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20 May 2021, Volume 29 Issue 5 Previous Issue    Next Issue

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Excess Control of Family Board Seats and Stock Price Crash Risk——Based on the Perspective of Related Party Transactions LIU Xing, SU Chun, SHAO Huan 2021, 29 (5):  1-13.  doi: 10.16381/j.cnki.issn1003-207x.2019.1652 Abstract ( 418 )   PDF (1013KB) ( 113 )   Save As a strengthening mechanism of family control,the excess control of family board seats will give the controlling family a strong incentive to carry out related party transactions,which will affect the stock price crash risk. The samples of family firms listed in Shanghai and Shenzhen A shares are manually identified from the sub-database of the private listed companies in CSMAR database,and the key data such as the proportion of family shareholding and the number of family directors are collected manually. Other data come from CSMAR database and RESSET database.The sample period is from December 31,2008 to December 31,2017. The degree of excess control of family board seats (ECFBS) is measured by the difference between the proportion of board seats controlled by the family and the proportion of shares held by the family. The related party transaction behavior variables are measured by Tunnel_dum and Tunnel_asset. The stock price crash risk variables are measured by CrashRisk,including two indicators of NCSKEW and DUVOL. Based on the perspective of related party transactions,the relationship between the degree of excess control of family board seats and stock price crash risk is examined. The results show that the degree of excess control of family board seats is positively related to the stock price crash risk and the related party transaction behaviorof the controlling family. The related transaction behavior of the controlling family has a significant positive effect on the stock price crash risk,and this effect is more obvious in companies with higher degree of excess control of family board seats.Further analysis shows that with a lower proportion of institutional shareholding,a combination of two positions and a smaller board size,the degree of excess control of family board seats has a stronger positive correlation with the stock price crash risk and the related party transactionbehavior of the controlling family; the related party transactionbehavior of the controlling family have a more significant positive impact on the stock price crash risk,and its interaction relationship with the degree of excess control of family board seats has a more significant positive impact on the stock price crash risk.Finally,after controlling potential endogenous problems and conducting a series of robustness tests,the conclusion is still valid. References | Related Articles | Metrics

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Does Insurance Play a “Media” Role in the Path of Financial Systemic Risk Contagion?——Empirical Analysis on the Tail Risk Contagion Path of the Chinese Financial Market WANG Yao-dong, FENG Yan, ZHOU Hua 2021, 29 (5):  14-24.  doi: 10.16381/j.cnki.issn1003-207x.2019.0150 Abstract ( 433 )   PDF (2974KB) ( 164 )   Save After the financial crisis, the traditional perception that insurance industry does not generate systemic risks was broken. By the analysis of its business characteristics and risk contagion characteristics, the conjecture of the ‘media’ role and conduct empirical research regarding the role of the insurance industry in the path of financial systemic risk contagion network was put forward. The empirical research follows the current mainstream research methods, using the tail risk infection network to study the magnitude of its median effect. 34 listed financial institutions including six listed insurance institutions are selected for empirical analysis, and the study period is from 2011 to 2018. According to the "thick tail" and "asymmetry" features of financial market data, the AR-(GJR) GARCH-Skew-t model is chosen to process the stock return sequences, and then the tail dependence degree can be calculated by the Copula function. Finally, the Minimum Spanning Tree and Threshold Method are used to construct risk contagion network in financial market. An index of insurance media centrality index based on betweenness centrality is constructed to explore the role of insurance industry in the systemic risk contagion network. The empirical results are showed as follows:(1) In the risk contagion network of financial markets, the insurance industry plays an important role in connecting the banking market and the security market; (2) The risk contagion effect of Ping An, which is a diversified insurance company, is the strongest, followed by China Life Insurance. (3) In the banking market, Industrial Bank and insurance market are most closely connected, while for the securities trust market is CITIC securities and GF securities. The path and key nodes of risk contagion network are identified in our study, which is very helpful to provide a reference for the formulation of more targeted systemic risk supervision measures. The innovation of this paper is to identify the "intermediary" role of the insurance industry in the financial risk contagion network from an empirical perspective, which is of certain value to academic research and practical systemic risk regulation. References | Related Articles | Metrics

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Research on Portfolio Optimization Based on Complex Network MO Dong-xu, ZHENG Tian-dan 2021, 29 (5):  25-33.  doi: 10.16381/j.cnki.issn1003-207x.2020.0350 Abstract ( 697 )   PDF (3689KB) ( 318 )   Save The extentions of global minimum variance (GMV) model have received significant attention over the past decades. A vast literature focused on improved estimation of covariance and modified the risk measurement. We consider herein the extention of GMV model from a perspective of complex network in which nodes represent stocks and the edges represent the dependence structure of stock returns. Precisely, the objective function of GMV is modified by taking into account an interconnectedness matrix, consisting of the local clustering coefficients which charaterize how much an individual stock is embedded in the portfolio system. Hence, our proposed method considers not only the volatility of each stock but also the interconnection of each stock with the whole portfolio system. The main steps of our approach are summurized as follows:(1) construct the stock network via the correlation matrix (Pearson and Kendall); (2) compute the local clustering coefficients of stock network and the clustering coefficients matrix; (3) formulate the objective function of GMV model by introducing the clustering coefficients matrix; (4) model optimization. In order to evaluate our proposed method, an empirical analysis of China's stock market is performed in which portfolios obtained from our proposed model (based on Pearson and Kendall correlation matrix refer to PGMV and KGMV) will be compared with the classical GMV portfolio and the equally weighted porfolio (EW). The performance of different portfolios is examined by the Sharpe Ratio, the Information Ratio and the Omega Ratio. As a robustness check, our proposed method is applied to different rolling windows. The emperical study shows that the portfolios of PGMV and KGMV outperfom those of GMV and EW according to Sharpe, Information and Omega Ratio. Regarding the robustness check, it is observed that all the considered methods provide worse results when a shorter rolling window (60 days and 120 days) is used, but the portfolios based our approach are consistently better than the others. In all, considering the underlying structure of financial network is an effective way in improving the portfolio optimzation process and our approach gives investors a better tool for asset allocation. References | Related Articles | Metrics

