Table of Content

25 September 2020, Volume 29 Issue 9

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Theory Analysis and Methodology Study

Research on Order Batching Problem of Intelligent Warehouse System Based on AGV

LI Zhen-ping, FU Hong-ye, BU Xiao-qi, ZHANG Guo-wei, WU Ling-yun

2020, 29(9):  1-9.  DOI: 10.12005/orms.2020.0221

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The problem of order batching in parts-to-picker intelligent warehouse based on automatic guided vehicle(AGV)is studied. The costs of workers picking items from shelves and the costs of AGV transporting shelves are considered simultaneously. An integer programming model of order batching problem is established to minimize the total costs. Based on the items contained in each order and the shelves where the items of an order are stored, the weighted similarity is formulated to describe the relationship between orders. The positive correlation between weighted similarity and total picking cost is analyzed. Based on the weighted similarity between orders, a greedy algorithm for solving the model is designed. The simulation is done on a specific example. The sensitivity analysis of weighted coefficient is done. The influence of weighting coefficient change on batching results, and the relationship among the value of and the cost of λ worker picking one item c₁ and the cost of AGV moving one shelf c₂ are analyzed. The results show that the approximate optimal solution of the order batching problem can be obtained in a short time by using the greedy algorithm with appropriate weighting coefficient. For small scale examples, the approximate ratio is less than 1.35 in the worst case. Using the model and algorithm in this paper for order batching, two types of costs are considered at the same time, which can effectively improve the efficiency and reduce the total costs of order picking.

Research on Optimization Algorithm for Aircraft Routing Recovery Based on Multi-objectives Programming

HU Yu-zhen, ZHANG Song

2020, 29(9):  10-17.  DOI: 10.12005/orms.2020.0222

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This paper considers a multi-objective optimization problem of aircraft routing recovery under the disruption of single fleet multi-aircraft in one airport. Firstly, according to the common principles of practical airline flight rescheduling and basic ideas of airline disruption management, one multi-objective programming model is established based on connection network, and two objectives are listed according to their priorities. One is to minimize the maximal flight delay time and the other is to minimize the number of swapping aircraft respectively. Secondly, several optimization characters of the model are analyzed in accordance with the feathers of flight waves of the problem and combined with stratified sequencing method. And then one polynomial algorithm is designed based on quick sort algorithm and minimum cost path algorithm. Finally, a case study is given to illustrate the effectiveness of the algorithm. The outcome of this research could provide theoretical and practical supports for airlines to reduce flight delays.

Modelling and Optimization Algorithm for Bundling from Buyer’s Perspective in Procurement Auction

HUANG Xue-wen, SUN Rong, AI Ya-qing

2020, 29(9):  18-26.  DOI: 10.12005/orms.2020.0223

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Procurement auction plays an import role for sourcing items (products and/or services), which significantly affects the purchase performance. Literature on bundling from buyer’s perspective is quite scarce. Bundling from buyer’s perspective is the problem of determining a set of mutually exclusive bundles from the buyer perspective, which will induce competitive bidding behavior under the constraint that suppliers are required to bid on all the items in a bundle. In this paper, we present a buy-side perspective on bundling, by clarifying the definitions of the concepts of a bundle and a bundling solution, and introduce a 0-1 integer program optimization model, with the objective of minimizing the number of bundles in the bundling solution. The optimization model is proved to be NP-hard. For the sake of efficiently solving this problem, the model is first transformed into a traveling salesman problem and then solved using a genetic algorithm proposed in this paper. The performance of the proposed approach is compared with those of a traditional integer program solver and an existing bi-clustering approach. The experimental results show that the proposed approach can provide promising results in terms of a bundling solution and computing efficiency.

