Table of Content

25 January 2020, Volume 29 Issue 1

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Theory Analysis and Methodology Study

Optimization of Government Financial Strategy for Urban Garbage Green Power Generation Based on Multi-Dimensional Evolutionary Game of Government, Enterprise and Residents

LIU Qin, YANG Qing, XIA De

2020, 29(1):  1-9.  DOI: 10.12005/orms.2020.0001

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The technology of urban garbage power generation tends to be mature, but some enterprises do not choose green technology for clean incineration of green power generation, which causes public protests. Aiming at the optimization of current fiscal strategy in guiding green power generation behavior of enterprises, a multi-dimensional evolutionary game model of government, enterprise and resident is established, and the influence of fiscal decision variables on green power generation behavior strategy of enterprises is analyzed, and propositions are put forward. There are four fiscal decision variables, including electricity price subsidy, garbage disposal fee payment, tax rebate and equipment purchase tax deduction, which can effectively guide the parameter range of green power generation behavior of enterprises. Based on the actual data, the green power generation behavior of enterprises is simulated by Matlab. The convergence and sensitivity of fiscal decision variables to the green power generation behavior strategy of enterprises are analyzed, and finally the optimization suggestions of fiscal strategy are put forward. The results show that indirect financial support may lead enterprises to take green incineration behavior, lower the threshold of electricity price subsidy, and reduce the cost of direct fiscal expenditure.

Study on PROMETHEE Method Optimization Based on Poset

ZHANG Fei, YUE Li-zhu, WANG Guo-hui

2020, 29(1):  10-16.  DOI: 10.12005/orms.2020.0002

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Although PROMETHEE is one of the most popular multi-criteria decision making methods at present, its application scope and quality are still subject to the index weight in the practical application. Some frequently-used weighting methods not only fail to solve the problem of uncertain weight, but also increase the decision-making risk. On the basis of the correlation theorems of Poset, coupled with the qualitative information of weight-weight order, the Poset expression of PROMETHEE is obtained by means of such definitions as outflow matrix, inflow matrix and net current matrix. If the sum of inflow and outflow is constant, it proves that the model has the duality. According to the dual nature, the analysis steps of the PROMETHEE method are simplified with the redundant information deleted. The PROMETHEE model expressed by Poset breaks the mind-set that the method cannot be used without specific weights, with the difficulty of model weighting overcome. Meanwhile, it also enhances the robustness of the model and expands the data type scope.

Game Analysis of the “Last Kilometer”Joint Distribution Driven by the Block Chain

YU Xiao-hui, HE Ming-ke, ZHANG Qiang, PANG Jin-hui

2020, 29(1):  17-22.  DOI: 10.12005/orms.2020.0003

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From the point of view of the government, we analyze the strategy for the express enterprises to choose the common distribution under the block chain driving. The effectiveness of the government compensation mechanism is analyzed to solve the “last kilometer” delivery under the driving of block chain.Through the evolutionary game analysis, we analyze the reasonable scope of the government's subsidy for the express logistics enterprises and community. The analysis shows that under the anarchic compensation mechanism, it is difficult to completely solve the dilemma of the last mile development of express logistics based on the efforts of the express companies and communities. The government needs to give some policy support to the express companies and community, and to ensure that the subsidies have a certain degree of strength. This can ensure that the express enterprise and community have enough power to build the last one kilometer distribution network based on the block chain.