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A Loan Credit Risk Model Incorporating Text Prior Information WANG Xiao-yan, ZHANG Zhong-yan, MA Shuang-ge 2021, 29 (5):  34-44.  doi: 10.16381/j.cnki.issn1003-207x.2019.1554 Abstract ( 559 )   PDF (1582KB) ( 208 )   Save Loan is not only an important way to solve the shortage of finances, but also an important business of financial institutions. The management of loan credit risk is quite essential for the survival and development of those institutions. A key step to control the credit risk is to identify the factors having significant effect on the default. In the existing studies, there may be much valuable and important information which can benefit our study. To incorporate the information, a loan credit risk evaluation model named PIPL is constructed in this study. It first searches text prior information from existing literatures via text mining techniques, obtaining the prior frequency for the credit risk indexes which indicates their importance. Then a penalized variable selection method is used to transfer the prior frequency into a prior response, which realizes the transformation from qualitative information to its quantitative counterpart. Finally the loss function of the proposed model is constructed by weighting the prior response and original observations. To achieve risk index selection, an Elastic net method is adopted. To estimate the parameters, an iteratively reweighted least squares method and a coordinate descent algorithm are used. Simulation study is developed to verify the validity of the proposed PIPL model. Especially, various types of prior information with different extend of quality are set in the simulation, which can examine the model's utilization of the good information and the robustness to the bad information. The result shows that PIPL model can adaptively adjust the quality of prior information. When the information is of high quality, PIPL improves the weight of prior information in the model and then enhances the model's performance in terms of index selection and classification. When it lacks reliability, PIPL can adaptively reduce the weight of prior response, presenting some extend of robustness on classification. In the empirical analysis, 123 literatures about credit risk are mined from the CNKI. Taking P2P data from Lending Club as an example, the analysis shows that PIPL model can enhance the classification accuracy and present satisfactory robustness. Both simulation and empirical study show the reasonability of the new model. It may have some practicability in the financial risk management. References | Related Articles | Metrics

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RFID Adoption Decision and Financing Optimization in a Capital-constrained Supply Chain ZHANG Li-Hao, Chang Lu-Yu, FAN Ti-Jun 2021, 29 (5):  45-54.  doi: 10.16381/j.cnki.issn1003-207x.2020.0050 Abstract ( 347 )   PDF (1020KB) ( 119 )   Save The decision-making of RFID adoption and the financing strategies in a supply chain with a manufacturer and a capital-constrained retailer, who faces inventory misplacement problem is investigated in this paper. Four scenarios of trade credit financing or bank financing without/with RFID technology through the Newsvendor model are considered. The corresponding optimal profits under different scenarios are derived, and then the equilibrium strategies for RFID adoption and financing of the supply chain are explored. It is found that the capital-constrained retailer can obtain more funds from bank financing, whereas the retailer is more willingness to choose trade credit financing as the initial capital decreases. When the retailer's initial capital is moderate, the retailer prefers trade credit financing to bank financing if the misplacement rate increases or the RFID cost decreases. Furthermore, bank financing may alleviate the retailer's inventory misplacement problem. References | Related Articles | Metrics

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The Impacts of Analyst's Herding Behavior on Stock Price Synchronicity ZHANG Da-yong, LIU Qian, JI Qiang 2021, 29 (5):  55-64.  doi: 10.16381/j.cnki.issn1003-207x.2019.0747 Abstract ( 563 )   PDF (961KB) ( 134 )   Save Price synchronicity has been studied intensively in the literature and it is particularly relevant to the Chinese stock market. Synchronicity means that stock prices tend to move up or down together, which has happened regularly in the past. This price co-movement, especially during market turmoil, can increase systemic risks and cause significant losses to companies and investors. A market with strong price synchronicity is also considered as a less efficient market, and thus damaging the market's further development. Understanding the fundamental causes of stock price synchronicity is therefore important for policymakers and practitioners. Among all attempts to explain this phenomenon in the existing literature, herding behaviors of analysts are especially interesting aspect to explore. Analysts are very important participants in the stock market in terms of discovering and spreading information in the market. These people often have strong academic and industrial background, and thus able to extract critical information for companies. Their recommendation and research results are frequently used by companies and investors. In the behavioral finance literature, herding is a typical issue that causes price deviating from fundamentals. It is also found that herding behavior applies to analyst. Given their importance as an information intermediary, herding behavior among analyst can potentially help explain price synchronicity. Extending from the current literature, and to explore how and to what extent herding in analyst drives price co-movement, an empirical investigation on these issues is provided. To be specific, four testable hypotheses are set. The main hypothesis on whether herding in analyst contributes to the price synchronicity in China is tested. The second to test what the real driving forces for the herding behavior in analyst are, in other words, whether the herding is driven by information or non-information. Following the existing literature, institutional investors, and market sentiment are included into our modelling framework to further explore the role of herding analysts on price synchronicity. It is expected to see, first, the higher institutional investors, the stronger herding impacts; and second, herding role is stronger in bearish market conditions. Our empirical analysis uses listed A share firms in China from 2010 to 2017. The original data are collected from CSMAR, Wind and RESSET database. Morck et al. (2000) is followed to construct price synchronicity. Analyst's herding index is the key variable of interest. It is constructed according to Gleason and Lee (2003), who use analyst's forecast of future earnings per share (EPS) and whether the analyst make adjustment towards the average value of all analysts. Through regression analysis and a set of robustness check, the following conclusions are given. First, it is confirmed that herding among analysts can limit their information discovery role, and thus a driving factor of stock price synchronicity. Second, our analysis using a non-star analysts' herding index show that herding among analyst in China is essentially non-information driven. Third, institutional share can reduce synchronicity and potentially dominate the role from analysts. And last, the fourth hypothesis is confirmed that herding analysts have stronger role in pushing price co-movements in bearish market. While providing interesting addition to the current literature on understanding stock price synchronicity, this paper has also some important policy implications. Regulating analyst and reforming compensation mechanisms of analysts are needed to give stronger incentives for them to provide objective reports. Further reinforce institutional investors' share in certain companies and improving information disclosure can alleviate price synchronicity and avoid negative role played by analysts. Overall, efforts are needed to establish incentive compatible mechanisms for efficient information distribution in the market. References | Related Articles | Metrics

