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    29 May 2020, Volume 29 Issue 3 Previous Issue    Next Issue
    An Empirical Analysis of Pairing Factors in Sino-US Stock Markets
    ZHOU Zhizhong, XU Jie
    2020, 29 (3):  417-424.  doi: 10.3969/j.issn.1005-2542.2020.03.001
    Abstract ( )   PDF (3625KB) ( )  

    Paired trading and multi-factor stock selection are typical quantitative trading strategies. The former is based on statistical arbitrage, which takes advantage of the short-term price deviation of two assets and then hedges the risk to obtain the Alpha return of the two assets. The core assumption is that the spread of paired assets has the property of mean reversion. The latter selects stocks with high comprehensive scores on factors with logical meanings. Due to the high degree of economic connection between China and the United States, there exists price co-movement in the stock markets of the two countries. We construct US equities-A share paired factor according to the ideas of the paired trading. Then the factor is used to select stocks. The empirical analysis reveals that the constructed factor has a relatively good performance in differentiating A share. And it has a low correlation with traditional stock selection factors. Therefore, the factor can be used in the multi-factor model to select stocks. The contribution of this paper lies in the fact that we propose a stock selection factor not examined in the previous research, and verify the validity of this factor in the empirical research.

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    Optimal Scale and Competitive Strategies of Platform in Long-Tailed Market
    ZHANG Yifei, CHEN Hongmin
    2020, 29 (3):  425-433.  doi: 10.3969/j.issn.1005-2542.2020.03.002
    Abstract ( )   PDF (1824KB) ( )  

    In the context of the long-tailed distribution of the trading volume of a platform, and based on the  interaction of trading volumes between end-users, this paper establishes an analytical model to examine the optimal scale of the platform and its strategies in a competitive market, explaining limited scales and co-existence between similar platforms, showing how recommendation systems can benefit the platforms in an online B2C market. User heterogeneity is the necessary condition for a monopoly platform to have a limited optimal scale. When the trading volumes of sellers conform to long-tailed distribution, there will be a unique market equilibrium between two competitive platforms. The recommendation system can increase both the profits and the scale of a platform by redistributing the total trading volume.

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    Evaluation Model to Identify Key Users in Mass Incident Diffusion Network 
    PAN Jun, SHEN Huizhang, CHEN Zhong
    2020, 29 (3):  434-442.  doi: 10.3969/j.issn.1005-2542.2020.03.003
    Abstract ( )   PDF (2300KB) ( )  

    To help people have a better understanding of the mechanism of message dissemination in micro-blog when mass incident happens and have a better idea of how to identify the key users in the diffusion network, the micro blog of social group events is analyzed based on the real case communication data by combining qualitative analysis and quantitative research. Besides, a micro blog communication system of group events is constructed through the information forwarding relationship of events. Moreover, a comprehensive evaluation model of the importance of group event user communication is constructed through the principal component analysis of some basic communication indicators. Furthermore, a correlation analysis of the evaluation value of the model and the central indicators of complex network is carried out in combination with the related theory of complex network. The analysis and research indicate that the network of group events is a complex network with a scale-free nature, small world characteristics, and a high clustering coefficient, in which, the evaluation value of user communication importance is highly correlated with the K-core decomposition index of the user complex network. Therefore, people can rely on the K-core decomposition analysis method to find more accurate and effective important users who affect group event micro blog communication.

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    Stock Price Oscillation and Simulation with External Incentives
    CHEN Qionghao, YING Yirong, YUE Yan
    2020, 29 (3):  443-451.  doi: 10.3969/j.issn.1005-2542.2020.03.004
    Abstract ( )   PDF (1183KB) ( )  

    With the rise of unilateral trading doctrine and the further opening of China’s financial market, the volatility of cross-border capital flows has increased, so has the systemic risk of China’s stock market. In the context of the Sino-US trade war and China’s economic transformation, China needs to explore ways to prevent the stock market crash. Based on the self-organization theory of complex systems, this paper establishes a self-organization model of stock market crash based on forced vibration of the single degree of freedom system. Besides, it compares the real data stock market crash in history from trend form, volume-price relationship, power-law property, and momentum effect, which proves the reliability of the model. Moreover, it studies the process of stock market crash and discusses the internal mechanism to provide a theoretical basis for predicting the occurrence of stock market crash.

