Table of Content

25 March 2018, Volume 27 Issue 3

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Theory Analysis and Methodology Study

An Exact Epsilon-constraint Algorithm for the Bi-objective Optimization Problem of Scheduling Staple Fiber Production

ZHENG Fei-feng, HE Jun-kai, LIU Ming

2018, 27(3):  1-8.  DOI: 10.12005/orms.2018.0053

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This paper studies the scheduling problem of staple fiber production with successive orders, which considers the demand and due date differences between clients and the setup time of machine when switching components. Firstly, we establish a bi-objective integer linear programming model so as to minimize the total tardiness of orders and total setup time of machine. Then, we conduct an accurate algorithm to get the precise solutions of proposed model, i.e., Pareto frontier. Finally, we NSGA-II to sovle this model within a devise substantial amount of time. Simulation experiments prove the correctness and effectiveness of this model and proposed algorithms, which can be considered to use as an reference in daily process.

A Discrete Event Simulation Based Approach for Admission Control of Pregnant Women in Obstetrics Units

YI Jia-qi, GENG Na

2018, 27(3):  9-16.  DOI: 10.12005/orms.2018.0054

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Pregnant women need to go to one hospital and apply for admission afterthe 9th pregnant week. The scheduler should make the instant decision of admission or not. Once the women are accepted, the obstetrics unit will provide long-term consistent cares for women from the antenatal care to perinatal stage. It is a challeng for the scheduler to make such a decision due to the features of multiple resources requirement, multi-reentrance, and uncertainties in both demand arrival time and service time of the critical resources. Improper decision will lead to the unbalanced distribution of resource utilization rate of obstetrics and gynecology, and eventhe diversion of pregnant women to other hospitals. To solve this problem, this paper develops the dynamic programming (DP) model to control the resource utilization distribution. However, it is difficult to establish structural properties of the optimal control policy due to the complex structure of the model. Therefore, this paper proposes a discrete-event simulation model and multiple threshold-based admission control policies. The parameters of the policies are improved with the objective of minimizing the weighted cost of beds’ idle and overloaded and patients’ diversion penalty by using the extensive search method.Thenumerical experiments show that the optimal threshold performs much better than that from practices. A sensitivity ana lysis is performed and finds that the match between the capacity and the demand can further reduce the criteria value.

Research on Solving Multi-objective 0-1 Programming by Cellular Wolf Pack Algorithm

MA Long, LU Cai-wu, GU Qing-hua, CHEN Xiao-ni

2018, 27(3):  17-24.  DOI: 10.12005/orms.2018.0055

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A cellular wolf pack algorithm,based on cellular automation principleand artificial intelligent wolf algorithm,is proposed for solving the multi-objective 0-1 programming problem. Using cellular and its neighbors to enhance the diversity and distribution of the search process,evolution rules of celluar automation and howling pheromone update rule as well as wolf update rule are combined, in order to realize global search and obtain more global non-dominated solution in cellular space search process. Secondly, search space, mobile operator, cellular evolution rules and update rules of optimal solution sets are defined by using mathematical form to describe the cellular wolfpackalgorithm. What’s more,the specific steps of implementation by celluar wolf pack algorithm are presented. Finally, the three typical examples of multi-objective 0-1 programming problem are the solution through the MATLAB software, and compared with the solutions of the other artificial intelligence algorithm,the results show that cellular wolf algorithm can get more non-dominated solution sets and better non-dominated solution in solving multi-objective 0-1 programming problem, and at the same time,the algorithm has faster convergence speed and better global search ability.

Optimization Research of Combined Cooling, Heating and Power System for Building Clusters Based on Stochastic Programming

CHU Xiao-lin, YANG Dong

2018, 27(3):  25-31.  DOI: 10.12005/orms.2018.0056

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The design and optimal operation strategy of the combined cooling, heating and power (CCHP) system for building clusters is the significant way to reduce energy cost of the building. The stochastic factors, such as energy demand and energy price, cannot be ignored in this optimization problem. Considering that the energy need of the building is stochastic variable, the stochastic mixed integer programming model is established, in order to solve the optimization problem of CCHP system for building clusters with minimization of the buildings’ total cost as objective. Furthermore, Benders multi-cut algorithm is proposed to solve the multi-objective programming model, which is aimed at finding the Pareto optimal decision of device configuration and running plan of CCHP system. Finally, the stochastic mixed integer programming model and Benders multi-cut algorithm are proved to be effective through experiment, and it is demonstrated that buildings have the less energy cost under collaborative strategy compared with non-cooperative strategy.