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Value-added Service Quality Investment Competition Decision of Bilateral Platform in Competitive Environment GUI Yun-miao, WU Zhong, GONG Ben-gang 2021, 29 (5):  65-76.  doi: 10.16381/j.cnki.issn1003-207x.2018.1245 Abstract ( 461 )   PDF (1179KB) ( 541 )   Save A two-sided platform is defined as intermediaries to connect buyers and sellers, such as Alipay, JD mall. Platform economy has become an important part of Chinese new era. With the intensification of competition among platform enterprises, the subsidy strategy can no longer be a useful means for platform to expand basic users and improve users' loyalty. Platform invested value-added services, which can improve the value and experience of the platform. Therefore, it has become a key issue to choose value-added services for bilateral platforms in a competitive environment. Based on the Hotelling model, the influence of investment on network externality, investment cost, profit and users' utilities is explored. Considering three different user-homing conditions, the two-sided game model is developed. Through comparative analysis, it is found that when the two-sided users are single-homing, whether the platform one-sided or two-sided value-added service quality investment is performed, high quality investment is the dominant strategy of the two platforms. When only one-sided users is multi-homing, if value-added services investments on consumers side are performed, low quality investment is the dominant strategy of the two platforms; if value-added service investments on suppliers side or two-sided are performed, high quality investment is the dominant strategy of the two platforms. When two-sided users are multi-homing, whether one-sided or two-sided value-added service quality investment is performed, low quality investment is the dominant strategy of the two platforms. The results have some practical implications for two-sided platforms' investment strategies. Firstly, more attention should be paid to improve users' experiences and avoid subsidy war. Secondly, investing value-added services should become the most important way to improve customers' loyalty. Finally, making use of bilateral market characteristics of platform investment, it can reduce barriers to entry the right users' side to promote competitive advantage. References | Related Articles | Metrics

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Implementation Method and Optimization of Relational Rent Distribution SHI Wen-lei, RUAN Ping-nan, WEI Yun-feng, LIU Xiao-yan 2021, 29 (5):  77-87.  doi: 10.16381/j.cnki.issn1003-207x.2019.0497 Abstract ( 414 )   PDF (1320KB) ( 107 )   Save The stability is the basic condition to ensure sustainable development of network organization, relational rent distribution is the core element to ensure stability, and relational rent distribution design is the key to realize scientific distribution.The objective of this paper is to provide a method that can be utilized to distribute relational rent to the members of a network organization. Firstly, the function model of network organization operation is constructed, the relational rent generation process is systematically analyzed, and the overall plan of relational rent distribution is designed. Secondly, analyzing the influencing factors, three-stage allocation method for relational rent is proposed, and the integration and modification algorithms of the above allocation methods are designed. Thirdly, based on the stability analysis of network organization, the optimization stage identifies methods for considering the fundamental stability requirements of network organizations based on the proportions of common benefits and private benefits, network organizational stability is also discussed and the optimized distribution method for relational rent is proposed. The summary steps and case analysis stages summarize the rent distribution flow chart and discuss the usefulness of the methods to participants for generating conclusions. This rent distribution method clearly demonstrates the need to easily allocate all types of network organizations and it emphasizes facilitating distribution, proving the rationality of the method. The feasibility and rationality of the distribution method are verified by an example. References | Related Articles | Metrics

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Farmers' Cooperative and Supply Chain Coordination under Platform Model——from the Perspective of Farmer Leading HU Yu-feng, DING Yong-qiang, SUN Yuan-xin 2021, 29 (5):  88-96.  doi: 10.16381/j.cnki.issn1003-207x.2018.1830 Abstract ( 413 )   PDF (3081KB) ( 173 )   Save The relationship of farmers and farmland has been weakened by the development of rural economy, the increase of non-farm income and the promotion of new rural construction, which not only promotes the transfer of farmland, but also provides a living space for the development of cooperatives. To build the development model of rural industry integration is an effective way to let farmers share the value added of the industry. Aiming at the problem of farmers' cooperative and supply chain coordination under the model of platform, a multistage Stackelberg Game model of farmer leading has been proposed under the background of farmland transfer, and a centralized decision-making model and four decentralized decision-making models have been designed. Risk transfer, decision priorities, marginal costs and risk costs are considered, profits maximization models of farmers, cooperatives, small farmers and platforms have been constructed, which were influenced by factors, such as the number of farmers (or the proportion of cooperation), the revenue of farmland transfer, the rate of increase in production, and the sales goals. The functions of optimal revenue of farmland transfer and maximum profits were obtained, and it was found that the number of farmers (or the proportion of cooperation), the revenue sharing rate, and the sales goals all had impacts on the optimal solution. Through numerical simulation, some conclusions are shown. Large farmer's(or cooperatives') priority can increase large farmer's(or cooperatives') profits; Under certain conditions, the cooperative model can achieve supply chain coordination; In the large farmer(or cooperative) model, platform and small farmers' profits are usually lower than those of other models; When the supply chain is coordinated and the profits of small farmers are not reduced, the platform's profits loss can be compensated through an effective way to ensure the continuous equilibrium of the cooperative model. References | Related Articles | Metrics

