By improving the current measurement method on uncertainty, a high-dimensional factor model based on a 274-dimensional monthly data of economic and financial parameters from 2002 to 2018 is adopted to achieve goal of separating and measuring China's economic uncertainty and financial uncertainty, and then the relationship between them will be discussed with the help of nonlinear Granger causality test and dynamic spillover index method. Moreover, an SV-TVP-FAVAR model will be used to carry out dynamic econometric test which could reveal the macroeconomic effects of economic and financial uncertainties. The results are as follows: First, prominent staged volatility is found in both China's economic uncertainty and financial uncertainty, and the level of financial uncertainty is significantly greater than its economic counterpart since the new-normal-period. Second, financial uncertainty is an important cause of the formation of economic uncertainty, while economic uncertainty has a relatively lower impact on financial uncertainty, and particularly, their interaction is basically a one-way impact that financial uncertainty laid on economic uncertainty since the new-normal-period came. Third, both economic and financial uncertainty are important factors that cause output fluctuations and price fluctuations, specifically, the amplification effect, time lag and persistency of the impact from financial uncertainty are greater than that from economic. Carried out from the perspective of uncertainty, this research could offer certain help on interpreting the impact mechanism of modern economic and financial systems, and on providing practical policy implications on strengthening expectation management.
Lenders in online lending markets face the same old problems of information asymmetry and moral hazard, but also encounter new challenges of fast bidding in order to participate in loans. Online platforms attract lenders with new forms of tools and essentially serve as technological intermediaries. In this study, we studied one technological intermediary offered by the platform from three aspects including quantity, quality and competition. It was found although experienced lenders react better based on their information about the platform, first-time lenders on this platform are as competitive as more experienced lenders due to the investment tool. The intermediary seemingly makes the online market a fair playfield for first-time lenders.
There is few literature about corporate risk information disclosure in the bond market. Using the sample of bond prospectuses issued in Shanghai Stock Exchange or Shenzhen Stock Exchange from 2006-2017 and through textual analysis on corporate risk information, this paper studies the impact and mechanism of corporate risk information disclosure on bond risk premium. The empirical results show that there is a significant positive association between risk disclosure level in bond prospectus and bond risk premium. In the parts of further analysis, it is found that the positive association between risk disclosure and bond risk premium can be moderated by guarantee clause, ownership style, corporate performance and investors' risk sensitivity. This paper shows the impact mechanism that the rise of risk disclosure level in bond prospectus will improve investors' default risk perception, which leads to the rise of risk premium.
Basing on market microstructure theory, we try to analyze the implications of public information disclosure for heterogeneously informed traders' trading strategies, profits allocation and the consequent market quality (including market liquidity and market efficiency) on premise of multiple-fundamental assumption in a Kyle-type model (Kyle, 1985). We conclude the results as follows. Firstly, the informed trader, whose private information and the public information are on the same fundamental, trades on the public information reversely, and the relative weight between his trading on his private information and that on the public information decreases with the precision of the disclosed public information. Secondly, the informed trader, whose private information is about different fundamental from that of the public information, only trades on his private information. But his trading intensity is determined and increasing with the quality of the public information. In addition, public information disclosure reduces information asymmetry between the informed traders and market maker and so market liquidity is improved with information disclosure. Public information disclosure harms the welfare of the informed trader whose private information is from the same fundamental to the public information, whereas makes the heterogeneously informed trader and liquidity traders better off. However, market efficiency is nonmonotonic with the precision of the public information. We prove that there exists at least one threshold value which can be zero or some positive value, that when the precision of the disclosed information exceeds this threshold value, market efficiency will gets worsen with more precise public information. In our paper, public information promotes market liquidity by affecting strategic trading behaviors of the two heterogeneously informed traders, but can also generate counterproductive negative influence on the efficiency of asset pricing discovery-market information efficiency, and thus harm the overall market quality. Our findings provide meaningful theoretical foundations for the future reform of public information disclosure policy in China's securities market.
