Table of Content

25 May 2022, Volume 31 Issue 5

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Theory Analysis and Methodology Study

How does the Delayed Effect Affect the Cooperation between Government and Enterprises in Disaster Relief? Research Based on Differential Game

YANG Man, LIU De-hai

2022, 31(5):  1-7.  DOI: 10.12005/orms.2022.0140

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“Government-led, social participation” collaborative disaster relief has become the direction of China's disaster relief system reform. Communication interruption and destruction of transport networks often lead to the delayed rescue. Is the rescue efficiency of government-enterprise cooperation necessarily higher than that of spontaneous rescue in the emergency scenario of delayed rescue? Considering the delayed effect of rescue, a differential game model of government-enterprise disaster relief cooperation is constructed to analyze the influence of rescue delay on government-enterprise disaster relief strategies, and the applicable conditions of government cost subsidy to improve the cooperative disaster relief. Finally, the case of the Ludian earthquake in Yunnan province is verified. The results show that cooperative rescue is more efficient when the delay time is less than a certain threshold. Compared with spontaneous rescue, the government's input increases sharply with the delay time, while the enterprise's input changes little. The enterprise unit income coefficient can be used as an indicator to measure the severity of disasters. The higher the value is, the greater the proportion of government subsidies for disaster relief costs of enterprises.

Emergency Response Solutions Evaluation Method Based on Dual Hesitant Fuzzy Unbalanced Linguistic Prioritized Aggregation Operator

QI Xiao-wen, LIANG Chang-yong, ZHANG Jun-ling

2022, 31(5):  8-13.  DOI: 10.12005/orms.2022.0141

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Aiming at the complex emergency response solutions evaluation problems where assessments are generally of high uncertainty and relative importance among evaluative attributes often only can be recognized as prioritization relations among them, we investigate effective multiple attribute decision making(MADM)approaches in this paper. Firstly, to help decision makers elicit their uncertain opinions more effectively and comprehensively, we define a dual hesitant fuzzy unbalanced linguistic set, and develop its operational rules, entropy and distance measures. Then, we develop a dual hesitant fuzzy unbalanced linguistic prioritized weighted aggregation(DHFUBLPWA)operator. Next, we construct an MADM approach based on DHFUBLPWA operator and the entropy measure to effectively accommodate situations with attributes' prioritization relations and another MADM approach based on classic VIKOR framework to address the situations with unknown weighting vector for evaluative attributes. Finally, application studies have verified the effectiveness of our proposed methods.

Evolutionary Game Analysis of Corporate Social Responsibility in Supply Chain Based on System Dynamics

CHENG Hui-jin, DING Hao

2022, 31(5):  14-22.  DOI: 10.12005/orms.2022.0142

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In this paper, evolutionary game model and system dynamics are combined to explore the decision-making of corporate social responsibility in supply chain under different governance measures. The simulation results show that there is an interaction between the decision-making of enterprises in each link of the supply chain. When one party has a high sense of fulfilling corporate social responsibility the other has a low one. The higher conscious party will eventually tend to fulfill corporate social responsibility regardless of whether there are incentives or not, while the lower one will choose not to fulfill the decision, unless there is a strong incentive. The implementation of incentive measures is more effective for manufacturers when they make decisions on the performance of corporate social responsibility with a neutral attitude. Compared with retailers, manufacturers are more dependent on the market effect brought by consumers' preferences when they fulfill their corporate social responsibilities. Government subsidies are more effective in the short term. The stronger the punishment, the better the incentive effect and the longer the duration. If the two incentive measures are used together, the incentive effect can be better played.

Pricing Game between Repair and Support Ships and Shipyards for Repairing Damaged Ships at Sea

ZHAO Rui-jia, XIE Xin-lian, LI Guo-dong

2022, 31(5):  23-29.  DOI: 10.12005/orms.2022.0143

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Repair and support ships could carry out spot maintenance and repair for damaged ships at sea, and would compete with shipyards when entering the maintenance and repair market for ships. In order to solve the optimal pricing problem between repair and support ships and shipyards to repair damaged ships at sea, a pricing game model between repair and support ships and shipyards is established by analyzing the differences in space, time and cost between the repair and support ship modes and shipyard modes. An iterative algorithm is designed to solve this bi-level programming model. Taking a maintenance and repair work of a ship with damaged hulls at sea as an example, the optimal pricing and maximum benefits of repair and support ships and shipyards, and the requirements of ship owners for these two maintenance and repair modes are obtained, which verifies the validity of the model and algorithm. The influence rules of some factors such as dispatch distance, damage degree of ships and difficulty of marine maintenance and repair technology on the pricing of repair and support ships and shipyards is analyzed. This method can provide optimal pricing strategy for operators of repair and support ships and shipyards, and provide theoretical support for pricing game of these two maintenance and repair modes.