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Research on A Two-period Supply Chain Recycling Pricing Model Considering Consumer Behavior in A Two-sided Network Environment ZHU Xiao-dong, LI Wei 2021, 29 (5):  97-107.  doi: 10.16381/j.cnki.issn1003-207x.2020.0098 Abstract ( 455 )   PDF (1305KB) ( 256 )   Save Closed-loop supply chain management has been an effective way to improve the economic and environmental benefits and has become a core solution of product recycling system. A closed-loop supply chain model including manufacturers, consumers and the third-party recycling platform is considered, building a complete monopoly two-sided platform in a two-period dynamic game. Based on the model, the optimal recycling prices and profits of the decentralized and centralized decision model are analyzed and compared respectively. Pareto improvement is also lived through revenue sharing contract. Finally, a numerical simulationisused to analyze the impact of remanufacturing proportion and profit contribution rate of users on the profits, which verifies the effectiveness of the contract. Overall, the results show that decentralized decision will lead to loss of profits of closed-loop supply chain, while the profit of the whole closed-loop supply chain is optimal under the centralized decision. By subsidizing consumers,the third-party recycling platform effectively increases the recycling efficiency. The recycling rate and consumers' awareness of recycling are also raised by this way.Additionally, each participant is motivated to implement the revenue sharing contract due to its mutual benefits, which increases the profit of each party. Consequently, the overall profit of the closed-loop supply chain increases as well. References | Related Articles | Metrics

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Cost Allocation for Collaborative Procurement with Carbon Cap and Trade Policy FENG Hai-rong, ZENG Yin-lian, ZHOU Jie 2021, 29 (5):  108-116.  doi: 10.16381/j.cnki.issn1003-207x.2019.0260 Abstract ( 445 )   PDF (937KB) ( 143 )   Save In a two-tier supply chain consisting of a single supplier and multiple retailers, the collaborative ordering decisions for the multi-retailers under the carbon trading mechanism are studied. In the full information situation, the cost allocation problem among retailers are studied in the framework of cooperative game theory. The corresponding cooperative games are established and are proved to be submodular games, and allocation rules which can be realized by the population monotonic allocation scheme are proposed. Moreover, the stability of the grand coalition is analyzed using the concept of the largest consistent set. For cost allocation problem with incomplete information, the existence of the pure strategy Nash equilibrium is proved. The results show that collaboration among retailers not only reduces the total cost, but also reduces the carbon emissions. However, the cost shared by the retailers in the incomplete information situation is more than that in the full information situation. References | Related Articles | Metrics

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Research on the Policy Synergy of Central and Local Government on New Energy Vehicle Industry under the Perspective of Policy Field and Time Dimension HE Yuan, LE Wei, GUO Ben-hai 2021, 29 (5):  117-128.  doi: 10.16381/j.cnki.issn1003-207x.2019.1576 Abstract ( 625 )   PDF (3205KB) ( 348 )   Save New energy vehicle industrial policies play an important role in promoting the early stages of industrial development. For the high-quality development of the industry, the future work should focus on policy coordination. Sorting out from the policies of the past ten years, the existing shortcomings on policy appear gradually, such as the policy intentions of policy subject bias policy objectives and imbalances of policy tool matching, etc. These problems make some industry areas lack of guidance and norms in practice. At present, most researches focus on the analysis of the coordination of each policy making subject and the qualitative analysis of policy synergy between central and local government. However, few studies focus on the quantitative analysis and optimization direction in policy tools using. Referring to the conclusions of process theorists in the research on policy coordination, "new energy vehicle industry policy coordination" is defined as the coordination of policy makers and different policy measures to achieve or support the development of the industry. The fuzzy mathematical method is used to measure the coordination degree from 2009 to 2018 to describe the synergy trend. 263 new energy vehicle industrial policies are sorted out which issued by the governments (four districts such as Beijing) from 2009 to 2018, and divided industrial policies into five categories:fiscal and tax support, industry regulation, planning guidance, supervision and other measures. Furthermore, the industry value chain is decomposed into five links:research and development, production, purchase, use and recycle. Therefore, the coupling coordination model is used to measure the coordination degree in each policy action link from 2015 to 2018.The main research shows that the policy coordination trend of "Central-Shanghai" and "Central-Jiangsu" policies is basically the same and the differences are mainly reflected in R&D, production and recycling links. Improving the policy effectiveness of "policy guidance" and "guarantee measures" will help to improve the coordination level of the central government policy through sensitivity analysis.The results can provide guiding suggestions for the government in optimizing promotion ways of central policies and enhancing regulatory safeguards policy measures. The guiding suggestions for new energy vehicles industry are beneficial to crack the uncoordinated dilemma. References | Related Articles | Metrics