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    Loan Portfolio Optimization Model Based on CVaR and Improved Entropy
    CHI Guotai, XIANG Jun
    2020, 29 (3):  452-463.  doi: 10.3969/j.issn.1005-2542.2020.03.005
    Abstract ( )   PDF (1060KB) ( )  

    The optimal allocation of loan portfolio is the core problem of commercial bank asset management. To solve this problem, a whole loan portfolio optimization model based on CVaR and improved entropy is constructed from the perspectives of the overall risk and the risk dispersion of all loan portfolios. This paper is innovative because it has measured the degree of diversification of all loan portfolios by introducing adjustment coefficient into the proportionality entropies to improve the entropy, which improves the drawbacks of the excessive diversification caused by the proportion of entropy constraint that must give every enterprise loan weight and makes the diversification measurement of the entire loan portfolio more reasonable. Besides, it has established a multi-objective programming model by controlling the total portfolio risk after the combination of stock portfolio and incremental portfolio to get the optimal allocation of incremental assets. It has changed the popularity of research by only controlling the lack of incremental risk, which changes the lack of only controlling the incremental risk in the popular research. Furthermore, the risk control of all loan portfolio is based on the loan return rates, following the Laplace distribution assumption, which is in line with the “rush fat tails” feature of the return on financial assets, making it possible for the risk can accurately assessed. It therefore, improves the research based on the normal distribution assumption which cannot accurately fit the actual distribution of the loan rate of return, and thus cannot reasonably estimate the disadvantages of the risk.

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    Simulation of Innovation Network Evolution Game of Industry-University-Research Cooperation Under Market Mechanism and Government Regulation: A Case Study of New Energy Vehicle Industry
    CAO Xia, LI Chuanyun, YU Juan, YU Bing
    2020, 29 (3):  464-474.  doi: 10.3969/j.issn.1005-2542.2020.03.006
    Abstract ( )   PDF (7134KB) ( )  

    Taking the new energy vehicle industry-university-research cooperation innovation network as the empirical analysis object, and by using the network evolution game theory and the simulation analysis method, this paper analyzes the cooperation behavior of innovation agents and network structure evolution regularity in the process of interaction in industry-university-research cooperation innovation network under market mechanism and government regulation. The research results show that market mechanism and government regulation have a promoting effect on the maintenance cooperation behavior of innovation agents and network clustering. Besides, there is a synergetic interaction between the cooperative behavior of innovation agents and the network structure. Moreover, the greater the influence of market mechanism and government regulation, the more significant the synergistic interaction between them. Furthermore, under the market mechanism, the increase in the role of market mechanisms will reduce the speed of network evolution. Only when the role of the market mechanism exceeds a certain threshold will the maintenance cooperation behavior emerge between the innovation agents. Under government control, the innovation agents is more sensitive to government regulation. When the government regulation is under the threshold level, the maintenance of the cooperation relationship between innovation agents is affected.

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    Effect of Extrinsic Reward on Employee Creativity
    HUANG Qiufeng, TANG Ningyu, GE Minglei
    2020, 29 (3):  475-484.  doi: 10.3969/j.issn.1005-2542.2020.03.007
    Abstract ( )   PDF (1024KB) ( )  

    Based on the social comparison theory, this paper discussed the effects of extrinsic reward social comparison on individual creativity and the intermediary role of positive emotions in the relationship between them, and examined positive emotion as a mediator and locus of control as a moderator. Based on an experiment and the questionnaires of two organizations, it tested the hypotheses using different methods of creativity measurement and multiple samples. The results show that compared with the upward comparison, individuals in an extrinsic reward will have a higher creativity than those in an extrinsic reward downward social comparison. Besides, positive emotion mediates the relationship between extrinsic reward social comparison and creativity. Locus of control moderates the relationship between extrinsic reward social comparison and positive emotion, especially when the external orientation is high and the individual in downward social comparison reported is more positive than those in upward social comparison.

