compared with the other 4 popular risk measurement methods, BHW methods shows relative better accuracy; (2) In the small sample case (125 days), the advantage of BHW are significantly better than other methods, when the sample size become larger (250 days), HW, BHW and GARCH models all show relative better accuracy, and the HW approach is slightly better than other methods; (3) the accuracy of different historical simualtion methods are influenced by rolling sample size differently.
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    Production-Distribution Network Optimization Model and Experimental Design Considering Risk Aversion under Uncertainty
    QIU Ruo-zhen, LIU Jian, YU Yue, ZHU zhu
    2019, 27 (7):  56-67.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.006
    Abstract ( 372 )   PDF (1233KB) ( 132 )   Save
    The problem of designing a production-distribution network which consists of plants, distribution centers and terminal markets is studied under the uncertainty of upstream production and downstream demand. Two statements of normality and abnormality are taken into consideration for the uncertainty of upstream production, and three statements of low, medium and high are taken into consideration for the uncertainty of downstream demand. Due to the abnormality in production can lead to the defective products, whether implementating the products monitoring in the upstream plant is considered. By considering both the cost of network operation and the performance risk caused by the uncertainty, three two-stage stochastic programming models for designing a production-distribtion network are developed. The first one is based on the expected cost minimization model which ignores the risk caused by the uncertainty; The second one is then presented by using condition value-at-rick (CVaR) to measure the cost performance of the production-distribution network. However, the CVaR criterion focus exclusively on the down-side risk which will lead to a too conservative solution. To overcome this weakness, both the expected cost and the corresponding CVaR measurement are considered to develop a Mean-CVaR-based model which is characterized by the risk aversion level and the pessimistic coefficient. Specially, the uncertainties in production and demand are described with a series of discrete scenarios which are generated by scenario tree approach. For the large-scale numbers of uncertain scenarios caused by the numerous potential nodes in the network, the scenario reduction technology is used to filtrate the scenarios, which significantly reduces the difficulty of solving the presented models. At last, some numerical calculations are executed to analyze the influence of the relevant parameters on the network performance, and the Pareto Effective Frontier evaluated by the expected cost and the conditional risk value is given. Furthermore, the impacts of the risk aversion level and the pessimistic coefficient on the performance of the production-distribution network are examined by the regression experimental design. The results show that the pessimistic coefficient has a greater impact on the network performance than the risk aversion level.In theory, the developed models in this paper can be easily expanded by considering the supplier selection or multi-period operations. In practice, the proposed models provideflexible options for the enterprise to build the production-distribution network. Moreover, by considering the risk-aversion attitude of the decision maker, the CVaR-based models can also provide effective operational decision support for the enterprise to avoid the potential loss induced by the uncertainty and risk.
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    Emergency Channel Decisions of Closed-Loop Supply Chain with Production Diseconomies under Demand Disruptions
    ZHAO Lin, MU Zong-yu
    2019, 27 (7):  68-82.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.007
    Abstract ( 405 )   PDF (1250KB) ( 195 )   Save
    Considering the product process faces diseconomies of scales and the product demand can be disrupted for many reasons, we analyze the emergency channel decisions of closed-loop supply with production diseconomies under demand disruptions. Two decentralized decision models are given with manufacturer and retailer as collector respectively, and the results about the two models are compared to give the effective collecting structure. Furthermore, emergency revenue and expense sharing contracts are designed to coordinate the member's independent decision-making behavior in the two decentralized systems to improve their efficiency. The simulated analysis method is combined to examine the results and it is found that if the demand disruption is small, ordering quantity of new products and collecting quantity of used products in normal operation state have some robustness, if the demand disruption is large, they should be adjusted along the same direction with the disruption. In addition to this, the "double marginalization" problems in decentralized decision systems of two collection channels can be solved by the designed emergency revenue and expense sharing contracts. Meanwhile, each member can determine sharing proportion by bargaining to get improved Pareto profits. The numerical examples also analyze the impacts of demand disruptions, diseconomy coefficients and sharing proportion on equilibrium decisions. The results show that manufacturer's profits and system's total profits in decentralized decision system of manufacturer collection channel are greater than that in retailer collection channel system, and manufacturer make use of recycling products with higher proportion to produce remanufactured products. So, manufacturer prefers to collect used products directly. And the profits of each member and system decrease with the increase of diseconomy coefficient. These results provide some references for emergency equilibrium decisions and channel choice.