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Optimal Price Discrimination Strategies in Reward-based Crowdfunding XUE Wang, HANG Wei 2021, 29 (5):  129-137.  doi: 10.16381/j.cnki.issn1003-207x.2019.1147 Abstract ( 475 )   PDF (987KB) ( 118 )   Save Reward-based crowdfunding is a common form of crowdfunding that requests project creators to provide innovative production or service as a reward for backers to raise funds for starting their ventures. It has always been a concern that how to improve the success rate of projects for crowdfunding creators, and amounts of creators prefer to adopt price discrimination strategy to simulate bakers pledging and increase project success rate. A model is considered that helps creators promote the success rate which in an all-or-nothing(AoN) mechanism by optimizing the price discrimination that through optimizing pricing and volume. A stochastic model is utilized within a function of pledging probability, and a two-stage model is adopted to discuss the related factors of price gap. In particular, it is shown that success rate, project's quality and innovation degree, the warm affection effect has the positive impact on the pledging behavior. Then the basic model is extended from the backer's valuation type, and the backers' pledging behavior in different valuation types when facing a range of price gap is analyzed. It is shown that a large or small price gap will impede the pricing discrimination strategy effect on simulating pledging, and calculate the optimal price gap which can help the price discrimination strategy work best on increasing success rate. Lastly, the optimal low price volume is solved by maximizing the project profit, and the influencing relationship between low price volume and price gap is discussed. References | Related Articles | Metrics

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Optimal Contract for the Agency Problem Considering Agent's Uncertain Effort in Reducing Project Duration MA Jun-yang, HUANG Xiao-xia, FU Ying-shi, ZHOU Xiao-guang 2021, 29 (5):  138-146.  doi: 10.16381/j.cnki.issn1003-207x.2018.1658 Abstract ( 467 )   PDF (948KB) ( 84 )   Save Agency problem occurs when the principal authorizes an agent for a specific project. In many industries, principal can earn higher return if the project is completed earlier. Since there is some asymmetric information between the two participators, principal cannot know how much effort that agent invests to accelerate completion of the project. The existence of asymmetric information may result in less agent's effort which delays the expected project duration. This is because conflict exists between principal and agent and agent may act on his own interests instead of principal's return. From principal's perspective, he wishes that the agent will exert his effort to shorten the project duration to gain more profit. Besides, due to complexity of the market, in many cases project returns can hardly be predicted exactly by the principal in advance. This paper focuses on analyzing how to design an optimal contract for principal to stimulate the agent to expedite the project completion. Most previous researches used random variables to determine project parameters and the agent's effort in project agency problems. However, in some cases, the project parameters and the agent's effort cannot be obtained by the historical data and have to be estimated by experts. In this paper, uncertain variables are used to describe the experts' estimations of these parameters and the use of them is justified. By applying the uncertainty theory, an optimal contract for the agency problem considering the agent's uncertain effort in reducing project duration is proposed. After that, the deterministic form of the model is given for solving the problem. Furthermore, the optimal contract considering the agent's uncertain effort is compared with that without considering the agent's uncertain effort. It is concluded that when everything else is same, the expected return of optimal contract is not less than that without considering the agent's uncertain effort. Finally, an example is presented to illustrate the application of the proposed model. References | Related Articles | Metrics

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Modeling and Approach for the Energy-aware Production Scheduling Problem under TOU Tariff CUI Wei-wei, TAN Xin-lin 2021, 29 (5):  147-156.  doi: 10.16381/j.cnki.issn1003-207x.2019.2015 Abstract ( 424 )   PDF (1190KB) ( 154 )   Save Research background.With the rising problem of environment pollution and energy shortage, adapting to the feature of energy supply side to reduce the operation cost and increase its competitiveness is becoming more and more important for manufacturers who need draw a huge amount of power. Time-of-Use tariff is a kind of method to encourage the manufacturing plants to move their power demand from the peak hours to the off-peak hours by setting different prices in different hours. Therefore, the managers need to know how to schedule the production plan in order to minimize the energy cost and satisfy the production deadline constraint at the same time. Almost articles in literature use the discrete-time model and meta-heuristic to solve this kind of problem. Our motivation is establishing a continuous-time model and designing an exact algorithm, which can be useful for the industrial practitioners and the following researchers. Problem description. A set of jobs need to be processed during the production horizon[0, W], which is divided into some periods {[0,a1];[a1,a2];…;[aT-1,aT]}.The energy price in the tth period is et. It is needed to decide the start time si of each job Ji. Then, the energy cost of Ji in the tth period can be calculated as et*v* max{0,min(at,si+pi)-max(at-1,si)}, where v is the power demand of running machine and pi is the processing time of Ji. Combining the assignment and positional formulation, which uses binary variables to directly assign jobs to positions in a permutation, a continuous-time mixed integer programming mathematical model for the single machine system under time-of-use tariff is established. Algorithmdesigning.Firstly, for the subproblem with fixed jobs' sequence, the relation between jobs' start times and energy price period is analyzed. A theorem is proven as follows. The optimal start times of jobs can only be four scenarios. Scenario (a):this job is started at its arrival time. Scenario (b):this job is started at the beginning of one price period. Scenario (c):this job is started at some time and finished exactly at the ending of one price period. Scenario (d):this job is located in a compact block which consists of several consecutive jobs and the start time of this block satisfies the scenario (a) or (b) or (c). According to the theorem, the start times become discrete variables. Therefore, a structural branch-and-bound algorithm is designed based on branching the start times. Meanwhile, the method calculating lower bound and the method cutting branches are proposed to improve the efficiency of algorithm. Finally, four different strategies are designed to explore the impact of jobs' sequence on the total energy cost. The algorithm proposed solves the nonlinearity difficulty caused by the period, which can be used to solve other complicated extended problems, for example, the energy allocation problem in manufacturing plant when the renewable energy resources are considered. Main results. Compared with the CPLEX which can only solve the small-sized problems, the computation time of our branch-and-bound is quite short. Comparing four strategies searching jobs' sequence, it shows that the impact of jobs' sequence is quite small and the manager should focus on the buffer time allocation. The numerical experiments show that the model proposed in this paper can reduce the energy cost significantly compared with the traditional way. No matter with the distribution of jobs' arrival time, the highest reduction reaches 40% when the number of price periods equals to 200. It also validates that the impact of increasing energy price is larger when the production deadline is rather tight. References | Related Articles | Metrics