Evolutionary Game Analysis of Medical Information Sharing Based on the Government Regulation

ZHANG Qiang, WANG Li-ya, GENG Na, JIANG Zhi-bin

2020, 29(1):  23-31.  DOI: 10.12005/orms.2020.0004

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Medical and health services are a knowledge-intensive industry that requires effective information sharing. At present, the problem of “high expense and difficulties in medical” has become a heated social problem in China, and medical information sharing is one of the most important ways to solve the problem. However, there still exist lots of barriers in medical information sharing among hospitals, especially for the lack of government incentives and regulation. In this paper, based on the analysis of the characteristics of hospital medical information sharing under government regulation, the problem of medical information sharing is studied. With the hospital information sharing process of the Medical Consortium in China, we introduce the Metcalfe's law and patients' supervision, and the interests of the governments and hospitals are analyzed. An evolutionary game model between hospitals and governments is established and the equilibrium state under different conditions are studied by solving the replicator dynamic equations. The results show that the government has great influence on the evolutionary stable state of the hospital through supervising and establishing the incentive and punishment mechanism. Reducing the risk cost of information sharing, standardizing and improving the quality of information sharing in the hospital, encouraging patients to supervise hospitals behavior of information sharing, making attractive reward and proper punishment policy are the key factors to promote the medical information sharing. The results can provide a reference for governments to evaluate the information sharing trend of the hospital and to establish incentive and punishment mechanism to stimulate medical information sharing.

PM_2.5 Governance Strategy Analysis of Central and Local government perspectives

ZHOU Zhen, XING Yao-yao, LIN Yun, YU Xiao-hui, TAN Zhi-bin, WANG Jie

2020, 29(1):  32-37.  DOI: 10.12005/orms.2020.0005

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This paper analyzes the preference of PM_2.5 governance strategies from the perspective of central and local governments by comprehensively considering the impact of PM_2.5 on asymmetric cross-border transmission between regions, and the synergistic effect of PM_2.5 governance on people, businesses, and governments. The results show that: the removal of cooperation and non-cooperation is not the same all the time due to the influence of transboundary transmission factors. There is no difference between the cost of cooperation and non-cooperation when the amount of cooperation and non-cooperation between regions is the same; otherwise, the cost of cooperation is lower than that of non-cooperation. With the reduction(increase)of cross-border transmission factors between regions, the cost gap between cooperative and non-cooperative governance is reduced(increased), and governments at all levels are more inclined to non-cooperative governance(the central government may wish to cooperate). The emission reduction target setting should consider the difference in returns between cooperation and non-cooperation, as well as the impact of factors such as the level of economic development.

A Study of Express Vehicle Online Schedule Problem with Service Time and Service Flexibility

MA Jun-ping, XU Yin-feng, WU Teng-yu

2020, 29(1):  38-46.  DOI: 10.12005/orms.2020.0006

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Considering the uncertain requests with various service time , and the fact that not all the requests have to be accepted, the express vehicle online schedule problem with service time and service flexibility is built and the lower bound of online schedule strategies for this problem is proved. Replan strategy, ReOPT strategy and GRH strategy and their competitive ratios are given for the nonnegative real line, the real line and the general metric space respectively. The results show that considering service time can improve the competitive performance of online strategies. The online strategies are practical in express vehicle schedule. The conclusion will provide basis for express vehicle online schedule.

Research on the Co-Coupling Evolution Mechanism of Pollution NIMBY Conflict Events-Based on Coupling Coordination Degree Model

KANG Wei, DU Lei, CAO Tai-xin

2020, 29(1):  47-56.  DOI: 10.12005/orms.2020.0007

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With the development of democracy and citizen's environmental protection consciousness, the NIMBY conflicts caused by the construction of some public infrastructures increase year by year, and show a trend to protest against pollution project as the core. The coupling effect between the factors causing the pollution NIMBY conflict affects the development direction of events. Therefore, it is of great practical significance to construct a Co-Coupling Model of conflict events and explore the mechanism of event evolution. Based on coupling theory and the analysis of the intrinsic induced factors, extrinsic inducedfactors, emotional induced factors, coupling forces between inducedfactors and internal evolutionary mechanism of pollution NIMBY conflict events, selecting three pollution NIMBY events of “Yu hangZhongtai waste incineration plant event”, “Jiangsu Qidong event” and “Hubei Xiantao waste incineration power plant event” as typical cases, the event Co-Coupling Model and the Co-Coupling Coordination Degree Model are constructed in this paper to explore the relationship between the coupling degree of induced factors and the evolution of the pollution NIMBY conflict events.The research finds that there is a positive correlation between the coupling coordination degree and the influence value of the event, and the coupling coordination degree is closely related to the development and evolution of the conflict events; emotional factors in pollution NIMBY conflict play a strengthening push effect on the influence of the pollution NIMBY conflict events, and accelerate the process of the event development and evolution. The research results provide a new idea for the government to build the mechanism of blocking the induced factors of the pollution NIMBY conflict, and provide a new way to resolve the emotional coupling force of the masses.