Optimization and Application of GM(1,1) Model Based on Initial Value and Background Value

LU Jie, LI Feng

2020, 29(9):  27-33.  DOI: 10.12005/orms.2020.0224

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In real life, the prediction accuracy of classical GM(1, 1) model is unstable, and most of the previous optimization methods are one-sided. In this paper, the background and initial values of classical GM(1, 1) model are improved, and a combined optimization method is proposed. According to the principle of dynamic optimization, the background value is set as a variable, and its parameters and time response formula are determined by the minimum value of MRE. At the same time, the difference equation is used to replace the static equation with x⁽¹⁾(1) as the fixed point.Initial and background values are taken as variables to systematically reduce model errors. Combining with the domestic annual oil consumption data, the classical GM(1, 1) model and the improved GM(1, 1) model are used to calculate and compare the errors, which proves that the improved model is significantly better than the classical model in accuracy.

Production Scheduling Optimization Method for Metal Mine Enterprises

MA Long, LU Cai-wu, GU Qing-hua

2020, 29(9):  34-42.  DOI: 10.12005/orms.2020.0225

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According to the problems of large unit costs of mining and transportation as well as deviated results at metal mining enterprises, firstly, depending on the principle of production scheduling for metal mining enterprises, the minimizing cost of ore mining and transportation is seen as optimization goal, and with an integer programming method, a mathematical model of metal mining enterprise production planning is constructed based on the goal of minimizing the cost of mining and transportation. Secondly, an improve quantum particle swarm optimization is proposed, to accurately and quickly solve the production scheduling model of metal mining enterprises, the inertial weights are dynamically adjusted by using the evolution speed and aggregation factor, and a search strategy of dual-layer feasible region is designed for improve local and global search capabilities of algorithm. Finally, we take a large-scale mining and transportation operations of metal mining enterprises as a case, and compare with the actual production indicators, non-linear programming results and results of particle swarm optimization. The results show that the algorithm in this paper is superior to the other two optimization methods under the same economic index and parameters, and the mining and transportation unit costs per ton ore is reduced by about 0.05 yuan, which improves the overall economic profits of metal mining enterprises.

Study on Public Evacuation Mode of Emergency Planning Zone

QI Wen-hui, QI Ming-liang

2020, 29(9):  43-52.  DOI: 10.12005/orms.2020.0226

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Public evacuation is an important safety measure in the emergency response status of the Emergency Planning Zone. The model of “government organizing evacuation+self-evacuation under the guidance of the government” is proposed. Based on the theory of cell transmission, the paper establishes a public evacuation model with the goal of minimizing the evacuation time, and plans the vehicle travel route. This model is used to analyze the change law of the ratio of government organizing evacuation and self-evacuation. The results show: evacuation time of the “government organizing evacuation+self-evacuation under the guidance of the government” model is less than that of the “government organizing evacuation” model, and there is an optimal proportional structure between the government organizing evacuation and self-evacuation, which makes the total evacuation time reach a satisfactory level.

Reliable Emergency Facility Location with Disruptionand Fortification Considerations

YU Dong-mei, GAO Lei-fu, ZHAO Shi-jie

2020, 29(9):  53-61.  DOI: 10.12005/orms.2020.0227

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In order to improve the reliability and ability to withstand disruption risk of emergency facility, reliable facility location-allocation design under disruptions is studied. Expanding the uncapacitated fixed-charge location problem, we present a bi-objective location optimal model for designing of reliable distribution networks from the perspective of preventing facilities disruption and improving service quality. The objective of the optimization model is to minimize the total facility establishment cost and the total transportation cost associated with satisfying all customers’ demands, and to maximize coverage of quality of service levels. The model considers heterogenous facility failure probabilities and facility fortification within a finite budget. Non-dominated sorting genetic algorithm Ⅱ(NSGA-II)is proposed to solve the model, a pareto front solution set can be obtained by the algorithm. We verify the feasibility of the model and algorithm via numerical experiments. Through the sensitivity analysis of different disruptions probability, the distribution of pareto optimal set and the topology of emergency facility location network are given. The research results will provide decision support for decision-makers to design a reliable location network under disruption environment.

