Table of Content

25 November 2021, Volume 30 Issue 11

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Theory Analysis and Methodology Study

Research on Multi-attribute Group Decision-making Method Based on Evidence Theory and Vague Sets

CUI Chun-sheng, CAO Yan-li, QIU Chuang-chuang, GUO Yu-jie, WANG Mei-qi, ZANG Zhen-chun

2021, 30(11):  1-5.  DOI: 10.12005/orms.2021.0341

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In order to solve the problem of difficult decision-making in complex environments, a multi-attribute group decision-making method based on Vague sets and evidence theory is proposed. Vague sets have the advantage of describing uncertain information. Evidence theory can fuse the information of Vague sets. Firstly, after considering the credibility of expert evaluation information, this paper uses evidence theory to fuse the evaluation information of expert set under the analysis of mathematical relationship between Vague sets and evidence theory. Secondly, the weight of every attribute can be obtained through the use of score function and the Vague evaluation value of every solution under all attributes can be corrected through weighted average algorithm. Then, evidence theory is used to fuse the evaluation information of attribute set. Thirdly, the optimal solution is determined according to the score of every solution obtained from the score function. Finally, an example is used to further illustrate the feasibility and effectiveness of the proposed method. The decision-makers can make decisions rationally and select the optimal solution through the algorithm given in the paper.

Study on Green Production Decision of Heterogeneous Power Generators under Renewable Portfolio Standards

SHANG Bo, HUANG Tao-zhen

2021, 30(11):  6-13.  DOI: 10.12005/orms.2021.0342

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The game decision model of green production under three different market power structures of power generators are constructed based on the latest policy background of renewable portfolio standards. The influence of sensitive parameters on the decision results of the heterogeneous power generators is emphatically discussed, and the optimal decision effects of different game structures are analyzed based on parameter range. We identify the optimal market structure of decision-making effect under the optimal parameter range. The results indicate that, when the transaction price of green certificates and minimum quota ratio exceed the minimum critical value, green generators can achieve the market competitive advantage of optimal output and maximum profit, but?it has a significant “crowding out” effect on the maximum profit of conventional generators. If tradable green certificates price and the price elasticity coefficient of demand are within the optimal and reasonable range, then traditional and green generators can not only achieve the optimal decision-making effect, but also maximize the monotonous increase of social welfare utility, that is, there exists an optimal market decision structure dominated by green generators, but there is no optimal Nash decision structure.

Multi-Objective Optimization Model and Algorithm of Financing Decision for the Exporting Offshore Inventory

SONG Yun-ting, YU An-qi, WU Di, ZHAO Wei-jie, TIAN Xi-huan

2021, 30(11):  14-18.  DOI: 10.12005/orms.2021.0343

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The decision-making of credit line allocation is an important issue in the exporting offshore/in-transit inventory financing business. In order to weigh the risks and benefits in this business, the paper comprehensively considers the political risks, risk value constraints and credit risks of exporting countries, and constructs an optimization model aiming at the highest income and the lowest risk. According to the characteristics of the model, a hybrid algorithm combining simulated annealing and NSGA-II algorithm is proposed to solve the model. Finally, taking the common 1-5-month pledge period as an example, the applicability and effectiveness of this method are verified.

Dynamic Vehicle Routing Problem with Inventory Synergetic

XUE Gui-qin, WANG Zheng

2021, 30(11):  19-25.  DOI: 10.12005/orms.2021.0344

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With the continuous deepening of internet commercial iteration, more and more companies tend to resolve the contradiction between distribution distance and timeliness of distribution from the perspective of putting forward commodity. Therefore, based on the dynamic vehicle scheduling problem with inventory synergetic customer (DVRP-ISC), this paper designs the method of selecting the customer of the coordinated sub-warehouse with the characteristics of regional division, and establishes the multi-stage dynamic distribution network optimization model. In view of the particularity of the research problem, a multi-stage two-level network collaborative distribution path optimization algorithm is designed. Finally, the model, algorithm performance, and their scalability are verified by simulating examples, and the customized and benchmark examples.

Open Vehicle Routing Problem Based on Joint Distribution Mode under Time-dependent Road Networks

LIU Chang-shi, WANG Song, LUO Liang, DENG Sheng-qian

2021, 30(11):  26-33.  DOI: 10.12005/orms.2021.0345

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The multi-depot vehicle routing problem based on joint distribution mode in urban logistics system is studied. A multi-depot processing method is proposed in order to share all logistics resources. A calculating method for the road travel time is designed based on the time-dependent characteristics of urban road network. A mathematical model for the open time-dependent vehicle routing problem based on joint distribution mode is formulated by considering customer demand, time window, flexible vehicle departure time, fuel consumption, carbon emissions, and joint distribution mode. The objective of the model is to minimize total cost. An improved ant colony algorithm is designed to solve the problem. The experimental results verify the feasibility and validity of the proposed approaches.