Stochastic Comparison of the Generalized Mean-preserving Transformations and Its Applications to Inventory Decisions and Optimization

YU Hai-bo, LI Yuan

2018, 27(3):  32-40.  DOI: 10.12005/orms.2018.0057

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In this paper, we provide a generalized mean-preserving transformation which has non-linear and mean inequality conversions, to study the sufficient conditions or sufficient and necessary conditions which can achieve its stochastic comparison. We also characterize the effect of demand uncertainty in decision and profit in inventory system. First, we get the relationship between the distribution function and the random monotonicity before and after the conversion. We also get the connection between the generalized mean-preserving transformation and generalized TTT transformation. In addition, three special generalized mean-preserving transformations are used for validation. Finally, the transition is applied to the newsvendor model which has both minimize cost newsvendor problem and maximize profit newsvendor problem, and the random monotonicity of the unified newspaper problem transformation is obtained.

Research on Supplier Classification in High-end Equipment Manufacturing Industry Based on Improved Support Vector Machine

LI Kun, SHI Chun-sheng, ZHENG Zuo-long, WANG Cheng-gang

2018, 27(3):  41-49.  DOI: 10.12005/orms.2018.0058

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There are some limitations of existing supplier classification methods which target high-end equipment manufacturing industry. From the perspective of interdependence, the paper divides suppliers of high-end equipment manufacturing industry into four types, including interdependence, supplier dominance, buyer dominance and independence. Meanwhile, the paper constructs a supplier classification index system based on literature analysis, interviews and expert judgment. The paper further proposes a classification model of high-end equipment manufacturing industry suppliers based on improved support vector machine. According to different misclassification costs of suppliers, the proposed model designs the cost sensitive support vector machine classifier. The particle swarm optimization algorithm is used to optimize model parameters, and the obtained optimized two-class models are assembled to realize multi-class classification according to probability outputs. The experimental results show that the proposed model can improve the classification performance of existing methods and reduce overall cost of errors. The proposed model also can identify suppliers which have significant impact on high-end equipment manufacturing enterprises effectively. The paper aims to provide a theoretical basis and practical guideline for high-end equipment manufacturing enterprises to implement supplier classification management.

Supply Chain Contract Coordination Considering Supplier’s Quality Investment under Fairness Preference

YAN Feng, LIANG Gong-qian, LIU Xin, NIN Lie

2018, 27(3):  50-58.  DOI: 10.12005/orms.2018.0059

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The paper aims at the insufficiency that the traditional bonus-penalty contract based on quantitative criteria cannot adapt to the current demand characteristics of many varieties and small batch and coordinate the supply chain. In the context of fairness preference, this paper builds the bonus-penalty contract based on the product quality criteria provided by suppliers,to study how the contract influences the coordination of supply chain. Assuming the retailer is fairness preferred in the two-echelon supply chain with a manufacturer and a supplier, the paper analyzes two situations, namely, the same and different channel power of supply chain participants. We find that the suppliers and retailers will cooperate in accordance with the contract , get a balanced result and achieve supply chain coordination, when the retailer has the same degree of concern for own income and fairness. Furthermore, the difference of channel power will much affect supply chain overall profit. Finally, a numerical example is given to demonstrate the model.

An Integrated Model of Production, Inventory and Distribution of Limited Vehicles in Emergency Management

LIU Jiao-feng, HE Su-xiang

2018, 27(3):  59-65.  DOI: 10.12005/orms.2018.0060

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After the disaster, sending the relief supplies to the demand points in the shortest time can avoid many casualties and property losses. In view of the shortage of relief supplies, limited vehicles’ number and capacity, this paper considers the manufacturers’ production and packaging of new relief supplies and constructs a function about the time of the manufacturers’ vehicles waiting for an order completed.Then a mixed integer programming model of integration of production, inventory and distribution is established.The model consists of raw material suppliers, manufacturers, distribution centers and customer demand points. The goal is to complete the transportation of raw material, production and as signment of relief supplies by manufacturers to the customer demand points and ass ignment of relief supplies at distribution centers to the customer demand points in the shortest time. The model is divided into two sub-models. One is solved by improved genetic algorithm and the other implicit enumeration method. Finally, the rationality of the model and effectiveness of the algorithm are verified by one specific case.