This paper selects the listed companies of Shanghai and Shenzhen A-shares from 2008 to 2017 as a sample, and studies the impact of stock price informativeness on enterprise innovation and its mechanism and function environment. The research results show that stock price informativeness has a significant role in promoting enterprise innovation. The higher the stock price informativeness, the more innovation output the company has. The conclusions are still valid after a series of robustness tests, such as transforming the econometric model, changing the metrics of the main research variables, changing the samples, and using the instrumental variable estimates and propensity score matching methods to control endogeneity. Further, research on the mechanism of action shows that the stock price informativeness mainly promotes enterprise innovation by reducing financing constraints, improving operational efficiency and reducing managerial myopia. When studying the role of stock price informativeness in enterprise innovation, it is found that in the state-owned enterprises, the worse the institutional environment, the less attention of analysts and the smaller the scale, the effect of stock price informativeness on corporate innovation is more significant. This paper not only enriches the research on stock price informativeness and enterprise innovation related fields, also has certain enlightenment on how to improve the ability and level of capital market to serve the real economy.
Hubei, Shanghai, and Shenzhen carbon pilot markets, as the earliest pilot markets, not only performed well in the market, but also ranked first in terms of trading volume and trading volume. Therefore, the spot closing prices of these three markets are selected as samples, and the wavelet multi-resolution analysis method is used to decompose to remove the interference information in the time series. The dynamic characteristics of the fluctuation components of the yield are analyzed at different scales to capture multiple scale characteristics and market missing information. The comparison with the fluctuation characteristics of the EU carbon emissions system explained the short-term fluctuations, long-term trends, and differences with the European carbon market of the three pilot market rates of return. The comparison found that the trading price of China's carbon emission rights market is subject to factors such as trading policies, monitoring mechanisms, trading volume, and willingness to participate in the market. Market activity is not high. Therefore, China puts forward countermeasures to strengthen market system construction and supervision, enrich the diversity of carbon financial products, increase the activeness of market participants, and strengthen market information disclosure, thereby reducing market risks.
Based on the urban panel data from 2004 to 2017 of the three urban agglomerations, that is Beijing-Tianjin-Hebei, Yangtze River Delta and Pearl River Delta, this paper measures the regional differences and the sources of differences of economic development for three major urban agglomerations in China using Dagum Gini coefficient and the method of decomposition by subgroup, and tests the convergence of economic development of three major urban agglomerations using a spatial panel regression model. The results indicate that the overall difference of economic development in China's three major urban agglomerations shows an oscillatory downward trend, and the Pearl River Delta has the largest intra-agglomeration difference, Beijing-Tianjin-Hebei has the smallest intra-agglomeration difference, while the Pearl River Delta and Beijing-Tianjin-Hebei have the largest inter-agglomeration difference, and inter-agglomeration difference is the main source of regional difference of economic development in three major urban agglomerations, followed by intra-agglomeration difference. Furthermore, the economic development of the three major urban agglomerations appears the phenomenon of spatial agglomeration under the influence of spatial factors, and all of them have the absolute β-convergence trend. When relevant control variables are added, the economic development of each urban agglomeration also has the characteristic of conditional β-convergence.
Exploring the motivation and rules of population migration can help the government management departments allocate resources efficiently and make policies effectively, so as to guide the residents to distribute rationally, thus promoting the coordinated development among different regions. Aiming at the problem that the traditional gravity model lacks a constraint on the upper limit of population migration, an improved population migration gravity model is proposed based on population migration push-pull theory and system dynamics. The model assumes that urban residents will make comprehensive decisions regarding expected income, employment opportunities, transportation resistance, and housing prices to make relocation decisions. The cases of Suzhou Industrial Park and Shenzhen are introduced to prove the validity of the model. Finally, the sensitivity analysis relating to several policy factors shows that the number of population migration will be higher for a lower traffic resistance, higher expected income ratio, and smaller housing price growth. Therefore, the transportation planning department should carry out the rail transit construction and resource allocation plan by considering the characteristics of proposed factors influencing the population migration, to optimize the development among different regions.