The Research on Design of Score Function for Improving Ability of Ranking Intuitionistic Fuzzy Set

TAO Xi-wen, JIANG Wen-qi

2021, 30(11):  34-39.  DOI: 10.12005/orms.2021.0346

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For the problem of multi-criterion decision making, score function's ability of ranking intuitionistic fuzzy set is a significant factor, which influences the performance of decision making. Starting with the analysis of intuitionistic fuzzy set score functions' properties, we analyze the boundedness, consistent with intuition, ranking ability and continuity of existing score functions. Then, based on the situation of existing score functions' satisfying properties above, a new score function with piecewise form is proposed, which proves to satisfy all properties. Finally, the ranking ability and distinction degree of the new score function and the existing ones are compared in order to show the advantage and validity of the approach.

Analysis of Heterogeneous Information Customer Behavior in M/M/1 Queueing Systems with N-policy

MA Qing-qing, LIU Wei-qi, LI Ji-hong

2021, 30(11):  40-46.  DOI: 10.12005/orms.2021.0347

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This study considers the strategy of heterogeneous information customer and the optimal social welfare in an M/M/1 queue with N-policy. The arriving customers are divided into two types. Customers of Type I have all the information of the system, knowing the server state and the queue length upon arrival; customers of Type II have no information of the system, knowing neither the server state nor the queue length upon arrival. Using Particle Swarm Optimization Algorithm, the customer optimal strategic behavior is illustrated. The results indicate that the optimal social welfare decreases with N, but increases with v and ρ. Besides, the larger the proportion of customers of Type I, the higher the social welfare.

Study on the Coordination of Supply Chain Based on Carbon Trading Mechanism Considering the Competition and Asymmetry Information

LI Xiao-yan, WANG Dao-ping

2021, 30(11):  47-52.  DOI: 10.12005/orms.2021.0348

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In this paper, under the carbon trading mechanism, considering that there is competition among manufacturers and the cost coefficient of emission reduction is the private information of low-carbon manufacturer, supply chain models under the condition of information symmetry and asymmetry are constructed respectively to make decisions on emission reduction rate and product sales price of low-carbon manufacturer. By introducing a joint contract which consists of wholesale price and cost sharing, the low-carbon manufacturer is encouraged to transfer the real information of emission reduction cost, sensitivity analysis of carbon trading price and emission reduction cost coefficient is carried out through calculation examples. The results show that the introduction of joint contract can make the profit of supply chain under asymmetric information reach the level of centralized decision. The increase in carbon trading price will encourage manufacturers to reduce emissions actively, reduce total carbon emissions and improve the profits of supply chain. The lowering of emission reduction cost coefficient of low-carbon manufacturer is conducive to reducing carbon emissions, increasing product market demand and realizing profit growth of supply chain.

Two-stage DEA Cross-efficiency Evaluation Model Based on Prospect Theory

WU Hui, ANG Sheng, YANG Feng

2021, 30(11):  53-59.  DOI: 10.12005/orms.2021.0349

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Existing researches assume that the decision makers are completely rational and ignore the influence of decision makers' psychological factors on the evaluation, when addressing the non-uniqueness issue of the cross-efficiency for two-stage systems. This study uses the average value to construct new references for two-stage systems, and then proposes a two-stage DEA cross-efficiency model based on prospect theory in both the centralized and the decentralized decision-making environments. An example illustrates the applicability and effectiveness of the proposed method.

Analysis of Resource Allocation Efficiency of Primary Education in China Based on Parallel Structure DEA Model

LI Yong-jun, JIANG Ying

2021, 30(11):  60-64.  DOI: 10.12005/orms.2021.0350

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Primary education is the foundation of the education stage and part of our compulsory education. However, how to improve the efficiency of resource allocation in primary education in each province is a question worth considering when the gender ratios of the provinces are quite different. In order to avoid the large difference in gender ratio between male and female populations in different provinces which may affect the evaluation of the efficiency of the allocation of primary education resources, the parallel structure DEA model can be used to treat student gender as two different parallel subsystems to measure the resource allocation of primary education in China's provinces during 2012~2018. The study finds that the total system efficiency of primary education resource allocation in most provinces has not reached the effective boundary, and there is still room for improvement. The efficiency of male students in primary education is usually better than that of female students in primary education. However, with the improvement of education system in recent years, the efficiency of female students in primary education is on the rise. In addition, the efficiency of primary education resource allocation in western China is generally better than that in eastern and central regions in some years, but the efficiency of the overall primary education system in the central and eastern regions is relatively stable, while the efficiency of the primary education system in the western region fluctuates greatly.

