This paper decomposes the common trend and codependent cycle of the economic growth and inflation, to reveal the equilibrium matching range of the economic growth and inflation, and studies the impact of real and nominal factors on common trend and codependent cycle of economic and inflation. This paper illustrates following facts. First, the economic growth and inflation formed common trend and codependent cycle. Moreover, these common trend and codependent cycle changed with the transformation of economic structure. After economic transformation, the economic growth and inflation formed a new "common" running situation, in which the trend economic growth rate decreases slowly but unstably. For the economic growth goal that beyond 6.5% under new norm, the target of inflation should be slightly lower than 2%. Furthermore, both real and nominal factors have a significant impact on the interval control of the economic growth and inflation. However, investment, consumption, financial expenditure, monetary policy and opening to the outside world are the main factors to keep the economic growth and inflation in a reasonable range.
Enhancing enterprise competitiveness and promoting outward foreign direct investment (OFDI) has become the focus for both academics and practitioners. However, there is a dearth of literature on how foreign ownership influences OFDI in the Chinese context. Based on a sample of A-share listed companies in China from 2006 to 2016, this paper investigates the impact of large foreign shareholders on the propensity of OFDI, and then analyses the impact of heterogeneous enterprises on the relationship between foreign ownership and the propensity of OFDI. Finally we discuss two types of impact mechanisms of large foreign shareholders on the possibility of OFDI. Empirical results show that foreign ownership generally increase the tendency of FDI among Chinese listed companies, however long-term foreign ownership can significantly increase the propensity of FDI. In addition, foreign ownership has a greater impact on OFDI in developed countries than in developing countries and the foreign ownership in non-state owned listed companies has a greater impact on the tendency of FDI than that in state-owned listed companies. Foreign ownership cannot improve the possibility of enterprises by the efficiency of R&D, but it plays a role of information transmission. In theory, the conclusion of this paper enriches the theory of enterprise heterogeneity of OFDI, and also in practice provides policy reference to China's opening-up of the capital market and the reform of mixed ownership of state-owned enterprises.
Using a sample of Chinese A-share listed firms from 2008 to 2017, this study examines the influence of corporate competitive strategy on firm value from the perspective of enterprise life cycle. Empirical results show that differentiation strategy is positively related with firm value, while cost leadership strategy is negatively related with firm value. We also find that the positive relation between differentiation strategy and firm value is most pronounced for firms in mature period, and the negative relation between cost leadership strategy and firm value is most pronounced for firms in recession period. Additional tests show that economic policy uncertainty and internal control moderate the negative relation between cost leadership strategy and firm value. Our study contributes to existing literature in that we study the relation between corporate competitive strategy on firm value from a dynamic view of enterprise life cycle, which enhances our understanding towards the relation between corporate competitive strategy and firm value.
Under the framework of mean-variance analysis, investors need to estimate the mean vector and covariance matrix of asset returns to make investment decision. The most common estimation method is called "backward-looking" method since it relies only on historical data. However, it does not use the "forward-looking" information implied by the market variables, such as asset prices, and then cannot predict the future well. In this paper, we consider the general situation that market participants are consisting of informed investors and noise traders, and extract the "forward-looking" information on asset returns implied in the equilibrium market portfolio. By combining the historical "backward-looking" information with the market implied "forward-looking" information via Bayesian analysis, we propose a "combined" method for return prediction. The theoretical analysis show that the "combined" method can adaptively select more "forward-looking" information when the informed investor has a higher market share, a lower risk-averse degree, or the noise trader has a lower noise trading intensity; otherwise, it will use more "backward-looking" information. Both the simulation experiments and the empirical tests demonstrate that the "combined" model can provide more flexible and robust prediction on asset returns in portfolio management.
In this paper, we use quantum field theory to model the term structure of the risk-free treasury bond forward interest rate and the spread forward interest rate which represent credit default risk, and then construct the term structure of the risk-adjusted local government bond forward interest rate. The empirical analysis compares the fitting effect of the new model under the quantum field theory, the traditional model under the quantum field theory and the traditional financial two-factor HJM model, deduces the updating process of the instantaneous forward rate of local government bond under the new model, predicts the instantaneous forward rate of local government bond and tests the robustness. The empirical results show that the prediction effect of the new model under the quantum field theory is better than the traditional model under the quantum field theory and the traditional financial two-factor HJM model, and it has passed the robustness test of the model. Through the reasonable modeling and prediction of the term structure of local government bond forward interest rate, it is of great significance for relevant departments to understand the default risk of local government bond.
