With the deepening of the globalization of financial markets and the closer political connections between countries in the world, the transnational contagion of sovereign risk has been confirmed by reality. Under the background of the "Belt and Road Initiative", this paper investigates node characteristics and structural characteristics of sovereign risk spillover network among belt-road countries from the perspective of sovereign risk networking and regional grouping using spillover index approach based on FEV (forecast error variance) decomposition. We find that the overall spillover effect of the 25 countries alongside the "Belt and Road" is relatively high, and the Central and Eastern European countries is dominant in the sovereign risk spillover network of countries alongside the route. In addition, the overall sovereign risk spillover effect alongside the route shows obvious dynamic characteristics and phase characteristics over time. The sovereign risk spillover effect between China and ASEAN (Association of Southeast Asian Nations) group is always the strongest at any stage, while the Central and Eastern Europe is the regional group of countries that can well reveal changes in the overall sovereign risk spillover effect alongside the route. All these findings can help macro policy-makers and investors participating in the sovereign debt and related derivatives markets understand the essential characteristics and internal structure of the sovereign risk spillover network along the "Belt and Road".
The finance-constrained startup always balances the trade-off between cash flow to avoid bankruptcy and quality investment for future growths. This study proposes a two-stage model to investigate the profit-seeking and survival-seeking strategies. It is set that startup must earn profit larger than the survival threshold by the end of every stage. We establish a hedge with price setting and quality investing strategies against the bankruptcy risk, and investigate how the uncertainty of preference for quality, market shock, and survival threshold affect the hedges. Results show that than the deterministic case, the profit-seeking startup will set lower (higher) price and invest in lower (higher) quality in the stochastic environment. Its quality investment will be encouraged by both increasing mean and increasing variance. Besides, the survival-seeking startup always sets its price linked to quality in positive direction in the stochastic environment. Its quality investment will be cut down when the mean of preference for quality increases to a certain level or the variance of preference for quality increases. What's more, as the survival threshold increases, the profit-seeking startup always decreases its investment, while the survival-seeking startup increases its investment first, and then decreases its investment. Finally, this paper provides the startup managers some guidance on the quality investing strategy under financial constraint.
Using the payment settlement network as an example and constructing the liquidity circulation model in a complex network, the systemic risk and liquidity rescue under different network topologies and different risk scenarios are studied. The results are as follows:1) The network topology has a significant impact on the stability of the system, and the system shows the characteristics of "stable but fragile", which means that the smaller the differences between nodes and the closer the connections, the smaller the probability of systematic risk and the more serious the consequence when the risk is formed. 2) Because the degree of systemic risk is positively correlated with the system's liquidity gap, the rescue strategy based on using the nodes' liquidity gaps to allocate the rescue fund is not inferior to other strategies. Under different network topologies, the degree of differences between strategies is significantly different. 3) Under the strategy based on the node's liquidity gaps, the order of rescue also matters under different network topology. But the impact is significant only when there are large differences between the network nodes and with medium rescue scale.
This paper considers the optimal technology investment-dividend strategy for a R&D firm in the presence of new technology investment. Supposing that the firm's capital reserve follows a dual risk model and that the firm has a liquidation value when it declares bankruptcy, our objective is to maximize the expected present value of cumulate dividend payments plus liquidation value. Using the theories of mixed singular control and optimal stopping, we explicitly obtain the firm's optimal technology investment-dividend strategy and the optimal value function when its profits are exponentially distributed. Finally, we analyze the effect of model parameters on the firm's optimal strategy and provide some economic insights.