Location Optimization of Rural Primary Schools Under Uncertain Condition

CHEN Yu-long, LAI Zhi-zhu

2021, 30(11):  65-70.  DOI: 10.12005/orms.2021.0351

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The scientific site selection of schools is an important way to optimize the allocation of educational resources, improve the efficiency of running schools and realize the balanced development of education, especially for rural areas. Many scholars have studied the location problem of schools, but most of them have neglected the impact of transportation network conditions on the location of schools and the time cost differences caused by different travel speeds under different road conditions. On the basis of previous studies, this study considers the impact of traffic network on the optimization location of primary schools in rural areas. The object of this study is to minimize the total transportation costs for students, construction costs for new schools, construction and upgrade costs for roads on a traffic network with travel time uncertainty indicated by different travel time scenarios. A mixed integer programming model for this problem is proposed. Furthermore, a hybrid simulated annealing algorithm is used to solve the problem. Finally, a practical case study is presented in detail to illustrate the application of the proposed mathematical model.

A Knowledge Points Labeling Method for Test Questions Based on Bipartite Graph

GUO Chong-hui, XING Xiao-yu, WEI Wei

2021, 30(11):  71-75.  DOI: 10.12005/orms.2021.0352

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Aiming at the problem of knowledge points labeling for test questions in online education, a bipartite graph-based method is proposed for knowledge points labeling in this paper. Firstly, considering the problem that the granularity of knowledge points is fuzzy, the knowledge graph of knowledge points is constructed to integrate knowledge points. Secondly, based on the corpus of textbooks and test questions, we extract the knowledge points bipartite graph as well as the test questions bipartite graph, calculate the weights of edges by the TF-IDF to construct a bipartite graph model between knowledge points and test questions. Besides, similarity measurement method based on term frequency weighting is used to calculate the similarity between questions and knowledge points, marking the knowledge points with the highest similarity to the test questions. Finally, the high school history test questions on the online education platform are used as the experimental data sets.The experiments and analysis show that the proposed method is obviously superior to classical machine learning methods such as Naive Bayes, K-Nearest Neighbor, Random Forest and Support Vector Machines.

An Improved Cuckoo Algorithm for Distributed Flexible Flow-shop Scheduling Problem with Transport Time Consideration

TANG Hong-tao, LIU Jia-yi

2021, 30(11):  76-83.  DOI: 10.12005/orms.2021.0353

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Considering the transport time among adjacent operations, a distributed flexible flow-shop scheduling model to minimize the maximum completion time is proposed by analyzing the characteristics of actual enterprise production situation under the distributed multi-shop manufacturing environment,and an improved cuckoo algorithm is presented to solve this model. Athree-layer encoding scheme based on operation, factory and machine is designed, a hybrid population initialization strategy is proposed to improve the quality of population in terms of the characteristic of this problem, a search operator of cuckoo is modified for solving the proposed model and a population evolution strategy is designed to enhance the rate of convergence and the quality of solution. At the last,asimulationexperiment is carried out to verify the effectiveness and superiority of the algorithm by comparing others.

A Multi-strategy Guided Electromagnetic Field Optimization Algorithm for Job Shop Scheduling

CHEN Bin, MA Liang, LIU Yong

2021, 30(11):  84-91.  DOI: 10.12005/orms.2021.0354

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The electromagnetic field optimization algorithm is a relatively novel swarm intelligence optimization algorithm, which uses the repulsive force generated by electromagnetic fields of different polarities to move the electromagnetic particles toward the optimal solution. Aimed at the problems of the standard electromagnetic field optimization algorithm easy to fall into local extreme points and poor convergence accuracy while solving the job shop scheduling problem, a multi-strategy guided electromagnetic field optimization algorithm is proposed. Particles in the algorithm are subject to repulsive forces from three different sources. During the iterative process, the particle's guidance method is determined by calculating the electrical difference, cumulative electrical difference, and comprehensive electrical difference of each mobile strategy, and the probability mutation algorithm is used to avoid being trapped into the locally optimal solution. Through simulation experiments of FT and LA series test cases of job shop scheduling problems, the test results of the new algorithm and other algorithms are compared and analyzed. The research shows that the algorithm has higher precision and faster computing speed.