Research on Flood Disaster Emergency Management Based on Two-stage Mixed Integer Programming Model

ZHANG Qing, YU Miao

2020, 29(9):  62-69.  DOI: 10.12005/orms.2020.0228

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On the background of flood disasters, this paper considers various emergency supplies, the uncertainty of disaster events and the multiple otjectives of emergency response, combining the emergency preparation with the emergency response, and establishes a two stages bi-objective mixed integer programming model under a certain maximum rescue time. The first objective of the model is to minimize the expectation of penalty due to supply shortage and the loss owing to distribution delay in the emergency response stage under different disaster scenarios. The second objective is to minimize the total cost of the two stages. The model ensures the timely and effective response to flood disaster and the equity of supply distribution.In this paper, a multi-objective genetic algorithm is developed to solve the model and the pareto-optimal decision schemes are obtained at any maximum rescue time within the range of four to nine, which well satisfies the different needs of the decision maker. Finally, the paper suggests that the optimal maximum rescue time can be set to 5.7 from the trend in our case.

Interval Type-2 Fuzzy Muti-criteria Decision Making Method Based on Fuzzy Measures and Cumulative Prospect Theory

LIU Chao, TANG Guo-lin, LIU Pei-de

2020, 29(9):  70-81.  DOI: 10.12005/orms.2020.0229

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For risk muti-criteria decision making problems with interactive condition and interval type-2 fuzzyinformation, an interval type-2 fuzzy decision making method is proposed based on fuzzy measures theory and cumulative prospect theory. Firstly, in order to globally consider the interactions among the criteria, this paper proposes the Shapley interval type-2 fuzzy Choquet operator. Meanwhile, some desirable properties of this operator are studied. Then, to capture the diversities of risk attitudes and sensitivities among experts with limited relational behaviors, this paper defines the prospect effect and the prospect value function of interval type-2 fuzzy number, and proposes the cumulative prospect Shapley interval type-2 fuzzy Choquet operator. In addition, based on the defined bidirectional projection measures of interval type-2 fuzzy sets and the Shapley function, the models for the optimal fuzzy measures on a criteria set are established. After that, an approach to muti-criteria decision making with interaction condition, experts’ risk preference and incomplete weight information under interval type-2 fuzzy environment is developed. Finally, a practical example regarding risk investment is provided to demonstrate the applicability and validity of the developed approach.

Differential Game Study of Industrial Cluster Synergetic Innovation Knowledge Sharing Strategy

MA Yong-hong, LIU Hai-jiao, LIU Qing

2020, 29(9):  82-88.  DOI: 10.12005/orms.2020.0230

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According to the knowledge sharing question of core enterprises and supporting enterprises in industrial cluster synergetic innovation, it analyses separately the knowledge sharing strategies of core enterprises and supporting enterprises in the case of three different knowledge sharing games using the HJB equation by constructing the differential game model. Comparing the three kinds of games analysis results, we find that: in the case of Stackelberg game, knowledge sharing input subsidy as a kind of incentive strategy can promote the knowledge sharing desire of supporting enterprises, the knowledge sharing revenue of each side and the total revenue of both sides are better than Nash game. In the case of cooperative game, the knowledge sharing desire, knowledge sharing revenue of each side and the total revenue of both sides are better than the non cooperative case. There is a threshold in the revenue distribution level coefficient, the Pareto optimality of both individual revenue can be achieved. Finally, the results of theoretical derivation are verified by numerical examples.

Cooperative Stability Analysis of Franchise Express Based on Evolutionary Game Theory

