Table of Content

25 December 2018, Volume 27 Issue 12

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Theory Analysis and Methodology Study

Cooperation Strategies for Supply Chains with Hybrid Sales Channels

LIN Gui-hua, LIU Rui, ZOU Yuan-yang

2018, 27(12):  1-9.  DOI: 10.12005/orms.2018.0273

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In this paper,we study the effects of different cooperation strategies with dual channel manufacturers on pricing and profits of a supply chain with hybrid sales channels by means of the Stackelberg game theory. It is shown that in the cooperation with dual channel manufacturers, the cooperation strategies not only increase the profit of the cooperative alliance, but also the profits of other members out of the alliance. Moreover, the more enterprises are involved in cooperation alliance, the greater the total profit of the supply chain. In addition, if the number of members in a cooperative alliance is fixed,the vertical cooperation brings more profit to the supply chain than the horizontal cooperation. Finally, we obtain similar conclusions by numerical experiments.

Supply Chain Financing Strategies for a Capital Constrained Supplier with Yield and Demand Uncertainty

PENG Hong-jun, PANG Tao

2018, 27(12):  10-18.  DOI: 10.12005/orms.2018.0274

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We consider a supply chain containing a capital constrained supplier and a retailer, where the retailer faces the demand uncertainty and the supplier faces the yield uncertainty. We propose the concept of excepted interest rate and a coordination mechanism of advance payment. Based on this, we analyze the optimal strategies of financing, ordering and production under the bank financing case and the advance payment coordination mechanism. The result shows that the retailer is always willing to finance the supplier by advance payment with the expected interest rate which is not higher than the bank loan interest rate; through negotiating an appropriate level of the expected interest rate of the advance payment, the advance payment coordination mechanism can realize Pareto improvement in the supply chain system over the bank financing.

Research on the Combination Model of Supply Chain Financing and Credit Insurance Based on Risk Aversion

JIN Wei, LUO Jian-wen

2018, 27(12):  19-27.  DOI: 10.12005/orms.2018.0275

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Based on the supply chain constraint problem, this paper considers a financing system consisting of a capital-constrained retailer, a capital-unconstrained supplier, a risk-averse bank and an insurance company. We first build a risk-averse bank financing model and the combination model of bank financing and credit insurance, respectively. Then we provide the optimal decisions of the financing system members under the two models. Our study shows that the combination model of bank financing and credit insurance can effectively increase the retailer’s credit size as well as decrease the bank’s loss risk in comparison with the traditional risk-averse bank financing model. Therefore, the combination model of bank financing and credit insurance can bring strict Pareto improvement to the financing system. Finally, we use numerical examples to examine the effectiveness of the conclusion.

Ship Scheduling Optimization in One-way Channel Bulk Harbor

ZHENG Hong-xing, LIU Bao-li, DENG Chun-yuan, FENG Pan-pan

2018, 27(12):  28-37.  DOI: 10.12005/orms.2018.0276

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To improve the utilization rate of berths in one-way channel bulk harbor, ship scheduling optimization of the bulk harbor with multi-harbor basin is studied. The need to maintain safe navigation distance of ship in/outbound harbor, in/outbound harbor time alternating conditions and ship in/outbound harbor in cluster is considered. A mixed integer linear programming model is established to minimize the waiting time of the ship in the port. Based on the characteristics of the problem, heuristic rule combined with simulated annealing algorithm is designed to solve the problem. The initial population is constructed by solving four sub-problems: the number of inbound ships, the inbound order, the number of outbound ships and the outbound order. The algorithm integrates the neighborhood transformation operator, the times of dynamic internal circulation and the dynamic cooling coefficient to improve the search performance of the algorithm. In the numerical experiment, the results of algorithm are compared with the lower bound and the two practical scheduling schemes. The results show that the average relative deviation between the result of hybrid algorithm and the lower bound is 5.28%. Compared with the two practical scheduling plans, the average optimization rate is significantly improved as well as the average berth optimization rate is 6.74% and 4.71% respectively. Finally, the validity of the scheme and the algorithm is validated.