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    Pay for Luck and Over Determinate Contract Incorporating Fairness
    WEI Guangxing, MENG Guolian, FANG Yong
    2020, 29 (3):  485-493.  doi: 10.3969/j.issn.1005-2542.2020.03.008
    Abstract ( )   PDF (964KB) ( )  

    The classical contract theory cannot explain the pay for luck and over determinate contract, which has been found and proven by many empirical studies. Aimed at solving the contradiction, fairness preference is introduced in this paper and a behavioral principal-agent model is developed for approach of behavioral game theory, which finds that the optimal incentive contract under fairness does include luck and hereby is over determinate. This not only theoretically explained why the pay for the executive is generally influenced by luck and why the contract is always over determinate, which solves the contradiction between theoretic and empirical findings, but also explains why many companies offer the stock ownership plan to normal employees except the executive, which are also found in the empirical studies. Therefore, regardless of the executive or normal staff, it is necessary to accurately screen the fairness and the reference group for the incentive system.

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    Modeling and Simulation of R&D Network Risk Propagation Considering Risk Perception of Enterprises
    LIU Hui, YANG Naiding, ZHANG Yanlu, LI Ruimeng
    2020, 29 (3):  494-501.  doi: 10.3969/j.issn.1005-2542.2020.03.009
    Abstract ( )   PDF (2905KB) ( )  

    Based on the consideration of the risk perception of enterprises, the state of each enterprise can be divided into unaware and susceptible, aware and susceptible, and unaware and infectible. This paper established a dynamic model of risk propagation in the R&D network based on the susceptible-infected-susceptible(SIS) model. The analytic solution and the simulations show that, first the threshold is determined by the risk perception of the enterprise, the transmission probability, and the degree of cooperation between two enterprises. Next, the percentage of infected enterprises can be influenced by the risk perception. Third, the robustness of the R&D network by taking risk perception into account is higher than that not considering risk perception. Fourth, with the increase of risk recovery probability, the robustness of the R&D network is much higher. Finally, risk perception has a negative effect on the speed and the scale of risk propagation in the R&D network. The research results are of great significance to improve the anti-risk ability of the R&D network.

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    Negative Impacts of Information Hiding Behaviors of Backers in Crowdfunding: Moderating Effect of Online Interaction Behavior of Creators
    ZHOU Yuan , , WANG Nianxin , MEI Qiang
    2020, 29 (3):  502-512.  doi: 10.3969/j.issn.1005-2542.2020.03.010
    Abstract ( )   PDF (1569KB) ( )  

    Past studies have confirmed that the information hiding behavior of backers will have a negative effect on crowdfunding performance. However, little is known about how to mitigate the negative effect. Focusing on the information hiding behavior of backers, this paper examines the negative effect on the pledge of the campaigns, and investigates whether online interaction (e.g., comments and updates) can alleviate the negative effect of the information hiding behavior of investors on the success of the campaign. The unbalanced panel data which consist of the information of 3918 campaigns, adding up to 212753 observations, are constructed and analyzed. The results indicate that the information hiding behavior of investors does decrease the campaign balance. Moreover, the comments of founders will strengthen the negative effect of the information hiding behavior of investors, while the updates of founders will weaken the negative effect of the information hiding behavior of investors.

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    A Discrete Water Wave Optimization Algorithm for  -Vehicle Exploration Problem
    2020, 29 (3):  513-521.  doi: 10.3969/j.issn.1005-2542.2020.03.011
    Abstract ( )   PDF (1043KB) ( )  

    The N-vehicle exploration problem is a NP-hard discrete optimization problem. In this paper, a discrete water wave optimization algorithm with local search enhancement (DWWO-LS) is proposed to solve this discrete optimization problem. First, according to the characteristic of permutation equivalence, a permutation sequence-based encoding scheme is employed. Next, a novel discrete water wave optimization algorithm (DWWO) is developed by redefining the propagation, refraction, and breaking operator. After that, an insertion-based local search is incorporated into the discrete water wave optimization algorithm in order to enhance its local search ability. Finally, the effects of key parameters with regard to the performance are investigated. The numerical results on fourteen benchmark instances demonstrate that the algorithm proposed, in average, is superior to the standard water wave optimization algorithm, particle swarm optimization, fireworks algorithm, and the existing heuristic algorithms named as H1-H4 in terms of solution accuracy and stability. Compared to DWWO-LS, tabu-based variable neighborhood local search (TBVLS) obtains a maximal relative deviation ratio of 0.017 at the expense of computational efforts of at least 66.6 times. These results indicate that DWWO-LS can obtain satisfactory results in a short time.