WAN Xiao-yu, JIANG Ting

2020, 29(9):  89-100.  DOI: 10.12005/orms.2020.0231

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The instability of the cooperation between the two parties is caused by the low service quality of the franchisees, their own affairs, the weak headquarters management and so on. Based on the evolutionary game model as the main theoretical tool, this paper develops an interactive evolutionary game system for expressing the behavior of company headquarters and affiliates under incomplete information.By solving Jacobian matrix, the influence of the change of initial conditions and decision parameters on the evolutionary stability results is revealed. Then, taking Stoexpress as an example, the numerical simulation is carried out by using MATLAB software. The results show that the system presents three evolutionary stable results and a periodic stochastic state when franchisors cooperate actively, and when the revenue, the fines, the degree of information asymmetry and the cost of supervision are located in different thresholds. Meanwhile, it is found that the unit price has a positive effect on the cooperation stability of the two parties. Finallyreducing the service cost of express franchisees and improving the quality of service, establishing a moderate penalty system for breach of contract and improving the profitdistribution mechanism, strengthening the information sharing of the platform and promoting the transparency of information, and creating a good competitive atmosphere and avoiding unnecessary price warfare will help guide the evolution of the system to the ideal state.

Analysis of Sequential Innovation Decisions: from the Perspective of Patent Policy

FANG Wen-li, FANG Shi-jian

2020, 29(9):  101-105.  DOI: 10.12005/orms.2020.0232

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When innovation is sequential, early innovators have the exclusive right to use their technology because of patent policy, so they may hold up the later ones. Under complete information, licensing before R&D may avoid holdup but fail under incomplete information. We provide a model when the development cost or value is private information, with which we analyze the innovators’ decision, give the conditions under which holdup occurs and its probability, and point out the optimal patent policy.

Impact of Different Game Power Structures on the Manufacturer Dual-channel Supply Chain

SUN Zi-lai, WANG Xu-ping, RUAN Jun-hu, FAN Wen-ping

2020, 29(9):  106-114.  DOI: 10.12005/orms.2020.0233

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Considering a supply chain composed of a manufacturer with both an offline traditional channel and an online direct channel and a retailer, a dual-channel demand function for the manufacturer is established based on the theory of consumer surplus. Then, it analyzes the impact of three power structures on supply chain participants’ pricing decisions, demands, and profits through constructing the manufacturer Stackelberg game, retailer Stackelberg game and Nash game models. The results show that the three games are shown to have no effect on manufacturer’s online direct channel price; the impacts of the two Stackelberg games on the retail price and the demand of the offline traditional channel, manufacturer’s online direct channel demands and supply chain’s total profits are identical. In Nash game, the offline channel retailer’s price and manufacturer’s online direct channel demands are the minimum, however, the offline channel retailer’s demands and supply chain’s total profits are the maximum. The manufacturer’s wholesale price and profits and the retailer’s profits decrease with the decline of the game dominance in the three games.

RevenueAllocationfor Cooperative Innovation Based on Relative Risk in Cluster Supply Chain

LV Pu, MA Ke-xin

2020, 29(9):  115-123.  DOI: 10.12005/orms.2020.0234

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Cooperative innovation is an important means for cluster supply chain enterprises to research and develop new technologies and product upgrades. However, there is a risk of collaborative innovation. Due to the difference in risk tolerance of supporting enterprises and core enterprises in the cluster supply chain, the actual risks they bear when facing the same innovation risks are different. To solve this problem, in this paper, we build a collaborative innovation game model between supporting enterprise and core enterprise, design a revenue allocation based on relative risk sharing, and compare it with existing distribution methods.The research shows that the allocation mechanism based on relative risk sharing can not only enhance the willingness of both enterprises to participate in collaborative innovation, but also make the profits obtained by the enterprise more closely matching the risksundertaken, and achieve the purpose of encouraging the supporting enterprises to invest in innovation.