Optimization Method of Passenger Vehicle Transportation Network Based on Orthogonal Experimental

QIN Lu, LIU Hong-chao, SUN Zhi-yuan

2018, 27(12):  38-46.  DOI: 10.12005/orms.2018.0277

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In the context of the Ministry of Transportation to control the road overrun transport, this paper studies the problem of network optimization under multimodal transport mode of passenger vehicle logistics enterprises, and taking the minimum cost of transportation network as the goal, taking into account the logistics timeliness, hub node capacity and economies of scale and other factors, the transportation network optimization model is established based on hub and spoke theory, and a hybrid intelligent optimization algorithm is proposed. Orthogonal test is designed to solve the problem of multi parameter and multi-level optimization, and the three key input parameters of model are hub node number, hub node capacity and scale effect discount coefficient, which effectively reduces the solving multiple parameters level optimization problem of work, and it provides a new way to determine the reasonable values of each parameter. The results show that: Hub node capacity, discount coefficient and hub number, the three input parameters have the order of influence on optimization results, and the degree of influence decreases successively; moreover, only the hub node capacity and discount coefficient play a significant role in the total benefit of passenger vehicle transportation network. And a hybrid hub and spoke network structure and multimodal transport organization model are used to optimize the transportation network, and compared with the original “point to point” road transportation network, the total cost is reduced by 10%, so that it can effectively deal with the risks of administering highway overload both in operation management and cost control.

Research on Co-evolution Mechanism and Optimum Design of Regional Innovation System

MA Yong-hong, SU Xin, ZHAO Yue

2018, 27(12):  47-56.  DOI: 10.12005/orms.2018.0278

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In order to reveal the essence and law of the co-evolution mechanism of regional innovation system, based on the description of the self-organization characteristics on it, the paper selects the datum of basic generic technology innovation and institution innovation to do an empirical research, uses Minitab software to design system evolution plan and puts forward optimization measures. The results show that the representative quantity of basic generic technology innovation is the order parameter of the regional innovation system dynamic evolution; the basic generic technology innovation and the institution innovation have a synergistic effect on the evolution of regional innovation system, but the synergy is poor; the positive feedback mechanism with institution innovation incremental has the highest signal-to-noise ratio; the basic generic technology innovation can make the fastest response to institution innovation; when the parameterλ₂<0 of signal-to-noise ratio is the highest, a positive feedback mechanism of institutional innovation is formed, the parameters of a ,b,λ₁ should be less than 0 and try to keep the absolute value of parameter a maximum, and the regional innovation system will achieve the optimal level of evolution.

Object Multi-attribute Differences Based Grey Dynamic Clustering Method and Its Application

LIU Yong, ZHOU Ting, QUAN Bing-ting, LIU Si-feng

2018, 27(12):  57-63.  DOI: 10.12005/orms.2018.0279

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The behavior states of decision making objects and their classes from different period often take on a certain development law in the real decision-making problems, however, it is difficult for the existing clustering methods to fully exploit and extract the development information of clustering objects, related information between objects, and difference information of development attributes from clustering objects. To effectively deal with these problems, according to the trends and behaviors of the development and the attribute differences of the development amount and increment amount from the objects, the thought and method of GM(1,1) and gray fixed weight clustering is utilized to construct a novel object multi-attribute differences based grey dynamic clustering method, and then an example of the clustering problems on the regional high-tech industrialization in China tests and verifies the validity and rationality of the proposed model. The results show that the proposed model can well describe the development trends or future behavior of decision making objects, and realize the effective clustering of the decision making objects.

Research into the Average Loading Rate and 4-stage Algorithm of the Capacitated Vehicle Routing Problem

RAO Wei-zhen, LI Mei-yan, XUN Nan, WANG Bing-cheng, YU Hao, HOU Yan-hui

2018, 27(12):  64-72.  DOI: 10.12005/orms.2018.0280

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The capacitated vehicle routing problem(CVRP)is a classical combinatorial optimization problem, which generally minimizes the number of vehicles and distance discovered by vehicles. The average loading rate of vehicles is important when it is used to evaluate logistics level in the actual logistics distribution, and is directly affected by the customer’s demand quantity. This paper proves that the average loading rate of vehicles is ρ ∈(50%; 100%], and the more the consumers with demand quantity exceed and be close to 0.5Q, the lower the average loading rate is. A 4-stage algorithm is proposed based on Savings, Lin-Kernighan and Large Neighborhood Algorithm to solve CVRP and to identify the conclusion. Finally, the 60 CVRP instances with big demand are devised based on the 20 Golden CVRP benchmark instances (the number of consumers is from 200 to 483). Then we use the 4-stage algorithm to solve the 60 instances. The experimental results indicate that the theory analysis is scientific and reasonable, and the 4-stage algorithm is efficient and competitive in comparison with the previous heuristics. The average deviation of the solutions obtained with the 4-stage algorithm from the Bestknown solutions is only 0.92%.

