Table of Content

25 January 2021, Volume 30 Issue 1

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Theory Analysis and Methodology Study

Canonical Duality for a Class of Nonmonotone Complementarity Problems

LIU Guo-shan, DING Bing-jie, DIAO Hai-can

2021, 30(1):  1-5.  DOI: 10.12005/orms.2021.0001

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We construct a canonical dual problem for a class of non-monotonic complementary problems with a wide range of applications. The dual problems can be written as complementary problems with the same structure to the original problem. We discuss the relationship between the solution of the dual problem and that of the original problem. Then we transform the dual problem into a one-dimensional optimization one, which not only can be easily solved, but also provides a very intuitive research tool for studying the properties of this kind of problem. Finally, we give a few examples to demonstrate the properties of the dual problem.

Disruption Management Model Based on Customer Lifetime Value under Travel Time Delay in Distribution

DING Qiu-lei, HU Xiang-pei, QI Fei, JIANG Yang

2021, 30(1):  6-12.  DOI: 10.12005/orms.2021.0002

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It is difficult to generate a new distribution plan for minimizing the negative impact under accidental travel time delay. In such cases, continuing with the original plan may not be optimal or feasible. First of all, the method to measure the deviation is presented by taking the customer lifetime value into consideration. Then, a disruption management model is constructed by combining the deviation cost and original objective, and a heuristics is proposed to solve the above model. Finally, the computational result proves that our approach is more practical and valid than the existing rescheduling. The proposed approach presents a new idea to analyze and measure the deviation cost in the field of disruption management, and provides a useful tool of quantitative analysis to obtain the plan that minimizes the negative impact.

Coordination of Supply Chain with Option Contracts Based on Profit-CvaR

HU Zhong-quan, TIAN Jun, SHEN Ao, FENG Geng-zhong

2021, 30(1):  13-22.  DOI: 10.12005/orms.2021.0003

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Based on a two-level supply chain composed of a risk-averse retailer and a risk-neutral supplier, the paper takes the weighted average of conditional value at risk (CVaR) and expected profit as the retailer's objective function to study the ordering strategy and supply chain coordination under option contracts, and compares with the situation when the retailer takes CVaR as objective function. After giving the retailer's optimal ordering strategy at different risk aversion levels, the paper further derives the corresponding conditions of supply chain coordination, and analyzes the effects of option price, retailer' risk aversion and expected profit weight on the profits of both the retailer and the supplier. It is found that the effect of retailer's risk aversion on their profits is different from the situation when the retailer takes CVaR as objective function, but the option price still plays a role in distributing the profits of the whole supply chain. The conclusion that the increase of retailer's expected profit weight reduces his own profit and improves the supplier's profit is also derived. Finally, the above conclusions are verified by numerical simulation.

An Extended Global PCPAlgorithm for Linear Bilevel Programming

YANG Jing-lei, LUO Mei-feng, YUAN Shuai-shi

2021, 30(1):  23-28.  DOI: 10.12005/orms.2021.0004

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After reformulating the linear bilevel programming model into a single level problem with the K-T conditions, we introduce a parameter into the upper level objective function to construct the Parametric Linear Complementary Problem (PLCP), whose properties are discussed in this paper. Then an extended Parametric Complementary Pivot (PCP) algorithm is proposed based on some modifications of the rules for determining the entering basis variable in Lemke's Algorithm after introducing a sufficiently small positive numberε. The extended PCP algorithm, which maintains the original advantages of the complementary pivoting approach, can achieve the global optimal solution. The computational results of two examples demonstrate that this algorithm is effective.

Research on Carbon Reduction Optimization Strategy and Coordination Mechanism in Consideration of Corporate Social Responsibility

LIN Huan, MA Cheng, SUN Qi, LI Dan

2021, 30(1):  29-35.  DOI: 10.12005/orms.2021.0005

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Based on the perspective of corporate social responsibility(CSR), this paper studies the optimal strategy and supply chain coordination for a two-stage supply chain composed of a manufacturer who producing low-carbon products and a retailer. By constructing the utility function with the members of the supply chain having social responsibility,we analyze the impact of CSR on the profits of each member and environment.We find that both manufacturers and retailers show social responsibility by reducing carbon emissions.If the manufacturer or the retailer has social responsibility, the profit of the supply chain increases. The designed contract(RC contract)about revenue-sharing and cost-sharing enables both the manufacturer and the retailer to achieve a win-win situation(pareto optimality). Retailers should bear more social responsibility to reduce carbon emission levels.