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Research on Vehicle Routing Problem of Multiple Oil Depot Passive Distribution under Multi Oil Supply Constraints XU Xiao-feng, LIN Zi-ru, ZHOU Peng 2021, 29 (5):  157-165.  doi: 10.16381/j.cnki.issn1003-207x.2018.1472 Abstract ( 467 )   PDF (2091KB) ( 305 )   Save The insufficient supply of refined oil will cause that the oil gas stationcan't fully meet the orders. How to arrange the reasonable distribution of limited oil is essential to ensure the safety of energy supply. To this end, the distribution priority of different customers under limited supply is considered, distribution planning, vehicle scheduling, path optimization and other oil distribution network planning activities are carried out, in-depth study on the Multiple Depot Vehicle Routing Problem (MDVRP) with multi-oil supply constraints is conducted. Firstly, a multi-objective optimization model of vehicle routing for multi-oil products and multi-oil depots is constructed, which considers the priority of demand and the cost of distribution. Secondly, the Multi-Objective Particle Swarm Optimization (MOPSO) is used to solve the model to achieve efficient vehicle scheduling and oil distribution routing optimization. Finally, based on the data information of CNPC in some oil depots and fueling stations in Qingdao, an oil distribution network is constructed for empirical testing. The results of the example show that the Pareto optimal set is generated after the optimization of vehicle routing, the distribution cost is significantly reduced, and the delivery satisfaction rate is significantly improved, which further verifies the feasibility and effectiveness of the model and related algorithms.The model and algorithm can be further extended to various supply and demand situations, which is helpful to solve the distribution problem of refined oil products with different priority of gas stations. References | Related Articles | Metrics

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A Two-stage Stochastic Programming Approach for Urban Medical Waste Recycling Network Design PU Song, XIA Chang 2021, 29 (5):  166-172.  doi: 10.16381/j.cnki.issn1003-207x.2018.0943 Abstract ( 404 )   PDF (1011KB) ( 127 )   Save The urban medical waste demand increases greatly, which is also difficult to be determined accurately with the influence of many factors. Therefore, the model for urban medical waste recycling network design model with deterministic recycling demand might not match the actual demand. The problem that the location,assignment as well as transportation are optimized collaboratively is considered, and a two-stage stochastic programming model is built with minimizing the location cost and transportation cost as well as considering the facility and vehicle capacity constraints. And a benders decomposition algorithm is developed according to the model structure. In addition, a series of acceleration techniques are designed to improve the efficiency of this algorithm. Finally, the feasibility and effectiveness of the proposed model and solution strategy are verified through case studies which based on the certain city in China. The results show that the solution of stochastic programming can save more cost than the deterministic programming, and the benders decomposition method combined with a series of accelerating techniques has more advantages than the CPLEX and pure benders decomposition without any accelerating technique. References | Related Articles | Metrics

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Online Two Parallel Batch Machines Scheduling with Order Types ZHENG Fei-feng, JIN Kai-yuan, ZHANG E, LIU Ming 2021, 29 (5):  173-179.  doi: 10.16381/j.cnki.issn1003-207x.2018.1849 Abstract ( 375 )   PDF (928KB) ( 84 )   Save The problem of order processing on two parallel batch machines where orders are of different types is investigated in this paper. Each order type corresponds to a uniform processing time, order size and revenue of order. The machines are of bounded capacities, and each processing batch consists of orders with identical type. The problem originates from catering service industry and other manufacturing applications in internet economy era, where processing orders collected from different customers over internet channel can be handled jointly and simultaneously. This processing mode can improve the utilization efficiency of the corresponding manufacturing or service resources, and make customer demand be better satisfied. The online scenario is considered where orders arrive over time, and the full information of each order can only be released to the decision-maker on its arrival. The decision-maker has to decide immediately whether to accept the order on its arrival and make a feasible processing schedule for accepted orders as well. An online scheduling model is established, where the objective of the model is to maximize the total revenue of completed order. For solving online problems, the general idea is to design online algorithms, and the parameter of competitive ratio is usually adopted to measure their performances. A lower bound of competitive ratio is first proven for the considered problem such that any online algorithms cannot be better than 2Bw/(1+√Bw)-competitive, where B and w are the batch capacity and maximum revenue of one order, respectively. Then both cases with tight and non-tight deadlines of orders are investigated for the problem under consideration, constructing online algorithms and using the method of worst-case analysis to prove their competitive ratios theoretically. For the case with tight deadline, an online algorithm named Profit Threshold is proposed and its competitive ratio of 2(1+Bw)/(1+√Bw) is proven. For the case with non-tight deadline, a revised Profit Threshold algorithm is presented and it is proved 1+2(1+Bw)/(1+√Bw)-competitive. Finally it is shown that for both cases, the gaps between upper bounds and lower bounds of competitive ratio are small, especially when the values of batch capacity and maximum revenue of one order are relatively large. References | Related Articles | Metrics