The process of RMB internationalization will inevitably face constraints and resistance from existing major international currencies. From the perspective of international currency competition, this paper establishes a Stackelberg model, to analyze the choice of competitive strategy and the game relationship of competition and cooperation between different international currencies. The game analysis result shows that the following currency will be suppressed by the leading currency, and the two currencies will have a prisoner's dilemma. However, under the conditions of long-term repeated games, the two currencies will achieve mutual compromise and cooperation through strategic interactions such as reciprocity or interest compensation to achieve Pareto improvements. Therefore, the internationalization of the RMB is bound to be a long and dynamic international game process.
Extended producer responsibility (EPR) policy requires companies responsible for product ecological design (eco-design) and product recycling, which is called dual environmental responsible behavior. In this paper, a producing-remanufacturing competition system comprising one producer and one remanufacturer was considered, then a two-stage decision-making model was constructed to explore behavioral characteristics and incentive strategies of dual environmental responsible behavior under constraints of EPR policy. Results show that: The ratio of producer factor to remanufacturer factor defines three decision regions: Full, partial, and no remanufacturing; EPR policy can promote remanufacturing by changing the ratio. Besides, there is a trade-off between product eco-design and product recycling when it comes to discussing influences of factors (EPR policy, eco-design environment, and product competition) on dual environmental responsible behavior. In particular, subsidy policy has certain advantages in balancing economic and environmental benefits, and can achieve higher social welfare. Moreover, when tax reduction value is above a certain threshold, producers will be more inclined to develop remanufacturing-oriented eco-design to promote source prevention of waste. Therefore, government should comprehensively consider multiple factors and design a combination of EPR policies to promote the fulfillment of dual environmental responsibilities under product competition environment.
This paper studies a two-stage supply chain consisting of a mobile phone manufacturer and a telecom operator, in which the telecom operator purchases mobile phones from the mobile phone manufacturer and bundles the mobile phone and telecom services as "contract mobile phone" for sale, and discusses the impact of leading player changes and different contract designs on supply chain quality input and pricing. The research shows that the change of quality effort cost is an important variable that affects the supply chain operation decision. When the player of high-quality effort cost is dominant in the supply chain, the quality effort input, sales price, leading player's income and the total profit of the supply chain are more favorable, and followers of low-quality effort costs can also use the cost advantage to obtain higher profits than when they are the leader. In addition, regardless of whether it is the leadership of a mobile phone manufacturer or a telecommunications operator, a cost-sharing contract can distribute the profits of the supply chain more reasonably, so compared with a wholesale price contract, a cost-sharing contract can improve the quality of mobile phones and services and the profit of each player. The quality of mobile phones, quality of services, sales prices and the profits of various players are all negatively affected by the cost coefficient of mobile phone quality efforts and the cost coefficient of service quality efforts, and positively affected by consumers' sensitivity to quality and the degree of complementarity between products and services. Moreover, complementarity also plays an important role in the change of the leading players.
The demand uncertainties in different regional markets exacerbate the mismatch between supply and demand in the overall market. Lateral transshipment inventory strategy can be used to solve this mismatch problem. In this paper, we study the preventive lateral transshipment inventory strategies by considering two retailers who can update the forecast information of demand when the manufacturer provides two ordering opportunities at different prices. Based on the description of the demand information update process, we first carry out inventory adjustment judgment through the collected demand information signal, then develop two inventory decision models according to whether the retailers implement transshipments. Sensitivity analysis is performed for the parameters of transfer price and demand information update. The analysis of numerical examples show that demand information update and the preventive lateral transshipment strategy can not only increase the profit of retailers and the whole supply chain system, but also help manufacturer meet market demand with lower production scale. Then the validity of the model is verified.
Task assignment and path planning should be solved in "last mile" cargo delivery and pickup for unmanned aerial vehicles (UAVs). This article introduces the idea of "blockchain", an auction algorithm that optimizes the task allocations of drone formation. Blockchain converts integrated centralized computing to distributed multi-agent interconnection computing, which make the UAVs readjust the unreasonable mission results during the mission planning process, and reduces the decision calculation time and costs of drone transportation. After determining the initial and final positions of drone delivery, we establish a cost function model with constraints on path length, terrain, radar threat, and drone collisions resulting in an improved quantum particle swarm algorithm (QPSO). The task allocation strategy and path planning method proposed in this paper can achieve better results than traditional methods, and thereby reduce computing resource consumption. The simulation results from our analysis show that the proposed two methods in terms of computational efficiency and task execution is very effective.