Stochastic DifferentialInvestment and ProportionalReinsuranceGame with Delay

BIN Ning, ZHU Huai-nian

2022, 31(5):  30-36.  DOI: 10.12005/orms.2022.0144

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There is keen competition between insurersin the financial markets. Insurers not only seek to maximize their own wealth, but also focus on comparing their wealth with that of their competitors. This paperstudies a class of stochastic differential investment and proportional reinsurance game with delay, and investigates the effects of delay and competition coefficients on optimal investment and reinsurance strategies of insurers. Firstly, for the classical Cramér-Lundberg model, equilibrium investment and reinsurance strategies with delay are obtained using the differential game and stochastic optimal control theory, and an explicitform of the value function is given. Secondly, further for the approximate diffusion process, explicit expressions for the equilibrium investment strategy and proportional reinsurance strategy under exponential utility are obtained. The sensitivity of equilibrium strategy to the model parameters is analyzed by a numerical example.The results show that: whether or not the delay information is taken into account will have a significant impact on the final equilibrium reinsurance strategy and optimal investment strategy. The more value of wealth at an earlier time is considered, the more prudent and rational insurers' investmentbehavior will be; on the other hand, the more importance they place on industry competition, the more risky andaggressivetheir investment behaviortends to be.

Evolutionary Game Study of Choice of Hotel Cancellation Policies Based on Cancellation Rate

LU Xin-yuan, FAN Ya-rui, QIN Ze-jia, FANG Wen-qi

2022, 31(5):  37-42.  DOI: 10.12005/orms.2022.0145

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Based on the customer's cancellation behavior, this paper constructs a game model of hotels under the framework of Hotelling model and analyzes the choice of cancellation policies between two competitive hotels. The results show that, when the sensitivity of customers to the horizontal differentiation between two hotels is high, if the cancellation rate differentiation between the two hotels is small, the two hotels will choose loose cancellation policy, and if the cancellation rate differentiation is large, the hotel with high cancellation rate will choose the strict cancellation policy, and the hotel with low cancellation rate will choose the loose cancellation policy. When the sensitivity of customers to the horizontal differentiation between the hotels is low and the cancellation rate differentiation between the two hotels is small, there are two evolutionarily stable strategies, and the hotel only chooses the opposite strategy to the competitor to get the maximum profit. Our study provides theoretical support for hotels in cancellation policy decision and revenue management.

Research on Minimum Asymmetric Cost Consensus Problem Based on Interval Opinions

CHENG Dong, ZHANG Jing-yang, YUAN Yu-xiang, CHENG Fa-xin

2022, 31(5):  43-48.  DOI: 10.12005/orms.2022.0146

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Most of the existing consensus models are based on precise opinions and do not consider the direction constraints of adjusting decision makers' opinions. To solve the problem, this article introducesinterval opinions and explores the consensus-reaching problem under the situation ofasymmetric cost from the perspective of optimization adjustment cost. Firstly, an asymmetric minimum cost consensus model is constructed based on interval opinions. Then, considering the actual needs of decision makers for different levels of consensus, a decision-maker weight allocation method based on the length of the interval opinion is proposed by introducing the soft consensus measures, and an asymmetric minimum cost soft consensus model based on the interval opinion is constructed accordingly. Finally, the effectiveness of the model is verified through an example of the decision-making on pollution reduction between the government and polluters, and then a sensitivity analysis and comparative study are conducted. The results show that: (1)Compared with the precise opinions, using interval opinions can reduce the consensus cost; (2)Compared with the symmetric cost, the total consensus cost considering the asymmetric adjustment cost will not increase indefinitely as the unit adjustment cost increases.

VIKOR Multi-attribute Decision Approach With the Aid of A Novel Picture Fuzzy Distance

WANG Lei, YAO Xing-na

2022, 31(5):  49-54.  DOI: 10.12005/orms.2022.0147

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Considering the deficiencies of the existing Picture fuzzy distance, a novel Picture fuzzy distance with parameter is established in this paper, which can portray the preference of decision makers. Then the established novel distance is extended to the multi-attribute compromise solution sorting approach (VIKOR). The novel distance is employed to compute the whole benefit value and individual regret value for every alternative, and then the decision making outcome is determined. Finally, an example is provided to show the effectiveness and merits of the established approach, and the sensitivity analysis is also conducted.

Research on the Performance of Dynamic Group Decision Making by Integrating Knowledge Share/Transfer

ZHANG Xiao-peng, GUAN Lei, WU Su-han

2022, 31(5):  55-61.  DOI: 10.12005/orms.2022.0148

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The current group decision making practice always has drawbacks in both decision speed and convergence. This article, based on the interactive decision process, investigates the underlying mechanism as well as determinants of dynamic group decision performance (convergence and decision time) by integrating knowledge share/transfer. First, the quantitative model of interactive process is established to demonstrate the consensus of group decision integrating knowledge share/transfer. Second, the qualitative simulation is employed to analyze the impact of knowledge share/transfer on decision time. Specifically, to minimize the decision time, the action plans under various decision scenarios are developedby searching the optimal level of knowledge share/transfer.