Risk Management of Complex System under CF-GERT Network of Multi-parameter Variables

DONG Wen-jie, LIU Si-feng, TAO Liang-yan, FANG Zhi-geng, ZHANG Xi-xi

2021, 30(11):  92-98.  DOI: 10.12005/orms.2021.0355

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In the process of complex product development, as the activities between milestone events contain multiple characteristic parameters and some parameters have uncertain stochastic distribution features, the analysis of traditional GERT network based on moment generating function misses some information, so that the assessment and optimization for project objectives become extremely difficult. In this paper, the development of complex equipment isregarded as an entire network system, which is constituted by a series of events. By defining CF-GERT network whose equivalent transmission relationship is made up of characteristic function and the probability of transmission, when there are multiple independent parameter variables between the state of product development activitiesthe analytical algorithm of complex equipment is studied. Taking the development process of a micro satellite as an example, the probability of success which is influenced by whole star weight, development cost, development schedule and other characteristic parameters of the event simultaneously is researched. By analyzing the reasons for low success rate, we can balance and optimize the performance indexes of the microsatellite, which can support risk management in the process of product research and development.

Estimating the Missing Sales Data with the Time Series Matrix Factorization Model

CHEN Si-min, YANG Lei, CHEN Wen-na, HUANG Xiao-yu

2021, 30(11):  99-105.  DOI: 10.12005/orms.2021.0356

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The historical sales data are one of the most important data sources for supply chain optimization (SCO) research. However, for most SCO researchers, the publicly accessible sales data is usually highly incomplete, which makes their work difficult. In order to solve this problem, we propose to use MAFTIS, atime series matrix factorization model, to estimate the missing sales data with respective to the collected ones.In addition, to speed up the computation procedure of MAFTIS, we also present an alternating least square (ALS) based solution algorithm for the model.For evaluations, we apply the proposed method to estimate the missing entries of three real sales data sets, and all results show that, compared with competitive algorithms, our proposed model achieve the best performance in terms of prediction accuracy and convergence speed.

Reliability-oriented Network Cascading Failure Analysis

DUI Hong-yan, CHEN Shuan-shuan, DUAN Dong-li, XU Xin

2021, 30(11):  106-112.  DOI: 10.12005/orms.2021.0357

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In order to study the role of different types of nodes in the network during the failure propagation process and its impact on cascading failures, this paper uses the aggregation to investigate the load transfer efficiency of different network nodes. Firstly, the aggregation is used to describe the characteristics of network topology changes when a node fails. Through the aggregation, a network cascading failure model is established. Then the model determines the critical failure path of the network. Finally, through case analysis, it is found that the traffic network is more stable and has improved liquidity after aggregation changes.

Modeling and Solving Multilinear Utility Function Based on 2-additive Fuzzy Measures

ZHANG Xin-wei, FENG Qiong, LI Jing, TONG Shu-rong

2021, 30(11):  113-119.  DOI: 10.12005/orms.2021.0358

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It is critically important to build appropriate multi-attribute utility functions(MAUT)for multi-attribute utility analysis. Multiple types of MAUT are developed in terms of different preference assumptions, such as additive independence, utility independence and utility dependence. However, in view of complexity in solving MAUT, most applications of MAUT focus on additive function form and multiplicative function form. A novel method based on 2-additive fuzzy measures is proposed to model and solve multilinear utility function in this paper. Firstly, the equivalence between multilinear utility function in a special condition and fuzzy measure-based multilinear model is proved, which can transform multilinear utility function into fuzzy measure-based multilinear model. Then, considering the characteristic of multilinear model and complexity of identifying fuzzy measures, Banzhaf interaction index and 2-additive fuzzy measures are introduced to model fuzzy measure-based multilinear model. 2-additive fuzzy measures and Banzhaf interaction indices are then identified through minimum variance method, which are substituted into multilinear utility function. The method is finally applied to building a multilinear utility function based on customer requirements for a wearable medical equipment. It provides an alternative and effective method to solve multilinear utility functions.

Application Research

Research on the Impact of Capacity Sharing on Equipment Manufacturers and User Enterprises

ZHAO Dao-zhi, ZHU Chen-wei

2021, 30(11):  120-126.  DOI: 10.12005/orms.2021.0359

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The Stackelberg game model is used to compare the profits of equipment manufacturers and equipment user enterprises under the traditional manufacturing model and capacity sharing model. It is found that equipment user enterprises always benefit from the capacity sharing model, but companies with different order demand increments have different benefits. The equipment rental price established by the platform will have an impact on the profit of the equipment manufacturer and the purchase decision of the equipment user enterprise. For any fixed-price equipment, the optimal rental price established by the platform is unique, and the optimal profit of the platform is Inverse U-shaped function of equipment price. The emergence of capacity sharing business has a profit and loss impact on equipment manufacturers. When the platform adopts the optimal pricing strategy, the purchase demand for relatively high-priced equipment increases, and equipment manufacturers benefit from the capacity sharing business. the purchase demand for relatively low-priced equipment decreases, and equipment manufacturers have suffered a loss with the capacity-sharing business. Finally, the above results are verified by a case study.