Based on the related data of 30 provincial units in our country, using the entropy value method and Moore structure change, respectively was carried out on the new high-level urbanization level and industry structure level measure, by calculating the global Moran's I index, analyzed the existence space depend on the characteristics of China's economic growth, on this basis, the introduction of control variables, establish spatial panel econometric model, spatial effect decomposition model and panel threshold model, empirical analysis on the economic growth effect of new urbanization and industrial structure upgrade, research shows that:the new urbanization through the use of its "agglomeration effect", optimize the industrial structure, improve the social productivity, effectively promote China's economic growth; China's industrial structure is in a period of adjustment, and the industrial structure upgrade has caused a "structural slowdown" phenomenon in China's economic development, but its economic growth effect is still significant. "Production city synergy" significantly promoted China's economic growth, from city linkage for alleviating China's economic growth is slowing in "structural slowdown" and "triple pressure" and the problem has important practical significance; The economic growth effect of new-type urbanization and industrial structure upgrade has the "threshold effect" because of the period of sex mismatch in the production of city relations.
Based on the background of the carbon emissions trading market in China, the article considers the impact of low-carbon technology innovation (sharing) on emission reduction interests and the characteristics of inter-temporal effects of technology innovation and external technology sharing in local area. By using differential methods, this article also analyses the dynamic strategies of the regional low-carbon technology stock, which is jointly determined by both the efforts of the local low-carbon technology innovation and the external technology sharing. On the basis of the relevant assumptions, we construct the dynamic models under decentralized decision-making without cost-sharing, decentralized decision-making with cost-sharing and centralized decision-making respectively, and respectively obtain their optimal feedback equilibrium strategies, low-carbon technology stock and the optimal trajectory of profit value function over time. By comparing the three feedback equilibrium strategies, through the extent of Pareto improvement of both the cost-sharing mechanism and cooperative innovation mechanism to the main emission reduction interests, it is found that in the case of centralized decision-making, the more the efforts of low-carbon technological innovation (sharing) in local regions and external regions are endeavored, the higher the overall emission reduction interests than those of non-cooperation to achieve the Pareto optimality. The cost-sharing mechanism can improve the efforts of all subjects and improve the emission reduction interests moderately. Finally, the validity of the model is verified through numerical simulation and the sensitivity of the relevant parameters in the case of cooperative innovation of low-carbon technology is analyzed. And relevant theoretical basis is provided for promoting the long-term cooperation of regional low-carbon technology collaborative sharing in different places.
This paper employs the quantum game paradigm to study the incentive mechanism of the industry-university-institute (IUI for short) collaborative innovation, and construct the IUI collaborative innovation model. The result indicates that the quantum game analysis shows great advantage over the classical game model, and implies that considering entanglement of states, the hardworking side will not take the risk of the other side's betrayal, which resolves the "Prisoners' Dilemma" in the classical game theory to some degree. In the IUI collaboration case, both sides need to negotiate and delegate a third party to formulate some performance indicators, and they also need to sign an "entanglement contract" to ensure that neither of them has the motivation to deviate from the quantum strategy. Thus, the quantum strategy with maximal effort is the most profitable.
This paper studies the demand forecast information sharing strategy and game structure decision in online platform selling model. In this paper, we consider an online platform-selling model consisting of an e-retailer, an e-commerce platform and a third-party logistics. There are two important assumptions:1) the e-retailer owns the private demand forecast information and can choose to share with the e-platform, the 3PL, or both; 2) the e-commerce platform could determine the game structure. Based on these, we investigate the e-retailer's optimal information sharing strategies under different game structures and then analyze the e-platform's optimal game structure selections under different information sharing strategies. Our results show that, 1) when the service efficiency of the e-commerce platform is weak, the equilibrium strategy of e-retailer is not sharing the information, and that of e-commerce platform is making decisions before 3PL. 2) When the service efficiency of the e-commerce platform is strong, or when the service efficiency of the e-commerce platform is moderate and the accuracy of the demand forecast is high, the equilibrium strategy of e-retailer is sharing the information with the e-commerce platform, and that of e-commerce platform is making decisions after 3PL.
