Table of Content

25 October 2019, Volume 28 Issue 10

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Theory Analysis and Methodology Study

Research IntoGeneralized Maintenance Process for Air Force Station Repairable Equipment

LIU Liu, HUANG Zhi-jie, LIU Shen-yang

2019, 28(10):  1-4.  DOI: 10.12005/orms.2019.0216

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This paper explores the generalized maintenance processmodelapplied to air force stationrepairable equipment at multiple levels of spare parts and inventory. Based on the Monte Carlo algorithm, a large number of sampledata are generated by iteration. After fitting, themaintenance process is found to converge to the Lognor-mality in distribution, parameters are deduced by the least squaresmethod and maximum likelihood evaluate-on, and then steady state distribution function is obtained. Through the goodness-of-fit test, finally, the parameters of steady state maintenance and availability are obtained. Compared with evaluation results of simlox model for the system, the data consistency is ideal.

Facility Location under Existing Facilities: Responses to Terrorist Attacks

SONG Yan, TENG Chen-mei

2019, 28(10):  5-12.  DOI: 10.12005/orms.2019.0217

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The paper studies a location game underneath (in case of) the terrorist attack with astate and an extremist organization being two players, in which the terrorist attacks cities to maximize its utility while the state being a leader in the Stackelberg CompetitionModelforesees terrorist tactics to make location decisions for minimizing its loss.For the object of location decision, we deliberate a more realistic scenario: consideration of the existing facilities’ layout. Faced with these existing facilities, which have already been there before terrorist incident, weconductcasestudies of 20 urban areas todiscusswhen to consider the reconstruction or construction, as well as how to carry out the strategic choice. In addition, the location game is regarded as a mathematical programming problem in the condition among both fixed and variable number of facilities,and the location decision model based on existing facilities is constructed. At the same time, the state’s equilibrium utilities are discussed when the number of facilities is a variable. The consequences demonstrate that, for the government, the strategy to consider rebuilding facilities is always better than a strategy that does not consider rebuilding facilities, and considering the rebuilding strategy, there is an inherent relationship between the building numbers and rebuilding numbers when the facilities number is fixed, which poses an effect on the equilibrium strategy together with their cost parameters. The state’s strategychoice mainly depends on the ratio between the two cost parameters, and keeps constantin some threshold areas. The change rule of optimal gross facilities number exists when the number of facilities is variable. The government's equilibrium utility is not a monotonic function of K, Namely, the state can use fewer facilities than K butachieve the goal of K facilities.

Research on Demand-Oriented Competitive Location Problem of Capacitated Facility

YU Wu-yang, LV Jing

2019, 28(10):  13-19.  DOI: 10.12005/orms.2019.0218

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Customer willingness and capacity constraints are two important factors in competitive facility location problem. Considering the interact relationship of customer willingness and facility capacity, a bi-objective competitive location model is established aiming at minimizing enterprise cost and customer payment. A simulated annealing-based algorithm is proposed to solve the model by designing demand-oriented service allocation mechanism. Finally, a numerical example illustrates the influence of service allocation mechanism and some parameters, such as the target weight and the budget limit et al. The demand oriented factors will increase the total cost of the enterprise, but it can reduce the payment of customers to enhance the attractiveness to customers. In addition, the budget limit of the enterprise has an important influence on the decision of the location of the enterprise. The market share that the enterprise can obtain is positively related to the location budget limit. There is a negative correlation between the total payments of customers and the total cost of the services provided by enterprises, so the optimal location decision should be realized through the tradeoff between the quality of service and total costs.