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    Dynamic Inventory Rationing for Cross-Season Sales of Fresh Products
    GONG Yuan-yuan, XIAO Yong-bo
    2019, 27 (7):  83-93.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.008
    Abstract ( 381 )   PDF (1272KB) ( 207 )   Save
    With the development of cold chain and the rise of fresh food e-commerce, inventory management for fresh products gets a great deal of attention both from academic and industry areas. Different from managing durable products, the wholesaler faces a difficult challenge of managing fresh products because of their highly perishable nature. This paper focuses on a specific issue that fresh products are sold across several seasons when the wholesaler meets complicated operational risks. On one hand, the product's quality decreases all the time, resulting in a higher demand uncertainty; on the other hand, there's only one chance to purchase in the harvest period while there are several sales periods afterwards. Unlike the traditional inventory problems solving the optimal ordering quantities and times, this paper aims to figure out when and how many to sell across different periods.
    Based on the assumption that the product's quality declines in a given stochastic process, a two-stage model is developed to manage the inventory in a dynamic manner. Specifically, in the first stage the wholesaler determines the total procurement quantity for the whole horizon, and in the second stage he determines the sales quantity for each selling period. The dynamic programming approach is used to solve those rationing decisions backwards. By analyzing the structural properties of the profit functions, it is proved that the optimal inventory rationing decision of each period is only determined and can be solved by the KKT condition. Furthermore, the parameter influences on the seller's different rationing decisions are analyzed, for example, with other parameters unchanged, the larger the current inventory amount is, the lower the current price is, the higher the current freshness level is or the less the perishable risk is, the larger the inventory amount rationed to the future selling periods will be. In addition, our numerical experiments show that comparing with the static policy which analyzes the multi-periods as independent markets, the dynamic policy can take the inventory pooling effect on reducing risks and increasing profits, especially when the perishability risk is higher, when the market size is bigger, or when the demand is less uncertain.
    A dynamic method is presented in this paper to help the wholesaler match limited supply with multi-period demand effectively, and some meaningful insights into the inventory management of fresh products are provided. Further work is required to extend the model in more realistic conditions, such as adding the freshness-keeping effort decisions and so on.
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    Pricing Strategy and Social Welfare in Supply Chain with Competing Manufacturers Based on Carbon Tax Policy
    ZHOU Yan-ju, HU Feng-ying, ZHOU Zheng-long
    2019, 27 (7):  94-105.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.009
    Abstract ( 432 )   PDF (1281KB) ( 208 )   Save
    In recent years, global warming and greenhouse effect have received increasing attention. Countries have also put forward corresponding regulations and policies to curb carbon emissions. Carbon tax, as one of the important policy tools for controlling carbon emissions, is widely adopted by many countries and local governments. Meanwhile, the environmental awareness of consumers is also increasing. Therefore, the optimal carbon tax policy is formulated based on the government's goal of maximizing social welfare, and the pricing decisions of companies under the carbon tax and increasingly rising consumer environmental awareness, which is of great practical significance for enterprises and policy makers. Due to the fact that the manufacturers are in the complete monopoly situation is relatively rare, they are generally faced with fierce competition in the market, such as electronic and electrical industry. Thus, this research will be conducted in the situation with two competing manufacturers. Specifically, a two-level supply chain consisting of two manufacturers and one retailer is taken as the research object and a three-stage Stackelberg game model with government participation is built. The Stackelberg game model consists of three stages. First, the government decides the carbon tax rate; then the manufacturers decide the wholesale price of their own products; finally the retailer decides the selling price of each