An Improved Particle Swarm Optimization for Simultaneous Pickup and Delivery Vehicle Routing Problems with Time

MA Yan-fang, YAN Fang, KANG Kai, LI Zong-min

2018, 27(12):  73-83.  DOI: 10.12005/orms.2018.0281

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This article studies the vehicle routing problem with simultaneous pickup and delivery(VRPSPD)under a fuzzy random environment, considering the uncertainties in the operational environment, the customer’s time requirements, and the situation of simultaneous pickup and delivery for customers. A mathematical model is formulated for the uncertain VRPSPD, where the objectives are to seek the most economic route for each vehicle with the minimum operational cost and to maximize the customer satisfaction in the same time. In this model, the fuzzy random theory is used to describe the double uncertainties in the decision environment, namely assuming the delivery amount(customer’s demand)and pickup amount are fuzzy random variables. And then, an improved hybrid particle swarm optimization with fuzzy random simulation is proposed to solve the model. Chance constrained operator is used in constraints to deal with the random fuzzy variables in this model. More specifically, to adapt to the mathematical model and improve the algorithm performance, this approach makes improvements and modifications in encoding and decoding, multi-objective handling, and particle updating. The encoding and decoding are suitable for the VRPSPD, multiple fitness functions are used to deal with the multi-objectives, and the improved update function can help overcome the shortcomings of the basic particle swarm optimization(PSO). Finally, in the case study, parameter tests and results analysis are presented to highlight the performance of the optimization method, and algorithm comparison demonstrates its efficiency.

Probability Rule Mining in Emergency Cases Based on Rough Set

WANG Ning, LIU Hai-yuan, ZHOU Xue-ke

2018, 27(12):  84-94.  DOI: 10.12005/orms.2018.0282

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As texts describing the process of occurrence, development and response of emergencies, emergency cases contain underlying laws and valuable experience. In order to mine the potential relationship among the elements in the emergency cases, the probability rule mining method based on rough set is developed. First, we build a knowledge quintuple to describe the common features of emergency cases, and the information of emergency cases are organized into a decision table; then we use genetic algorithms to reduce the attributes of the decision table of emergency cases, and thus the probability rules can be acquired. Finally, taking the case of 50 cases of heavy fire in Daxinganling forest area as an example, the concrete implementation process of the method is expounded, and two groups of testing experiments prove the feasibility and validity of the method. This method describes the common ontology characteristics of emergency cases, having high reusability, and it is helpful to provide decision support for decision-makers to take emergency management measures.

Research into Signature Algorithms for Modular Reliability System

JIA Xu-jie, MA Rui-hong , LI Yu-jie, SONG Xue-ying

2018, 27(12):  95-99.  DOI: 10.12005/orms.2018.0283

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System Signature is a set of vectors reflecting the superiority of structural design that can describe the impact of system design on system failure rates. It shows powerful features such as system reliability analysis, system design, system life comparison, system life-limit behavior and system design optimization, and has become an increasingly important research method in reliability research. The difficulty of Signature calculation increases exponentially with the increase of the components number as the system is large and complex, which undoubtedly poses a huge obstacle to subsequent analysis, so the key step in the analysis is to solve a system signature. This paper establishes algorithms of system Signature based on ideas of modularization, and gives algorithms of Signature of modular series or parallel system and modular redundancy system. Compared with conventional ways, using ideas of modularization can efficiently reduce the time and the complexity and amount of calculation in computing Signature, and expand the system range that can be solved for system Signature.

Game Decision Model of Inventory Financing Based on Overconfidence Retailer

LIU Jian, JIANG Wei-fan

2018, 27(12):  100-107.  DOI: 10.12005/orms.2018.0284

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Inventory financing is an effective measure of short-term financing for small and medium-sized enterprises, and the overconfidence of enterprises on demand affects the decisions of financing enterprises and banks, which influence the expected profits of enterprises and banks. Aiming at the problem of inventory financing decision-making in overconfidence environment, a joint decision model of inventory financing is constructed, which consists of the overconfidence retailer and bank. The Stackelberg is adopted to analyze the impact of two kinds of overconfidence degree which includes high estimation of capacity and excessive precision of estimation on the decision variables. It shows that the overconfident retailers are radical on inventory impawn financing, and the retailers' demand on capital, effort and procurement increase with the increase of the degree of overconfidence. Furthermore, it brings deviation between the expected profit and the actual profit. When the market environment is low profit, loan-to-value ratio declines with the increase of the overconfidence degree, and in the lucrative market environment, the loan-to-value ratio declines with the increase of the overconfidence of estimation of capacity, and increases with the increase of the overconfidence of precision of estimation.