Research on Resource Allocation Optimization of Synergetic Development in Beijing-Tianjin-Hebei Region

QU Chong-chong, WANG Jing, HE Ming-ke

2021, 30(1):  36-42.  DOI: 10.12005/orms.2021.0006

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Coordinated development for the Beijing-Tianjin-Hebei region as a national strategy reveals the importance of regional coordinated construction. Beijing-Tianjin-Hebei's district is adjacent and disasters which influence the region is similar.In this paper, a multi-objective programming model which contains the economics and fairness targets for multi-stage and multi-disaster emergency distribution center location is established. And an immune algorithm is designed to establish the model. Based on the scenario probability of natural disaster in the region, the validity of the model and the algorithm is verified, which provides theoretical guidance and scientific decision-making for the optimal allocation of emergency resources in coordination between the Beijing-Tianjin-Hebei region and even the world urban agglomerations.

Salp Swarm Algorithm Based on Statistical Guidance and Polynomial Difference Learning

LIU Xiao-long, XU Yan, XU Wei-jun

2021, 30(1):  43-49.  DOI: 10.12005/orms.2021.0007

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The Salp Swarm Algorithm(SSA)has better robustness and optimization capacity than the traditional swarm intelligence optimization algorithm. However, there are still some defects such as the limited global optimization ability, low execution efficiency and easily running into the local extreme value. In allusion to these problems, this paper proposes a new method of polynomial differential learning strategy to distinguish and improve the traditional linear difference method, and also designs a random population partition method to make the information transfer uniformly in the neighborhood topology. In addition, we define the global exploration operator and local development operator of polynomial difference learning, and introduce the statistical guiding coefficient A to develop different polynomial learning methods, thereby further improving the global search ability and optimization precision of the algorithm. Finally, the numerical comparison experiments and practical problem tests are made to confirm the superiority and robustness of the improved algorithm, and expands the application range of the original algorithm.

Multi-criteria Decision Making Method with Probability Linguistic Weight Information Based on Design of Experiment

ZHAO Meng, ZHANG Chen-xi, QIN Jin-lei, ZHANG Bing

2021, 30(1):  50-56.  DOI: 10.12005/orms.2021.0008

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As a kind of fuzzy language sets, the probability language sets can reflect the importance and the probability ofevaluation criteria weights, which is more practical in decision-making problems. In this paper, the design of experiment(DOE)method is used to study the multi-criteria decision-making problems given by probability language. Firstly, by simulating the importance and probability of weight repeatedly, the multiple weight of experiment can be designed. Secondly, the GRA method is used to obtain the scores of each experimental data and the most applicable regression equation describing the influence of relationship between the criteria value and the evaluation results of the decision-making problems can be obtained. Then the actual data of the decision-making problems is brought into the equation to calculate the ranking orders of alternatives. Finally, the proposed method is applied to two cases, includingrapid prototyping process andflexible manufacturing system process, to illustrate the application and feasibility of the method. The results show that the proposed method is appropriate to deal with the multi-criteria decision-making problem based on probability linguistic weight information.

Two-sided Matching Decision Based on Triangular Intuitionistic Fuzzy Number Information

YUE Qi, ZHU Jia-gui

2021, 30(1):  57-62.  DOI: 10.12005/orms.2021.0009

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The two-sided matching problem based on triangular intuitionistic fuzzy number information is studied. First, the theories on triangular fuzzy numbers and two-sided matchings are given. Then, the multi-objective two-sided matching model under the constraint of one-to-one two-sided matching is established, where the triangular intuitionistic fuzzy number satisfaction degrees of agents are the objective functions. The multi-objective two-sided matching model can be transformed into a single-objective two-sided matching model by using the linear weighting method and the triangular fuzzy number centroid method. Moreover, the “best” two-sided matching scheme can be obtained through solving the single-objective two-sided matching model. The feasibility and practicability of the proposed two-sided matching decision is proved by the matching example between venture capitalists and venture capital enterprises.