Air Pollution Impact Prediction of Chemical Industry Park Based on Ensemble Learning Strategy

WANG Xu-ping, YU Xiu-li, WANG Tian-teng

2021, 30(11):  127-134.  DOI: 10.12005/orms.2021.0360

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Establishing a scientific, effective and accurate air quality prediction system has important scientific value and practical significance for protecting people's health and promoting social harmony and stability. In this paper, we focus on chemical industry parks, with the data of enterprise emissions and meteorological information, utilizing supervised machine learning (decision tree, multiple linear regression, Lasso regression, support vector machine, Xgboost, gradient boosting machine, Light GBM, MLP) and ensemble learning Stack strategy to realize the prediction and control of atmospheric environmental pollution in chemical industry park. The results show that: (1)The prediction results under stacking strategy have improved significantly compared with the prediction result of single model. (2)In stacking strategy, the choice of primary and secondary learners affects the accuracy and generalization of prediction. The best mode is to use strong learners at the primary level and linear models at the secondary level. (3)Different outlets in the same park and different enterprises have different impacts on air quality. In this paper, the trend of pollution events in chemical industrial parks is predicted reasonably, which can provide decision support for the government in the management and control of enterprises in chemical industry parks.

Economic Consequences of Institutional Investors' Increased-holdings: an Empirical Study Based on Private Placement

CHENG Xin-sheng, SUN Hong-yan, JIA Xiao-ling

2021, 30(11):  135-141.  DOI: 10.12005/orms.2021.0361

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It is of great practical significance to study the economic consequences of institutional investors' increased-holdings under private placement background. Taking the Shanghai and Shenzhen A-listed companies that successfully conducted private placement from 2008 to 2017 as samples, this paper conducts an empirical analysis and robustness test on the economic consequences and mechanism of institutional investors' increased-holdings by means of OLS, POISSON, PSM and other methods. The results show that the increased-holdings of the whole institutional investors significantly improves the long-term market performance of listed companies with private placement. Considering the heterogeneity characteristics of the institutional investors, the Value-investors' increased-holdings promote the long-term market performance of listed companies with private placement, while the Price-followers' increased-holdings inhibit the long-term market. Furthermore, Value-investors improve the long-term value of listed companies after private placement by cultivating innovation, while Price-followers pursue short-term equity value fluctuation, which reduces innovation and fails to promote the long-term market performance. In addition, the lockups effectively curbing the “chasing the rise and killing the fall” behavior of Price-follower. This research provides a theoretical basis to cultivate medium and long-term value-oriented institutional investors and improve the allocation efficiency of private placement.

Research on the Effect of Economic Policy Uncertainty for the Long-term Dynamic Correlations between China-U.S. Stock Markets as well as China Stock Market-Gold Market Based on DCC-MIDAS model

YANG Ya-juan, MA Ru-fei, CHEN Kong-yan

2021, 30(11):  142-146.  DOI: 10.12005/orms.2021.0362

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This paper focuses on the impact of China's economic policy uncertainty on the long-term dynamic correlation of China-U.S. stock markets and China stock market-gold market. For the purpose of this, the EPU index proposed by Baker for measuring economic policy uncertainty is introduced to establish a modified DCC-MIDAS model and the empirical results based on this model are carried out as follows: First, the change of China's economic policy uncertainty index has a significant positive influence on the long-term correlation of China-U.S. stock markets. Second, the change of China's economic policy uncertainty index has a significant negative impact on the long-term correlation of China's stock market-gold market. Moreover, investors tend to choose gold that is the relatively safe assets when the economic policy uncertainty is high and this finding is in accordance with the flight-to-quality phenomenon. In addition, as a case study, we analyze the effect of U.S. stock index futures and gold futures in hedging risks of China's stock market, and the result shows that U.S. stock index futures is better than gold futures.

Multi-period Fuzzy Asset-liability Portfolio Optimization Model with Bankruptcy Control

YANG Xing-yu, LIU Wei-long, ZHAO Xue-jin, ZHANG Yong

2021, 30(11):  147-154.  DOI: 10.12005/orms.2021.0363

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Considering that some investors need to manage both assets and liabilities in the real investment decision-making process, we study an asset-liability management problem with bankruptcy control and debt-paying behavior. Assuming that the return rates of risky assets and the growth rate of liability are fuzzy numbers, we measure the return and risk of the asset-liability portfolio by its expected value and lower semi-absolute deviation. With objectives of maximizing the final expected net wealth and minimizing the final cumulative risk, we build a multi-period fuzzy asset-liability portfolio optimization model allowing restricted short selling. Then, we design a hybrid intelligent algorithm based on Particle Swarm Optimization and Simulated Annealing to solve the proposed model. Finally, using a numerical example based on real data, we illustrate that the designed algorithm is more effective and stable than the traditional PSO. The proposed strategy can provide decision support for investors who need to manage both assets and liabilities.