product. The problem is solved by the backward induction. The study results show that:(1) when the carbon tax policy is imposed, the wholesale and retail prices of both ordinary product and low-carbon product will rise, and the rising trend of price in ordinary product is more obvious than that in low-carbon product. Compared with the scenario with no carbon tax policy, in the scenario with carbon tax, low-carbon manufacturer has a comparative advantage over ordinary manufacturer in product demand and profit changes. (2) Competition between manufacturers is conducive to carbon tax policy to guide manufacturers to reduce carbon emissions per unit of product and achieve green transformation. In the industry with competing manufacturers, it's beneficial for both low-carbon manufacturer and ordinary manufacturer to reduce their respective carbon emissions per unit of product. (3) When the competition between manufacturers is not intensive, the implementation of optimal carbon tax policy can significantly improve social welfare; especially when the consumer environmental awareness is low, the implementation of optimal carbon tax policy is more necessary. (4) When the competitiveness between manufacturers is large, the intuitive tax rate of 1 can be regarded as an approximate optimal carbon tax policy to improve the social welfare, regardless of the consumer environmental awareness. In this paper, the issues about the formulation of government's carbon tax policy and the adjustment of the firms' operational decisions in scenario with competing manufacturers are answered. Further, the relevant research is enriched under the conditions with manufacturers' competition, which can provide a basic research framework and idea for low-carbon supply chain that considers upstream competition.
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    Inventory Competition and Promotion Strategy in a Dual-channel Supply Chain with Free Riding Behavior
    CAO Yu, YI Chao-qun, WAN Guang-yu
    2019, 27 (7):  106-115.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.010
    Abstract ( 477 )   PDF (908KB) ( 416 )   Save
    With the increasing development of the Internet, more and more manufacturers have introduced online channels to sell the same products through traditional retail channels and online channels. However, such dual-channel strategy of manufacturers creates inventory competition among the channels. Meanwhile, there is a mutual substitution problem between traditional retail channels and online channels. That is, when one of the channels is out of stock, a certain percentage of customers will switch to another channel to purchase products. This leads to free riding problem in the dual channel supply chain system, that is consumers and manufacturers with online channels hitch a ride with offline retailers. However, the existing literatures only focuse on the problem of stock-out-based consumer switching or free riding behavior. Few literatures studied both the impact of free-riding behavior and stock-out consumer switching behavior between channels on the decision-making of each subject in the supply chain. In this problem background, two questions are studied:how stock-out-based consumer switching behavior affects the dual-channel inventory strategy, and how the free riding behavior of manufacturers affects the dual-channel inventory strategy and promotion efforts of retailer. To answer these two questions, a dual-channel supply chain model consisting of a manufacturer and a retailer is established in this paper. First the dual-channel supply chain model is analyzed in a decentralized decision-making setting with general stochastic demand, and discuss the effect of the free riding behavior and stock-out-based consumer switching behavior on inventory strategies. Then inventory strategies and promotion strategies are considered when the demand in each channel follows a uniform distribution. Finally, the inventory strategy and promotion strategy in centralized decision-making setting are analyzed for comparison. The results show that the higher the substitution rate of the online channel, the higher the retailer's optimal order. Meanwhile, the larger the substitution rate of retail channels, the more inventory of the manufacturer will be provided for the online channel. However, the impact of free riding behaviors on the retailers and the manufacturers depends on the magnitude of substitution rate between channels, but free riding can reduce the promotional efforts from the retailers. Our research can enrich existing dual-channel supply chain literature and provide decision support for dual-channel supply chain manufacturers and retailers.