State-owned Enterprises' Supplier Selection Based on the Consideration of Policy Burden and Economic Goals

WU Yang, YAO Jian-ming, TONG Chang-zhe

2021, 30(1):  63-70.  DOI: 10.12005/orms.2021.0010

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State-owned enterprises' commitment to policy burdens is often at the cost of their economic benefits, thus maintaining a balance between policy burdens and economic goals is significant for the sustainable development of state-owned enterprises. The selection of suppliers of state-owned enterprises is one of the key operating strategies that affect the balanced development of their policy burden and economic goals. Among them, the nature of supply chain members and their role in improving employment, pensions, and social stability are important factors influencing the state-owned enterprises' policy burden; the capacity of supply chain members has a significant impact on the economic indicators of state-owned enterprises. To comprehensively optimize the policy burden and economic goals of state-owned enterprises, this article first translates the the policy burden of the state-owned enterprises into a series of non-economic goals and quantifies them. On this basis, a supplier optimization model with non-economic indicators and economic indicators as optimization objectives is constructed, and a solution algorithm is constructed. Finally, an example is given to verify the effectiveness and feasibility of the model and algorithm. The result shows that the supplier selection model constructed can effectively optimize the economic goals and the policy burdens of state-owned enterprises.

A Historical Review for Research Methodology of Generic Competitive Strategies ——A New Research Framework Based on Game-constrained Optimization Modelling

CHEN Qi

2021, 30(1):  71-81.  DOI: 10.12005/orms.2021.0011

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This paper reviews the history of empirical research of generic competitive strategies from a unique perspective, and pays attention to the introduction and application of Palepu assumptions for strategy identification and strategic mathematical analysis for the first time. Then, the paper indicates the key problems of in this area. And, it also overviews the breakthrough in the analytical modeling for generic strategies and the advances of relative empirical research, finding the opportunity faced by unconventional theoretical constructive research. Furthermore, the paper forecasts that the game modeling of generic strategies, the analytical verification of Palepu assumptions and its related empirical studies may become a research front. Lastly, we propose the new interdisciplinary research framework for this area which involves strategic management, financial management and game theory.

A New Characterization of the Shapley Value on Minimum Cost Spanning Tree Games and Its Application

SHAN Er-fang, WU Mei-hui, LIU He-yu

2021, 30(1):  82-86.  DOI: 10.12005/orms.2021.0012

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In 2002, Kar characterized the Shapley value on minimum cost spanning tree games by using four axioms: efficiency, absence of cross subsidization, group independence, and equal treatment. This paper introduces a new axiom, called “group efficiency”. Combining it with “equal treatment”, we propose a new characterization of the Shapley value on minimum cost spanning tree games. Finally, we analyze the allocation of network service cost by the Shapley value on minimum cost spanning tree games.

Intuitionistic Linguistic Hamacher Weighted Aggregation Operators and Their Application

YANG Yi, LI Yan-lai, DING Heng, LV Hong-xia

2021, 30(1):  87-93.  DOI: 10。12005/orms.2021.0013

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Some intuitionistic linguistic Hamacher weighted aggregation operators with parameter are investigated. The Hamacher operations for intuitionistic linguistic numbers are defined via application of Hamacher t-norm and s-norm. And then, by using these operations, the intuitionistic linguistic Hamacher weighted averaging operator and geometric operator with parameter are proposed. and their properties are also discussed. Furthermore, the relationship between the operators and parameter are analyzed such as the monotonicity of operators and limiting cases of operators with respect to parameter. And the decision making approach is provided based on the developed aggregation operators, and an example is furnished to demonstrated the applicably and effectiveness of the method.