FinancialFrictions, CapitalMisallocationand Principle of AssetBubbles Emergence: Evolution Games Analysis Based on Agents Actions

CHENG Dao-jin, CHENG Li-wei

2021, 30(11):  155-161.  DOI: 10.12005/orms.2021.0364

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This paper constructs an asymmetric evolutionary game model betweenentrepreneurs and lenders, so as to explore the micro-mechanism of asset bubbles emergence. This study finds that the impact of financial frictions on entrepreneurs and lenderis heterogenous, both of which can result in capital misallocation. The generation of asset bubbles is the results that staff take on non-rational economic actions with the action of herd effect and contagion effect on individual carries on irrational economic actions in short-term under financial friction shock. It also shows that lenders' seek for higher rents of capital could account for the emergence of asset bubbles, and entrepreneurs provide capital in the process of asset bubbles expansion. Asset bubbles divide individual maximization effect and macroeconomic development. Since financial frictions are the condition of asset bubbles emergence, hence, the effective method to cut off the path of asset bubbles generation is to improve financial efficiency and financial function.

Research on the Innovation Mechanism of Investment-Loan Linkage Based on Dynamic Evolutionary Game Analysis

CHEN Zhi-ying, QIAN Chong-xiu, CHEN Miao-zhen

2021, 30(11):  162-167.  DOI: 10.12005/orms.2021.0365

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Through a dynamic evolutionary game model involving equity investment companies, commercial banks and the government, a government-guided Investment-Loan Linkage is established. Ideally, technological enterprises could obtain credit support from commercial banks, non-technol ogicalones could reduce financial leverage through equity financing, and the government could obtain higher taxes and equity income. It is found that the government plays an irreplaceable important role in further promoting the linkage between investment and loan. Improvement of the project quality, value promotion of non-technological enterprises and appropriate government intervention are three important paths to promoting investment-loan linkage. The research conclusion has certain reference value for further promoting the supply-side structural reform, easing the financing dilemma of technological enterprises, and reducing the corporate leverage ratio.

Box Office Prediction Model Based on Web Search Data and Machine Learning

LI Pei-zhi, DONG Qing-li

2021, 30(11):  168-175.  DOI: 10.12005/orms.2021.0366

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Movie box office prediction has always been an important and complex task for the relevant departments of industry management. Film-related variables are complex and difficult to choose objectively, and the difficulty of data acquisition restricts the main factors of this kind of models. In contrast, web search data is structured data released by Internet companies to record the search behavior of netizens. It has clear meaning, easy-access, and can reflect the development trend of things objectively and timely. Based on the web search data, a hybrid prediction model including data selection method and machine learning algorithm is established in this study. Firstly, the optimal training set is constructed by selecting the training data with the greatest similarity to the test set. Secondly, Imperialist Competition Algorithms is applied to select the best combination of parameters of Least Squares Support Vector Machine. Finally, the optimized model is used for prediction. In order to test the stability and applicability, an empirical study is carried out using the box office data of the films released in mainland China in 2017, which shows that the proposed hybrid model has higher prediction accuracy. The built model is suitable for box office prediction and can provide decision-making reference for industry management departments.

Research on Causes Mining Model of Product Quality Crisis Event

LIU Shu-qing WANG Yi-ping

2021, 30(11):  176-182.  DOI: 10.12005/orms.2021.0367

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In order to effectively solve the problem of improper selection and implementation of response measures caused by inaccurate disclosure of the causes of product quality crisis events, according to the discovering results based on the influencing factors of product quality crisis, the possible causes of product quality crisis events are extracted, and the relationship model of potential causes of quality crisis events is constructed by using fault tree method. Combining the fault tree method and the Bayesian network, based on expert investigation and fuzzy set theory, we infer the underlying cause prior probability algorithm, input the prior probability into the Bayesian network model to obtain the underlying cause posterior probability and critical importance degree, and use the posterior probability and critical importance degree together as the diagnosis basis of the quality crisis key causes. We build the cause mining model of product quality crisis event. The accuracy of the key causes mining results is verified through practical cases, which provides a theoretical basis for companies to mine the causes of quality crisis events.