Multi-objective Scheduling Optimization of Second-line Lock under “Time-limited Service Rule”

WU Xiao-yuan, WU Feng-ping

2022, 31(5):  62-67.  DOI: 10.12005/orms.2022.0149

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In view of the shortage of the existing queuing rules for ships passing through locks, the “time-limited service rules” are proposed to construct the multi-objective bilayer optimal scheduling model for second-line ship locks. The upper model is used to obtain the feasible scheme for ship arrangement of two lock safe areas while the lower is used to obtain the optimal number of sluices to be arranged for different ship scheduling schemes. The lower model is completed in two stages among them: For ships conforming to the “time-limited service rule”, a 0-1 planning model is constructed with the goal of minimum number of locks to obtain the number of sluices arranged by such ships. For other ships, the “first-come-first-served rule” shall apply, a multi-objective decision model is constructed with the goal of minimum number of sluices and maximum utilization rate of lock rooms to gain the frequency of different ship arrangements and standards should be obtained. Taking the data of a double lock on the main channel of Jiangsu province within 24 hours of a day as an example, the calculation results show that: Compared with the “empirical arrangement”, the optimization scheme obtained by the optimization model in this paper can save 2 sluices for each of the two locks, The average utilization rate of lock rooms of the two ship locks increased by 3.66 and 4.72 percentage points respectively.

New Mathematical Model and Algorithm for the Task Assignment Problem Considering the Personnel Training

LIU Hai-chao, WAng Yang, FAN Qiong-yu

2022, 31(5):  68-73.  DOI: 10.12005/orms.2022.0150

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With the rapid increase of the labor cost, more and more companies prefer to hire on-call employees. This paper investigates a new task assignment problem from a home improvement company in China. In this problem, each task is composed of multiple sub-tasks and the assignment takes the personnel training and service time of customers into account. The objective of this problem is to maximize the weighted combination of the number of assigned tasks and the total profit. To solve this problem, we build an integer programming model and design a highly effective local branching algorithm. In addition, we analyze how the different branching variables and parameter settings impact the behavior of the algorithm and determine the best parameter settings. In particular, we observe that the effective selection of local branching variables is dependent on the problem instances. Experimental results disclose that our proposed local branching algorithm is able to obtain better solutions than the general purpose Gurobi solver in competitive computational time.

Study on Order Parameter Analysis Method of Industrial Structure and Environment

JIN Zheng-hao, ZHAO Xi-nan, JIANG Zhe-yi

2022, 31(5):  74-80.  DOI: 10.12005/orms.2022.0151

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The analysis of industrial structure and environment is not only the indispensable way to find and master the mechanism of industrial operation but also an important part of corporate strategic management, which will influence the decision-making and implement of corporate strategy directly. With a new value ideology of strategic management, this paper firstly deals with the re-interpretations of structural feature of industry and corporate behavior on the basis of Synergy and Jingyou theory. Secondly, it proposes a new analysis method of industrial structure and environment, i.e. the order parameter analysis method and its application paradigm. Such research results of this paper as the the multi-layer structure of industry, the position and distribution feature of enterprise groups in industry, the main developing mode of industry, the benchmarks and synergistic partners, the relationship between the enterprise groups or the composition of enterprises in groups and the performance can provide the directional assistance and technical supports for the strategic management practice in line with the modern industrial development environment.

A Neutral Interval Cross-efficiency Method Based on Deviation

YOU Cui-ling, HUANG Yan, HUANG Jia-wen, ZHANG Jie-hao, WEN Yong-xian

2022, 31(5):  81-85.  DOI: 10.12005/orms.2022.0152

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In uncertain environments, the input and output values of DMUs are interval numbers. In order to solve the cross-evaluation problem of decision-making-units (DMUs) that is neither cooperative nor competitive, by taking the minimum sum of the average deviations forinput scores and output scores as the goal,two neutral models are constructed for evaluating DMUs under the best and worst production conditions. From the perspective of the proposed neutral models, the sum of the average deviations for input scores and output scores of the DMUs reaches the minimum. The research results show the effectiveness of the neutral interval cross efficiency models and solve the problem of neutral evaluation in uncertain environments, which can ensure the objectivity of evaluation and make the evaluation results more credible and realistic.