TOPSIS Method with Intuitionistic Hesitant Fuzzy Sets

TAN Chun-qiao, ZHI Shuai

2018, 27(3):  66-73.  DOI: 10.12005/orms.2018.0061

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Intuitionistic hesitant fuzzy sets (IHFSs), synthesizing the advantages of intuitionistic fuzzy sets and hesitant fuzzy sets, express the inconsistent preferences for decision makers more effectively. However, there is little research on the distance measures between IHFSs despite the fact that distance measure has received close attention, so the Hamming distance, Euclidean distance and generalized distance between two IHFSs are defined. Besides, we define the generalized weighted distance if the weight of each element is taken into account. Considering that hesitancy is the fundamentally characteristic of IHFSs, several novel distance measures which take the hesitancy degree into account are defined, in which both the values of intuitionistic hesitant fuzzy numbers (IHFNs) and the hesitancy degree are taken into account. The distance measure with preference can be calculated by setting different preference values between the values of IHFNs and the hesitancy degree if decision makers have different preference. Then we introduce an extended TOPSIS method based on new distance measures under intuitionistic hesitant fuzzy environment. Finally, a numerical example is given to show the reasonability and applicability of the proposed method.

Multi-stage Decision Making Method Based on Prospect Theory and MULTIMOORA in the Triangular Fuzzy Environment

DAI Wen-feng, ZHONG Qiu-yan, QI Chun-ze

2018, 27(3):  74-81.  DOI: 10.12005/orms.2018.0062

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For the triangular fuzzy multi-attribute decision making problem, in which period weights and attribute weights are completely unknown, a new decisiong making method based on the prospect theory and MULTIMOORA was presented. Firstly, the triangular fuzzy prospect decision matrices in different periods are built and the period weight optimization model was established on the basis of the time degree and differences of prospect values of alternatives in different periods. According to the maximise deviation, attribute weights were determined. Then, a novel extension form of MULTIMOORA was proposed based on the triangular fuzzy number. Alternatives are ranked and selected by the triangular fuzzy MULTIMOORA and the dominance theory. Finally, the feasibility and validity of the proposed method are verified with an example.

Evolutionary Game Analysis of Stakeholders in the NIMBY Conflicts ——A Case Study of Pollution NIMBY Facility

KANG Wei, DU Lei

2018, 27(3):  82-92.  DOI: 10.12005/orms.2018.0063

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In the process of industrialization and urbanization, while promoting the development of social economy, it also gave birth to the awakening of citizen's right consciousness and environmental protection consciousness.Under the macro background of the overall interests and local interests, economic interests and environmental interests,pollution NIMBY facility has become an important incentive to lead to the NIMBY conflicts after labor disputes, illegal land acquisition.Therefore, it is important to explore the relationship between the government, the NIMBY facility construction enterprise and the surrounding resident, and to sort out the interests of the main body, which is of great significance in the prevention and treatment of the NIMBY conflicts.Based on the theory of stakeholders, this paper explores the role and function of the stakeholders in the conflict, so as to construct the three-party evolution game model of the government, the NIMBY facility construction enterprise and the surrounding resident from the perspective of evolutionary game theory.On this basis, through the analysis of the stable evolution game strategy of the government, the NIMBY facility construction enterprise and the surrounding resident, this paper concludes the conditions for the convergence of the three-party main body to the evolutionary stable strategy. This paper also uses Matlab to simulate the evolution model of the three-party, and finds thatthe government adopts the strategy of non-supervision, the NIMBY facility construction enterprise to adopt the strategy of cooperation and the surrounding resident to take the non-resistance strategy isthe stable strategy point of the evolution game of the three party interest main body in the NIMBY conflicts;high intensity of government incentives is conducive for the promotion of construction enterprises to adopt a cooperative strategy, and restrain the surrounding resident to choose the choice of resistance behavior strategy; the construction enterprises economic compensation has a critical point to reduce the resistance of the resident, only the high economic compensation will encourage people to choose the behavior strategy without resistance;and the resistance of the surrounding resident has no significant influence on the strategic choice of NIMBY facility construction companies.The results of this paper has a certain enlightenment for the stakeholders of NIMBY conflict: first, as NIMBY facilities’ regulator, government should grasping the extent of supervision, perfect the public participation channels, and reduce individual risk perception; second, as the executor of the NIMBY facilities, construction enterprises should actively use the environmental technologies, construct the scientific interest compensation mechanism; third, the surrounding people play a key role for the NIMBY “landing”, they should strengthen their own public rational, reasonable assessment of NIMBY risk, maintain the social public interest.