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    Pricing Decision Research of Closed-Loop Supply Chain under Asymmetric Information on Governmentregulation
    LI Fang, MA Xin, HONG Jia, YE Chun-ming
    2019, 27 (7):  116-126.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.011
    Abstract ( 393 )   PDF (1546KB) ( 177 )   Save
    To study on the impact of government regulation on differential pricing of asymmetric information in closed loop supply chain, three stage game model is constructed which is composed of government, manufacturer, retailer and consumers and analyze the optimal pricing strategy under government subsidies and punishment policy.Results show that:the optimal level of regulation by the government,asymmetric information of external costs per unit of product changes on manufacturers' profits is more significant; there exists a point of new and remanufactured replacement rate,which has a different effect on retailer pricing ofthe two decisions;the social welfare is a joint convex function of government regulation, and there is an optimum level existing in government's rewards and punishments, which increases the level of government control and plays a positive role for manufacturer to improve production processes and facilitates recovery levels.
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    Reward-penalty Mechanism of Government for Retailer-led Closed-loop Supply Chain under Collection Responsibility Sharing
    WANG Wen-bin, DING Jun-fei, WANG Zhi-hui, DA Qing-li
    2019, 27 (7):  127-136.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.012
    Abstract ( 641 )   PDF (1031KB) ( 236 )   Save
    In recent years, Waste Electrical and Electronic Equipment (WEEE) with significant environmental attribute, has attracted more and more attention of the public. The government has also emphasized the collection of WEEE with legislation to prevent pollution, such as the Extended Producer Responsibility (EPR). Despite of the laws and the efforts of the public, the environment still faces serious challenge. The government, further, has adopted several incentive mechanisms, such as subsidy, to encourage enterprises to collect WEEE.
    Based on these incentive policies, the reward-penalty mechanism (RPM) is proposed to increase the collection rate. In the RPM, the government sets the reward-penalty intensity and target collection rate. The enterprise will receive reward (penalty, resp.) if the actual collection rate is higher (lower, resp.) than the target collection rate. In addition, given the difficulty of collecting WEEE, the collection responsibility-sharing has been investigated in this paper.
    With the advance of the retail, the retailers, such as WAL-MART, SUNING, GOME and etc., play a more important role in the supply chain. Therefore, in this paper, a closed-loop supply chain (CLSC) model is developed, in which the retailer is a Stackelberg leader and the manufacturer and the third-party collector are followers. Then four cases are studied respectively:the government implements the RPM to manufacturer (Case M); the government implements RPM to the third-party collector (Case TP); the government implements RPM to manufacturer and retailer simultaneously (Case MR); the government implements RPM to manufacturer and the third-party collector simultaneously (Case MTP).
    With the comparison and analysis of the equilibrium, the main results are showed as follows. (i) Under Case M, Case TP and Case MTP, the retail prices, the collection rates, the wholesale prices and the total profits of the CLSC are respectively equal. (ii) Compared with other three cases, Case MR results in lower collection rate, higher wholesale price and lower total profit of the CLSC, while the retail price under four cases keeps the same. (iii) If the government implements RPM only to the manufacturer (the collector, resp.), the manufacturer (the collector, resp.) will suffer a profit loss, while the collector (the manufacturer, resp.) will share ‘free riding’. (iv) When the government implements RPM to the manufacturer and the collector, all the players in the CLSC can benefit the RPM if the manufacturer undertakes more collection responsibility relatively.
    Our paper extends and complements prior research that has only studied the CLSC with either the RPM or collection responsibility-sharing in the retailer-led setting.
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    Supply Chain Coordination Strategy Following Output Disruption
    WANG Yong-long, FU Heng, FAN Xin, JIAN Ming
    2019, 27 (7):  137-146.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.013
    Abstract ( 450 )   PDF (1094KB) ( 165 )   Save
    The sudden occurrence of uncertainty-creating factors such as natural disasters and public social events may have an impact on supply (production). For example, in recent years, the supply (production) of products has often been affected by hurricanes and strikes. The occurrence of these emergencies means the original optimal plan or mode of operation can no longer be carried out smoothly, and the coordinated supply chain is no longer coordinated, thus causing large losses to enterprises. Therefore, it is of great practical significance to study how the coordinated supply chain system deals with emergencies.