Study of Supply Chain Financing Mode under Stochastic Market Demand

YAN Ru-zhen, LI Ran, GAO Wei, WU Xu

2020, 29(9):  124-130.  DOI: 10.12005/orms.2020.0235

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The most traditional financing models only consider the internal financing and external financing under the linear market demand. This paper considers trade credit, debt and equity financing strategies, and studies a two-echelon supply chain consisting of a supplier and two capital shortage retailers under the stochastic demand. This paper also evaluates the impact of equity financing ratio, trade credit, stochastic demand on the financing decisions with SMEs, and formulates a financing model based on the stochastic demand to characterize the decision of retailer.    Further, we carry out numerical examples and sensitivity analyses with respect to these critical factors, when the proportion of debt financing is less than a certain threshold, the optimal order quantity of the retailer adopting the external financing mode is greater than the internal financing mode, and vice versa. When the market demand distribution function is greater than a certain threshold, the proportion of the debt financing is negatively correlated with the order quantity. Which indicates that, when the retailer adopts external financing in supply chain, a higher proportion of debt financing means a higher profit. In a situation, where the retailer has access to trade credit, we find that as interest rate of trade credit increases, the profit of retailer decreases. The relevant conclusions are fundamental to the choice of financing strategies for SMEs in the future.

Characteristic Test Method of Matrix Grey Incidence Degree and Its Application

LIU Zhen, XIE Yu-mei, DANG Yao-guo

2020, 29(9):  131-138.  DOI: 10.12005/orms.2020.0236

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In view of the shortcomings of the existing grey incidence theory, this paper puts forward the idea of characteristic test for grey incidence degree, and constructs the characteristic test method of matrix grey incidence degree. First, the matrix grey incidence model is optimized. The characteristic difference matrix is defined by the difference of behavior matrix, and the matrix 2 norm is used to construct the incidence degree formula. Then, the stability and trend of characteristic difference matrix are analyzed. The stability coefficient is constructed in the form of variation coefficient, and the trend coefficients are estimated by the least square method. These two coefficients together constitute the characteristic test method of matrix grey incidence degree. Finally, the model is applied to the chronic multidimensional poverty analysis of Enshi Prefecture in Hubei Province. Compared with the existing model, it is found that the evaluation results of correlation degree effectively distinguish the poverty situation of 8 cities and counties in Enshi Prefecture. The characteristic test method complements the results from two aspects of poverty uncertainty and trend. The feasibility and practicability of the model are verified.

Research on Marshall-Lerner Condition in China Under the Influence of Trump’s Policies

GUO Rong, WANG Yu, ZHAI Xin-yao, QIU Yong-qin

2020, 29(9):  139-148.  DOI: 10.12005/orms.2020.0237

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Sino-US trade relations have become more and more tense after Trump took office. In the new round of great power game, the RMB exchange rate remains the focus of debate between the two sides. However, the impact of the depreciation of the RMB on the trade balance should also take into account the changes in Marshall-Lerner condition. Based on the traditional definition of the point elasticity, the trade balance equation arc elasticity and the improved point elasticity, and combining the theoretical policy mechanism analysis, this paper calculates the Marshall-Lerner condition. Using the monthly data of 2005.7~2017.12 and the Bayesian-VAR model , we empirically test the impact of the trump’s policies on the bilateral Marshall-Lerner condition between China and the United States.The results find that: (1)Sino-US bilateral Marshall-Lerner condition is established. (2)Trump’s policies of withdrawing from TPP and reducing domestic corporate taxation have a positive impact on Marshall-Lerner condition, while strengthening China’s investment regulation over the US has a negative impact on Marshall-Lerner condition. In the robustness test, withdrawing from TPP and investmentsupervision policies are still valid. (3)The Trump policies have a short-term improvement effect on China’s Marshall-Lerner condition. Under this condition, the short-term depreciation of the RMB exchange rate is conducive to promoting trade surplus but is not sustainable in the long run. The “fair and open” trade policy, which is vigorously promoted by China recently, will effectively improve current accounts, boost economic fundamentals, and maintain long-term stability of the exchange rate.

Application Research

The Application of Improved Whale Optimization Algorithm in Power Load Dispatching

XU Jian-zhong, YAN Fu

2020, 29(9):  149-159.  DOI: 10.12005/orms.2020.0238

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To improve global optimization performance of the whale optimization algorithm (WOA), an improved WOA based on the golden section search algorithm, called GWOA, is proposed. Firstly, the golden section algorithm is adopted in the algorithm to initiate the individuals’ position so as to enable the possibility of the initial population close to the global optimal solution. Secondly, the variable interval, which is formed by the process of golden section search, is introduced for non-uniform mutation operation, and this method improves the capacity of jumping out local optimum trap and enhances the diversity of particle. The proposed algorithm is first applied to 15 test functions and the experimental results show that the proposed algorithm has considerably improvement in solution precision and optimum efficiency and so on, and then, the simulation results of the power optimal load dispatch problems also show that the GWOA has good convergence property and better in quality of solution than other algorithms reported in recent literature.