Stackelberg Game Considering Selling Effort in Supply Chain Led by Retailers in Fuzzy Environment

HUANG Xiao-ling, HONG Mei-xiang

2020, 29(1):  57-68.  DOI: 10.12005/orms.2020.0008

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A two-echelon supply chain including one manufacturer and one retailer is considered in this paper. In the supply chain, the retailer plays a dominant role. In order to increase sales, selling effort is made. This paper supposes the retailer provides selling effort and bears the costs by itself. Considering the uncertainty of economic environment, the market demand function is supposed to be linear with price and selling effort, and to be fuzzy variables with the same as the manufacturer's producing cost and retailer's operating costs. Stackelberg model is employed to solve the game problem between the manufacturer and the retailer. As well as the expected value model, the chance constrained model is employed to solve the optimal decision problem. To illustrate the effectiveness of the supply chain game model, a numerical example is given in the end. The research shows that in the equilibrium, considering the cost of retailer's selling effort, the expected profit of retailer is lower than that of manufacturer, but the marginal profit of unit product is higher. The reason is that the dominant position of the retailer not only improves the sales volume of products through selling effort, but also the profits of the whole supply chain. Meanwhile, the retailer can lower wholesale price to make itself gain more profits in the supply chain.

Anti-Attack Social Recommendation Algorithm Based on Multiple Implicit Trust Relationship

LV Cheng-shu

2020, 29(1):  69-78.  DOI: 10.12005/orms.2020.0009

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Under the commercial competition environment, recommendation system is vulnerable to shilling attack. The social recommendation algorithm based on trust relationship is proved to be an effective way to solve the shilling attack problem. However, most of the existing algorithms focus on explicit trust relationships, and implicit trust relationships are not really exploited. A social recommendation algorithm based on multiple implicit trust relation is proposed. Firstly, referring to the framework of trust antecedents in sociology and organizational behavior science, from the two perspectives of global trust and partial trust, we deeply study the extraction and quantification of trust elements. Then, the overall trust degree is obtained by integrating the local trust degree and the global trust degree by the trust adjustment factor. Finally, based on the overall trust of users, the attackers are isolated from trusted neighbors,realization of personalized recommendation. Extensive experiments are carried out on two datasets.The experimental results show that the algorithm improves the recommendation accuracy and effectively suppresses the impact of the shilling attacks.

Worm Propagation Model Considering Attack Correlation

SONG Ming-qiu, LI Yan-bo

2020, 29(1):  79-85.  DOI: 10.12005/orms.2020.0010

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The infection probability of the network node directly affects the propagation process of the worm, and the correlation of the attack behavior increases the infection probability of the node. This paper proposes a worm propagation model-STIR that considers attack correlation. According to the characteristics of attack correlation, the model presents the update formula of the infection probability. The state transition probability method is used to mathematically describe the propagation process, and the calculation formula of the propagation threshold is deduced. Finally, the simulation experiment is performed in a scale-free network. The results verify the correctness of propagation threshold. Compared with the worm propagation model which does not consider attack correlation, this model can simulate the worm propagation process better. At the same time, it is also showed that the increase in the initial value of the infection probability, the rate of infection change and the propagation probability also accelerate the speed and scale of worm propagation.