    In this paper, a three-level supply chain system consisting of a manufacturer, a distributor and a retailer is considered where the manufacturer's output is random. At the same time, it is assumed that retail price depends on random output. It is studied that how a revenue sharing contract deals with disruptions to output caused by emergencies.
    The decentralized decision-making model and centralized decision-making model are analyzed in the case of no emergencies and construct a revenue sharing contract model (original revenue sharing contract) to coordinate the supply chain. Second, it is assumed that emergencies will lead to changes in the distribution of random output. The optimal adjustment strategy is put forward for production following emergencies, a revised revenue sharing contract model is established, and the original revenue sharing contract and the revised revenue sharing contract model are compared. Finally, the impact of emergencies on optimal production planning, pricing decisions, profit and the coordination of the supply chain are analyzed.
    Through the analysis of theoretical and numerical examples, the following conclusions are drawn:(1) After the emergency, the optimal production input quantity for a supply chain is not necessarily related to the output scale but depends on the new expected output and the output volatility. (2) When the range of output disruption due to emergencies is small, the optimal production plan and wholesale price of supply chain remain unchanged, and the retail price changes small. However, the coordination of the supply chain under the original revenue sharing contract will be broken, and the revised revenue sharing contract can better withstand emergencies. (3) When emergencies lead to a large range of output disruption, the optimal production input quantity of the supply chain is negatively related to the expected output and output volatility, and the optimal retail price is also negatively related to the expected output, while the optimal retail price is positively related to output volatility. (4) When emergencies lead to a large range of output disruption, the optimal wholesale price for distributor and retailer is negatively related to expected output and first decreases and then increases with the increase in output volatility. (5) Following an emergency, whether under the original revenue sharing contract or a revised revenue sharing contract, the profit of the supply chain system increases with the increase of expected output but decreases with the increase of output volatility. This study provides a basic method to mitigate the impact of emergencies on product supply (production) and therefore enriches current theoretical knowledge of supply chain emergency management while also providing some theoretical guidance for supply chain managers regarding the handling of emergencies.
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    A Bi-level Programming Model for Locating Terror Response Facilities
    XIANG Yin
    2019, 27 (7):  147-157.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.014
    Abstract ( 372 )   PDF (2010KB) ( 141 )   Save
    Since September 11 and a series of terrorist attacks, terror has become a major threat in the world. In order to mitigate the effect of terrorist attacks, the government can pre-position enough relief resource and rescue equipments in some terror response facilities, which is helpful for improving the efficiency of emergency management.
    A terror response facility location problem is considered which can be treated as a Stackelberg game between two rational decision-makers, namely, the government and the terrorist. The government is a leader, with limited budget, which first chooses some nodes in the network for building facilities, while the terrorist is a follower who chooses a node as attack target after observing the government's action. As the terrorist can always make the best response to the government, the main decision problem in this paper is how to locate some terror response facilities within a given budget such that the worst attack effect can be mitigated.
    Different from current researches associate with location of terror response facility, this is the first paper that presents an integer programming model with further consideration of a budget constraint. Compared with those theoretical location models that associate with this problem, our integer model is not only more suitable for applying and designing existing combinatorial optimization algorithms, but also provides a basic model for future extensions such as stochastic and dynamic scenarios.
    In this paper, a bi-level programming model is presented to characterize the interaction between the two decision-makers. The upper level problem is associated to the facility location problem of the government, and the lower level problem refers to the target choosing problem of the terrorist. All of the decision variables in both level problems are binary.
    In order to solve the bi-level programming model, a hybrid algorithm is proposed for the exact solution, where a branch and bound algorithm that used in the upper level problem enumerate the location strategies implicitly, and the another quick search algorithm is designed for solving the lower level problem once a location strategy is fixed.