Empirical Research of PLF. Sets and Its High Quality Simulation Application

LIU yu-cheng, WANG Chuan-sheng, YANG lu-xin, Richard. Ding

2020, 29(9):  160-169.  DOI: 10.12005/orms.2020.0239

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In order to simulate the migration and evolution of urban population with high efficiency and high quality, this paper introduces the concepts of oppositional negation, mediation negation and contradictory negation in philosophical negation and computer logic. After repeatedly studying and demonstrating the internal relations, basic characteristics and integration conditions of the three logical negations, the paper innovatively proposes the PLF. sets of universal logic fuzzy sets, which can form the evaluation factor sets of various logic variables and their evolution forms that can be directly involved in the calculation. On the premise of verifying the feasibility of its operation rules and logical transformation through saturation, the PLF. sets can be used to construct the global membership function f(x) with good approximation performance by using the known local membership function g(x). It can map any x(x∈U) to the value of f(x) within the defined range U[a, b]. At the same time, the logic simplifies the complexity calculation of the system function. The empirical research results of the PLF. sets in the teaching quality evaluation of management information system fully prove that the PLF. sets method can change the complex into simple, and simplify the operation methods and steps. It shows the characteristics of universality, high efficiency, accuracy and simplicity. The application of the PLF. sets method in the simulation of Beijing urban population migration and evolution trend shows that: 1.The positioning of net added value of Beijing urban population movement changes is all at the level of “big”; 2.The qualitative grade of Beijing urban population mobility network and its correlation degree is “high”. Finally, it evaluates the population flow pattern, population migration and evolution trend of the cities which are positive migration with high quality.

Capacity Allocation Policy for Car Rental Systems with Customer Behavior Consideration

ZHANG Li-feng, MU Yin-ping

2020, 29(9):  170-178.  DOI: 10.12005/orms.2020.0240

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With the development of the Internet of Things, the rental company can monitor customers’ behavior in time by intelligent technology. An increasing number of car rental companies are motivated to design a subsidy policy to encourage customers to maintain good behavior in the rental process. Taking rental prices as a function of customer behavior, a dynamic programming model has been constructed to analyze the capacity allocation policy and subsidy policy under multi-period and-product. Because of the highly dimension of the state variable, it is difficult to solve the problem. We have proposed two approximation algorithms to solve this problem and testified the properties of the model. After considering the transfer of customer behavior, the results about capacity allocation, upgrade mechanism and subsidy policies are as follows: The capacity control policy depends on opportunity cost. The upgrade mechanism is in accordance with the hierarchy of the product and the upgrade strategy is upgraded in sequence. An increase in subsidy will not decrease the expected revenue under certain conditions. Thus, an appropriate subsidy strategy can raise the revenue of the company.

Dynamic Pricing Strategy for Perishable Products in Competitive Markets with Customer Inertia

HOU Fu-jun, ZHAI Yu-bing, HU Yu-sheng

2020, 29(9):  179-185.  DOI: 10.12005/orms.2020.0241

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Revenue management is deeply influenced by the behavioral tendency of consumers’ purchasing decision. In this paper, the influence of customer inertia, that is to say, the irrational delay tendency of customer purchasing decision, is considered in the dynamic pricing of competitive enterprises. In the multi-enterprise multi-period game, it is proved that there is a unique pure strategic Nash equilibrium in each sales period under the condition of sufficient inventory. Numerical simulation shows that customer inertia has a negative impact on the optimal pricing and the maximum expected revenue of the enterprises, and the situation is worse for the enterprise selling low-quality product. In addition, the marginal effect of the inertia width increases, while for the inertia depth, it decreases.