Equity Analysis of Tradable Credit Schemes in Traffic Congestion Management

LI Min, TANG Jie, WU Zhong-ming

2022, 31(5):  86-92.  DOI: 10.12005/orms.2022.0153

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Based on the reference dependence model in the loss aversion theory, we construct the perceived travel cost function. With the consideration on transaction cost ratios in the credit cards market, we develop the variational inequality model under the conditions of user equilibrium and market equilibrium for the traffic network with fixed demand. By some simulation experiments, we illustrate that according to the adjustment of the market transaction cost ratio, government can affect the credit trading market and promote the equity of tradable credit schemes. Furthermore, we measure the equity of tradable credit schemes by the weighted average of the travel cost ratio fluctuation of all the OD pairs in the traffic network. A utility function is proposed to balance the reduction of total system cost and the requirement of increasing the equity of tradable credit schemes. The optimal solution under different conditions can be obtained by changing the weights of the utility function.

DEA Model for Fixed Cost Allocation in Two-stage Systems Based on Fairness

ANG Sheng, FAN Ting-ting, YANG Feng

2022, 31(5):  93-100.  DOI: 10.12005/orms.2022.0154

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Methods for fixed cost allocation in two-stage systems in most existing researches are based on the principle of efficiency invariance or the satisfaction degree. However, few of them consider the fairness of fixed cost allocation. This study first introduces the non-egoistic principle to obtain the upper bound of cost of the system and each stage, and then proposesa new fixed cost allocation model for two-stage systems with the group organizational structure, where the resulted allocating plan is fairer. Finally, the feasibility and applicability of the model are verified by a practical example.

Partial Ordered Set Representation of Comprehensive Evaluation Model

YUE Li-zhu, LU Chang, ZHANG Zhi-jie

2022, 31(5):  101-106.  DOI: 10.12005/orms.2022.0155

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The comprehensive evaluation model represented by partial order set can transform the complete rational paradigm of evaluation into the finite rational paradigm, and then improve the ability of the model to deal with uncertainty and reduce the evaluation risk. On the basis of partial order set theory, the full order weight is extended to partial order weight, and the partial order representation of evaluation function under partial weight sequence is solved. The generalized representation theorem of partial order sets shows that the function expressed in partial order can be valued as fuzzy number, fuzzy hesitation value, interval number, random number and so on. The results show that the comprehensive evaluation of partial order representation solves the problem of empowerment completely and fully expresses the personal preference of decision makers. From the perspective of the operation effect of the model, the range of data processed by the model is increased, the evaluation result is more robust and reliable, and the structured information between schemes is presented through Hasse graph, which has the function of layering and clustering.

Reliability Analysis of Multi-stage Shock and Degradation Model Based on Markov Renewal Process

XU Dong, JIA Xu-jie, YAO Zhao-sheng, QANG Qi

2022, 31(5):  107-111.  DOI: 10.12005/orms.2022.0156

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In the process of shock and degradation of reliability systems, it is usually multi-stage and dependent. In order to analyze the dependence of the shock and degradation more accurately, a composite model of multi-stage system with dependent shock and degradation process is established. In the model, a more generalized dependence on shock and degradation processes is proposed. The shock and degradation contribute to the damage accumulation process of the system, which leads to the change of the system stage, and the state transition affects the impact and degradation process. By constructing Markov update process and based on semi Markov kernel, the reliability expression of this impact degradation model is obtained.

Application Research

Systematic-Estimation Error Trade-off in Portfolio Selection with Variable Cardinality

QI Yue, LIAO Ke-zhi

2022, 31(5):  112-120.  DOI: 10.12005/orms.2022.0157

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The systematic error and estimation error in the choice of portfolios are important factors that determine the out-of-sample performance, but its tradeoff is affected by the asset cardinality N. In this paper, under the setting of the variable cardinality, the method of Bootstrapping and out-of-sample rolling are applied to the test of the equally weighted, the minimum variance portfolio and its error correction strategy performance and tail risk. The findings are as follows: (1)There is an inverted U-shaped relationship between the difference between the minimum variance portfolio and the equally weighted strategy in the out-of-sample period and N. (2)The tail risk of the minimum variance portfolio decreases rapidly with the expansion of N. Overall, the tail risk of the minimum variance portfolio is lower than the equally weighted strategy. (3)There is a positive correlation between the turnover rate of the minimum variance portfolioand N, and blindly increasing the cardinality will bring unnecessary losses. The research results show that investors should choose the asset cardinality rationally according to the length of the estimation window, and make full use of the diversification benefits brought by the minimum variance portfolio.