A Multidimensional Filter Algorithm for Sequential Quadratic Programming with Trust Region

SUN Tao, YANG Xue-feng

2019, 28(10):  20-25.  DOI: 10.12005/orms.2019.0219

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Sequential quadratic programming(SQP)is one of the most effective methods for solving nonlinear programming(NLP)problems. However, due to the combination of trust region and SQP, there may be no solution(i.e. incompatibility). In view of incompatibility, a multidimensional compatible filter algorithm based on SQP and trust region is proposed. Firstly, according to the methods mentioned in the general literature, this paper introduces parameter variables to its constraints and punishes its objective function, which implements the feasibility treatment to overcome the incompatibility(i.e. without feasibility recovery stage). Secondly, this paper proposes a multi-dimensional filter condition to selectively accept the iteration step, thus avoiding the strict conditions of the traditional two-dimensional filter algorithm, which greatly relaxes the acceptance of the iteration step. Finally, we propose a modified multi-dimensional filter algorithm based on second-order correction strategy for possible effects. At the same time, the algorithm has global convergence under certain assumptions.

Bike Sharing Rebalancing Problem and Capacity Range Length Insertion Heuristic Algorithm

PAN Li-jun, FU Zhuo, LIU Xi-mei

2019, 28(10):  26-32.  DOI: 10.12005/orms.2019.0220

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Bike SharingRebalancing Problem(BRP)is an NP-Hard Problem. With the problem scale expansion, the existing heuristic algorithms computing speed is significantly slower. In this paper, the route feasible transformation property of this problem is discussed firstly, and then it is deduced that the insertion position allows the insertion of the capacity range of the customer point when constructing a feasible solution. On this basis, the concept of Capacity Range Length(CRL)is proposed, and also theCapacity Range Length Insertion Heuristics(CRLIH)is presented. The existing heuristics on the benchmarkproblems show that:1) CRLIHis faster than other reported heuristics and have smaller parameters to set. 2)CRLIH finds the current best solution for the 11 problems, and one of them is the new current best solution. 3)When solving large-capacity problems, the quality of CRLIH is superior to that of medium-and small-capacity problems.

A Game Model for End-of-life Vehicles Recycling Based on Government Intervention

ZHU Qing-hua, LI Huan-yun

2019, 28(10):  33-39.  DOI: 10.12005/orms.2019.0221

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In order to analyze the effect of government intervention on the recycling efficiency of end-of-life vehicles, game models are introduced to analyze the game relations between market entities based on government subsidies and government regulations, and then compare the decisions of recycling and dismantling enterprise and black market without and with subsidies or regulations. The results show that the two strategies play significantly positive roles in recycling market, which are influenced by consumer’s environmental awareness and the competition between the entities. However, compared with regulations, subsidies are more conducive to the recycling market in current situation. Further, a numerical simulation is presented to research the effects of subsidies and regulations, which provides some insights into the decision-making of government and enterprises.

An Evolutionary Game Analysis on the PPP projects of NIMBY Facility Based on System Dynamics

CHENG Min, LIU Ya-qun, WANG Hong-qiang

2019, 28(10):  40-49.  DOI: 10.12005/orms.2019.0222

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In order to understand the factors that influence the behavior options of the government, the enterprise, and the public in PPP projects of not-in-my-backyard(NIMBY)facility, the evolutionary game method and the system dynamics method are combined to carry out the study. Firstly, an evolutionary game model is constructed based on the assumption that the three parties have bounded rationality, and the interaction mechanism and the stability of the three parties are analyzed. Then, the system dynamics method is used to simulate the three-party evolution game process, and the influence of various uncertain factors on the game evolution process is studied, which provides a basis for formulating relevant policies. Finally, countermeasures are proposed based on the simulation results. The simulation results show that the strategic choice of the three parties is influenced jointly by some external variables. When changing the value of the external variables in the simulation system, the game will eventually reach the equilibrium state in which the government supervises positively, the enterprise makes positive efforts and the public participates in supervision. It is also shown that the government is the dominant player in the process of tripartite game and the public supervision is important in PPP projects of NIMBY facility. Meanwhile, a reasonable project punishment scheme is helpful for reducing the opportunistic behavior of the enterprise. Therefore, it is possible to promote the smooth progress of the PPP project of the NIMBY facility from the aspects of constructing a multi-agent coordination mechanism, attaching importance to public supervision, constructing a social supervision system, and designing a reasonable incentive plan.