    Our model is finally applied in a case study of 16 cities in south Xinjiang province. The numerical results show that:(i) the optimal location strategy and attack strategy under different budget are totally different, (ii) with the budget added, the government can build more facilities, and the attack effect reduces, (iii) the computing time become longer when the budget increases.
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    The Information Disclosure Strategy and Product Line Design and in AON Crowdfunding
    LIU Xiao-feng, GU Ling
    2019, 27 (7):  158-166.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.015
    Abstract ( 395 )   PDF (1026KB) ( 140 )   Save
    Global crowdfunding has shown tremendous growth for the last couple of years. The startling rise of crowdfunding is drawing a high amount of interest in research as well as practice. How to design the optimal product and pricing decisions in a reward-based crowdfunding is an important question. Hu et al. (2015) developed a simple but elegant two-stage theoretical model and drew the conclusion that product line qualities are less differentiated in crowdfunding than in the traditional scenario under an optimal menu pricing strategy with the assumption that a high-type consumer always prefers low-price product if there is no risk of project failure. Their study commendably pointed at an important direction of research on crowdfunding for marketing scholars. However, the fact does not hold any more when product qualities are endogenized, because a high-type consumer can get either a larger or smaller surplus depending on the creator's offering and the market condition if there is no risk of project failure. Using a two-period theoretical model, the product line design is studied in sequential and simultaneous disclosure framework. The problem of product and pricing decisions in crowdfunding is revisited by fully incorporating individual rationality into a crowdfunding mechanism. It is found that in the sequential information strategy, qualities differentiation of the product line can be equally, less, or more differentiated in crowdfunding than in the traditional scenario, depending on the specific marketing conditions such as the heterogeneity of consumer and the proportion of high type consumers; in the simultaneous information strategy, the qualities differentiation will be always equal to the traditional scenario, surprisingly, the price gap in crowdfunding can be larger than in the traditional scenario, which means the entrepreneurs can set higher price in crowdfunding than traditional scenario even with the same product quality. It is also found that the simultaneous information strategy dominates the sequence information strategy in all market conditions because the former can decrease the propensity of free riding. With these new results, our findings provide important considerations for entrepreneurs to optimize their product line design and choose an optimal pricing policy in crowdfunding. The study contributes to not only the stream of product line decisions but also the growing literature on crowdfunding and sharing economy.
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    Identifying Regional Demand Preferences from Online Reviews
    WANG An-ning, ZHANG Qiang, PENG Zhang-lin, NI Xin
    2019, 27 (7):  167-176.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.016
    Abstract ( 364 )   PDF (1659KB) ( 159 )   Save
    Due to the regional difference in customer needs,customer preferences of different region are not the same. Therefore, the identification of the relationship between customer preferences and regional characteristics has become the basis for decision-marking of regional management strategies. A framework of regional preference identification based on online product reviews is presented in this paper. Firstly, the product features are extracted from online reviews, and the sentiment polarity of product features is determined according to the emotion dictionary. Then, the product satisfaction is measured based on the feature sentiment. Finally, the hypothesis test method is used to identify the regional differences on customer satisfaction and sentiment polarity of product features. In order to verify the validity of the framework, the automotive product review data from autohome com are utilized for case studies. The experimental results show that customer satisfaction and sentiment polarity of fuel consumption, space, appearance and interior are significantly affected by the regional factors. The relationship between customer satisfaction, sentiment polarity of product features and regional characteristics is established to identify customer preferences in different regions and provide theoretical basis for regional design and marketing strategies of enterprises.