Pricing Decision of Dual Channel Closed Loop Supply Chain with Different Channel Preferences and Operating Costs

ZHAO jing, XIAO Ya-qian

2018, 27(12):  108-114.  DOI: 10.12005/orms.2018.0285

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Based on the difference of channel preference of consumers and operating costs of consumers to the traditional retail channels and network direct channels, this paper studies the pricing decision of the dual channel closed loop supply chain, which is responsible for the retailer to recycle the waste products and the manufacturer to open the direct channel. Three game pricing decision models under different market power structures are established, and the corresponding optimal solutions are solved by backward induction, and then the effects of channel preference and channel operation cost on the optimal pricing strategies and the maximum profits are analyzed. The results show that the optimal direct prices increase and the optimal retail prices decrease, as the consumer direct channel preference increases; the increase of online channel operating cost of online direct selling channel is beneficial to the retailer, but it hurts the manufacturer; the increase of traditional channel operating cost is not beneficial to them.

Application Research

Individual Bounded Rationality and Crowdsourcing Performance: An Agent-based Simulation

YAN Jie, LIU Ren-jing

2018, 27(12):  115-124.  DOI: 10.12005/orms.2018.0286

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The advancement of internet makes firms able to use collective intelligence to solve complex problems with the help of crowdsourcing by combining knowledge of outside participants. However, compared to inside employees, the bounded rationality level of outside participants is relatively low, which becomes a major concern of the firms. Therefore, how to recruit participants is a key issue for firms to implement crowdsourcing. To solve the problem, by introducing individual bounded rationality, an agent-based model that simulates problem solving process of tournament-based crowdsourcing is constructed by extending the NK model to explore the effects of the level of bounded rationality, the systematization of bounded rationality and the standard deviation of bounded rationality level on crowdsourcing performance. The results of simulation experiments suggest that the level of bounded rationality has a significant positive effect on crowdsourcing performance, especially in cases where the task complexity is high. The systematization of bounded rationality and the standard deviation of bounded rationality level also have a positive effect on the crowdsourcing performance, but they depend on the level of bounded rationality. Therefore, when there is a higher complexity task, and if the firm pursues the overall improvement of all solutions, the best strategy is to recruit individuals with higher bounded rationality level and form a group with higher systematization of bounded rationality and higher standard deviation of bounded rationality level; but if the firm pursues a small number of high-quality solutions, the best strategy is to recruit individuals with higher bounded rationality level and form a group with lower systematization of bounded rationality and higher standard deviation of bounded rationality level.

Research on the Influence Factors on the Debt Financing Structure of Cultural and Creative Industries ——Based on the panel data of listed companies from 2012 to 2016

ZHOU Xiao-guang, GUAN Yue, HUANG Xiao-xia

2018, 27(12):  125-132.  DOI: 10.12005/orms.2018.0287

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Cultural and creative enterprises have the following characteristics: light physical assets but heavy intangible assets; uncertain income and high creative value; large difference in input and output efficiency and long chain of derivatives. Based on the panel data of 159 cultural and creative listed companies from 2012 to 2016 in Shanghai and Shenzhen Stock Exchanges, this paper studies the influence factors on the financing structure of cultural and creative industries by adopting fixed effect model and dynamic panel model. Different from the existing results, the holding ratio of intangible assets is positively correlated with asset-liability ratio, and the profitability is negatively correlated with asset-liability ratio. The ownership structure, firm size and growth rate are not relevant to asset-liability ratio. What’s more, there is a self-adjustment mechanism of assets and liabilities, that is, the lagged two-period asset-liability ratio affects the current asset-liability ratio. Based on the conclusions and the characteristics of the cultural and creative enterprises, some suggestions are put forward to improve the capital structure of cultural and creative enterprises.