Risk-averse Supply Chain Coordination Model Based on Joint Promotion Effort under Strategic Customer Behavior

WANG Jun-ping, YAO Da-qing, MIN Jie

2019, 28(10):  50-56.  DOI: 10.12005/orms.2019.0223

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Under the condition of the risk measurement criteria, the risk-averse supply chain coordination model based on the joint promotion effort is developed. The decision-making behaviors of the risk-averse retailer and risk-averse supplier are analyzed under the centralized and decentralized decision making systems, respectively. Main research conclusions are obtained: (1)In the centralized system, the price commitment can not only motivate the production of the supplier in the supply chain, but also mitigate the negative effects of the customer strategy behavior. (2)In the decentralized system, the retailer’s optimal order quantity and the supplier’s optimal sales effort increase with the increase of the risk aversion coefficient of retailer, but decrease with the increase of the risk aversion coefficient of suppliers; in addition, the retailer’s optimal sales effort is not related to the risk aversion coefficient of retailer and supplier. (3)Since the complexity of the supply chain, it is unable to use the traditional buy-back contract to realize the coordination of supply chain, but a combined contract is designed to realize the perfect coordination of supply chain.

Pricing Decisions of Closed-loop Supply Chain Based on the Risk of Recycled Product

MENG Li-jun, HUANG Zu-qing, ZHANG Bao-you, YANG Yu-xiang

2019, 28(10):  57-67.  DOI: 10.12005/orms.2019.0224

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This paper develops a closed-loop supply chain(CLSC) model with a monopolist firm which produces the new product in the first period, and offers both the remanufactured product and the new product in the second period. This study assumes that the new product and remanufactured product are clearly distinguishable by the customers, so they have different prices in the market. Based on these assumptions, two models are constructed according to the case of the centralized closed-loop supply chain (the manufacturer collect the used products by itself) and the decentralized closed-loop supply chain (the manufacturer outsources the collection process to one third-party independent collector). Using the game theory, the equilibrium solutions between the recycling price decision and the retail price decision are derived and analyzed. Further, numerical examples are used to demonstrate the managerial results. It is shown that: (1)the closed-loop supply chain structure affects the price of remanufactured products and the recycling price of waste products, but has no influence on the pricing of new OEM products. (2)the impact of changes in recycling risks on price decisions depends on the structural characteristics of CLSC. When the recycling risk is low, the manufacturer’s self-recycling mode is better than the third-party recycler’s recycling mode in stimulating consumers’ demand for remanufactured products, encouraging consumers to return waste products and improving the overall efficiency of the closed-loop supply chain. When the recycling risk is high, the recycling mode of the third party recycler is better than that of the manufacturer. (3)the reduction of recycling risk makes the total profit of the closed-loop supply chain show a growing trend, which further reflects the economic value of remanufacturing. (4)OEM self-recovery of waste products should take into account the price competition between new products and remanufactured products. When the price competition is weak, OEM self-recycling used products can bring more profits to OEM; the price competition between new products and remanufactured products is also conducive to the improvement of demand for remanufactured products.

An OptimalModel of Packaging Processfor Fruit and Vegetable Products under Online Direct Selling

ZHANG Dong, HU Xiang-pei, HUANG Min-fang

2019, 28(10):  68-76.  DOI: 10.12005/orms.2019.0225

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Based on the methodologies of batch flow-shop production, just-in-time manufacturing and cyclic scheduling, this paper studies the production scheduling problem of fruit and vegetable products’ standard sales unit packing in an online direct selling setting. This problem is of large scale and involves multiple products, high order customization, and frequent deliveries, etc. To solve this problem, we establish the standard sales unit packaging operation optimization model and design a modified “compressed annealing algorithm” to solve it. Reasonable standard sales unit packing plans are then generated so that picking, sorting and loading operations are smoothly connected, as a result, the standard sales unit packing time can be reduced and the freshness of fruits and vegetables can be retained as much as possible. We validate the effectiveness of the model and algorithm through a practical example. Compared with the normal non-cyclic scheduling method, our model and algorithm of cyclic production scheduling are able to cut the cost of packing standard sales unit, which serves as a theoretical guideline for enterprises direct-selling fruit and vegetable products online.