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    Choice of Optimal Environmental Technology Based on Government Subsidy
    LI Dong-dong, YANG Jing-yu
    2019, 27 (7):  177-185.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.017
    Abstract ( 400 )   PDF (1103KB) ( 180 )   Save
    A three-stage dynamic game model between government and firm to is constructed explore the firm's optimal R&D investment and the government optimal subsidy policy under different abatement technology modes. Moreover, a numerical method is used to analysis the factors that influence the firm's abatement and social performance. First, the R&D subsidy policy is always welfare-enhancing rather than the case of laissez-faire. Second, with the optimal subsidy policy, output, R&D investment, profit, and social welfare under the progress integrated abatement technology scenario become greater than those under end-of-pipe abatement technology for any value of the spillover. Social welfare under the progress integrated abatement technology scenario becomes greater than those under end-of-pipe abatement if the emission tax is sufficiently small. Moreover, output, R&D investment, profit, and social welfare under the progress integrated abatement technology scenario become greater than those under end-of-pipe abatement technology if the damage parameter is sufficiently small.
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    Study on Consumer Satisfaction of Tangshan Hot Springs based on ISM and Online Reviews
    MIAO Xiu-mei, CHEN Ye-tian, MI Chuan-min
    2019, 27 (7):  186-194.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.018
    Abstract ( 528 )   PDF (1031KB) ( 234 )   Save
    With the increasing popularity of leisure tourism, hot springs tourism has gradually become an important presence as a scarce resource for both tourism and leisure. China has hot spring resources and a broad market developing rapidly everywhere. However, due to immature development models and blind investments by tourism developers, the development of hot spring tourism has exposed many problems. How to improve customer satisfaction becomes an urgent problem to be solved. Researches on hot spring tourism in China lack a comprehensive understanding of perceived factors and perceptions of tourists' satisfaction. There is a lack of quantitative analysis tools to further consider the influence relationship between factors. In addition, the current researches on the satisfaction of destination tourists do not take the characteristics of hot spring tourism into account, nor can it reflect the tourist's perception and evaluation of hot spring tourism scientifically and effectively.
    Based on the above management practice and theoretical research needs, the customer satisfaction theory is taken as the research basis, and the tourist satisfaction of hot spring tourism is discussed from the perspective of hot spring tourists. Taking Tangshan Hot Spring in Nanjing as a case study, firstly, online review data was used to mine the factors affecting the satisfaction of hot spring tourists. Based on the grounded theory analysis of the review texts, the concept of the consumer is extracted and categorized, forming a systematic list of influencing factors and their impact on the satisfaction of tourists. On this basis, the interpretative structural model was used to discover relationships between these factors and determine the level of factors and the path of influence on satisfaction. Then the MICMAC method was used to classify and analyze the factors in the model, eliminating the factors that are not related to the system, and finally determining the customer satisfaction model.
    The results show that the model contains 11 influencing factors, some of which rarely appear in the previous hot spring literature, such as "special resources", "target consumers", and "consumption emotion". It is found that the correlation between "price" and system is very small, and consumers are not sensitive to "price". In addition, the "target consumers" is the core of the system, and it provides the only way to transfer the impact from the lower to the higher levels. As for practical significance, hot spring managers are supposed to improve the environment quality and dig out specialties, conduct accurate marketing and focus on customers' experience and emotion.
    The paper's results reveal the path and methods of improving the satisfaction, and provide effective suggestions for the development of hot spring tourism.