Research on the Moral Hazards of P2P Insurance

YANG Chao, YANG Tian-yu, CHEN Bing-zheng

2018, 27(12):  133-141.  DOI: 10.12005/orms.2018.0288

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With the rapid development of information industry and the wide application of Internet insurance, for recent years, a new type of insurance mode-P2P Insurance(Peer to Peer Insurance)has emerged in the world. This model is based on the Internet, through gathering a number of policyholders with similar risks to set up risk-sharing group. Members of risk support group are usually relatives, friends or acquaintances. Mutual supervision mechanism and reputation mechanism formed by P2P insurance can solve the moral hazard problem in the traditional insurance market. In this paper, using the comparative static analysis method in economics, we study the problems of moral hazard of P2P insurance and prove theoretically that under the P2P insurance mode, the policyholder tends to guard against the risk to reduce the risk probability, and the moral hazard problems can be effectively alleviated.

Hedging Properties of Coastal Dry Bulk Freight Derivatives Based on GC-MSV Model

LI Guang-hui

2018, 27(12):  142-146.  DOI: 10.12005/orms.2018.0289

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In the face of bulk freight rate fluctuations, the shipper and shipping companies need to take appropriate method to control the risk. Hedging through the shipping freight derivatives is one of the major methods. This paper using GC-MSV model, with the minimum variance criterion, studies the optimal hedge ratio of coastal bulk freight derivatives and hedging effect with the decrease of variance, and compares other models. According to the hedging effect, the GC-MSV model adjusting dynamically has better performance than the other two models. It can reduce 20%~40% of the volatility through hedging. The coastal coal freight derivatives can hedge risk to some extent with the limit effect to reduce the assets variance.

Risk Assessment of FMEA Based on Prospect Theory and PROMETHEE

ZHU Jiang-hong, LI Yan-lai, WANG Rui

2018, 27(12):  147-157.  DOI: 10.12005/orms.2018.0290

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In order to consider the influence of group evaluation consistency and expert psychological perception behavior in risk assessment of failure mode and effect analysis, a method of risk assessment based on prospect theory and preference ranking organization method for enrichment evaluations (PROMETHEE) is proposed. Firstly, linguistic variables are introduced to characterize the risk factor evaluation information, and intuitionistic fuzzy entropy is used to determine the objective weight of risk factors. Secondly, the consistency of expert evaluation and group evaluation is depicted by the grey relation degree, and a optimization model is constructed with the maximum correlation degree and maximum entropy criterion. Thirdly, the subjective and objective weights of risk factors and experts are integrated, and the comprehensive weights of risk factors and experts are obtained. Then, the intuitionistic fuzzy weighted averaging operator is used to aggregate the expert evaluation information, and with the help of prospect theory, the prospect matrix of the reaction expert’s psychological perception is constructed. Finally, the PROMETHEE method is applied to determine the risk ranking of failure mode and effect analysis, and the validity and feasibility of the proposed method is verified by a case of liquid crystal display.

Study on Construction of Fractal Statistics Measure and Its Application to the Portfolio

WU Xu,LI Ran, YAN Ru-zhen, LI Yi-zhuo

2018, 27(12):  158-165.  DOI: 10.12005/orms.2018.0291

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Accurate measurement of the risks and benefits of securities is important not only for investment management, but also for financial theoretical research and even for transformation of theoretical results into practical application. Based on the fractal theory, this paper constructs two fractal statistical measures, such as fractal expectation and fractal variance, in order to overcome the shortcomings of non-fractal statistical measures in terms of risk income. On this basis, the portfolio model is constructed by using the fractal statistical measure. Also, the analytic solution to the fractal model is given; then, the effectiveness of fractal statistic measurement in the portfolio application is verified by empirical analysis. The innovation of this paper is that two fractal statistical measures are constructed, which are fractal expectation and fractal variance, based on the reality of fractal characteristics of securities price. Moreover, the investment portfolio model is constructed under the fractal statistical measure, and this paper takes the fractal characteristics present in the securities price into the portfolio research.