Study on the Relationship between Routines Replication and Knowledge Transfer: Mechanism and Contingency

WEI Long, DANG Xing-hua

2020, 29(1):  86-95.  DOI: 10.12005/orms.2020.0011

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In order to deal with the routine replication dilemma when routine can not be matched with the external environment, an analysis is conducted based on the paradox relationship among the two routine replication mechanisms with knowledge transfer. This research is focused on the shifting effects and interaction effects over the range of network closure and environment uncertainty. Then an empirical survey is made by multiple regression model with R&D cooperation intensity industry data. The results show that: network closure and environment uncertainty are contingency conditions between routines replication and knowledge transfer. The network closure enhances the promotion effect on conventional routine replication with knowledge transfer, but has inhibitory effect on flexible routine replication. The environment uncertainty has the reduction effect on conventional routine replication, but has no significant moderated effect on flexible routine replication. The two routine replication mechanisms functions as complements in sparse network and stable environment, but they become substitutes in closed network and dynamic uncertain environment. This research can reveal the contingency mechanism of routine replication, while it has significant meaning to improve the capacity of knowledge transfer in technology innovation network.

Forecasting of the Strength in Shock Model

ZHANG Quan, LI Yan-jun, HAN Yang

2020, 29(1):  96-98.  DOI: 10.12005/orms.2020.0012

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In practical engineering applications, many factors of system themselves and of random environments cause systems to suffer from degradation and shocks. Shocking is a significant cause of system failure and hence has been paid more attention to. In this paper, A forecasting model of the shock strength is presented. Based on the available history of the strength series up to time t, we would forecast the valve of in the minimum mean square error forecasting. The confidence interval for the predicated valve is given in normality assumption. This model will have wide application in many fields. A numerical example is given to illustrate the model.

Chinese Medium and Long-term Coal Demand Forecast Based on Monte Carlo Method

HOU Xiao-chao, ZHANG Lei, YANG Qing

2020, 29(1):  99-105.  DOI: 10.12005/orms.2020.0013

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In order to avoid the subjectivity of parameters value of traditional prediction methods, Monte Carlo method, which can randomly generate parameters value, is used to predict the medium and long-term coal demand in China. Firstly, three main influencing factors of coal demand such as economic growth, energy structure and industrial structure are analyzed. And then the coal demand equation is fitted with Ordinary Least Squares based on the historical data of coal consumption and its influencing factors from 1980 to 2015. On this basis, the probability distribution of each influencing factor is constructed, and the coal demand of 1981~2015 is simulated by Monte Carlo method. It is found that the simulation results can better fit the reality and can be used as an effective tool for simulation prediction. Combining with the “new normal” of China's economy and its energy structure adjustment, the Monte Carlo simulation prediction is carried out by controlling the range of parameters value. The results show that the coal demand from 2016 to 2025 will first increase and then decrease, and reach the peak demand of 4.025 billion ton in 2020. These results play an important role in the scientific decision-making of the coal industry.

Application Research

Study of the Incentive Mechanism of Trade between Windfarm and Thermal Plant within a Company for Wind Curtailment Reduction

ZHU Wan-shan, MAO Qi-jing, CHEN Zhen-zhen

2020, 29(1):  106-115.  DOI: 10.12005/orms.2020.0014

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To overcome the challenge of excessive wind curtailment, this paper focuses on the incentive mechanism design that encourages the trade between a wind farm and a thermal plant within the same company. The goal is to achieve the maximum profit for the whole company and to improve the profits of both the wind farm and the thermal plant. We first develop a centralized model to maximize the company's total profit by optimally making the production plan for both wind and thermal plants. This model provides a benchmark for decentralized models where the thermal plant and wind plant make production decisions to maximize their own profits. We study mechanisms of a single price and a multi-tier price for the decentralized system, and find that the multi-tier price mechanism facilitates the trade between the windfarm and the thermal plant and improves the profits of all parties to achieve the company's maximum profit, while the single price mechanism cannot do so. The mechanisms within the company do not require the reform of the current electricity policy and can be implemented within a company. Hence, these mechanisms are practical for reducing wind curtailment.