Effect of Defuzzifying Triangular Fuzzy Number on Compromise Solutions in VIKOR

JIANG Wen-qi, JIANG Wen-qi, DAI Yue-wei

2019, 28(10):  77-82.  DOI: 10.12005/orms.2019.0226

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According to the multi-criteria decision making problems in which the criteria and their weights are also triangular fuzzy numbers, the paper studies whether different defuzzification methods of triangular fuzzy numbers are suitable for the mathematical operational laws, the necessary steps and the preconditions of defuzzifying triangular fuzzy numbers in VIKOR, and the effect of defuzifying triangular fuzzy numbers on group utilities and individual regret and compromise solutions is also proposed. Then the decision steps of extension of VIKOR method are applied to solve the multi-criteria decision making problems. Finally, an example illustrates the procedures and effectiveness of the proposed method.

A Branch and Bound Algorithm for the Bi-agent Single-machine Scheduling Problem with Release Dates

LIANG Jian-heng, XUE Han-yu, BAI Dan-yu, MIAO Yun-hui

2019, 28(10):  83-88.  DOI: 10.12005/orms.2019.0227

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This paper investigates a bi-agent single-machine scheduling problem with release dates. The objective is to minimize the sum of makespans. A mixed integer programming model is established for solving the problem by using optimization software. Given the NP-hardness of the problem, approximate and accurate algorithms are presented to handle different scale instances. For large-scale problems, available dominance agent first heuristic algorithm is proposed and its asymptotic optimality is proved. For small-scale problems, a branch and bound algorithm is designed to obtain optimal solution, in which a release-date-based branching rule and a preemption-based lower bound reduce the running time effectively. Numerical experiments show the effectiveness of the proposed algorithms.

Aplication Research

Test for Bayesian Quantile Panel Cointegration Based on Dynamic Factor Model

LI Su-fang, ZHANG Hu, WU Fang

2019, 28(10):  89-99.  DOI: 10.12005/orms.2019.0228

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The traditional panel cointegration methods are based on conditional mean models, which is relatively sensitive to outliers. Meanwhile, the cointegration results may differ when the null hypothesis varies, which causes the difficulty of the cointegration tests in the case of different null hypothesis. This paper proposes Bayesian quantile panel cointegration method on the basis of the panel data dynamic factor model, which implements dynamic common factor to characterize the possible cross-section dependence in panel data. To get the parameter estimates of the model and conduct Bayesian quantile panel cointegration test in the major quantiles, the Gibbs sampling algorithms are designed. We also conduct a Monte Carlo study to illustrate the feasibility and validity of Bayesian quantile panel cointegration. Finally, through the empirical application of Chinese financial development and economic growth, we find there are cointegration relationships between Chinese financial development and economic growth in the major quantiles. It shows that Bayesian quantile cointegration method avoids the bias caused by the set of null hypothesis in the traditional panel cointegration and tends to be impervious to outliers. It also shows that Bayesian quantile panel cointegration can provide full and exact information on parameter estimation and cointegration tests.