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    Vehicle Routing Problem with Mixed Fleet of Conventional and Electric Vehicles
    LI Ying, ZHANG Pengwei, WU Yifan
    2020, 29 (3):  522-531.  doi: 10.3969/j.issn.1005-2542.2020.03.012
    Abstract ( )   PDF (1329KB) ( )  

    In view of the situation of fleet management in enterprises in which electric vehicles and traditional vehicles coexisted, this paper proposed a vehicle routing model with composition optimization for a mixed fleet of conventional and electric vehicles. The model proposed optimizes the number of the electric vehicle and the conventional vehicle in the fleet, which differed in fixed costs, variable costs, and driving range, when routing them. The recharging infrastructures were considered as well. Besides, the no-linear objective function was modified to ensure that the model was a standard linear programming problem. A hybrid heuristic algorithm containing scatter search and modified ant colony optimization was designed and proved to be effective by comparing with the Cplex solver. The results indicate that high fixed costs and low variable costs make electric vehicles need long-distance distribution, which is restricted by the limited driving range. This collision blurs the role of electric vehicles in distribution. Besides, the increase in driving range cannot completely change the configuration results of the fleet. Moreover, recharging infrastructures do influence the adoption of electric vehicles.

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    Policy Tool Combination of Housing Rental Market in China Based on Improved High-Dimensional Multi-Objective Optimization Algorithm
    LIU Xiaojun, GUO Xiaotong, LI Lingyan, ZHU Chunyang
    2020, 29 (3):  532-540.  doi: 10.3969/j.issn.1005-2542.2020.03.013
    Abstract ( )   PDF (1293KB) ( )  

    China’s urban housing system has long focused on improving the self-owned housing of residents, ignoring the important role of leasing in the housing market equilibrium, and failing to effectively play its essential role in the rational allocation and flow of urban housing resources. At present, China’s housing leasing market is at the initial stage of development, whose related theoretical research is also lagging behind. This paper focuses on the design of housing rental market development policy. From the perspective of policy tool combination, the policy design process is abstracted into a high-dimensional multi-objective optimization problem. Based on the ideas of opinion mining, using the co-occurrence network, text mining and other methods, and using authoritative literature and expert opinions as data sources, the objective function and the constraint function coefficients are determined to construct a multi-objective function of housing rental market policy combination in line with China’s reality of development. In addition, this paper proposes a two-stage evolutionary high-dimensional multi-objective optimization algorithm based on Pareto dominance relationship to solve the problem of solving high-dimensional multi-objective functions. Therefore, the design framework, process, and method of housing rental market policy tools are established to provide a methodology for government policy formulation.

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    A Non-Binary Implicit Power Measurement Method Based on Social Network and Viewpoint Interaction
    SHI Ruili , GUO Chunxiang, GU Xin,
    2020, 29 (3):  541-548.  doi: 10.3969/j.issn.1005-2542.2020.03.014
    Abstract ( )   PDF (1154KB) ( )  

    From the perspective of social network, and considering the influence of viewpoint interaction among voters on voting behavior, in this paper, the ability of voters to influence other people’s behavior and decision-making based on social relations is defined as implicit power. Based on factors like knowledge level, individual influence, and self-confidence, the influence of viewpoint interaction among voters on voting results is analyzed, a measurement of implicit power under non-binary selection is proposed, and the impact of social network structure, individual influence, and knowledge level on the implicit power index is analyzed. Based on knowledge level, individual influence, and self-confidence, the perspective interaction between voters and its impact on voting results are analyzed. The analysis results show that the implicit power may be positive or negative. A more closely and broadly connected individual has more implicit power. The individual influence is positively correlated with the implicit power, except for the individuals with the highest or lowest influence. However, there is no clear correlation between the knowledge level and the implicit power. The method proposed is no longer limited to measuring voting power according to decision-making rules, but pays more attention to the influence of opinion interaction, which provides a new perspective for the identification of key voters.