Research on Dynamic Incentive Mechanism of Competitive Crowdsourcing under the Consideration of Reputation Effect

ZHU Bin-xin, MA Zhi-qiang, LEON Williams

2020, 29(1):  116-123.  DOI: 10.12005/orms.2020.0015

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Introducing the reputation mechanism into the incentive mechanism of crowdsourcing contest can encourage the crowdsourcees to improve their current efforts under the consideration of future performance gains. Therefore, a dynamic incentive model of two consecutive task stages under explicit and implicit reputation effects is established and solved. The influences of explicit reputation correction coefficient, implicit reputation coefficient and the number of participants are discussed and compared with the incentive mechanism which reputation is not considered. The research shows that the reputation incentive mechanism works through the two modes of unit performance incentive intensity and fixed reward level. Increasing the implicit reputation coefficient helps to improve the level of effort at each stage of the task, the uncertainty of explicit reputation decreases the effort in the second task stage. The impact of the implementation of reputation incentive in various situations on the effort level and unit performance incentive in the first task stage contains uncertainty; the increasing number of participants helps to weaken ratchet effect in the first task cycle, but to deduce positive value of the reputation incentive mechanism to the extent of the effort and then to expand the negative value of the reputation incentive mechanism to the unit performance reward.

The Model and Application of Video Vehicle Classification and Counting

ZUO Jing, DOU Xiang-sheng

2020, 29(1):  124-130.  DOI: 10.12005/orms.2020.0016

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Due to the influence of shape, illumination, visual collisions and visual blur, vehicle classification and counting are complex problems in video-based surveillance. Specifically, there is an indispensable part that should be handled carefully, i.e., the foreground extraction. In the initial foreground extraction, a model is established to determine whether there is a vehicle bonding. For the vehicles with visual collision, the model candetermine more accurate foregrounds through the gray space double threshold and the YCbCr image space processing. For such purpose, the paper defines the gap feature vector to recast the vehicle segmentation problem into the optimization problem of finding the dividing points, and gives an efficient vehicle segmentation algorithm to segment the vehicle. Final, a deep neural network is employed to classify the segmented vehicles. The experimental results show that our model is in a position to handle the surveillance videos in practice. Compared with manually calculating vehicle traffic or establishing a three-dimensional model to analyze vehicle classification and counting in the case of vehicle collisions, the proposed method takes the accuracy and timeliness into account. The efficiency is improved but the cost is reduced.

Study of the Environmental Innovation Capability Evaluation Model of Manufacturing Enterprises Based on Entropy Weighted TOPSIS-PSO-ELM and Empirical Research

XU Jian-zhong, SUN Ying, SUN Xiao-guang

2020, 29(1):  131-140.  DOI: 10.12005/orms.2020.0017

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In order to objectively and accurately evaluate the environmental innovation capability of manufacturing enterprises, this study establishes anevaluation indicator system of environmental innovation ability of manufacturing enterprises. We propose the evaluation model of environmental innovation capability of manufacturing enterprises based on the integrated learning algorithm which is Entropy weighted TOPSIS and Extreme Learning Machine(ELM)with Particle Swarm Optimization (PSO). First, the Entropy weight method is employed to calculate the weighted index and comprehensive evaluation of environmental innovation capability of manufacturing enterprises by TOPSIS method. Then, the evaluation value is used as a priori sample for the training and testing of Extreme Learning Machine. This model produces a better network architecture and initial connection weights,and trains the traditional backward propagation again by PSO. The environmental innovation ability of the manufacturing enterprises is analyzed and evaluated in a more comprehensive way. Furthermore, an empirical evaluation of the sixty enterprises are taken as the example to illustrate the feasibility of this method, and a comparative analysis of the environmental innovative capability of the enterprises was also carried on. The validity of the prediction model is verified by comparing the proposed the Entropy weighted TOPSIS-PSO-ELM algorithm with traditional ELM regression fitting algorithms. The resultsshows that the evaluation results based on the Entropy weighted TOPSIS-PSO-ELM model is more accurate and reliable than the existing methods. In addition, it provides theoretical suggestions for further improving the environmental innovation capability of manufacturing enterprises in China.