With regard to the implementation of environmental regulation in China, this paper discusses the evolution process of inter-regional government supervision on emission reduction by using evolutionary game theory, and analyzes the evolutionary game of government supervision over enterprises' green technology transformation. Then, two evolutionary game models of inter-regional local governments and local government and enterprises were established. Finally, the simulation analysis of the interest relationship of each subject is carried out. The research results show that: 1) Local governments could reduce the extra cost of technology conversion by increasing green technology cost subsidies, so as to motivate enterprises to carry out green technology conversion. 2) Increasing emission reduction efforts by regional governments will promote the transformation of enterprises to green technologies. However, when too much emission reduction by governments leads to too much cost of strict supervision, the game of strict supervision will eventually evolve towards the strategy of strict supervision by one government and lax supervision by the other. 3) When local governments increase supervision and subsidize the cost of green technologies, enterprises will be encouraged to transform to green technologies. However, when the cost of green technologies is very high, enterprises will not choose to transform green technologies completely even if local governments increase emission reduction efforts. Some enterprises will choose green technologies to transform while others choose to keep the original pollution technologies. Therefore, strict environmental regulation policies and strict supervision mechanisms will promote the transformation of enterprises' green technologies to a certain extent, which is of great significance to promoting economic green development.
This study constructs a two-level maritime supply chain consisting of a single port and shipping company in view of their cooperation under the emission control. Four decision-making models were established, namely, port-led Stackelberg game, maritime vertical integration model, maritime Nash bargaining game and maritime coordination model; moreover, port price, abatement level, shipping companies' freight volume, and both parties' profits were examined. Results show that the profits of the port and shipping company under their vertical integration decision are greater than those under the port-led Stackelberg game. Moreover, revenue sharing contract cannot achieve the coordination of the maritime supply chain, whereas emission reduction cost sharing contract can improve the overall efficiency of the maritime supply chain and realize the overall Pareto improvement. Futhermore, port tends to make emission reduction cost-sharing decisions, whereas shipping companies tend to join the Nash bargaining game. However, because the latter's overall profit and abatement level are higher than the former, the government should encourage the port to accept the maritime Nash bargaining game.
Through the analysis of the operation environment and process integration of manufacturing and services during the blending process of them, a modularized vertical integration scheme of intelligent manufacturing and service process is established. This scheme is based on the industrial Internet environment, it adopts the modularized technical design and includes the construction scheme and operation scheme of the vertical integration of intelligent manufacturing and service process. It uses Petri net technology to analyze the process relationship and vertical integration strategy of intelligent manufacturing and service operation, establishes the vertical integration mode of intelligent manufacturing and service process in industrial Internet and determines the vertical integration process of intelligent manufacturing and service process. Through the application of a concrete example, it demonstrates the feasibility and superiority of the vertical integration strategy of intelligent manufacturing and service process.
In this paper, a biform game is used to study the cooperation and technological innovation of two-stage cloud service supply chain, which is composed of one cloud application developer and three cloud service operators. The strategy selection of supply chain members is analyzed according to non-cooperative game. The clique solution of cooperative game is used to distribute the profits of cooperative developers and operators. The results obtained in this paper show that, when not considering the technological innovation of the downstream operators, the upstream developers will choose the combination of stronger operators for cooperation, and only when the cost of labeling is low they will choose the branding strategy to increase the distribution revenue. When considering the technological innovation of the downstream operators, the poor downstream operators are only likely to cooperate with the developers if their innovation revenue is higher than that of the stronger operators, and only the operators cooperating with the developers will choose the technological innovation. The conclusion obtained in this paper will provide operational suggestions for the strategy choice and the distribution of benefits of the two-stage supply chain with multi-developers and multi-operators.