Research into Incentive Strategy of Third-party B2B Platform Based on Risk Aversion of Banks

YU Jing, ZHUANG Xin-tian

2020, 29(9):  186-195.  DOI: 10.12005/orms.2020.0242

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Taking electronic warehouse receipt financing as an example, which is based on bank’s downside risk aversion, this paper applies the principal-agent theory to study the incentive strategy design of banks for B2B platforms when B2B platforms have hidden moral risks under the joint credit mode and the entrusted credit mode. The study finds that the optimal effort level of B2B platform decreases with the increase of income distribution ratio and repurchase ratio, and increases with the increase of pledge rate, loan interest rate, product purchase quantity and loss compensation ratio. At the same time, in order to avoid default risks, banks need to set the upper limit of pledge rate, loan interest rate and loan amount and the lower limit of repurchase ratio. What’s more, the bank’s optimal income distribution ratio is positively correlated with the loss compensation ratio, and the optimal loss compensation ratio is also positively correlated with the loan loss rate. In addition, with the improvement of working efficiency of B2B platform, the optimal income distribution ratio will be reduced and the optimal loss compensation ratio will be increased under the joint credit mode, and finally the optimal loss compensation ratio will be similar to the optimal loss compensation ratio which is under the entrusted credit mode. At last, a numerical analysis is given.

Industry-level Asymmetry Volatility Spillover Effects in Chinese Stock Market ——Based on Good Volatility and Bad Volatility Anlysis

LIU Jing-yi, LI Tong, JIAN Zhi-hong

2020, 29(9):  196-203.  DOI: 10.12005/orms.2020.0243

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This paper is based on the 5-minute high-frequency data of the Shanghai Stock Exchange Series Industry Index, using the generalized forecast error variance decomposition, the volatility spillover index and spillover asymmetry measure (SAM) to study the time-varying property and asymmetry of inter-industry volatility spillover in Chinese stock market. The empirical results show that there are significant asymmetry and time-varying characteristics of inter-industry volatility spillovers and bad volatility spillover dominates in most periods. What’s more, static analysis shows that there is significant volatility spillover effect among different sectors of theChinese stock market, and the consumer discretionary is the most important source of market volatility; dynamic analysis shows that raw materials, industrials and consumer discretionary are the net exporters of market volatility spillover, and the financial and real estate business is the net importer of market volatility spillover; telecommunication services, utilities and health care et al. are more effective in delivering bad news, while consumer discretionary is more powerful in good news. The dynamic comparison of the spillover contribution of various industries before and after the S & P 500 index shows that the research conclusions are robust.

Management Science

Research on the Comprehensive Integration of Military Facility Construction Project Management

SHI Yue, ZHANG Jiang-shui, SUN Tao, ZHAO Bo, ZHI Peng-yu

2020, 29(9):  204-207.  DOI: 10.12005/orms.2020.0244

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Engineering construction project is an important component of the construction of military facilities and has a far-reaching impact on the construction and development of our army. This paper takes the project management integration of military facilities construction of our army as the research object, and comprehensively considers the dynamic influence relationship of project cost, schedule, quality and safety. We carry out comprehensive and integrated management on the whole process of the project life cycle, including the overall planning stage, the planning control stage, the survey and design stage, the construction stage and the tracking management stage. The main methods that can be applied to the integrated management of military construction projects are put forward and the process of military construction project management is optimized.