Dynamic Rating Model for User Credit Based on Continuous Electricity Consumption and Payment Time Interval

XIE Hong-wei, WEI Wei, GUO Cheng-hui, CHENG Hai-ming, LI Wen-jie, CHENG Chong

2020, 29(1):  141-147.  DOI: 10.12005/orms.2020.0018

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Increasing power supply and improving the tariff recovery efficiency are the major approaches for power suppliers to enlarge their profit. And the payment time interval of electricity customers affects the completion of tariff recovery directly. Only using the information of users' continuous electricity consumption and payment time interval, we build a dynamic credit rating model by integrating both electricity consumption and payment time interval information based on improved “S” function. This model can be used for the dynamic evaluation of the continuous electricity consumption ability and payment positivity of electricity customers. Applying this model to the credit rating of electricity customers in Ningcheng county, Chifeng city, we verify that the credit rating results have high consistency with the results given by domain experts.

Value Evaluation for Cultural and Creative Enterprises Based on Intuitionistic Fuzzy Analytic Network Process and 2-tuple Linguistic

ZHOU Xiao-guang, XIAO Yu, HE Xin

2020, 29(1):  148-156.  DOI: 10.12005/orms.2020.0019

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Accurate assessment of corporate value in equity transfer, mortgage, listing, merger and acquisition helps managers and investors to make correct and effective decisions. Based on the characteristics of cultural and creative enterprises, this paper puts forward the idea of evaluating the value of cultural and creative enterprises from both financial and non-financial aspects. The financial aspect is evaluated using the discounted cash flow method. For the non-financial aspects, the indicators from the four aspects including business operation, creativity, growth and driving are selected, and a network systems with interaction and feedback relationships is constructed. To better express the opinions of experts and decision makers under uncertain conditions, intuitionistic fuzzy preference relationships are introduced to establish the judgment matrices. Combined with the 2-tuple linguistic comprehensive evaluation method, the influence of non-financial factors on the value of cultural and creative enterprises is obtained. Finally, taking the valuation of listed company China South Publishing & Media Group as an example, this paper illustrates how to apply the proposed method.

Comprehensive Evaluation of the Positions of the Ports along “21Maritime Silk Road”

CHEN Fu-ying, ZHANG Jian-tong, LUO Mei-feng

2020, 29(1):  157-164.  DOI: 10.12005/orms.2020.0020

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Based on the centrality indicators for node importance from complex network, this paper evaluates the positions of ports along “21 Maritime Silk Road” which participate in the construction of “Belt and Road Initiative” from the perspective of shipping network. Collecting the data of 102 ports along Maritime Silk Road, we construct the shipping network topology diagram of the ports and get the ranking of port positions by calculating degree centrality, closeness centrality, betweenness centrality and feature vector centrality combined with the method of Entropy-weight TOPSIS. The results show that Singapore port, Shanghai port and Klang port have high positions in “21Maritime Silk Road” shipping network. And existing complex network method of node importance ranking contains some limitations while the comprehensive evaluation method based on Entropy-weight TOPSIS is more realistic. In addition, node deletion method is used to analyze the results, and suggestions are put forward for Chinese ports in the construction of “Belt and Road Initiative”.