Research into Decision-making Mechanism of Industry-University-Institute Cooperation under the Perspective of Collaborative Innovation

ZANG Xin-yu, MA Yong-hong

2018, 27(3):  93-103.  DOI: 10.12005/orms.2018.0064

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Industry-university-institute cooperation is an effective form of science and technology with economy, and collaborative innovation theory puts forward higher requirements of industry-university-institute cooperation. From a collaborative innovation perspective, we build the cooperation between enterprises and research institutions cooperation decision-making game model based on the bounded rationality of evolutionary game theory, and make the strategy choices for stability analysis. Theoretical research and numerical simulation results show that: when the enterprises and research institutions in collaboration obtain more benefits than they choose to give up halfway, all of them will choose collaborative strategy. The total revenue of industry-university-institute cooperation, income distribution, compensation coefficient and collaborative costs have significant impacts on decision results of enterprises and research institutions, but the mechanisms are different. Government funding for industry-university-institute collaboration and punishment mechanism for the enterprises and research institutions will lead to the choice of cooperation strategy, but the effects of funding and punishment can maximize effect only in reasonable ranges.

Pythagorean Triangular Fuzzy Linguistic Hamacher Aggregation Operators and Their Application

DU Yu-qin, HOU Fu-jun, ZHAI Yu-bing, YU-qian

2018, 27(3):  104-112.  DOI: 10.12005/orms.2018.0065

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Based on the Pythagorean fuzzy set and Hamacher operator, the Pythagorean triangular fuzzy linguistic Hamacher aggregation operators are studied. Firstly, the definition, the operational laws, score function and accuracy function of the Pythagorean triangular fuzzy linguistic set are proposed. Then, a series of Pythagorean triangular fuzzy linguistic Hamacher aggregation operators are developed, such as the Pythagorean triangular fuzzy linguistic Hamacher weighted average (PTrFLHWA) operator and the Pythagorean triangular fuzzy linguistic Hamacher geometric (PTrFLHWG) operator. Moreover, some properties of these operators are discussed in detail. Afterwards, two new approaches to Pythagorean triangular fuzzy linguistic multi-attribute group decision making are presented based on the proposed operators. Finally, a practical example is given to illustrate the effectiveness of the proposed approaches.

Parallel Machines Scheduling with Learning Effect and Controllable Processing Times

GUO Miao-miao, LIU Huan, WANG Ji-bo, NIU Yu-ping

2018, 27(3):  113-117.  DOI: 10.12005/orms.2018.0066

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In this paper we consider the unrelated parallel machines scheduling problem, in the problem the job of the processing time is with learning effect and necource controllable, that is to say in the model of this problem the job’s actual processing time is the function of the basic processing time, the location of the job (learning effect) and the controllable of the processing time. The objective function is to minimize the weighted sum of total machine load and total control cost, and minimize the weighted sum of total completion time and total control cost. The article found an optimization algorithm to solve the problem through the analysis of the related nature of the problem, and also proved that in the number of processor is a given condition, the time complexity of the problem is O(n^m+2). Finally the paper also gives corresponding numerical example to illustrate this problem.

Application Research

The Study on Capacity Investment of New Products with Short Cycles under Market Acceptance Uncertainty ——Investment Opportunity and Scale Decisions by Considering Competition

YAN Xia-min, LIN Jun, CUI Wen-tian, QIAN Yan-jun

2018, 27(3):  118-125.  DOI: 10.12005/orms.2018.0067

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Market acceptance of new products has a high degree of uncertainty, and traditional investment theories can not apply to investments of new products. For capacity investments of new products, we study how to make capacity investment opportunity and scale decisions of new products with short cycles for a monopoly enterprise and two competitive enterprises with different costs. There are two investment opportunities as “earlier” and “later” for enterprises to choose, and “earlier” investment is defined when enterprises know the mean and covariance of market size for the new product; and “later” investment when enterprises know real market size. A monopoly enterprise can’t collect sale information before entering the market, and it will choose “earlier” investment or no investment, therefore we give the condition of choosing “earlier” investment and corresponding optimal expected profit. There are four kinds of circumstances for two competitive enterprises with different costs, and we give optimal capacity investment scale decisions and corresponding optimal expected profits respectively. The optimal investment opportunity decision is given by comparing optimal expected profits for these four circumstances.