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Government's Optimal Subsidiesduring the Adoption of Green Products under Uncertain Demand HAI Jiang-tao, LI Xu 2021, 29 (5):  180-189.  doi: 10.16381/j.cnki.issn1003-207x.2018.1258 Abstract ( 444 )   PDF (4468KB) ( 204 )   Save Government subsidies for green products adoption while considering the supplier's response are studied in this paper. Government subsidies offered directly to consumers impact the supplier's production and pricing decisions. Considering the effects of uncertain demand, two different subsidy schemes are compared:a subsidy scheme and a price discount scheme. A frameworkfor policy makers to find optimal subsidies or optimal price discount rates is proposed. The results show that given the specific form of demand function, the optimal subsidy or price discount provided by governments, the optimal output of enterprises and the total expenditure of the government increase with the increase of thetarget adoption leveldesired by the government. From the perspective of minimizing government expected expenditure, the subsidy scheme is the best choice for governments. Given the government expenditure, from the perspective of maximizing the output of enterprises, a price discount scheme is the best choice for the government.The price discount scheme will reduce the consumers' expenditure and increase the welfare surplus of consumers, which is favorable to consumers. Our analysis expands the current understanding of the price-setting newsvendor model, and sheds some light on how demand uncertainty affects consumer subsidy policies, as well as price and production quantity decisions from manufacturers of green products. References | Related Articles | Metrics

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Research on “Dual Track” Salary Framework for Balancing Multiple Theoretical Functions YU Shun-kun, SONG Yu-qing, WANG Qiao-lian, JIA Yu 2021, 29 (5):  190-201.  doi: 10.16381/j.cnki.issn1003-207x.2020.0103 Abstract ( 537 )   PDF (1856KB) ( 296 )   Save With the aggravation of competition, management mode has become an important soft power of enterprises. Fair and reasonable salary management will encourage employees to work actively. However, there are some problems in small and medium-sized enterprises, such as the confusion of distribution orientation and unreasonable wages, which indicates that the traditional wage mode is not suitable for developing enterprises. Various distribution theories are comprehensively used to sort out distribution, wages and their work, and to reestablish the indicators which affect wage distribution. Regression analysis method is used to determine the salary design, to put forward analytic hierarchy process, to determine the weight, and to design a "dual track" salary model. Using this method, enterprise leaders can meet the development needs of enterprise organizations and employees. The sample data of 10 enterprises in different industries are selected, which include 430 evaluation representatives at different levels. By using the job evaluation model, the technical problems of job evaluation in the future are solved, and the influence of subjective evaluation is reduced. The empirical analysis shows that the "dual track" wage distribution model is effective, that is, taking into account the ability, quality and work contribution of employees, it straightens the distribution, and effectively promotes the organizational efficiency. It has a wide range of universality and has been verified in the practice of many enterprises. References | Related Articles | Metrics

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A Solution Method for Shapley-based Equilibrium Strategies of Biform Games NAN Jiang-xia, WANG Pan-pan, LI Deng-feng 2021, 29 (5):  202-210.  doi: 10.16381/j.cnki.issn1003-207x.2018.0642 Abstract ( 1030 )   PDF (933KB) ( 323 )   Save Under the background of the "economic globalization" with both competition and cooperation, economic entities are increasingly reflecting the characteristics of competition and cooperation. They have not only the choice of strategies, but also the distribution of benefits or the allocation of costs. That is, competition and cooperation are interrelated. Therefore, Brandenburger and Stuart proposed a Biform game model to provide an effective tool for this game. At present, there are a few Biform game researches, and there are some shortcomings in the Biform game proposed by Brandenburger and Stuart:the core solution of cooperative games may be empty or not unique. Shapley value is an important single-valued solution of cooperative game, satisfying anonymity, validity, additivity, virtuality, and the expression form is simple and unique. It provides players with a fair and satisfactory allocation scheme for some cost allocation problems and benefit allocation problems. Therefore, when Shapley value is used as the solution of cooperative game, the conditions are studied for the existence of Biform game solutions. In order to analyze the new theoretical framework of the Biform game based on Shapley value proposed in this paper, the condition is first given that the characteristic function satisfies the no externalities of coalition (Shorthand for CNE, it means any player changes strategy will be not affect the return value of the coalition that it does not participate in). Under the satisfaction of this condition, the existence and nature of the Biform game solution are proven. The advantages and disadvantages of using core and Shapley value to solve Biform game solutions are compared and analyzed with numerical examples. The research shows that when the cooperative game solution is solved by the Shapley value, the existence conditions of the Biform game solution are reduced. Therefore, the research in this paper not only makes up for the Biform game proposed by Brandenburger and Stuart, the core of the cooperative game is empty or not unique, and provides a new theoretical framework for the solution of the Biform game. Therefore, it provides a new solution method for the game problem of both competition and cooperation. Therefore, the research of this paper has certain theoretical value and application value. References | Related Articles | Metrics