Research on the Narrowing of Interest Rate Pricing Mechanism in Online Lending Platform Based on Propensity Score Match Method

DONG Chen-ke

2020, 29(1):  165-175.  DOI: 10.12005/orms.2020.0021

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Online lending has been developed into a new stage, drawing great attention from the relevant academic circle. Interest rate pricing mechanism is considered as the most important factor in designing online lending mechanism because it reflects the nature of financial capital, that is, to price risks and decrease information asymmetry. Wei and Lin(2016)have recorded and analyzed the change of the online lending mechanism in the United States. This paper researches relevant data from a typical online lending platform in an effort to see the difference in its transaction behavior after its rate pricing mechanism changes. The result is that when the platform narrows the range of interest rate and gives permission to few potential borrowers, the default rate goes up with more herd behavior of the investors, and investors bid less percentage in the latter period. Since the change of the platform mainly reflects in the decrease of interest rate range, the paper explains the reason for the change by employing the interest rate weekly standard deviation as the proxy variable. Such decrease makes it difficult for people to differ good loan quality form bad loan quality. Thus, both the platform and the investors cannot identify the risk and the platform does not run at its best.

Study on the Dynamic Linkage of A-Shares and Hong Kong Stocks Based on MRS-SJC-Copula Model

WU Xiao-fei, ZHU Shu-zhen, BAI Zheng-wu

2020, 29(1):  176-184.  DOI: 10.12005/orms.2020.0022

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This paper studies the linkage between different stock markets, which considers the structure changes of mean and variance due to the phenomenon of high and low volatility of stock markets in different economic growth cycles. Firstly, based on the dynamic SJC-Copula with Markov state transition, this paper measures the linkage between the mainland stock market and Hong Kong stock market. Then, using the modified ICSS algorithm tests the structural change points of the upper and lower tails. The empirical results show that there is a non-linear asymmetric time-varying dependence between domestic and Hong Kong stock markets and a probability transition between high and low states. The stock index is affected by the negative news more than the positive news because of the dynamic linkage, and the upper and lower tails are affected by the last information continually. “Shanghai-Hong Kong-Tong”, “Shenzhen-Hong Kong-Tong”, Sino-US trade war and other factors make the upper and lower tails have structural changes. The linkage between the mainland and Hong Kong stock markets has increased and the volatility of the markets has become stronger.

The Stability of China Stock Market Network and Its Macroeconomic Factors ——An Empirical Study Based on Three Network Topologies and Robustness

ZHANG Wei-ping, ZHUANG Xin-tian, WU Dong-mei

2020, 29(1):  185-194.  DOI: 10.12005/orms.2020.0023

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Based on the multifractal characteristics of financial time series and the VaR model of measuring market risk, this paper constructs China's stock market networks and studies empirically three networks' topological features. Then through cointegration method, we analyze the long-term equilibrium relationship between network stability and macroeconomic variables. The results show that: the stock price network does not have scale-free features, while the multi-scale network and the risk network have scale-free features. Among three types of networks, the risk network is the most robust. Additionally, the stock market volatility and the network stability coefficient are Granger causality, and the early changes of the stock market volatility can effectively explain the changes of network stability coefficient. There is a long-term equilibrium relationship between network stability and macroeconomic variables. GDP growth rate and CPI have a positive effect on network stability, and the interest rate has a negative effect on network stability. The risk network provides a reference for analyzing the short-erm risk and stability of China's stock market, as well as formulating a defense strategy about system risk.

The Research on Multi-factor Interaction of Intertemporal Choice for Unbalanced Bid

JIN Lianghai, GONG Run, CHEN Shu, CHEN Yangao, ZHENG Xia-zhongi, YAO Ruo-jun

2020, 29(1):  195-201.  DOI: 10.12005/orms.2020.0024

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The psychological characteristics of the bidder's intertemporal choice will directly affect the unbalanced bid strategy, thereby affecting the amount of the project's settlement and operating benefits. To reveal the psychological mechanism of intertemporal choice under unbalanced bid, aiming at psychological effect of intertemporal choice during the process of making decision for unbalanced bid, the reasonable assumption is that decision makers are limited rational men in view of the maximum utility principle of intertemporal settled accounts strategy. Through releasing questionnaires, we study the multi factor interaction of intertemporal choice. The main effect of rational level, time scale and time frame is significant. The interaction is obvious between rational level and time frame, rational level and time scale. The interaction is also apparent among rational level, time frame and time scale. In date frame, the rational offer is significantly higher than emotional one. In delayed days frame, high rational level bidder prefers higher price when the time scale is larger, while the low rational level bidder are the opposite. The research results have important guiding significance for enhancing the efficiency of unbalanced bidding decision-making and realizing rational decision-making.