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    Prospect Theory, Mental Accounting, and Newsvendor Pull-to-Center Effect
    GU Bojuna, ZHANG Xiang, LI Yanlingb
    2020, 29 (3):  549-560.  doi: 10.3969/j.issn.1005-2542.2020.03.015
    Abstract ( )   PDF (1005KB) ( )  

    There still exist some questions about whether the prospect theory can explain the pull-to-center effect. This paper explored this problem from the perspective of the mental accounting theory. First, it extended the prospect theory to the compound-outcome condition and proposed a theoretical model for computing the value of prospects including the compound outcome based on the mental accounting theory. Then, it applied this model to the newsvendor problem, constructed a model for newsvendors based on the prospect-theory, and found that the ordering decision of retailers was decided by the combined effect of preferences. The numerical study shows that the prospect theory can explain the pull-to-center effect in certain combination of preference. Besides, the nonlinear weighting function of the prospect theory is counteractive to the pull-to-center effect, and the pull-to-center effect can be attributed to the value function formulated by multiple mental accounts.

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    Pricing Strategy of New Energy Vehicle Embedded Technical Service Providers Under Competitive Environment
    LI Sining, CHEN Kai
    2020, 29 (3):  561-572.  doi: 10.3969/j.issn.1005-2542.2020.03.016
    Abstract ( )   PDF (1410KB) ( )  

    This paper constructs a two-tier supply chain for the upstream technology service provider and downstream new energy manufacturers for cooperative innovation, considers the competition relationship and power structure of two manufacturers, and studies the impact of different competition modes on product pricing and product profit, providing reference for decision making of the technology service provider and new energy vehicle manufacturers. The results show that under the same condition, the technical service provider will provide technology to manufacturers under a competitive environment to optimize profits. Besides, the power structure between manufacturers will affect the profit of the technology service provider, and the profit in the FLC mode (i.e., the competitive mode by the same leading) is the largest. From the manufacturers’ perspective, both the intensity of competition and the contribution of technical output will affect the product price. In the case of a small contribution to the technical output, the product price in the M mode (i.e., the monopoly mode) is the highest, that in the SLC mode (i.e., competitive mode by the first manufacturer leading) and the TLC mode (i.e., competitive mode by the second manufacturer leading) is higher, and that in the FLC mode is the lowest. Numerical examples further show that when the contribution of technical output is small, the profitability of products in the M mode is greater than that in the C mode (i.e., the competitive model). In addition, the power structure between manufacturers affects the profitability of products in the competitive mode. Therefore, the dominant strategy of manufacturers in the C mode is to implement pricing through the FLC mode or to obtain pricing leadership in the SLC and TLC modes.

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    Capacity Management Based on Dealers’ Overconfidence
    2020, 29 (3):  573-580.  doi: 10.3969/j.issn.1005-2542.2020.03.017
    Abstract ( )   PDF (955KB) ( )  

    Based on the theory of overconfidence, this paper investigates a problem of capacity management involving initial stock and capacity allocation for a class of items with investment properties. The problem is formulated as a two-period MDP model under the assumptions of random demand and exogenously given prices. A threshold value is found on price variation. A combination of the theoretical analysis and the numerical example indicate that whether the effect of overconfidence on capacity management is positive or negative depends on the extent of price rise. When the price increases beyond the threshold value, overconfidence leads to the loss of expected sales profit. On the contrary, an appropriate extent of overconfidence helps to increase sales profit. At the same time, it is found that demand variation strengthens the effect of overconfidence on capacity management. Besides, capacity management via allocation sale helps to relieve the risk of capacity investment resulted from overconfidence.