A Hesitant Fuzzy Group Evaluation Method Considering Stochastic Domain Links

HOU Fang

2021, 30(11):  183-189.  DOI: 10.12005/orms.2021.0368

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Interaction is a difficult and inevitable problem in group decision making (GDM). We should be clear about whom we need to negotiate with and whether the interaction is effective. This paper proposes a method to explain how to interact in GDM using hesitant fuzzy elements. We take the GDM as a network in which experts are nodes and theirs' interactions are links. There are three assumptions and two parts to describethe network value and interaction process, includingthe random dominant matrix and network utility,using the Bellman equation and hesitant fuzzy elements. More specifically, this method gives advice in two levels, and both group and experts could improve their strategies. Therefore, to promote the GDM efficiency, the method could compare the utility, network value and links simultaneously.

Effect of Urban Traffic Restriction Policy Based on SD-VF Approach

CHEN Zhen, ZAN Zhe, JIA Shu-wei

2021, 30(11):  190-196.  DOI: 10.12005/orms.2021.0369

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With the continuous acceleration of urbanization in China, the contradiction between urban traffic supply and demand is increasingly prominent, and the problem of traffic congestion is becoming more and more serious. Therefore, various policies and measures have been implemented in various parts of China to alleviate traffic congestion. Taking Beijing as an example, aiming at the phenomenon of urban traffic congestion, from the perspective of system, this article uses the approach of integrating system dynamics and grey Verhulst prediction (SD-VF) to construct an urban traffic congestion model, and the Vensim software is used for dynamic simulation analysis to explore the influence of policies and measures on urban ecological carrying capacity and road ecological carrying capacity from the economic, social, environmental and other aspects. The results show that although the traffic restriction policy can improve the ecological carrying capacity of roads to some extent, it may also lead to the “paradox” effect. The policy of road repair has not fundamentally solved the problem of urban traffic congestion, but merely postponed the congestion; compared with a single policy, combining the development of public transportation with the policy of restricting traffic can effectively alleviate traffic congestion, improve air quality and improve environmental carrying capacity, which is a more scientific and reasonable policy measure.

Research on Equity Share of Project Investment with Effort Complementarity —Based on Fairness Preference

WANG Ding, GUO Peng, GUO Ning, WANG jing-mei

2021, 30(11):  197-202.  DOI: 10.12005/orms.2021.0370

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This paper focuses on the effect of fairness preference on the collaboration in project investment. In particular, it analyses how entrepreneur's fairness preference affects equity share and effort levels of the venture capitalist and the entrepreneur. Taking into account the effort complementarity of the venture capitalist and the entrepreneur, a venture capital incentive contracting model in which an entrepreneur displays fairness preference is analyzed. Nash bargaining solution is employed to interpret entrepreneur's reference point of fairness preference. We solve the venture capital's maximization problem in the presence of double-sided moral hazard. The results show that fairness preference changes the optimal equity share and effort levels. We simulate the model and show that the venture capitalist's effort does not monotonically decrease in the share allocated to the venture capital, while the entrepreneur's effort does not monotonically increase in his share. More importantly, the entrepreneur displaying fairness preference will take Nash bargaining solution as his lower limit of equity share in the case of a small degree of effort complementarity, and yet the Nash bargaining solution may be regarded as upper limit of equity share when the degree of effort complementarity is large. The result can provide decision support for venture capitalist to develop the incentive contract more effectively.

Auditing Strategy of Government and Core Enterprise on Supplier's Social Responsibility Violation

ZHAO Lian-xia, ZHANG Xiao-feng, YUE Chao-nan, WANG Fang-qing, YOU Jian-xin

2021, 30(11):  203-210.  DOI: 10.12005/orms.2021.0371

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With anincrease in public environmental and social consciousness, a core enterprise's brand reputation may be damaged by scandals caused by its supplier's social responsibility violation. Therefore, is core enterprise willing to cooperate with the government to audit the supplier when government's audit level and supplier's compliance level are uncertain? Based on the different roles of government and core enterprise, this paper constructs governmentaudit model as well as government-core enterprise joint audit model respectively, and obtains the corresponding optimal strategies and the impact of parameters on the optimal decisions. A comparative analysis is carried out. The results show that: (1)core enterprise would like to cooperate with the government when the potential loss faced by the core enterprise is greater than that of the government or the supplier's compliance willingness is much higher; (2)the supplier's compliance level and expected loss under the joint audit strategy are higher compared with the government audit strategy. Considering the instability of the supply chain caused by the increased supplier loss under the joint audit, this paper proposes a tripartite joint investment strategy, and finds that there exists a certain range of investment amount which can simultaneously reduce the tripartite loss.