In this paper, we present an optimal planning of vehicle routing problem with simultaneous delivery and pick-up for urban small package shipping under electronic commerce context. At the same time, the location strategy of the fast-pick areas are taken into consideration, vehicles can be replenished and unloading can be done at the fast-pick areas. The problem is formulated as two integer programming models which aim to reduce the operational cost of logistics enterprises with the consideration of routing, location and service strategies. A hybrid heuristic algorithm called CWIGALNS with different modified operators are proposed to solve the problem and the validity of the models and the reliability of CWIGALNS are assess on 9 small-scale instances. Finally, experiments are performed on multiple sets of instances belonging to two different series. The model in which unloading can be done at the fast-pick areas could decrease the operational cost with less vehicles. The models and algorithm proposed in this paper can provide good reference and help for the service strategy of urban small package shipping enterprises.
Based on the hypothesis of the limited shelf life and modularity of relief materials, we propose a stochastic dynamic pre-positioning model to study the lateral transshipment pre-positioning strategy. In order to solve the dimensional disaster problem of the proposed model, we use the approximate dynamic programming method to simulate the utility function of relief materials for transforming the proposed model into a set of linear programming problems. Then, we apply the proposed approach to the simulated emergency pre-positioning activities of five central-level emergency materials' warehouses in China. Results show that the pre-positioning strategies obtained by the proposed approach can improve the expected disaster-relieving utility of materials under the relatively high degree of demand satisfaction.
As electric vehicles are becoming increasingly popular, more and more logistics companies deliver products by both conventional fuel vehicles and electric vehicles. Based on the difference between maximum capacity, maximum travel distance and operating cost of conventional vehicles and electric vehicles, and the charging behavior of electric vehicles, electric vehicle routing problem with time window and mixed fleet is examined. An integer programming model is presented and it is decomposed into the main problem and the sub-problem based on the Dantzig-Wolfe decomposition principle. A heuristic rule and genetic algorithm are proposed to generate the initial solution quickly for both small-scale instances and large-scale instances respectively. The branch and price algorithm is developed to obtain the optimal solution. The performances of proposed model and algorithm are validated by comparison with CPLEX. Finally, sensitivity analyses of the influence of number of electric vehicle, vehicle capacity, battery capacity, charging rate on the total cost are performed, and managerial insights are obtained.
This paper analyzed travelers' route choice inertia in stochastic network and proposed an inertia-based route choice model. The inertia-based route choice model included different inertial behavior mechanisms and could be reduced to several route choice models in the literatures by setting special values to the parameters. The proposed route choice model was further applied to establish the stochastic-network inertial user equilibrium model as well as its equivalent non-linear complimentarity problem. The paper also conducted numerical examples to illustrate the inertial route choice model as well as the traffic assignment model.
The coordinated control of integrating variable speed limits (VSL) and multi-ramps metering for freeway based on pining synchronization of complex networks was studied. The improved cell transmission model of each segment under VSL on a freeway was established. Then each node was defined and a node coupling model was established. The coordinated controller of integrating VSL and ramps metering was designed based on pinning synchronization of complex networks, where the pinning nodes corresponding to the subsystems are used to input control signal. Total time spent calculated by the predicting module is used as the index to optimize the speed limit value. The range of inputting control signal is obtained and the ramp metering parameters are optimized in order to realize the system synchronization using the system stability condition. The controlling effects were verified via the simulation experiments. The results indicate that the advantages and disadvantages of VSL and inflow control can be integrated and the unbalanced characteristics of traffic flow spatial-temporal distribution can be utilized using the designed controller based on the proposed method. The phenomena of traffic jams can be suppressed utmost and the operating efficiency can be enhanced at an optimized control mode and range cost.