This paper constructs a traceability method that does not require any electronic identification on the product by using blockchain technology. The digital tokens representing the product are issued by the source side of the product in the block chain, upstream traders in a trading network may, when delivering products to downstream traders, choose whether to deliver the same number of digital tokens to downstream traders. Collecting the circulation of the digital token for a period of time, based on these information, a mathematical model is built to calculate the probability of the product from the source side of the product from any trader in the circulating network. Finally, through the numerical analysis, it is shown that when the probability value is published in an environment where the competition is good and the authenticity rate is an important purchase reference index, the complete traceability can be realized under the synergy of the network.
New products usually face greater market uncertainty. How to ensure the matching between product supply and market demand is particularly important for enterprises. Obtaining demand information in advance is helpful to achieve this goal. Considering the loss aversion of strategic consumers, this paper studies retailers' advance selling and return policies. Based on the behavioral characteristics of strategic and myopic consumers, a two-stage model of pre-sale and normal sales is constructed. This paper makes a comparative study on the two advance selling strategies of permitted return and non-permitted return. By constructing the profit model of retailers under the two strategies, the optimal pre-sale price and the optimal return price are obtained, and the corresponding range of return price is given. It is found that the retailer has to lower price for pre-sale products because of loss aversion among strategic consumers. When the return price after the end of the presale period is not higher than a specific value, the implementation of the return strategy can enable the retailer to obtain a better return, and there is an optimal return price. It makes the expected profit of the retailer reach the maximum under the return mode.
Accurate prediction of social logistics demands is essential to government's policy formulation for the logistics industry as well as to enterprise's logistics activity planning. In this paper, a logistics demand prediction model construction method based on the fuzzy cognitive map (FCM) is proposed. This method comprehensively considers the mutual influence between five economic elements (GDP, total import and export volume, etc.) and logistics demands, and acquires the mutual influence weight through machine learning of historical data. Finally, a logistics demand prediction model is built, which can realize accurate prediction of the future logistics demands. The experimental results provide solid evidence for high precision and favorable performance of the model in predicting logistics demands.
This paper generates an organization-task interdependent network model based upon functional dependence between tasks and executive dependence between organizations and tasks in an complex product research and development (R&D) project. Then it develops and simulates the dynamic model of technical risk diffusion by analyzing the interaction between organizations and tasks when facing with technical risks. The results show that the technical risk diffusion caused by a few tasks can significantly turbulent the network in a short time; the diffusion process has three stages:slow stage, out of control stage, and relatively stable stage; the relationship between the organization network scale and the consequence of diffusion shows approximate "inverse U" shape; the more even executive dependence, the weaker the robustness of the network when fixes the number of organizations; there exists a best level of resource input which makes the impact of diffusion remain at the lowest level; there is no significant difference in the diffusion process under different attack strategies. This research riches the dynamic theory of risk diffusion, and has provided reference for optimization of complex product development project architecture and improving the risk resisting capacity of R&D projects.
The distributed resource constrained multi-project scheduling problem (DRCMPSP) involves the individual scheduling of multiple projects and the coordination of shared resources among the projects. It is the crux of solving the DRCMPSP that designing an effective mechanism to obtain the necessary projects' information in order to coordinate the global resources. We constructed the hierarchical model with the global objective of optimizing the total delay cost of the multi-projects under the consideration of different unit project. And we designed a cooperative-game based negotiation mechanism to allocate the global resources and the hierarchical model was solved by the proposed phased evolution algorithm under the account of the information asymmetry in DRCMPSP and the self-interested project decision makers. According to the computational results of instances in MPSPLIB, it is effectively to decrease the total delay cost of the multi-projects that using the cooperative-game based negotiation mechanism and the approach is available to various problems with different sizes and utilization factors. In addition, in order to get low delay cost the autonomous agents should participate in the cooperative game and behave honestly and meanwhile a high-quality solution will be obtained.