Management Science

Financialization and Product Quality of Export Firms: Extrusion or Reservoir

WANG Yu, ZHAO Shuang, ZHAI Xin-yao

2021, 30(11):  211-217.  DOI: 10.12005/orms.2021.0372

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In order to analyze the mode of influence between the financialization and product quality of export enterprises, this paper matches the data of the China Industrial Enterprise Database, the Customs Database and the Guotaian Database between 2000 and 2009 to obtain the large sample microdata. Combined with the nonparametric quantile panel, it is found that: (1)The financialization of export enterprises has a non-linear impact on product quality, and there is an optimal level of financialization at the middle and high score points (0.4857 & 0.4361 ,respectively) to maximize product quality. (2)The financialization of export enterprises has a heterogeneous impact on product quality. At the high score point, excessive financialization is more represented by the inverted U-shaped extrusion effect, while at the middle and low quantile points, it is more represented as a reservoir effect. (3)The quality of non-state-owned enterprises and high-tech products is more sensitive to the level of enterprise financialization.

Research on the Formation of Brand Fan Effect in New Media Environment

XU Xin-liang, MENG Rui, XU Jian-zhong

2021, 30(11):  218-225.  DOI: 10.12005/orms.2021.0373

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With the continuous development of new media technologies and the change of consumption patterns, e-commerce has given rise to new business forms, which bring new challenges to brand marketing. Consumers' brand consumption has shifted from traditional functional requirements to more value requirements, giving rise to ‘fan effect'. This paper studies the formation mechanism of fan effect in a new media environment. Combined with the new media environment, this paper describes the concept and connotation of ‘fan effect', we assume that ‘fan effect' is a causal phenomenon caused by the brand behavior of the fan group. With the emergence of new network platforms, the context of brand marketing has also changed, which shows higher interactivity, better content and social attributes.In this context, the realization process of brand fan effect includes four stages: traffic introduction, user precipitation, community construction and ‘fan effect'. The influencing factors in each stage in the new media environment include brand experience, brand identity, brand image and brand ‘fan effect'. In this paper, the publishers of Xiaohongshu APP notes are selected as the research population. A total of 349 questionnaires are distributed under the brand themes and 282 valid questionnaires are collected. With an empirical analysis using the explanatory structural equation, the results show that brand experience has a positive influence on brand identity; brand identity is divided into personal brand identity and social brand identity and personal brand identity has a positive impact on social brand identity; brand identity has positive influence on brand image; both brand identity and brand image have a positive effect on ‘fan effect'. Therefore, in the process of brand marketing, brand fan effect should be fully developed and utilized, which requires brands to pay more attention to consumer brand experience and cultivate consumers' brand identity.

Decentralized Competition, Willingness to Cooperate and Urban Agglomeration Construction: A Principal-agent Explanation Considering Fairness Preference

PAN Lin-wei, LU Hao

2021, 30(11):  226-231.  DOI: 10.12005/orms.2021.0374

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The lack of reciprocal cooperation mechanism and information asymmetry affects the regional coordinated investment of local governments, which is not conducive to the construction of urban agglomeration and high-quality economic development. On the basis of introducing fairness preference into the principal-agent model, this paper focuses on the impact of willingness to cooperate and information conditions on the level of effort. It is found that both fairness preference and information conditions affect the effort level of agents, and the information distribution among agents is more important. The effort level of local governments depends on the collaborative willingness of adjacent cities to meet the “reciprocal” behavior in fairness preference; And the effort level in the case of information symmetry is higher than that in the case of asymmetry, which means improving information distribution and guiding fairness preference is conducive to improving the regional collaborative input of local governments and the overall output level. It can be concluded the urban agglomeration construction and regional coordinated development need a sound coordination mechanism to enhance the level of mutual trust and mutual benefit mechanism between local governments, and to reduce and eliminate information asymmetry between regions, which would improve regional economic efficiency and promote high-quality economic development.

Pricing Strategies of the Asymmetrical Competition Enterprises in Consideration of Advertisement Delivery

ZHOU Hui-ni, WU Peng, WANG Xiao-lun

2021, 30(11):  232-239.  DOI: 10.12005/orms.2021.0375

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In accordance with the advertisement delivery and its pricing strategies in asymmetrical double-oligarch competitive enterprises, this paper first builds a uniform pricing model and a differentiated pricing model. On the basis of the pricing model, we buildthe profit model under different situations, and determine the equilibrium results at different stages with the analytical method of game theory. By analyzing the equilibrium results, this paper obtains the impact of the advertisement costs and the differentiation degree of the advertisement costs and the competitive markets on the equilibrium results. Finally, the effectiveness of the results is tested by the numerical analysis.