This work studies the processing schedules of parallel machines with strong response abilities to unexpected and urgent jobs. We consider the job scheduling on three parallel machines, aiming to minimize the maximum difference between the completion times of any two consecutively completed jobs, in other words, to minimize the maximum inter-completion time. We first give two upper bounds of the workload of machines which is the sufficient condition of feasible solutions. Based on the sufficient condition, we first give several basic properties of the optimal solution. Secondly, we further prove a lower bound of the objective value and design an O(n2) time algorithm to calculate the lower bound. Finally, we develop an improved algorithm based on the RMST algorithm to solve the considered problem, in which the RMST algorithm considers the case that one may reserve as much spare time as possible on one of the machines. Through computational comparisons between the improved algorithm and RMST algorithm together with the genetic algorithm and the lower bound of objective value, it is shown that our algorithm outperforms the other two algorithms. Numerical experiments verify the effectiveness of the improved algorithm.
In view of the uncertainty of processing time in distributed environment, this paper describes the processing time and product assembly time with triangular fuzzy numbers, establishes a distributed assembly flexible job shop scheduling model (DAFJSPF) aiming at production cost and delay time, and proposes a hybrid estimation of distribution (EDA)-based optimization algorithm that integrates differential evolution (DE)-based evolutionary operators and variable neighborhood search (VNS), named HEDA-DEV, for solution. Firstly, the algorithm adopts a new multi-dimensional coding scheme according to the characteristics of the problem; secondly, the similarity coefficient and two mutation operators based on the probability model are proposed to realize the dynamic selection of mutation strategy; in order to improve the optimization ability of the algorithm, five kinds of variable neighborhood structures are designed, and the specific search strategy is used to make the cooperation.Finally, the comparison experiments of several scale and different flexibility examples verify that the algorithm has strong advantages in solving DAFJSPF.
Knowledge-cooperation networks are widely used in innovation activities. Mining the link information in multi-layer networks, identifying potential cooperation opportunities and revealing the mechanism of cooperation relationships, will help build more complete cooperation networks. The link prediction method preserve the integrity of the network information to the greatest extent, it not only can predict the probability of the cooperative relationship generation, but also explore the rich connotation of the cooperative relationship. This paper proposes a hybrid weighted multi-layer algorithm of link prediction for knowledge-cooperation networks. First, in the knowledge-cooperation network including the process of knowledge transfer and collaboration, five types and definitions of knowledge attributes are proposed; Then, the node common neighbor and knowledge attribute information are both used to predict the link generation probability, and a hybrid weighted algorithm is constructed to analyze the impact of different knowledge attributes on the cooperation link generation. Finally, the test results in the patent data set show that: The hybrid weighted algorithms of link prediction not only can more accurately predict the links and formation mechanisms of multi-domain cooperation, but provide guidance for partner identification and recommendation.
In order to solve the problem of fuzziness and uncertainty of linguistic value evaluation in multi-attribute decision making, D-S evidence theory is introduced on the basis of cloud model evaluation. Firstly, the golden section method is used to transform the experts' linguistic evaluation into the cloud decision matrix, then the membership degree of each evaluation grade is obtained by referring to the standard cloud of different grades in the comment set, and the basic probability distribution function (BPA) of different experts' comments on different attributes in different schemes is constructed; Secondly, conflict coefficient, Jousselme distance and Pignistic distance are introduced based on D-S evidence theory, the amount of evidence conflict is defined, the experts' mass functions are modified and fused by calculating the relative weight of each evidence credibility and experts; Thirdly, BPA are fused by combining with each attribute weight, the optimal scheme is obtained by comparing the average fit degree, which roots in the comparision mass functions of each schemes with ideal cloud and negative ideal cloud; Lastly, the applicability of the algorithm is verified by an example, which provides a new technical approach for multi-attribute decision making.
Deep-sea manned submersible operation is a high-risk operation in special environment. In order to study the variation characteristics of the oceanauts human-factor reliability in dynamic thermal environment, firstly analyzed the human-machine-environment characteristics of manned submersible cabin and the dynamic environment changes of mission process. Then, on the basis of cognitive reliability and error analysis method (CREAM), established the functional relation between cognitive failure probabilities (CFP) and productivity (P), constructed CFP correction model by introducing environmental compensation coefficient (k). Furthermore, obtained quantitative environmental compensation coefficient (k) by predicted mean vote-productivity (PMV-P) method. At last analyzed the change characteristics of CFP for oceanauts through 7000m deep-sea operation mission. The results shown that the model can describe the changing characteristics of CFP for oceanauts in dynamic operating environment. During the submarine descent to 4000 meters, the thermal environment of the cabin have a great influence on CFP of the oceanauts. This method provided a theoretical basis of optimizing resource allocation and improving system design of submersible.