Real-time Response Strategy for Demand of Mobile Charging Vehicles Based on Appointment Mode

SUN Li-jun, LI Fang-fang, WANG Xin-yue, HU Xiang-pei

2022, 31(5):  121-129.  DOI: 10.12005/orms.2022.0158

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Real-time response problem for demand of mobile charging vehicles under appointment mode is new in the mobile charging industry. This problem contains two types of demands with different characteristics and dynamic alternating influence, which not only havetime window constraints and real-time response requirements but also havedynamic uncertainty. In order to solve this problem, with the goal of maximizing the overall income, we propose a linkage two-stage strategy, which uses approximate dynamic programming to solve the future value and is integrated into the two stages of demand response: In the first stage, a dynamically updatable service scheme is generated by combining the multi-stage stochastic dynamic decision model and the Tabu search algorithm. In the second stage, a real-time response decision-making process for dynamic arrival demand is proposed based on the first stage. Finally, the comparative experiment verifies the effectiveness of this strategy under different customer sizes and degrees of dynamism, as well as obtains the managerial implications. This study can provide decision support for the formulation of real-time demand response strategy for mobile charging vehicles, and has enlightening significance for similar demand response strategy problems with dynamic characteristics.

Researches on Evaluation Methods for Taxi Drivers' Contribution to Society

ZHANGShuo-shuo, DANG Yan-zhong

2022, 31(5):  130-135.  DOI: 10.12005/orms.2022.0159

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Taxi driver's contribution to society plays an important role in promoting urban economic development and social progress. The evaluation of taxi driver's contribution to society is an important means to inspire taxi driver to make contribution to the society. The goal of this paper is to evaluate taxi drivers' contribution to society. The paper proposes a method to evaluate taxi drivers' contribution to society based on the actual taxi operational data. And it summarizes taxi drivers' social contribution evaluation indexes including operating characteristic, key region, adverse weather and special event. And then this paper calculates the final weight ratio based on subjective values of G1 method and objectively deviation maximization method and establishes taxi drivers' social contribution evaluation model by using four methods of evaluation information aggregation. Finally, the feasibility of the model is demonstrated by the actual taxi operational data. This paper puts forward a new research idea to evaluate taxi drivers' contribution to society and has certain enlightenment to the formulation of government policies and the implementation of enterprise strategy.

Studying on the Impact of Carbon Trading on Manufacturing/Remanufacturing and Coordination Mechanism Based on Authorization Manufacturing

XIA Xi-qiang, LU Meng-yuan, XU Chun-qiu

2022, 31(5):  136-142.  DOI: 10.12005/orms.2022.0160

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In order to analyze the impact of carbon trading on manufacturing/ remanufacturing and the coordination mechanism of supply chain based on authorization manufacturing, the game models involving an original equipment manufacturer (OEM) and a remanufacturer are respectively constructed for decentralized and centralized decision-making. Based on the optimal solution of decentralized and centralized decision-making model, the effects of carbon trading on the optimal solution of the two decision-making modes are compared and analyzed, and the coordination mechanism of fixed authorization fee is given to solve the problem of marginal profit loss of supply chain caused by decentralized decision-making. The main research results are as follows: when the carbon trading price is greater than a certain threshold, carbon trading can not only reduce the environmental impact of the two products, but also increase the consumer surplus, whether it is the decentralized decision or centralized decision; when making decentralized decision, the OEM can increase its profit through reducing authorization fee based on the carbon trading; the OEM and the remanufacturer can sign a contract with fixed authorization fee to coordinate supply chain profit.

Research on the Impact of Corporate Financialization Behavior on Export Complexity

WANG Yu, QIU Yong-qin, WU Wei

2022, 31(5):  143-149.  DOI: 10.12005/orms.2022.0161

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This paper uses the China A-share listed manufacturing company, the customs database and CEPII BACI import and export data, to truly capture the non-linear heterogeneous impact of financialization of manufacturing industry on the firms' export complexity. The study shows that: (1)In the initial stage of the allocation of financial assets, the impact of financial assets on its export complexity is mainly manifested as crowding out effect. With the increase of financial assets, the promotion effect begins to show up. Specifically, the low-scoring exhibits a “U-shaped” relationship, while the high-scoring points have an “inverted-N-type” relationship. (2)The suppression effect of financialization on the export complexity of state-owned enterprises is stronger than the overall level, and the promotion effect on non-state-owned enterprises is stronger than the overall level, and the middle-high-quantity points are almost linear. (3)For high-tech enterprises, the crowding effect of financialization and the “reservoir” effect have gone through two stages. For non-high-tech industries, under the effect of catch-up effect, financialization will play more role as a “reservoir” and promote the complexity of exporting enterprises.