The collaborative distribution problem is a typical combined optimization cooperative game problem, and is named the collaborative vehicle routing problem. One of its core problems is to determine a fair and reasonable cost sharing plan. Among them, the nucleolus solution is a recognized scientific allocation plan in the field of cost sharing because of its uniqueness and fairness. This paper proposes a method to approximate the nucleolus solution of collaborative distribution problem. Firstly, the paper proves the cost allocation of collaborative vehicle routing problem will theoretically be a convex game problem when the location of the customer is evenly distributed. Based on the theory that the nucleolus solution will be equivalent to the prekernel solution in convex game problems, an approximate iterative algorithm (AIA) is proposed to get the nucleolus solution of convex game problems. The complexity of AIA is O(n^{4}2^{n}), and then the paper proposes two effective speed-up strategies of AIA, which reduce the complexity of AIA to polynomial level. Finally, by solving the cooperative distribution examples, it is verified that the AIA algorithm in this paper can accurately solve the nucleolus solution of the collaborative distribution cost allocation problem. The proposed solution can effectively reduce the time-consuming of calculation. And the average deviation between the final result of AIA and the actual nucleolus solution is less than 0.02%. More importantly, AIA can be used to get the nucleolus solution in all convex games.
As to the problem of time series prediction for small sample data with time delays, the dynamic changes of system time delays should be considered and expressed in the process of modeling. This paper extends the GM(1,1|τ_{i}) model to a more applicable GM(1,1|τ_{i}) model, which contains a time-varying delay function to describe the possible time-varying delays in series. An efficient algorithm for the model parameter estimation is given, together with the time response formula of GM(1,1|τ_{i}) model. Parameters of the time-varying delay function used in the model algorithm are optimized by the gray correlation degree theory. The method designed in this paper improves the fitting degree of the GM(1,1|τ_{i}) model to the analyzed sequence. It also helps to analyze the development trend of system based on the mathematical properties of time-varying delay functions. Finally, the model is applied to forecast the cargo throughput of coastal ports in Fujian province, and the results are compared with those based on GM(1,1) and GM(1,1,τ). Results show that the GM(1,1|τ_{i}) model has higher modeling precision when the raw data contains complex time-varying delays and this will enlarge the class of existing grey series prediction models with time delays.
With respect to these problems with unconsideration of practical semantics of membership and non-membership degrees and even "counterintuitive results" in some cases. In this paper, we propose a novel intuitionistic fuzzy similarity degree and then introduce it to intuitionistic fuzzy decision systems, in which the (α, β)-level cut sets under intuitionistic fuzzy similarity degrees are defined and the associated properties are given. The (α,β)-lower and upper approximation of the objective set and its three regions:positive region, negative region and boundary region are induced by using the rough membership function served as the evaluation function. Considering different risk attitudes of decision makers, an intuitionistic fuzzy three-way decision model with multiple risk preference is constructed based on Bayesian theory and the corresponding decision rules are derived. Based on which we propose an intuitionistic fuzzy three-way decision method on the basis of intuitionistic fuzzy similarity degrees. Finally, a numerical example is given to show its feasibility and effectiveness.
Choosing the right time to intervene public opinion dissemination is of great significance to the control of public opinion in online social networks (OSN). The key factors affecting the control of public opinion dissemination, such as user' network status, social strengthening effect and users' perception value, are analyzed. Aimed to identify the reasonable timing for intervention, a dissemination and control model of public opinion based on users' relative weight is constructed. Based on this model, simulation researches are carried out in two types of OSN. The results show that public opinion dissemination is closely related to the initial disseminator' network status; there exits a key phase transition point, which is related to timing of intervention in open OSN; users' activity decreases with the increase of the social strengthening effect's intensity, also decreases with the advance of intervention, and there exits an effective interval for intervention; the cost of "contrary to popular will" should be an important index for timing of intervention. Finally, the corresponding countermeasures for choosing the right time to intervene in reality are proposed.