After a PPP project enters the execution stage, changes in the internal and external environment of the project will inevitably lead to the redistribution of resources and rights of the relevant stakeholders, and the dynamic adjustment mechanism of control rights will become an inevitable choice for rapidly responding to environmental changes. Following the principles of equal rights and responsibilities, punishment rather than reward, this paper constructs an evolutionary game model for dynamic adjustment of control rights in PPP projects, and then analyzes the evolution law of stakeholders' strategy choice and the key sensitive factors. The results indicate that the evolutionary game system of the dynamic adjustment mechanism of control rights in the PPP project execution stage has complex path dependence, and the stable state of evolution depends on the initial state and the adjustment mechanism of key parameters of both parties' strategy choice. Specifically, the strategy choice of investors is more sensitive to the changes of transfer share of control rights, the amount of cooperative surplus sharing and the additional management cost, while the strategy choice of professional companies is more sensitive to the changes of cooperation cost, the amount of cooperative surplus sharing and the intensity of risk penalty. The research results can help improve the project governance theory and optimize the control allocation mechanism of PPP projects.
The retailer's fairness preference utility function is introduced in the manufacturer-led supply chain to study the value of retailers' fairness preference and strategic behavior under uncertainty of demand and information asymmetry. The research shows that the value of fairness preference is related to the information symmetry. When the information is symmetric, the fairness preference is the behavior of "doing good to himself by injuring others" with the total payoff of the supply chain unchanged. Under such circumstance, ratailer's fair preference behaviour is spontaneous. When the information is asymmetric, the fairness preference is the behavior of "injuring others while hurting himself", and the retailer should rationally choose to give up but strategically pretend to have fairness preference. For the irrational retailer, when the information is asymmetric, the manufacturer will suffer damage and should moderately overestimate the retailer's fair preference to avoid more losses. As for retailer, the impact on it depends on direction and degree of the deviation between manufacturer's estimated fair preference and retailer's real fair preference. The retailer should exaggerate its fairness preference, at which point the retailer's fairness preference become strategic in nature. In addition, it is found that the effect of demand uncertainty on the utility of fairness preference is related to seasonality. Demand uncertainty promotes the utility of fairness preference in the peak season and inhibits it in the off season. And the peak season will be more conducive to the one who gets larger income distribution in the supply chain.
For tripartite agents of online ridesourcing platform, drivers and passengers, the queuing theory and the birth and death process theory are used to describe the driver state transition process (idle-busy) in the car-hailing platform. With the ridesourcing price and revenue sharing between ridesourcing platform and driver as decision variables, the supply and the demand functions of driver's willingness to join the ridesourcing operation and the passengers' willingness to ride are both proposed. On this basis, the ridesourcing platform pricing models to maximize the social welfare under the static pricing strategy and the dynamic pricing strategy, are both proposed from angle of government regulation, and the algorithm for solving the model is also designed; In order to ensure that the theoretical model results be able to guide or supervise the pricing of the ridesourcing platform, the existence of market equilibrium of ridesourcing platform are proved, and the social welfares of static pricing strategy and the dynamic pricing strategy are compared. The research results show that the social welfare under dynamic pricing strategy is greater than the one of static pricing strategy under finite market size, while the social welfares under the dynamic and the static pricing strategy is equal under the large-market limit. The proposed model can not only solve the static and the dynamic optimal prices of ridesourcing platform, but also investigate the impacts of average ride time, the behavior of drivers and passengers choosing ridesourcing platform on pricing of the ridesourcing platform, thus provide theoretical foundation for the pricing and supervisation of ridesourcing platform.
This paper studies the morning commuting behavior in a bottleneck-constrained corridor when the autonomous and regular vehicles coexist, considering the behavioral differences between them in both driving and parking simultaneously. The following three cases are considered: 1) autonomous vehicles only improve the road capacity; 2) autonomous vehicles only reduce the value of time VOT; 3) both affect the road capacity and the VOT. All possible equilibrium travel patterns in each case are analyzed, and it is proved that commuters with the later travel mode have a lower equilibrium travel cost. Finally, numerical examples are presented to illustrate the effects of the autonomous vehicle penetration on travel costs, delay costs and empty run costs, and the impacts of changes in road capacity and VOT on the total system cost.