Research on Improved VIKOR Method Based on Fuzzy Measure of Association Criterion

JIANG Wen-qi, YUAN Ya-chun

2021, 30(1):  94-98.  DOI: 10.12005/orms.2020.0014

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Under the multi-criteria decision making environment, it is helpful to clarify the influence mechanism of criterion relevance on decision making results, so as to improve the reliability of decision making results. Firstly, the shapley value and interaction coefficient of the fuzzy measure representation of the association criterion are elaborated. Secondly, based on the VIKOR method, the influence law of the association criterion on the group utility value and the variance and the individual regret value is analyzed deeply, and three important properties are presented and an improved VIKOR method with criterion interaction coefficients is proposed. Finally, a comparative study of the examples highlights the superiority of the method.

Resource Leveling Algorithm Based on Decisive Factor Analysis of Duration in LOB

ZHANG Li-hui, WANG Ke-ke, CHAI Jian-xue, DAI Gu-yu, QI Jian-xun

2021, 30(1):  99-106.  DOI: 10.12005/orms.2021.0015

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Resource leveling is a classic scheduling problem in repetitive projects. This paper presents a method of resource leveling for repetitive projects in line of balance (line of balance, LOB). Firstly, it proposes a method to determine the critical path in LOB, and determines the critical path and critical activities types. Then, it analyzes the determinants of the project duration, and studies the characteristics of different types of critical activities, and the relationship between the total duration and resource adjustment. It proves that due to the existence of special activities, namely, the backward critical activity and the point critical activity, resource optimization can be achieved by adjusting critical activities and non-critical activities simultaneously under the premise of ensuring the project duration. According to this idea, the paper designs the genetic algorithm for resource leveling in LOB. Finally, an illustrative pipeline project is used to demonstrates the optimization performance of resource leveling model. The resource leveling ideas and algorithms proposed in the paper can help project planners to expand the resource optimization space and achieve better resource leveling effect.

Application Research

Research on the Spatial Spillover Effect of Total Factor Productivity in China's Light Industry: Analysis Based on Spatial Measurement and Social Network

YAN Xin, ZHU Fu-yun

2021, 30(1):  107-113.  DOI: 10.12005/orms.2021.0016

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Based on the data of China's light industry province total factor productivity by Malmquist index model, we use spatial measurement methods and social network analysis methods to explore the spatial correlation characteristics and spatial spillover effects of China's light industry total factor productivity, from a global and regional perspective to examine light industry in the region coordinated development. The study finds that the growth of total factor productivity of regional light industry is spatially related. Light industry is closely connected in various regions. Its network structure is strong, with high permeability, good stability and asymmetric accessibility. Light industry can be divided into four functional blocks, net spillover, main spillover, main beneficiary, and net beneficiary, which present an obvious feature of “ladder spillover”.

Evaluation of Innovation Ability of Chinese Shipbuilding Listed Companies from the Perspective of Civil-Military Integration

GUO Tao, WANG Song, LI Pan-pan, GUO Zhe

2021, 30(1):  114-120.  DOI: 10.12005/orms.2021.0017

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The national strategy of civil-military integration has given the shipping industry a new historical mission and set new demands on the building of innovative capabilities of the shipping industry enterprises. In order to scientifically evaluate the innovation capability of shipbuilding industry in the context of civil-military integration, this paper constructs an evaluation index system for innovation capability of shipbuilding industry, and the data of nineteen listed companies are analyzed by entropy weighted TOPSIS method. We put forward the innovation management inspiration of shipbuilding industry from the perspective of civil-military integration.