Research on Fresh-keeping Effort, Ordering and Pricing in Fresh Supply Chain

CAO Yu, WU Kan, XIONG Shou-yao

2019, 28(10):  100-109.  DOI: 10.12005/orms.2019.0229

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In combination with the background of severe fresh loss and excessive preservation, on the basis of distinction between quality guarantee period and actual effective delivery time length, a comparative study of two level fresh supply chain consisting of a single retailer and a single supplier ismade.Whether the two main subjects cooperate and the dominant subject changes or not has an important impact on the supply chain’s freshness, effort level and pricing. The research shows that, in the centralized supply chain, fresh effort increases with the freshness sensitivity, the fresh keeping effort increases with the effective delivery time length and is inverted ‘U’ type. The total profit of supply chain increases with the freshness and actual effective delivery time length. In the distributed supply chain, with the increase of sensitivity to freshness, the preservation efforts and overall profits increase. As the effective delivery time length increases, the preservation effort increases first and then decreases, and the total profit increases. There is a chance of free riding in decentralized supply chain, but since the effective delivery time length is different from the quality guarantee period, with the scale between the two time length changes, it may be more beneficial to conduct self preservation efforts than to take a free ride.

Optimal Pricing Strategy of Personal Cloud Storage under the Cloud Security Risk

YAO Meng-di, CHEN Dong-lin, DENG Guo-hua, XU Shang-ying

2019, 28(10):  110-116.  DOI: 10.12005/orms.2019.0230

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For the personal cloud storage service are shut down, how to make a reasonable pricing strategy according to the different market stage and cloud users’ features has become a challenge for the personal cloud storage service provider. Considering the impact of cloud security risk, cloud user perceived value and the elastic cost on the pricing of personal cloud storage, the two stage-pricing model based on cloud security risk is established, and then the optimal strategy under the determined free trial time, the optimal free trial time and price under the determined free trial time are put forward. Combined with the numerical analysis, the impacts of cloud security risk, cloud users perceived value and cloud security cost coefficient on the optimal free trial time and optimal profit are studied. The results show that the personal cloud storage service provider should adopt the two stage pricing strategy when the cloud security risk coefficient is moderate. In addition, the optimal profit increases and then decreases with the increase of cloud security risk coefficient, the free trial time and the unit cloud security operational cost.

Screw Thread Steel Option Pricing Based on Optimized Black-Scholes Model

LI Ming-xin, TANG Jun, BAI Yun, MA Xing-da

2019, 28(10):  117-122.  DOI: 10.12005/orms.2019.0231

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Energy finance and derivatives trading of commodities has gradually become a hot and leading edge topic in the field of finance. Research of Derivatives pricing and risk research of energy finance plays an important role in energy asset securitization and the development of finance. Under the existing share option pricing model, this paper optimizes the classic real option pricing model of Black-Scholes by combining the factors that influence the real option price of screw thread steel, and obtains the fuzzy real option pricing model of B-S. Then, it studies the pricing Mechanism of the real option of screw thread steel and quantifies the financial risks of coal by combining VaR method, and thus the purpose is to control the financial risk of screw thread steel reasonably.

Volatility Risk Premium and Its Influencing Factors by Jump Diffusion Model ——Evidence from the Shanghai 50 ETF Options

WANG Su-sheng, HU Ming-zhu, LI Zi-long

2019, 28(10):  123-131.  DOI: 10.12005/orms.2019.0232

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This paper uses the daily frequency data of Shanghai 50 ETF and ETF options. We use SVCJ model, MCMC and Fourier transform method to extract volatility risk premium from P measure and Q measure. The research shows that the SVCJ model has better market fitting goodness than the SV model and the SVJ model, and the Fourier transform method can improve the estimation efficiency. In the period of market turbulence, volatility risk premium is negative generally, and investors are risk-averse, who have a higher willingness to buy options to hedge volatility risk. In non-violent turbulence period, the volatility risk premium is positive generally, and investors generally act risk seeking. Market returns, volatility, turnover rate, and investor sentiment have a significant impact on volatility risk premium.