Theory and Application Study on PLS-DEMATEL Method ——Using influencing factors of organizational agility from the perspective of IT as an example

GAO Pei-ran, ZHANG Jin-long, AI Xue-yi, LI Ming, MA Zi-xiang

2018, 27(3):  126-132.  DOI: 10.12005/orms.2018.0068

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DEMATEL(decision making and evaluation laboratory)is a method which identifies and distinguishes influencing factors based on the evaluation of the correlation of influencing factors. In management reality, it is difficult to evaluate the correlation of influencing factors, which limits the application of DEMATEL method. Therefore, this study first uses structural equation modeling based on partial least squares(PLS) to get direct correlation matrix of influencing factors, uses the traditional DEMATEL method to analyze the influential factors, and the PLS-DEMATEL method is further put forward. Finally, this study uses the PLS-DEMATEL method for identifying influencing factors of organizational agility from the perspective of information technology (IT). According to the calculation results, IT strategies to enhance organizational agility are given, and the effectiveness of the PLS-DEMATEL method is also verified.

The Influence of the Certainty and the Appropriateness of Penalty on Information Security Compliance Behavior

WANG Xiao-long, LI Wen-li

2018, 27(3):  133-142.  DOI: 10.12005/orms.2018.0069

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The influence of the certainty and severity of penalty on the information security compliance behaviors of employees has been an issue of debate in the previous studies. In the present work, the compliance effort level on the information security policy is viewed to be a consequence of the dynamical game between the organization and its employee individual. An information security compliance game model is proposed, and then combined with the principal-agent theory to explore the influence of penalty on the information security compliance behavior of the employee. The incentive mechanisms of the certainty and the appropriateness of penalty on the compliance behavior are first considered, and then are further analyzed by using numerical simulation. Several significant results are obtained: (1)The organization (the principal) can design an optimal incentive contract which includes appropriate penalty for motivating the employee (an agent) to comply with the information security policy; (2)The certainty and the appropriateness of penalty are effective in motivating employee’s compliance; (3)The appropriateness of penalty can be determined in terms of the risk aversion of the employee, the compensation, the external benefit and the probability of the negative outcome of non-compliance. These theoretical insights are expected to provide useful reference for managers to understand and manage the information security compliance behaviors of employees in the organizational setting.

Research on Inverse Problem Based on the Graph Model for Ordinal Preference

ZHAO Jin-shuai, XU Hai-yan

2018, 27(3):  143-149.  DOI: 10.12005/orms.2018.0070

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In conflict negotiation, the vital condition is that you have acquired opponent’s preference for mastering initiative in hands. In this paper, a method is proposed for obtaining the preference within the framework of graph model for conflict resolution (GMCR). Through in-depth analyses of the three stability definitions of Nash, GMR and SEQ in GMCR, some mathematical models are constructed to get the opponent’s preference, which include least constraint conditions using inverse way of thinking in this research. In the premise of having known the outcome of a conflict,the method can make the decision maker gain his opponent’s preference. The proposed approach is employed for the conflict, Chromium pollution in Luliang county, Qujing city, Yunnan province, in which there are two main decision makers: Environmental protection department of Yunnan province and Luliang chemical enterprise. First, the GMCR model of this conflict is established. Then, its preference and the final stability outcome are analyzed. Finally, using the mathematical models proposed above, the Environmental protection department of Yunnan province can obtain all of its opponent’s preference ranking which make it in an invincible position in conflict negotiation. At the same time, the method’s feasibility and validity are verified. The results from this research provide a valuable view for one side in the conflict negotiation.

Empirical Study on Cross-district and Cross-industry Asset Allocation Model under Regime Switching Framework

JIN Xiu, CHEN Na, LIU Jia-he, YUAN Ying

2018, 27(3):  150-158.  DOI: 10.12005/orms.2018.0071

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We use Markov regime switching model to capture the nonlinear dynamic structural change of financial asset return series, and further considering sector rotation effect caused by liquidity between different districts and industries under different market regimes, we propose the model of cross-district and cross-industry asset allocation based on regime switching. On this basis, we make a detailed analysis of the impact of market regimes and sector rotation effect on the asset allocation. The study shows that: there are significant structural dynamic changes in Chinese financial market, which can be divided into bear and bull markets, and the optimal asset allocation structure under bear market is inconsistent with bull market. Asset allocation under regime switching improves returns to investors. The research shows that cross-district and cross-industry asset allocation model under regime switching framework could describe the return and risk characteristics of assets under asymmetric market regimes, diversify non-systematic risk while reducing market risk, and thus provide valuable reference for investors decisions.