Portfolio Selection Model and Empirical Study Based on EEMD and Fuzzy Regression

ZHOU Xiao-guang, HE Qian, HUANG Xiao-xia

2022, 31(5):  150-155.  DOI: 10.12005/orms.2022.0162

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With the continuous development of fuzzy theory and its extensive application in the securities market, more and more scholars have paid attention to the importance of fuzzy parameters for portfolio optimization. In this paper, a combination of ensemble empirical mode decomposition (EEMD) and fuzzy linear regression method is proposed to construct a portfolio selection model based on symmetric triangular fuzzy numbers. Compared with the method of ensemble empirical mode decomposition combined with ordinary least squares and single fuzzy linear regression method, the results of empirical study show that the portfolio model based on ensemble empirical mode decomposition and fuzzy linear regression is optimal, which is of reference significance for constructing the optimal portfolio.

Real-time Fault Risk Assessment Method for Power Distribution Equipment

MA Tian-yi, ZHU Jian-ming, ZHANG Chi, YANG Lin, WU Yue

2022, 31(5):  156-161.  DOI: 10.12005/orms.2022.0163

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The previous fault risk assessments of power distribution equipment are not comprehensive enough in factor analysis, failing to fully consider the impacts of environmental factors such as weather and equipment health status on the risk of equipment fault. Moreover, the data is mainly derived from long-term historical data, which lacks pertinence and timeliness. To solve this, this paper proposes a real-time fault risk assessment method for power distribution equipment. Firstly, the real-time fault probability of power distribution equipment is calculated combining both the weather conditions and equipment status. And then the impacts of faults on distribution equipment are evaluated through three factors: load loss, number of power outages, and load rating. Finally, a risk assessment model is established based on the fault probability and degree of impacts. In this study, the case of IEEE-RBTS BUS2 is analyzed and presented and the results prove that this method can effectively evaluate the real-time fault risk of power distribution equipment. Overall, it provides a new perspective to optimize equipment maintenance and has important significance of improving emergency management for power companies.

Joint Ordering and Pricing Policy and Salesforce Incentive under Inventory-dependent Salvage Value and Consumer's Low-carbon Preference

CHEN Ke-gui, WANG Xin-yu, HUANG Min, REN Liang

2022, 31(5):  162-168.  DOI: 10.12005/orms.2022.0164

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In this paper, we investigate the joint decision on production and pricing, the carbon emission reduction and the compensation strategy of a supply chain, where the manufacturer relies on the sales agent to sell the products. Most related literature assumes that the salvage value is a constant, but we consider the joint effect of carbon emission reduction, and the salvage value depends on leftover inventory at the end of a selling season. We develop the principal-agent model and further solve the model, and then analyze the impact of the variation rate of salvage value and the cost of carbon emission reduction in the decisions of both sides. It is found that, as the variation rate of salvage value increases, only the optimal production strategy and the manufacturer's profit depend on the variation rate of salvage value and decrease, the manufacturer's carbon emission reduction, pricing, sales contracts and retailer's decisions are not affected. However, the cost of carbon emission reduction will lead to the decline of manufacturers' profits and decision variables of both sides. Finally a numerical example is provided to demonstrate the validity of the proposed model and results. It has important guiding significance for the operation practice of supply chain.

Digital Transformation and Enterprise Innovation Efficiency ——Empirical Evidence from Chinese Manufacturing Listed Companies

YANG Shui-li, CHEN Na, LI Lei

2022, 31(5):  169-176.  DOI: 10.12005/orms.2022.0165

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Digitalization has become an important engine for innovation-driven development of enterprises, but how manufacturing enterprises mine data value to improve innovation efficiency is the hot issues of common concern. Based on the data of A-share listed manufacturing companies in Shanghai and Shenzhen from 2007 to 2019, this paper discussed the impact mechanism of digital transformation on innovation efficiency of manufacturing enterprises. The results show that digital transformation can significantly improve the innovation efficiency of manufacturing enterprises, and this conclusion still holds after the robustness test. Heterogeneity analysis shows that the higher degree of industry competition and the lower degree of marketization, the more obvious the role of digital transformation in promoting enterprise innovation efficiency. The research conclusions not only enrich the research on digital transformation and enterprise innovation, but also provide enlightenment for optimizing corporate governance, improving enterprise innovation environment and facilitating high-quality development of manufacturing enterprises.

Factors of Money Laundering Risk in China's Pilot Free Trade Zones Based on Fuzzy Cognitive Map

GAO Zeng-an, WANG Xiao-cao

2022, 31(5):  177-182.  DOI: 10.12005/orms.2022.0166

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The factors affecting money laundering risk in China's Pilot Free Trade Zones (CPFTZs) are interrelated, and their relationships are evaluated by experts' cognition. The paper uses the iterative reasoning mechanism of fuzzy cognitive map and the grey relational analysis to calculate the correlation degree between the factors and CPFTZ money laundering risk, and then recognizes the mainfactors that affect money laundering risk in CPFTZs. It finds that the soundness of anti-money laundering laws and regulations, the scale of predicate crimes, the effectiveness of anti-money laundering supervision authorities and obligatory subjects, the level of judicial cooperation, and the rate of settlement of predicatecrimes aremajor influencing factors, which can be referred to in CPFTZs'anti-money laundering decision-making practice.