Stock Prediction Model Based on Neural Network

QIAO Ruo-yu

2019, 28(10):  132-140.  DOI: 10.12005/orms.2019.0233

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To address the issues corresponding to the difficult feature extraction and low prediction accuracy in the stock market, this paper proposes a series of neural network-based models for stock market forecasting based on deep learning, which refers to multi-layer perceptron, convolutional neural network, recurrent neural network, long-and-short-term memory network and gated recurrent unit, respectively. In consideration of the case that RNN、LSTM and GRU models can not make full use of the referred information in time dimension, this paper introduces the attention mechanism to give different weights to the information of each time dimension which can distinguish the importance of different information to the prediction, and then improve the performance of the recursive network model. All the models are optimized with respect to the stock data. Extensive experiments on the Shanghai Stock Index demonstrate the effectiveness of the proposed models. In addition, the comparisons between different models further explore the effect of the important parameters in the models. The purpose of this paper is to give the optimization direction of the stock forecasting models based on neural network.

Audit Opinion, Top Managers’Financial Background and Internal Control Deficiencies Remediation

WANG Xiao, GAO Jie, LU Qiang

2019, 28(10):  141-149.  DOI: 10.12005/orms.2019.0234

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This paper first examines the relationship between audit opinions and internal control deficiencies remediation, based on internal control assessment reports disclosed by A-share listed companies of Shanghai and Shenzhen Stock Exchange from the year 2010 to 2014. Then we find that the higher the proportion of members with financial background of the top manager team, the more likely the deficiencies will be revised through group-level regression research, which indicates that the governance effect of modified external audit opinions on internal control may depend on top managers, as well as the importance of efficient allocation of human resources. Tracking the firms’ received modified audit opinions last year, we find that they receive the same opinions again, indicating that the remediation of the deficiencies in these companies may be on the surface, which is not effective.

The Vector Grey Model and Its Application

ZHOU Wei-jie, DANDG Yao-guo

2019, 28(10):  150-155.  DOI: 10.12005/orms.2019.0235

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When modeling actual data sets by the traditional multivariable grey forecasting model (abbreviated as MGM(1,m)), the simulated data are distorted at times, such that the simulated value is two times that of the true value, and the simulated value is negative while the true value is positive. In order to solve the distortion problem, a new model called the vector grey model (abbreviated as VGM(1,m)) is proposed based on the interrelated variables in the system. Compared with MGM(1,m)model, the VGM(1,m)structure is simpler and the model parameters are less, which is beneficial to the estimation of parameters. So, the amount of parameters calculation in VGM(1,m)is far less than that of MGM(1,m), and the multiple collinear and over fitting phenomena may be alleviated. With four actual examples included air quality index system, economic and energy system, rural household income system and total social fixed investment and gross domestic product(abbreviated as GDP), the results show that VGM(1,m)eliminates the distortion phenomenon which happens in MGM(1,m), so the stability of new model is enhanced. Meanwhile, the prediction accuracy of VGM(1,m)model is higher than GM(1,1)model, which denotes the new model possesses better generalization ability. The new model has expanded the existing grey prediction model system.

Study of the Influence of Asset Divestiture on Risk Premium

CHEN Jia, LI Qiang, ZENG Yong

2019, 28(10):  156-164.  DOI: 10.12005/orms.2019.0236

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Asset divestiture affects the risk-return characteristics of total assets by changing the composition of assets-in-place. Different from the literature in which asset divestiture is modeled as the exercising of put option, this paper develops a generalized exchange option model to describe the situation in which firms divest non-core assets and then refocus capital and management resources on core assets. Using a real option approach and the technique of pricing kernel in a continuous-time framework, the paper theoretically demonstrates the influence of asset divestiture on risk premium and provides supporting evidence from A-share listed firms in China. The results show that the direction of the influence of asset divestiture on risk premium depends on the relative magnitudes of risk premiums on core assets and non-core assets, while the influence degree of divesture is relate to the difference in the values of two kinds of assets and the proportion of exchange option value in firm value. Further results show that the waiting flexibility of divesture decision will weaken the influence of asset divestiture and divestiture will be more likely to have a positive influence on risk premium for firms in earlier stage of their life cycle.