Management Science

Selection of Virtual Enterprise Partners Based on Fuzzy Information Axiom and Cloud Model

ZHAO Jin-hui, WANG Xue-hui, GUAN Wen-Ge, YIN Li-jie, ZHOU Yu

2020, 29(1):  202-208.  DOI: 10.12005/orms.2020.0025

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Aiming at the selection of virtual enterprise partners, the key of building virtual enterprise, this paper proposes a method based on fuzzy information axiom and cloud model, driven by cooperation requirements. Quality function deployment(QFD)is used to translate cooperation requirements to decision attributes and their importance degrees; in this process, fuzzy triangular number is employed to deal with the uncertain information, and the relative preference relation analysis is adopted to calculate the relative important degree of decision attributes. The amount of information of each candidate is calculated by information axiom. With the information contents as cloud droplets, digital features of cloud models of evaluation results are obtained, which transforms information contents into qualitative assessment and we further analyze the evaluation results. Finally, an example is given to test the feasibility and validity of proposed method.

Does Real Estate Really Matter to China's Economy? Multiplier Decomposition and Structural Path Analysis Based on Chinese Social Accounting Matrices 2002, 2007 and 2012

ZHOU Wen

2020, 29(1):  209-222.  DOI: 10.12005/orms.2020.0026

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With the objective of evaluating the importance of the real estate on China's economy correctly, this paper compiles Chinese Social Accounting Matrices 2002, 2007 and 2012. The results of multiplier decomposition and structural path analysis show that the driving effects of real estate on Chinese total industrial output, the income of labor and capital, the income of resident and enterprise are extremely insignificant. The driving effects of real estate on the output of finance, renting and leasing, business services, construction, manufacture and processing of metals are significant on some level. Furthermore, paths of real estate's driving effects on the first three industries' output are of direct one-step styles. The close industrial chain of real estate is short. The total driving effects of real estate on the income of factor and institutional accounts are very limited, though the open loop driving effects are increasing. Meanwhile, paths of effect are going through real estate itself and finance sector. Especially the driving effects on capital and enterprise accounts are simple and direct, relying on these two paths. Land rents and taxes from real estate are the primary income sources for local governments. Property developers and operators, financial institutions and local governments are the main stakeholders in this sector.

Overview

A Review of Parallel Batch Scheduling

JING Cai-xia, WU Rui-qiang, JIA Zhao-hong

2020, 29(1):  223-239.  DOI: 10.12005/orms.2020.0027

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Parallel batch scheduling arises from semiconductor manufacturing. In this type of scheduling, jobs are processed in batch and the batch processing machine is capable of processing up to B jobs simultaneously as a batch. The processing time of a batch is equal to the longest processing time of the jobs in the batch. Firstly, achievements of parallel batch scheduling with different traditional machine environments and objective functions are introduced, where machine environments mainly refer to single machine and parallel machines, and objective functions are makespan, total completion time, maximum lateness, number of tardy jobs, total tardiness and maximum tardiness; then 16 new problems derived from general problems by combining with new characteristics are classified, and they are parallel batch scheduling problems with non-identical job sizes, problems with multi-objectives or new objectives, problems subject to precedence constraints, problems with transportation time, discretely controllable processing time, deteriorating jobs, learning effect, forbidden intervals, due windows, energy consumption consideration, rejection, bathing cost, job processing time compatibilities, two-agent, rescheduling and semi-continuous respectively; and research directions of parallel batch scheduling in the future are looked forward to at last.