Solving a Static Bike Repositioning Problem with Multiple Depots

SUN Zhuo, LI Yi-ming

2021, 30(1):  121-129.  DOI: 10.12005/orms.2021.0018

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Shared bike has been developing rapidly in China, encouraging people to cycle and use this low-carbon transport mode to make trips. Accelerating the development of shared bikes is an important way to solve the last mile, urban congestion and environmental pollution problems. With the irregularity of people parking share bikes, the station inventory is unbalanced in the shared bike system. How to optimize the station inventory to meet user demand that must be solved by related companies. The repositioning routing optimization of shared bikes is a key mean to realize the reasonable inventory level at stations. This paper investigates a static bike repositioning problem (SBRP) with multiple depots, and a mixed-integer nonlinear programming model is proposed. Different from the objective function of cost or time used in the path optimization problems, this paper uses the nonlinear penalty objective functions based on station inventory to describe user demand, leading to a convex optimization problem. In order to simplify our problem, we utilize a piecewise linear function to linearize the objective function. Based on characteristics ofstationnetwork,avariableneighborhoodsearchalgorithm(VNS)andagreedyalgorithmforconstructing the initial solutions are designed to solve our problem. Finally, a case study of a shared bike company is presentedtoaccountfortherationalityandeffectivenessofthemodelandalgorithm.

A Model for Knowledge Diffusion in Communities of Practice and Its Simulation

LI Bai-zhou, ZENG Jing-wei, DONG Heng-min, WANG Dan

2021, 30(1):  130-139.  DOI: 10.12005/orms.2021.0019

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The efficiency and effect of knowledge diffusion affect the creative ability of the communities of practice. Considering the influence of knowledge heterogeneity on knowledge diffusion in communities of practice, this paper introduces knowledge niche, compares the degree of overlap of knowledge niche of members in communities of practice, and constructs a knowledge diffusion model of the communities of practice. It defines the different situations of the interaction among members of the communities of practice, solves the knowledge diffusion model, gets the corresponding stable equilibrium points, and uses phase diagram analysis method to verify it. Finally, we use MATLAB to do numerical simulation. The results show that the degree of overlap of the knowledge niche has an important effect on knowledge diffusion. The degree of influence among the members of the communities of practice greatly influences the equilibrium point of the knowledge diffusion model. When the knowledge of the members in the communities of practice is complemented, it is the most efficient and effective form to knowledge diffusion. The research results provide a theoretical basis for promoting knowledge diffusion in communities of practice.

Research on Airline Customer Clustering Based on Improved Silhouette Coefficient Method

MA Xin, DUAN Gang-long, WANG Jian-ren, XUE Hong-quan

2021, 30(1):  140-146.  DOI: 10.12005/orms.2021.0020

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In view of the fact that the airlines evaluate the clustering effect in the clustering of customers and determine the best k-valued contour coefficient method, the time complexity is too high (O2) and the accuracy is low, firstly, the paper proposes an improved contour coefficient method, which uses the distance calculation between objects and clusters or different cluster centers to replace the distance calculation between similar or heterogeneous objects, and determines the contour coefficient adjustment position and weight adjustment by the clustering effect change rate; secondly, the paper builds a clustering model based on real-time airline customer data after pre-processing and feature selection, and determines the optimal customer grouping by means of improved contour coefficient method, and then constructs user profiles; finally, the paper describes the characteristics of different airline group customers and proposes corresponding personalized service measures to assist airlines to provide personalized products and services to customers. The results show that the accuracy of the improved contour coefficient method under different sample sizes is significantly improved and the operating efficiency is significantly improved and the airline customer grouping results, which are based on the improved contour coefficient method, are in line with objective reality, and the proposed service measures can provide reference for airlines to maximize customer demands and increase customer satisfaction.

Based on GARCH Method Research the Influence Mechanism of the Financial Shocks on the Inefficient Investment

ZHU Guan-ping, HU Wen-xiu, LI Xiao-yun

2021, 30(1):  147-153.  DOI: 10.12005/orms.2021.0021

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Agency theory believes that managers will make inefficient investment behaviors that deviate from the maximization of firm value in a turbulent and uncertain environment. In order to explore whether the financial shocks, a uncertain factor, will worsen the company's inefficient investment behavior, this paper first uses a mathematical model to illustrate the possible relationship between the financial shocks and inefficient investment. Then, the conditional heteroscedasticity of the GARCH method is applied to measure the three latent variables of financial shocks, which are the stock market shock, monetary shock and exchange rate shock. Finally, this paper examines the relationship between the three potential variables of the financial shocks and the inefficient investment. The research finds that the monetary shock and exchange rate shock can significantly increase inefficient investment, while the stock market shock can remarkably reduce inefficient investment. Further research shows that the monetary shock and exchange rate shock can increase inefficient investment behavior by significantly increasing excessive investment. The stock market shock can reduce inefficient investment behavior by significantly reducing underinvestment.