Management Science

Integrated Problem for Lot Sizing and Flexible Flow Shop Scheduling Problem in the Tobacco Industry Considering Setup times and Cigarette Quality

CHAI Jian-bin, LIUHe, BEI Xiao-qiang

2019, 28(10):  165-174.  DOI: 10.12005/orms.2019.0237

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Based on theintegrated problem for lot sizing and flexible flow shop scheduling problem in the tobacco industry, it is formulated as a mixed integer linear model to optimize the lot sizing and scheduling problem whose objective consists of four parts:the production time, the setup times, thecigarette quality and inventory cost. Given the problem is NP-hard, a genetic algorithm is designed to solve this problem based on monolithic method, the infeasible solutions are reduced through the design of genetic operator. Numerical examplesare conducted based on the operation data of a cigarette corporation. The result shows great advantage on decreasing setup times over the previous scheduling plan, which proves the feasibility and validity of our model and algorithm. The effectiveness of the algorithm can be well verified inscheduling decision support for the production of cigarette of real company.

Application Driven UpdatingPolicy for Dynamic Data in Enterprise InformationSystems

ZONG Wei, WU Feng, LIU Wei

2019, 28(10):  175-183.  DOI: 10.12005/orms.2019.0238

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In the age of big data, constantly changing data sourcesmake it a great challenging task to assure data timeliness in enterprise information systems. Taking the dynamic purchase data in an enterprise resource planning(ERP)system as the research object, this paper mainly studies how and when to update the purchase data in ERP systems from the application driven aspect so as to minimize the sum of updating cost and staleness cost. We apply Markov decision process to the problem of purchase data updating in ERP systems and design a dynamic programming algorithm to obtain the optimal updating policy. Compared with the traditional fixed interval updating policies throughnumerical analyses, the proposed application driven purchase data updating policy could not only assure data timeliness but also save enterprise cost effectively.

Impact of External Dependency on Industrial Value-added

YANG Shui-li , YANG Yi

2019, 28(10):  184-191.  DOI: 10.12005/orms.2019.0239

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To clarify “the threshold effect” of external dependency on industrial value-added is the basic logic for guiding manufacturing industry to utilize “technological dividend”, avoiding “low-end industrial development”, “core technology hollowing-out”, and “value-added impoverishment”. From the views of trade mechanism and industrial linkages, the paper explores the mechanism of external dependency to the industrial value-added, and verifies the moderating effect of basic research and applied research. The empirical results show that: There is a significant inverted U-shaped relationship between external dependency and industrial value-added, and applied research plays a significant positive moderating role between external dependency and industrial value-added, while basic research has a significant negative moderating effect on external dependency and industrial value-added. Moreover, the paper suggests setting up the red line of external dependency, and establishing the guarding mechanism of industrial safety; optimizing the proportion of applied research and basic research, and timely converting the direction of research and development investment.

Study of Dual-channel Manufacturer’s Referral Strategies with a Dominant Retailer

DOU Xiao-le, GUO Qiang, LI Zeng-lu, NIE Jia-jia

2019, 28(10):  192-199.  DOI: 10.12005/orms.2019.0240

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The referral strategies problem of dual-channel manufacturer is studied with a dominant retailer. First, we establish the model considering a weak retailer. In this benchmark, we find that: a large referral market size can encourage the manufacturer to recommend the consumer to an official store and retailing store. In this case, the retailer and manufacturer have high consistency in the referral strategies. In the decision mode with a dominant retailer, compared with the benchmark, when the referral market size is small, if the wholesale price is large, the manufacturer refers the consumer to the official store and retailing store; when the referral market size is large, if the wholesale price is small, the manufacturer refers the consumer to the official store. If and only if the referral market size and wholesale price are larger or smaller, the referral strategies of the retailer are in consistence with the manufacturer. In addition, we also study the consumer surplus and social welfare under different referral strategies.