System structures and developing process of large-scale complex weapon are characterized with networks. Research on risk evolution mechanism is useful to control risk and reduce complexity. Based on dynamic data samples presented by system process modeling and simulations, risk evolution networks was refined by Bayesian learning to recognize correlations among nodes with different risk levels. By this way, subjectivity is reduced than risk networks built only by experience. The risk networks from Bayesian learning was further used to implement Bayesian inference and calculate risk posterior probability distributions of risk network nodes under the conditions of system total risk at high level, and then the critical nodes and propogation chains of risk evolution were identified. Finally, comparing with static characteristics based on complex network characteristic indicators, the differences between dynamic and static characteristics of risk networks were under discussion. It is found that the critical nodes and chains of risk evolution are jointly determined by network structure characteristics and dynamic features of risk evolution.
For the problem of resource scheduling conflict of complex product design task modules, this study constructs a resource-constrained TCPN model based on TCPN network design task module with the analysis of the number of input and output repository design mission activities under the basic structure of the TCPN network resource constraints on change. Concerning the resource constrained TCPN network synchronization task transition and non-synchronous activity task transition, given different resource constrained scheduling rules, and design a complete resource constrained scheduling algorithm and correction algorithm, this paper presents a schedulable design task module resource constraint TCPN network. Finally, take a J-model car R&D project as an example, resource constraint TCPN model of vehicle chassis design module design task element is built and solved, the schedulable resource configuration of vehicle chassis design tasks module is given, and the meta activity changes of all design tasks in the automotive chassis collaborative R&D resource constraints TCPN network can be scheduled.
R-fuzzy membership function is given in the form of rough set, and classification is made according to the membership degree and the relevance of the descriptor to it. The membership values fitting perfectly with the descriptor are divided into the lower approximation set, while membership values related to the descriptor into upper approximation set. If you can introduce a kind of method on R-fuzzy approximation set to quantify the importance of membership values, then quantitative ordering of the membership degrees can be achieved, as such to achieve higher resolution to discriminate the differences among these membership values. This requirement can be realized well by the advantage measure concept proposed in this paper. Advantage measure theory is put forward firstly, and then the equivalence of the advantage measure to the type-1 fuzzy set is proved, and moreover the consistency of the concept with the R-fuzzy set is demonstrated. In essence, advantage measure fuzzy set serves as the validator for the R-fuzzy rough membership set. Finally, through the human visual perception experiment and visualization of advantage measures, the influence of group consensus and individual perception on the advantage measure of the R-fuzzy set is investigated followed by analysis of the advantages of the advantage measure over human cognitive identification.
The existing interval number grey target decision-making model ignores the important influence of interval distribution and the correlation between the indicators in scheme evaluation. And there are some fuzzy errors when setting the weight of indicators. In order to solve the above problems, this paper proposes an interval number grey target decision-making model based on multi-dimensional association sampling, taking into account the multi-dimensional joint probability density distribution of index space and its boundary, and weakens the impact of extreme index value on the decision-making results. In addition, this paper determines the weight of index by using set-valued statistical method, expanding the weight of grey target model from the real number sequence to the interval number sequence, and reducing the fuzzy error in the experts' judgment process. This improved model is applied to Pankou reservoir for the decision-making of water level operating in flood season. Compared with traditional models, the improved model fully considers the characteristics of interval data and the correlation between the indicators. Meanwhile, the setting of interval number weight is more scientific and reasonable.
In order to adapt to the characteristics of modern warfare system-of-systems (SoS) confrontation, the development and application of equipment system should serve the overall situation of the equipment combat SoS, and measure the contribution degree and equipment to the combat SoS from the aspect of SoS, and take this as the basic basis of equipment demonstration, development and usage. Because of the complexity of the combat SoS, the research on SoS contribution ratio evaluation (SoSCR) of equipment system involves many kinds of contributions from various aspects. Firstly, the paper establishes the research framework of SoSCR evaluation from the two aspects of the problem domain and the technique domain; then combs the research progress at home and abroad on this basis; Finally, analyzes analysis of the deficiencies of the research progress according to the research framework, and proposes key research directions of SoSCR evaluation.