Impact of WeChat Community Interaction on Users' Financial Product Portfolio Risk Decisions

TANG-Chao-ying, XIAO Xiang-yu

2021, 30(1):  154-162.  DOI: 10.12005/orms.2021.0022

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How the WeChat community affects clients'purchase decision of financial product is an important theoretical issue in the current field of financial product marketing. Based on the Valence Framework theory, this study proposes a model for the relationship among perceived risk, perceived benefit and clients'purchase decisions of the risk of financial product portfolio (PDRFPP). The influence of clients' WeChat community interaction on their PDRFPP is also introduced into the model. Based on the questionnaire data of 287 clients' investment bahaviors, the corresponding interaction behaviors data of 129 WeChat communities, and clients' the actual purchase data of financial products, we find that clients' PDRFPP is affected by their perceived risk and perceived return. Moreover, the interaction frequency of WeChat community negatively affects the negative relationship between clients' perceived risk and their PDRFPP.The negative emotions of WeChat community will strengthen the negative influence of clients' perceived risk on their PDRFPP, and weaken the positive influence of clients'perceived benefit on their PDRFPP. The finding expands the perspective of factors for the clients'financial product purchase decisions. It also has reference value for client management of financial products.

Research on the Direction of Stock Return Rate Using Data Mining Method

GOU Xiao-ju, WANG Qian

2021, 30(1):  163-169.  DOI: 10.12005/orms.2021.0023

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A data mining algorithm is proposed to study the direction of stock return rate. Firstly we use wavelet decomposition to get data under different frequency, threshold filter to reduce the noise of high frequency data. andXGBoost and other machine learning methods to analyze the components of CSI 300 and CSI 500. The result shows that XGBoost is highly accurate, with the accuracy of 54.69% and 55.13% respectively. At the same time, the investment strategy constructed can yield steady returns,meaning that this data mining algorithm is useful. On this basis, this paper makes up for the “black box” problem and tries to know the logic of stock selection in the model. Firstly, the relative importance of each indicator is measured, and we find that OBV、PB and PE are relatively important.Then the marginal effect of various features on direction of return rate are measured through the partial dependence analysis and we get some conclusions such that the model tends to select the stock with low PE and PB, which makes the algorithm more logical.

Researchon Risk Predictionof P2P Lending Platform

LIANG Shuang, DIAO Jie-wen, XIAO Bang

2021, 30(1):  170-176.  DOI: 10.12005/orms.2021.0024

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Big data and machine learning have gradually emerged in the field of bankruptcyprediction and risk prediction.In this paper, python is used to obtain 16815 pieces of data from 885 online lending platforms. Through factor analysis and model verification, several characteristics that can better evaluate the risks of P2P platforms are mined.In addition, Logistics regression, support vector machine, BP neural network, LightGBM and fusion model are established through the selected indicator system for learning and training, and the fusion model obtains the highest accuracy in the test set, which shows that the fusion model established in this paper can better evaluate the risk of online lending platform. Then, we select one decision tree to draw and rank features in order of importance. We select ten features that are important for identifying problem platforms. Thispaperis of great reference significance fo rinvestors to choose safe platforms for investment or regulators to choose key platforms for supervision.

Reforms of the Foreign Exchange Management System and the Volatility in Foreign Exchange Market: A Perspective from the Big Player Theory

GUO Xin-shuai, ZHANG Zhi-yue, JU Shan

2021, 30(1):  177-183.  DOI: 10.12005/orms.2021.0025

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The central bank's activities in foreign exchange market have a significant impact on market volatility. This paper, using the “big player theory” based on subjective expectation, explains differences of fluctuation of RMB exchange rate before and after China's reform of the foreign exchange administration system in 2005 and 2015. The central bank just plays the role of the “big player”. After reforms of foreign exchange administration system, the central bank's role as a “big player” has gradually weakened, causing less fluctuation and improving efficiency in the foreign exchange market. R/S analysis in the paper lends support to our explanation.