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    Enterprise Tacit Knowledge Propagation SIR Model with Consideration of Forgetting Mechanisms
    YANG Xiang-hao, DUAN Zhe-zhe, WANG Xiao-li
    2019, 27 (7):  195-202.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.019
    Abstract ( 362 )   PDF (1027KB) ( 107 )   Save
    Tacit knowledge and its spread are important foundations that constitute the core competitiveness of modern enterprises. Tacit knowledge cannot be explained by language. They can only be demonstrated to prove that it is an existing knowledge. The way to learn tacit knowledge is to comprehend and practice. The existing researches on the transmission of tacit knowledge mainly focus on qualitative research, and the number of the quantitative research is less. On the other hand, in the existing tacit knowledge simulation model, there is less discussion about the forgetting mechanism in tacit knowledge dissemination. The SIR model used in the epidemiological model of this study is suitable for simulating the propagation of tacit knowledge within a company. Firstly, the SIR model of a complex network of corporate tacit knowledge dissemination, which includes infected, susceptible, and removed persons, is considered. Secondly, the steady-state analysis of the model is used to calculate the propagation rate threshold of tacit knowledge dissemination in the enterprise which is λc. When the rate of tacit knowledge transmission is λ>λc, the tacit knowledge investigated can be disseminated within the enterprise, otherwise,the tacit knowledge investigated will gradually disappear within the company. Again, the Runge-Kuntt method is used to solve the above differential equations, and the impact of model parameters on the propagation of tacit knowledge is analyzed. Finally, Matlab is applied to numerical simulation of model parameters. It's found that:the propagation of tacit knowledge within the company is affected by the factors of forgetting and the network structure. Under the condition that the network structure is determined, the greater the rate of oblivion is, the slower the dissemination of tacit knowledge within the company is, or even disappears. In order to improve the effect of tacit knowledge dissemination, companies should regularly conduct intervention training to reduce the impact of forgetting mechanisms on the spread of tacit knowledge. This model has reference value for strengthening the enterprise knowledge management, cultural heritage, education and learning, rumors dissemination, and dissemination of public opinion to develop effective market strategies.
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    GM(0,N) Model for Its Application on Forecasting the Development Cost of Complicated Equipment
    WU Li-feng, YU Liang, WEN Zhao-xia
    2019, 27 (7):  203-207.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.020
    Abstract ( 372 )   PDF (497KB) ( 210 )   Save
    Complicated equipment development cost forecasting of the cross section data is studied, the GM(0, N) model is relatively stable when the sample is small. The data is sorted according to the similarity degree proposed, then GM(0,N) model is established, the more similar to the prediction the object sample data, the more sensitive to GM(0,N) model, the greater weight GM(0,N) model determine from the angle of sensitivity. Due to the similar equipment often produce similar development costs, making full use of the similar sample data to prediction object is helpful to improve the forecasting accuracy. The practical example is given to illustrate the practicability and validity of this model.
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    Meta-Network Analysis Based Risk Evaluation Framework and Empirical Study of Major Infrastructure Construction Projects
    WANG Tao, GAO Shang-de, LI Gui-jun
    2019, 27 (7):  208-216.  doi: 10.16381/j.cnki.issn1003-207x.2019.07.021
    Abstract ( 417 )   PDF (2153KB) ( 216 )   Save
    The major infrastructure projects are characterized by their strategicness, integration and complexity, and these characteristics directly affect and cause high risk level. Risk identification, analysis and assessment in the early stage of these projects have significant influence on the project objectives, therefore it is necessary to establish an effective risk analysis framework of major infrastructure construction projects. Previous research has not fully recognized the risks in the major infrastructure construction projects, and lacked of consideration of associations between risks and the management of multi-objectives. Hence, the purpose of this research was to develop a comprehensive evaluation model for risk management of major infrastructure construction projects. First, the risk list is identified and a risk interaction model consisting of three hierarchies of project objectives, risk events, and risk factors is established. Then, networks between the three hierarchies are identified, and a meta-network of risk management is built based on meta-network analysis. Subsequently, the links in the networks and the risk levels of risk factors are quantified, and critical risk factors are identified. Meanwhile the scheme comparison and selection of the dam transportation on river hydropower station project in China is chosen as a case study to verify the applicability of this method.The results show that the most important risk factors are the misjudgment of decision-making, such as miscalculation of economic and social environment, and the environment-related factors, such as destruction of ecosystem. Besides, among the design schemes, navigation structures have the higher risk level than dam getting-over scheme, and as time goes on, the overall risk levels of these construction schemesare increasing. A risk evaluation method based on meta-network analysis, is propased the black box process of the occurrence mechanism of risks in major infrastructure projects is revealed, and knowledge for future project risk assessment is provided.
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