Dual-channel Supply Chain Coordination with Advance Payment Financing Based on Combined Contract of New Revenue-sharing and Buy-back

ZHAO Liang, ZHUANG Xin-tian, SHI Jun

2018, 27(3):  159-167.  DOI: 10.12005/orms.2018.0072

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We consider a dual-channel supply chain model under stochastic demand, in which the manufacturer is capital constrained. This paper investigates an issue of dual-channel supply chain coordination with advance payment financing. Under the condition that the manufacturer is the Stackelberg leader, this paper analyzes the optimal stocking decisions of manufacturer and retailer in a decentralized decision-making system, and establishes a combined contract based on new revenue-sharing and buy-back contracts for the dual-channel supply chain coordination. Based on that, the conditions for the Pareto improvement are given by the analysis of the win-win situation in supply chain partnerships. Finally, a numerical example is used to verify the results and the effectiveness of the dual-channel supply chain coordination and Pareto improvement.

Cyclical Herding Behavior Based on Transformation of Private Information and Empirical Study of Chinese Stock Market

SHU Jian-ping, WANG Su-sheng, LI Zhi-chao

2018, 27(3):  168-174.  DOI: 10.12005/orms.2018.0073

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The paper constructs an evolution model of herding behavior based on transformation of private information, and points out that the evolution of herding behavior presents a character of “appeared→enhanced→weekend and disappeared→opposite herding behavior appeared→enhanced→weekend and disappeared…” driven by positive feedback effect, saturation effect and return reversal led by investors’ overreaction in the process of private information transferring to public information. An empirical research of Chinese A-share market shows that cyclical herding behaviorwith thecharacteristics above does exist.

Management Science

Research on the Evolution of Knowledge System Under Different Trust Environments in OKC

QIU Jiang-nan, ZHANG Mei-hui

2018, 27(3):  175-183.  DOI: 10.12005/orms.2018.0074

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Trust, as a social influence factor in the Online Knowledge Community(OKC), plays an important role in communication and learning among members of the community. Different Online Knowledge Communities have different trust environment, and different trust environments affect the mode of members’ learning and opinion evolution in community. Based on this, we present the opinion influence model which combinesTrust measurement model and Deffaunt model. First, in Trust model,we divide the trust of the network community between two agents into the cognitive trust and affective trust, and adjust parameter structure to simulate different trust environments. Then, we improve Deffaunt model as the opinion spread model to carry out multi group simulation experiment to simulate the evolution process of the knowledge system of online knowledge community under different trust environments.The results show that the level of trust environment determines whether the opinion in the community is convergent, and the proportion of rational population in the community and the degree of trust can influence the convergence rate of the view.

Outsourcing Decisions under Scale Effect for Competitive Firms with Product Substitutability

WU Jiang-hua, HUANG Qiu-ai, LI Xian-guo

2018, 27(3):  184-190.  DOI: 10.12005/orms.2018.0075

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The paper discusses outsourcing decisions for a supplier with scale effect and two competitive firms(firm 1 and firm 2)with product substitutability. The supply chain contains a supplier and two downstream firms. Based on the profit functions, this study analyzes the effect of firm 1’s outsourcing on the supplier and both firms, finds out the optimal outsourcing strategies and the best wholesale prices, and compares the effects of substitutability on decision variables before and after outsourcing. The results show that a firm may make products by itself when its production cost is higher than wholesale price. However, a firm may also choose to outsource products when its production cost is lower than wholesale price. Then we extend the model and compare the difference between the sequential outsourcing decision and the simultaneous one.

Study of Technology Innovation Efficiency of High Patent Intensity Industry in China Based on SBM-NDEA Model

CHEN Heng, HE Ping, LIN Chao-ran, FENG Zhi-jun

2018, 27(3):  191-199.  DOI: 10.12005/orms.2018.0076

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In this paper, the non-expected output and the non-radial SMB-NDEA model, which is characterized by innovation loss, are used to study the technological innovation efficiency of China’s patent-intensive industry from 2005 to 2015. The empirical results show that: (1)Most of the nine patent-intensive industries in China can guarantee high efficiency of technological innovation and can continue to innovate, especially the “computer, communication and other electronic equipment manufacturing” and “tobacco manufacturing”; (2)According to the efficiency of network nodes, nine industries can be clustered, and between the clusters the characterization of efficiency nodes is similar; (3)the inefficiency of innovation confirmation node and economic transformation node will lead to a sustainability inefficient of high patent-intensive industry as a whole. In view of the above research findings, this article provides reference recommendations for policy makers and business managers from the prospect of establishment of intellectual property intermediary service platform and enhance the technology forward-looking assessment.