Subspace Multiple Kernel Learning Methods for Prediction of Financial Distress

ZHANG Xiang-rong

2021, 30(1):  184-191.  DOI: 10.12005/orms.2021.0026

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Heterogeneity of financial indicators is an important factor affecting the accuracy of financial distress prediction. Existing multiple kernel learning (MKL) methods can be used to solve the problem of heterogeneous data learning. Firstly, this paper introduces the theoretical framework of financial distress prediction based on subspace MKL. On this basis, three subspace MKL methods are proposed according to the maximization variance criterion, the maximization of class separability criterion and the principle of non-linear subspace mapping. They are maximization variance projection subspace MKL, separability maximization subspace MKL, and nonlinear subspace MKL, respectively. Using the collected data of Listed Companies in China, the proposed methods are compared with the existing representative financial distress prediction methods, and the experimental results are analyzed. The experimental results show that the proposed subspace MKL financial distress prediction framework is effective, and the subspace MKL prediction methods constructed under this framework can effectively improve the accuracy of financial distress prediction.

Effect of Over-standard Performance Incentive for Teachers on Developmental Direction and Outcome of Universities

YU Bin, YU Xiao-tong, CAO Rong

2021, 30(1):  192-197.  DOI: 10.12005/orms.2021.0027

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This paper takes the performance income of university teachers in the Yangtze River Delta and nearby areas as the sample, and analyzes the impact of teachers' over proof salary incentive on the development results of colleges and universities from three aspects of teachers' over proof performance incentive based on the development direction of universities. The results show that the university should try its best to standardize the performance incentive when choosing the teacher performance incentive mode. It has a certain practical significance for the design of salary incentive system of university teachers.

Agent's Optimal Response and the Performance of Step-wise Incentive Contract

GU Chao-cheng, ZHOU Zi-xuan, DENG Shi-ming, LI Yan-hai

2021, 30(1):  198-203.  DOI: 10.12005/orms.2021.0028

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This paper investigates an agent's response to a simple stepwiseincentive contract and the optimal contract design. We characterize agent's optimal effortunder a general demand distribution and utility function. For an agent with concave utility, athreshold exists such that the agent's optimal effort switches from zero to a higher level if the incentivebonus exceeds this threshold. Further, this bonus threshold increases with the performancetarget and agent's marginal cost. The results stress the importance of identifying how bonus incentiveshould be coordinated with performance target in designing an effective step-wise incentivecontract. When agents are risk-averse, we show that the step-wise contract always outperforms alinear contract or piece-wise linear threshold contract if the performance of the agent only dependson his effort.

Strategies of Durable Equipment on-line Leasing Problem Based on Risk-reward Models

LIU Bin, WU Fan, XIN Chun-lin

2021, 30(1):  204-208.  DOI: 10.12005/orms.2021.0029

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The optimaldeterministic strategy from traditional online algorithm and competitive analysis theory is a risk-free strategy, but it has certain limitations. However, in reality many people are willing to increase their risk for some extra income. In this paper, we investigate risk-reward models of durable equipment on-line leasing problem by combing transaction cost and the fact that there exists a secondary market. Risk-reward models are an expansion to the optimal deterministic strategy, and the risk-reward strategy based on probabilistic forecast is also an expansion to the risk-reward strategy based on certain forecast. Numerical analysis shows that theperformance of the risk-reward strategy can be significantlyimproved, thusaccording to their risk tolerance and prediction, the optimal leasing strategy can be selected.