Research on the Impact of Economic Policy Uncertainty and Cryptocurrency Market volatility ——Empirical Analysis Based on GARCH-MIDAS Model

BAI Jian-cheng, HUANG Yun-fei, GAO Zeng-an, He Tian

2022, 31(5):  183-189.  DOI: 10.12005/orms.2022.0167

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This article empirically studies the impact of the economic policy uncertainty index (EPU) on the volatility of the Bitcoin market globally and in seven countries specifically through the mixed frequency model (GARCH-MIDAS). The results in the sample show that the world and seven countries' EPU indexes have a significant impact on the future Bitcoin market volatility; EPU can improve the prediction effect of Bitcoin volatility in the sample; and there is a positive correlation between the US and Australian EPU and Bitcoin market volatility, and negative one for the rest. Then, based on the Model Confidence Set (MCS) out-of-sample test, it is found that, compared with other EPU indicators, the uncertainty indicator of US economic policy can improve the prediction accuracy of the Bitcoin market volatility. In addition, this study further points out that understanding the impact of global and seven countries' economic policy uncertainties on digital currency market contributes to supervision organizations and policy makers to judge the trend of digital currency market and prevent financial risks caused by cryptocurrency market.

Dynamic Evolution Analysis of Index Insurance Market Equilibrium Based on Policyholders' Heterogeneous Risk Preferences

ZHAO Xin, XUE Yue-mei, DING Li-li

2022, 31(5):  190-197.  DOI: 10.12005/orms.2022.0168

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Index insurance, which combines immunity of moral hazard and adverse selection and immediate compensation, has become an important tool for catastrophe risk management. However, the rules of its market equilibrium is still unclear. Therefore, this paper constructs a three-part evolutionary game model of insurance companies, policyholders, and government. Considering the different attitudes of the policyholders in the face of loss and return, the heterogeneous risk preference is included to design the policyholder's decision function. Then, this paper analyzes the evolution path of the index insurance market equilibrium and its influencing factors. The results show that the equilibrium of the index insurance market changes along with its life cycle. The function of government in the index insurance market will move from the manager to the exit, but the subsidy needs to be within a reasonable range, and the government will subsidize the insurance company more effectively. In terms of influencing factors, the policyholders' heterogeneous risk preference has an important impact on the equilibrium evolution of the index insurance market. The sensitivity of loss will accelerate the convergence of the index insurance market to equilibrium; the immediate compensation advantage has the same effect. The spillover effect on non-participating entities delays the achievement of equilibrium. Based on the conclusion, this paper proposes some recommendations for the guidance and encouragement of the index insurance market.

Influence of Proactively Initiated Margin Buying and Short Selling: Evidence from China

GAO Ya, XIONG Xiong

2022, 31(5):  198-205.  DOI: 10.12005/orms.2022.0169

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Using the margin buying ratio and short selling ratio as the main proxies, we study the influence of investors' proactively initiated trading on stock return, liquidity and volatility, giving the current development status of margin trading and short selling in the Chinese stock market. Using the unbalanced paned data regression with fixed effects, we find the influence of margin buying (short selling) on stock return is positive (negative), which coincides with the policy-making target: margin trading is the reflection of investors' positive belief and short selling is the reflection of investors' negative belief. In addition, we find that margin buying (short selling) increases(decreases) the liquidity; margin buying (short selling) decreases (increases) stocks' volatility; the influences of margin buying and short selling on stocks' trading characteristics are gradually improved with time. Finally, we find the influence of margin buying and short selling varies with stocks listed on different boards, and with the adding of stocks listed on the SME and Chi-Next boards, adjusting and optimizing the performance of these stocks' trading remain the future main tasks of regulators.

Effect of Investors' Attention to the Concept on Stock Return —Empirical Evidence Based on Baidu Search

SU Zhen-xing, HU Wen-xiu, Yang Li

2022, 31(5):  206-213.  DOI: 10.12005/orms.2022.0170

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There is an obvious conceptual speculation in China's stock market, which distorts the benign pricing mechanism of the market. Based on the perspective of limited attention, this paper reveals the formation mechanism of investor attention to the concept and its influence on stock return. Baidu search data is used to measure investor attention to the concept, and the stocks of “One Belt and One Road”, “5G” and “PM2.5” conceptual plates are used as research samples for empirical research. The results show that under the control of the three factors of Fama-French model and the investor attention to individual stock, investor attention to the concept has a significant positive effect on the stock return, but the effect turns negative in subsequent periods. On one hand, the investor attention to individual stock will strengthen the positive effect of the investor attention to the concept on the stock return. On the other hand, because the higher the investor attention to individual stock, the stronger the liquidity of the stock, so it will weaken the reversal effect of the influence of the investor attention to the concept on the stock return. The conclusion enriches the theoretical research of investor attention and provides a theoretical basis and a practical approach to restraining conceptual speculation.