Based on the performance adaptation mechanism of adaptive performance, the adaptive process from cognitive crafting to ask focus is introduced, and a two-stage moderating mediated model is constructed. Three hundred and twenty-eight valid samples of six enterprises are tested by regression analysis, bootstrap and Johnson Neyman method. The results show that the performance dynamism threat does not necessarily lead to the improvement of subsequent performance, but under the moderated role of cognitive crafting in the first stage, the performance dynamism threat will be transformed into performance standard commitment, and then under the mediated role of task focus in the second stage, performance standard commitment will be transformed into task performance improvement. The theoretical value of the research lies in the construction of a complete performance adaptation mechanism to deal with the performance dynamism threat, and the practical implication lies in that it provides theoretical enlightenment for enterprises to deal with the challenges of changes, that is, through two stages of transition adaptation and reacquisition adaptation, guiding employees to focus on the challenges of tasks on the basis of reorganization of job cognition, so as to realize the performance dynamism threat is an opportunity for performance improvement.
Data envelopment analysis (DEA) requires that the evaluated decision-making units belong to the same kind of units, and their production activities must satisfy the same law of scale return. However, in reality, the production activities of the evaluated decision making units may obey different rules of scale return, and the original DEA method can not evaluate such problems. Therefore this paper firstly gives a method to measure the efficiency of decision-making units with mixed law of scale returns and a corresponding mathematical model. Then, the related properties of the model are discussed. Finally, this method is applied to analyze the performance of teachers in a university. By a comparative analysis, it shows that this method in this paper has certain advantages for analyzing the effectiveness of decision making unit with mixed law of scale returns.
A multi-objective efficient global optimization method based on partial least square method and Kriging model is proposed to solve the problems of low modeling efficiency, multi-objective conflict and expensive simulation optimization caused by too many parameters in practical engineering. First, partial least squares method is used to reduce dimension and determine principal components; Secondly, the initial Kriging model is established based on the new Gaussian kernel function of the adaptive partial least squares weighting coefficient matrix; Then, three kinds of matrix infill criteria are used to optimize the multi-objective problem. Finally, the Pareto optimal solution set is output according to the termination criterion. Simulation results show that the algorithm effectively improves the modeling efficiency, the objective function value converges faster, and has advantages in convergence accuracy and stability. Engineering examples show that the prediction performance of Kriging model after partial least squares transformation is better than the universial Kriging model.
The impact evaluation of meteorology and ocean operational simulation environments (MOOSE) has become a key issue to verify whether the simulation environments are consistent with the difficulty of simulation training. The current evaluation methods of MOOSE are mainly used to analyze the impact of static environment factors on weapons, equipment and combat platforms. They are not suitable for comprehensive evaluation of dynamic and complex simulation environments in simulation training. In order to effectively evaluate the complexity of the simulation environment, firstly, this paper clarifies the connotation of the complexity of MOOSE, and analyses the hierarchical structure of complexity evaluation and classification. Secondly, the evaluation indices of the complexity are put forward. Based on the matrix grey relational theory, the evaluation model of MOOSE complexity is established. Then, the principle of complexity classification is put forward. Based on the grey clustering method, the classification model of MOOSE complexity is established, and the whitening weight function is improved. Thus the complexity level of dynamic simulation environment is obtained. The method is illustrated by a simulation training of sea crossing and island landing. It shows that the method can reasonably evaluate the complexity level of dynamic simulation environment, and help to build a MOOSE which is in line with the difficulty of simulation training.
The VOCs emissions in the region affect each other. In order to study the harm of VOCs emission sources to other cities due to diffusion and migration, the VOCs cascade hazard assessment method based on stochastic Petri net is adopted to divide the regional system into three types: The correlation relationship within the regional subsystem, the correlation relationship between the internal elements of different regional subsystems and the external relationship between the regional subsystems. The representation and calculation method of cascade propagation are given. The VOCs concentration increment accumulation in each reservoir is used to record the pollution degree of each reservoir, and the VOCs hazard degree is integrated into the operation of the network system. In the program, an algorithm based on SPN hazard degree is given. In this paper, a Petri net model for VOCs diffusion and migration of regional systems is constructed, the Markov chain isomorphic to it is drawn, and the hazard degree affected by pollution sources and the steady-state probability of each reachable identification are calculated. This method provides a scientific evaluation system for studying the harm caused by VOCs to other regions under meteorological conditions.