Management Science

Credit Rating Model of Small Industrial Enterprises Based on Information Gain

ZHOU Ying

2021, 30(1):  209-216.  DOI: 10.12005/orms.2021.0030

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The credit rating is a measure of the likelihood for a debt default, and an assessment of the debt default risk. This paper uses the information gain to establish a credit rating model, and conducts an empirical analysis of the loan data of small industrial enterprises. Our contribution has three folds. First, according to the idea that the larger information gain, the greater performance of the default identification, we select the indicators that have a greater impact on the default status. The shortcomings of the existing research that does not take the default discrimination ability as indicator selection criterion are changed. Second, for a pair of indicators with a high correlation, we delete the indicator with a small information gain, so as to not only avoid the information redundancy between indicators, but also deleting indicators with greater default discrimination ability. Third, we use the information gain value to weigh the indicators to ensure that the indicators with greater default discrimination capabilities have greater weights. It has changed the disadvantages of the existing research in weighting for indicator. The empirical results show that the 31 indicators selected in this paper, including asset-liability ratio, industry prosperity index, and pledge guarantee, have significant default discriminant ability. Solvency is a key factor affecting the credit rating of small industrial enterprises.

Transformational Leadership, Knowledge Sharing and the Creativity of the R&D Team: A ∩ Moderating Role of Team's Membership Heterogeneity

YANG Hong, PENG Can, LI Rui-xue, YANG Xiao-na, LV Chao-lin

2021, 30(1):  217-224.  DOI: 10.12005/orms.2021.0031

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Based on the theory of transformational leadership, knowledge sharing, team creativity and membership heterogeneity, this paper studies the influence of the transformational leadership on the creativity of high-tech enterprise R&D team, introduces knowledge sharing as a mediator variable to examine its mediating effect, and proposes an mixed model with ∩ moderating effect to explore the ∩ moderating effect of team's membership heterogeneity. By the empirical research on 162 high-tech enterprises, we get the following main conclusions: the transformational leadership has a significant positive impact on the creativity of the R&D team; knowledge sharing plays a partial intermediary role between the transformational leadership and the creativity of the R&D team. Team's membership heterogeneity plays a ∩ moderating role between the transformational leadership and knowledge sharing, and between knowledge sharing and the R&D team creativity.

Excess Control and Corporate Cash Holdings ——A Moderating Effect Based on the Control of Family Founder

ZHANG Tao, LI Bing-xiang

2021, 30(1):  225-233.  DOI: 10.12005/orms.2021.0032

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Based on the agency cost theory and dynamic trade-off theory, this paper selects the data of listed companies in Shanghai and Shenzhen A-shares from 2007 to 2017, and empirically tests the internal relationship between the founder control of family enterprises and the level of cash holdings. The study finds that: (1)the family over-control is significantly positively correlated with the cash holding level; (2)the family controlled by founders, can effectively inhibit the impact of family over-control on cash holdings. (3)The further study indicates that, the cash holding level of the founder controlling family business in China is significantly lower than that of the non-founder controlling family business.These conclusions not only support the “rent-seeking view” of family control at the micro governance level, but also reveal the positive role played by founders in the corporate governance of family enterprises to some extent.

Analysis of Multistage Parallel Manufacturing Process Capability Based on Utility Ratio

WANG Ning, YAN Na, ZHANG Shuai, LIU Yu-min, YANG Jian-feng

2021, 30(1):  234-239.  DOI: 10.12005/orms.2021.0033

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In practical production, multistage process usually contains series and parallel structures, the multistage manufacturing process with series and parallel hybrid structure is the most common form in practice, and in the parallel structure with different modes, the effect of the quality variation in the upstream process on the downstream process and the total process capability is different. According to the characteristics of the multistage process with parallel structure, process capability in the parallel multistage process with parallel, disperse, and convergence three basic patterns is analyzed. Based on the perspective of variation decrease, the influence of the variation of each sub-process on the overall process capability in multistage manufacturing is studied. The effect of quality improvement is evaluated according to the “difficulty”and“utility ratio”of reducing quality variation of each sub-process.Then the basis for selecting the strategy of multistage process capability improvement is given and an example is provided to illustrate it. The results show that the method can identify the different influences of the quality variation reduction of each process on process capability of this process and total process capability, determine the priority of quality improvement, and then realize the economic quality improvement and optimization of the multistage manufacturing process.