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Trend Mining of Product Requirements from Online Reviews SHEN Chao, WANG An-ning, FANG Zhao, ZHANG Qiang 2021, 29 (5):  211-220.  doi: 10.16381/j.cnki.issn1003-207x.2018.1508 Abstract ( 927 )   PDF (2949KB) ( 427 )   Save Acquiring and meeting customer needs is the primary concern for product development. The changing market environment and the increasing people's consumption level make customer requirement information become personalized, fragmented and versatile. The product requirements acquired by traditional methods are not objective, timely and comprehensive, and are insufficient to support a customer-centric product development strategy. With the development of social media technology, consumers have published a lot of online reviews in order to share their shopping experience, which contains consumers' requirements for products. How to get product features and their emotional polarity from online reviews? How to identify spam comments in online reviews? How to acquire customer requirements for products using useful reviews? These are some new problems worth studying. In this paper, the process of acquiring product requirements from online reviews in social media environment is studied. Attribute recognition and sentiment analysis methods together with spam comments recognition model based on support vector machine and product requirement trend mining model based on time series analysis are presented. Firstly, unsupervised extraction technique based on crowdsourcing is built to identify product attributes from online reviews. The product attribute sentiment dictionary is constructed, and the adjacent-based method is used to determine the emotional polarity of the product attribute. Then, the product feature extraction is carried out based on the information quality and information gain respectively. For the binary classification problem of spam comments recognition, a spam comments recognition model based on support vector machine is proposed. Next, the non-parametric exponential smoothing model Holt-Winters is used to examine the requirement trend for the products in the next stage, and the Mann-Kendall test method is used to detect the trend of attention and positive and negative emotional changes of each attribute. Finally, the validity of the research model is verified by the review data on the automobile forum, and three automobile product attributes are selected to analyze the importance of product attributes and market satisfaction. The results show that the method of attribute recognition and sentiment analysis constructed in this paper can effectively identify product attributes and judge the emotional polarity of product attributes. The established spam comments recognition model can effectively eliminate spam comments. The proposed time series analysis model can predict the customer requirements for product. These results are useful to provide decision support for companies to undertake marketing strategies and product improvement and innovation. References | Related Articles | Metrics

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Can Seller Feedback Trigger High Quality Online Reviews?——Based on the Empirical Analysis of Taobao LI Zong-wei, ZHANG Yan-hui, XIA Wei-wei 2021, 29 (5):  221-230.  doi: 10.16381/j.cnki.issn1003-207x.2018.1271 Abstract ( 535 )   PDF (967KB) ( 427 )   Save High-quality online reviews bring e-store a good online reputation and increase sales. How can online sellers respond to comments to increase consumers' enthusiasm for posting comments and improve the quality of the content of reviews? The length of comments and the number of pictures are employed to measure the quality of online reviews, and a theoretical model of sellers' online review responses, e-store characteristics, and the impact of online review quality on consumer buying decisions is built. The research hypothesis is verified by collecting Taobao's transaction data. The seller's response positively affects the length of the comment and the number of photos, and the e-store star level and service ability have a mediating effect. High-quality online reviews promote consumers' buying decisions. Our findings provide practical advice for e-commerce platforms and sellers to improve business performance. References | Related Articles | Metrics

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A Group DEMATEL Decision-making Method with Incomplete Judgment Information HAN Wei, SUN Yong-he, MIAO Bin 2021, 29 (5):  231-239.  doi: 10.16381/j.cnki.issn1003-207x.2018.0411 Abstract ( 471 )   PDF (1556KB) ( 275 )   Save Decision-making trial and evaluation laboratory (DEMATEL) is a widely applied method to research the causal relationship of complicated socioeconomic system issues. DEMATEL method has drawbacks such as its invalidity with incomplete judgment information (IJI), unconformity of appointed evaluation scale with different granules of experts' knowledge. To overcome the above mentioned disadvantages, a group DEMATEL method with IJI is proposed in this paper. In the method, in order to aggregate the incomplete and multi-granular information, the influences between factors are considered as alternatives to be compared in a total ordered sequence with different lengths. Then, a group ranking approach for ordinal preferences based on group maximum consensus sequences is applied to aggregate the sequences of influences. Next, as a result of aggregation, the consensus scores are generated by a group consensus-ranking model, and to be regard as elements of group initial direct influence matrix. Finally, the group DEMATEL method can be processed based on the consensus scores direct influence matrix. A case study about the decision-making of medical-integrated pension institutions is given to illustrate the proposed method and demonstrate the feasibility and validity of the proposed method. It should be noted that this suggested method extends DEMATEL to handle IJI with multi-granular evaluation scales, which may improve flexibility of expert's preference judgment and the rationality of system analysis. References | Related Articles | Metrics

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The Improved FAGM(1, 1) Model Based on Simpson Formula and Its Applications XIA Jie, MA Xin, WU Wen-qing 2021, 29 (5):  240-248.  doi: 10.16381/j.cnki.issn1003-207x.2018.1093 Abstract ( 548 )   PDF (1556KB) ( 105 )   Save The errors in the traditional FAGM (1, 1) model are analyzed, and an improved FAGM(1,1) model with the Simpson formula is proposed. Firstly, the fractional FAGM (1, 1) model is developed based on the fractional order accumulating generation operator and the inverse accumulating generation operator. Secondly, employing the Simpson formula to construct the background value of the FAGM (1, 1) model to establish the SFAGM(1,1) model. Further, the genetic algorithm is used to determine the final optimal order of the SFAGM(1,1) model to improve the prediction accuracy of the model. Finally, taking China's per capita GDP as an example, the calculation results of the SFAGM(1,1) model are compared with the GM(1,1), the GM(1,1) model with Simpson formula (SGM(1,1)) and the FAGM(1,1) model, and then the GDP per capita in the "Thirteen-Five" period is predicted. The results show that the prediction accuracy of the SFAGM(1,1) is higher than GM(1,1), SGM(1,1), and FAGM(1,1) models, and the average annual growth rate of GDP per capita during Thirteenth Five-year plan is about 10.64%. The per capita GDP in 2020 will reach 83146.97 yuan,which is 2.69 times as much as that in 2010.And in ciew of 2010 per capita GDP in China, the double goal for 2020 per capita GDP will be achieved. References | Related Articles | Metrics