The Application of a New Dynamic Evaluation Method in Steelworks’ Low-carbon Competitiveness

JIANG Yu-guo, CHUN Wei-de

2018, 27(12):  166-171.  DOI: 10.12005/orms.2018.0292

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In the process of evaluation of enterprise competitiveness, we often encounter periodicity and contingency. In order to solve this problem, we extend the TOPSIS based on the idea of "pulling up the class" and adopt this method for steelworks’ low-carbon competitiveness. The results show that this method has the advantages of dynamics, flexibility and comprehensive compared with the existing static methods. The steelworks’ low-carbon competitiveness could be reflected from various angles.The practicability and validity of this method are verified, and it solves the occasional problem. At the same time, we present a new way to explore the dynamic evaluation of steelworks’ low-carbon competitiveness in this paper.

Management Science

Research into the Influencing Factors of Employee Creativity Based on Creative Process Engagement

TU Xing-yong, PENG Ya-ya, LIN Cheng-lu, LIU Xiang-yang

2018, 27(12):  172-180.  DOI: 10.12005/orms.2018.0293

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Creative process engagement has been a new concept in management for the past few years. Although existing research suggests this concept can help employee achieve creativity, the effect of knowledge workers’ intrinsic motivation on employees’ creativity does not give full explanation. This paper constructs a moderated mediation model based on the determination theory to test how intrinsic motivation influences employees’ creativity. The results show that: (1)intrinsic motivation is positively related to employees’ creativity, (2)creative process engagement partially mediates the relationship between intrinsic motivation and employees’ creativity, and (3)creative self-efficacy moderates the relationship between creative process engagement and employees’ creativity, and furthermore, (4)the mediated role of creative process engagement is moderated by creative self-efficacy, that is to say, the effect of knowledge workers’ intrinsic motivation of creativity through creative process engagement is stronger when creative self-efficacy is higher. The results show that a moderated mediation model provides a better understanding of creative process engagement, and the management implications, limitations and prospects of this study are discussed in the end.

Research on the Characteristic of Natural Monopoly and Regulation of Network Infrastructure Segment in Chinese Railway

QIU Lei, LIU Xiao-bing

2018, 27(12):  181-186.  DOI: 10.12005/orms.2018.0294

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From the view of network infrastructure and transportation separating, based on DEA model, the paper makes an empirical analysis of the characteristic of natural monopoly in Chinese railway network infrastructure segment by using related inputs and output indexes data from 1993 to 2016. The results show that the characteristic of natural monopoly of network infrastructure segment is not obvious. Therefore, regulation reform of network infrastructure segment in Chinese railway industry is necessary, including loosening entry and price regulation, taking moderate investment regulation and strengthening quality regulation.

Classification of Subway Operation Intervals Based on Affinity Propagation Cluster

WANG Wen-xian, XIAO Meng, CHENG Lin-na, DU Yan-shuai, NI Shao-quan

2018, 27(12):  187-192.  DOI: 10.12005/orms.2018.0295

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Passenger quantity of subway normally varies significantly by different time period like peak and non-peak hours. Reasonable classification of operation intervals is essential for adaptable adjustment of traffic plan for peak and non-peak hours. Actually, the classification method which is manually set based on experiences, is subjective and lack of accuracy. Taking 10 minute as a unit time interval, the daily operating period (6∶00~23∶00) can be divided into 102(10-min)time intervals. This article proposes affinity propagation algorithm merge time samples into different categories, together with arriving passenger volume alongside stations which are used as describing variables. Clustering validity indexes such as CH Hart and IGP are introduced to examine clustering result, so optimal operation intervals classification and switch time are finally confirmed. The study of Tianjin subway 2th line indicates that operation intervals classification based on clustering algorithm could respond the fluctuation of real passenger quantity more accurately. On the base of that, the optimized traffic plan causes obvious decrease of passenger average waiting time.

Research on the Green Innovation Diffusion Mechanism of Logistics Enterprises Based on Evolutionary Game

YU Li-jing, CHEN Zhong-quan

2018, 27(12):  193-199.  DOI: 10.12005/orms.2018.0296

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Green innovation is an effective way to maintain competitive advantage of logistics enterprises, which plays an important role in reducing environmental pollution and dealing with climate change. The paper builds a tripartite model of logistics enterprise groups, government regulators and consumer groups based on the basic theory and method of evolutionary game, and then analyzes the gradual stability of green innovation diffusion and the influence of different parameters on the diffusion of green innovation by matlab software. The result of the study shows that: the government’s regulation is the booster of the logistics enterprises’ diffusion of green innovation; with time, the government will choose to withdraw from the regulation eventually, but the speed is different under different regulatory ways; the government subsidies of innovation for the logistics enterprises should be controlled within a certain range.