Impact of Platform Cooperation Mode on Profit of Taxi Company

YANG Tong, WU Jiang-ning

2020, 29(9):  208-217.  DOI: 10.12005/orms.2020.0245

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By building a mixed Salop circle city model, this work analyzes two modes of taxi company in oligopoly taxi industry involving ride-sourcing services companies for increasing profits. As the online platform of ride-sourcing services companies leads to effectiveness and efficiency, the paper considers two kinds of platform cooperation modes including Information Sharing mode(IS)and Joint Action mode(JA). Ride-sourcing services companies share platform with taxi company for money under IS. The probabilistic service is provided to passengers by both ride-sourcing services companies and taxi company through the platform under JA, but taxi company does not have to pay. This work indicates that two platform cooperation modes can lead to increased profits of taxi company as well as the profits over the industry. Meanwhile, ride-sourcing services companies can always receive more profits under JA, but receive more profits under IS only if the transaction fee is satisfied. The paper discusses the operation effectiveness forboth taxi company and ride-sourcing services companies. When comparing two cooperation modes, this work concludes that JA outperforms IS when the relative operationeffectiveness of taxi company is high.

Model and Method for Traffic Demand Management with Parking Controlled on Bimodal Network

LIU Bing-quan, DU Wei

2020, 29(9):  218-223.  DOI: 10.12005/orms.2020.0246

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On a bimodal transportation network with auto and rail travel modes, reasonable parking capacity design of travel destination can optimize the use of private cars and migrate the travelers onto public transport system. The paper proposes a model of traffic demand management with the environmental capacity and parking constraints on the bimodal network and takes the destination parking pricing into account. Adopting a binary Logit model for the mode split and stochastic user equilibrium for the route-choice of car traveler, a fixed-point model is formulated under the constraint of destination demand. Taking the fixed-point model as a constraint, the model of traffic demand management is thus established as a mathematical programming with equilibrium constraints model. To solve the model, a sensitivity analysis method is presented by obtaining the gradient of link flow and destination demand to parking capacity fluctuation. The influence of parking charge on the variation trend of each index in the model is analyzed and the algorithm is also numerically validated by a network example.

Rebate Research of Company Considering the Existence of Social Influence

NIE Jia-jia, WANG Qi-jun, DING Long

2020, 29(9):  224-231.  DOI: 10.12005/orms.2020.0247

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This paper studies rebate strategies of company under the existence of social influence. Considering the continuity of the rebate in reality, the paper builds four kinds of modes including early rebate, later rebate, always rebate and never rebate via Hotelling model and analysis of the company’s choice of these four kinds rebate under monopoly and competition situation respectively. The results show that a little rebate would encourage companies to choose early rebate strategy in the case of monopoly, whereas too much rebate would push company to give up rebate. But in the case of duopoly, there will be three possible kinds of equilibrium. In addition, the two companies adopt differentiation rebate strategy in equilibrium if competition between them is intense, while they adopt the same rebate strategy if the competition is mitigated. Besides, although the fact that both of them choose the latter rebate strategy never happens in equilibrium, it still the most profitable condition in some situation.

Reputation Incentive Model of Open Service Innovation in Service-Oriented Manufacturing Enterprise

HE Zheng, ZHANG Zhi-zhao, LI Bo

2020, 29(9):  232-239.  DOI: 10.12005/orms.2020.0248

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In the process of open service innovation in service-oriented manufacturing enterprise, in order to encourage cooperative enterprise to participate in service innovation, the fairness theory is introduced into the design of reputation incentive mechanism. The cooperative enterprise’s fairness preference degree, service innovation capability coefficient, knowledge transfer capability coefficient, patient coefficient and other parameters are considered, and the reputation incentive model is established by principal-agent theory, and the model is solved and the numerical simulation is carried out. The corresponding research conclusions and management enlightenment are obtained. The study shows: when the cooperative enterprise is risk averse, in the case of complete information, the fairness preference coefficient of cooperative enterprise is positively correlated to reputation incentive coefficient; in the case of incomplete information, the influence of cooperative enterprise’s fairness preference coefficient on reputation incentive coefficient is not significant; whether or not we consider the fairness preference of cooperative enterprise, the cooperative enterprise’s effort level, service innovation capability coefficient, knowledge transfer capability coefficient and patient coefficient are positively correlated to reputation incentive coefficient; the cooperative enterprise’s effort cost coefficient, risk aversion coefficient, output sharing coefficient, external environment variable variance are negatively correlated to reputation incentive coefficient.