Study on Stock Index Prediction Based on ARIMA and Information Granular SVR Combination

YAO Jin-hai

2022, 31(5):  214-220.  DOI: 10.12005/orms.2022.0171

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For investors in the securities market, accurate prediction of future development direction and trend of asset price based on reasonable assumptions is related to investment success or failure. This paper constructs a combination prediction model based on ARIMA and information granulation SVR to predict the trend of stock market index price and income change. The empirical results show that the index prediction model based on the combination of ARIMA and information granulation SVR has a great improvement in prediction accuracy and validity compared with the traditional time series model. It can predict the price fluctuation range of risk assets , such that it can be predicted reliably in a certain time period, but the range of time series fluctuation can not be accurately predicted. In the future, it is necessary to further study other prediction models and prediction techniques in order to effectively improve the accuracy and practical guidance of stock index trend prediction.

Management Science

Regional Influence Expansion Planning with the Background of the Belt and Road Initiative

DENG Fei, LU Yi-ping, SONG Jing-hong

2022, 31(5):  221-225.  DOI: 10.12005/orms.2022.0172

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Wisely planning the development of regional service-influence is crucial to an ambitious enterprise that faces a new market distributedin a newgeographic area. We assume that the service-influence of an enterprise can be represented by its geographically distributed footholds. A single foothold covers a limited geographic region. And at a specific time, the state of the development of the service-influence of an enterprise is the summation of all the regions covered by the enterprise's current footholds. We assume further that the enterprise is planning to cover a specific of area,which should be economically strong enough to compose a market, in a given period, but the enterprise is with limited resources and has to achieve its goal gradually. So, it is important for enterprise to make footholds in many well-known cities by effective and efficient location optimization in thedesired developing time span. To deal with this problem, an economic index evaluation modelbased on a time series forecasting methodis firstly proposed for city and region. Then an optimization modelwith cost and satisfaction as its goals is establishedby mainly using a coverage model, and the branch and bound method is used to solve the problem. Finally, weuse related data from the belt and road area to test the model, and the results show that the method has reference value for enterprises with related questions.

Research on the Relationship between PPP Participation and Enterprise Technological Innovation Based on Double Difference Model

WANG Ran, XU Yun-bao

2022, 31(5):  226-232.  DOI: 10.12005/orms.2022.0173

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Taking the enterprises listed in main board of the stock market from 2011 to 2018 as the research object, this paper analyzes the impact of listed enterprises'participation in PPP project on their own technological innovation level and further explores the regulatory effect of industry competition on participating in PPP projects and technological innovation of enterprises. The results show that, enterprises' participation in PPP project will inhibit enterprises technology innovation investment, and the deeper participation in PPP projects, the more obvious inhibition effect. The relationship between them is heterogeneous in science and technology industry and traditional industry, the participation in PPP projects helps to improve technological innovation of technology-based enterprises, but it is not conducive to improving technological innovation of traditional enterprises. Industry competition has a significant regulatory effect on the relationship between PPP projects and technological innovation of enterprises. With the strengthening of industry competition, the greater the positive correlation between PPP project participation and technological innovation of technology-based enterprises, the smaller the negative correlation between PPP project participation and technological innovation of traditional enterprises. Therefore entrepreneurs should have a long-term awareness, adhere to innovative development, and at the same time, regulatory authorities should make full use of the market competition mechanism to accelerate the transformation and upgrading of industries, and break the monopoly relationship.

Research on the Relationship between Total Rewards and Employee Innovation Behavior: The Role of Organization-based Self-esteem and Job Engagement

WANG Hong-fang

2022, 31(5):  233-239.  DOI: 10.12005/orms.2022.0174

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In recent years, the exact relationship and underlying mechanism between total rewards and employee innovation are still under debate without conclusive results. Based on the social information processing theory, this paper takes organizational self-esteem as the mediator and work engagement as the moderator to build up a two-stage moderated mediation model of total rewards and employee innovation. The author collects time-lagged dyad data of 470 non R&D employees and their leaders from 140 enterprises in multiple industries from China, The results show that total rewards have a significant positive impact on employee innovation and organization-based self-esteem. In addition, organization-based self-esteem completely mediates the relationship between total rewards and employee innovation. Furthermore, work engagement strengthens the relationship between total rewards and organization-based self-esteem as well as the relationship between organization-based self-esteem and employee innovation. Overall, work engagement amplifies the indirect influence of total rewards on employee innovation through organization-based self-esteem. This study reveals the mechanism and boundary condition of total rewards stimulating employee innovation in China.