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    Low-Carbon Strategy Selection of Competitive Enterprises Based on Social Influence
    GUO Qiang, ZHANG Ting, SHI Chunlai, NIE Jiajia
    2020, 29 (3):  581-589.  doi: 10.3969/j.issn.1005-2542.2020.03.018
    Abstract ( )   PDF (1282KB) ( )  

    Considering the social influence of products, in this paper, the choice of production strategy of two competitive enterprises was discussed. In the case that both enterprises could choose to produce common products and low-carbon products, four strategic models, i.e., GG, GC, CG and CC, were constructed, and the optimal retail price and profits of each model are obtained. The results show that when consumers are more sensitive to the social influence of the products of the two enterprises, that is, when the difference is small, both enterprises will choose to produce common products. When the sensitivity of consumers to the social influence is moderate, the strategies of both enterprises are different and there is no pure strategic Nash equilibrium between them. When the sensitivity of  social influence of consumers is quite different, the enterprises will choose the low-carbon production mode.

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    Ordering Policy for Crowdsourcing Supply Chain on Internet Platform
    LI Jizi , , ZHANG Nian , LIU Chunling , WANG Zhongrui
    2020, 29 (3):  590-600.  doi: 10.3969/j.issn.1005-2542.2020.03.019
    Abstract ( )   PDF (1104KB) ( )  

    Crowdsourcing supply chain (CSC), as a new supply chain with the background of “Internet plus”, is becoming a hot topic of research nowadays. This paper first embedded the design link of crowdsourcing into supply chain, and established a multi-period basic ordering model for the whole crowdsourcing supply chain, based on which, considering that the Internet crowdsourcing platform had the features of open multi-frequency and rapid delivery design, it introduced the rapid turnover factor with time value of capital into extended model. In addition, taking into account the pre-requirement for implementing crowdsourcing supply chain, it further developed and discussed the ordering policy under minimum production quantity and risk aversion in the crowdsourcing supply chain. Moreover, through the optimization and comparative analysis of the models, it obtained the optimal order quantity and implementing conditions for manufacturers and retailers. Furthermore, it designed the multiple incentive contract to achieve Pareto optimality. Finally, it conducted a numerical study which confirmed the feasibility and efficiency of the ordering policy and contract.

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    Pricing and Coordination Strategy of Product and Extended Warranty in Product Service Supply Chain
    KOU Jun a, b, ZHANG Xumei a, b, ZHOU Maosen a, b, DAN Bina, b
    2020, 29 (3):  601-607.  doi: 10.3969/j.issn.1005-2542.2020.03.020
    Abstract ( )   PDF (982KB) ( )  

    Focusing on the purchase choices of customers on extended warranty when their expectations on failure rate are different, a theoretical analysis model of a two level product service supply chain model is developed. Based on customer utility, the decision equilibriums of the supply chain is analyzed when the manufacturer provides the extended warranty while the retailer sells the product and extended the warranty simultaneously. A fixed-payment-and-profit-sharing contract is designed to help the manufacturer improve the service and compensate for the profit loss caused by the increase in service cost. The conclusions show that the contract can decrease the price of extended warranty service, improve service, and increase the profits of both the manufacturer and the retailer, thus coordinating the supply chain. The numerical analyses reveal the effect of service and fixed payment on the profits of the system and its members.

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    Logistics Scheme Selection Method Based on Cumulative Prospect Theory
    LI Yanlai, Ying Chengshuo
    2020, 29 (3):  608-615.  doi: 10.3969/j.issn.1005-2542.2020.03.021
    Abstract ( )   PDF (991KB) ( )  

    To effectively reflect decision makers’ aspirations and behaviors in the process of logistics scheme selection, an approach of logistics scheme selection based on the cumulative prospect theory and the multiple attribute decision making theory was proposed. First, psychological behavior factors of decision makers are considered, and the aspiration of decision makers with respect to each attribute was chosen as the corresponding reference. Next, decision matrixes with clear numbers, interval numbers, and linguistic assessment terms were transformed into the corresponding decision matrixes of gains or losses relative to the set references. Finally, the comprehensive prospect value of each scheme was calculated based on the cumulative prospect theory considering the different risk attitudes of decision makers to gains and losses, and a ranking of logistics scheme alternatives was determined based on the comprehensive prospect values obtained. An example was given to demonstrate the effectiveness and rationality of the approach proposed.

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