This article introduces Hsue-shen Tsien's achievements and contributions in the innovation process from systems thinking to systems practice in details, including establishing systems science architecture and the epistemology of systems, systems synthesis architecture and the methodology of systems, systems engineering and the practices of systems. They reflect Tsien's thoughts on systems science, thoughts on systems synthesis, thoughts on systems practice which is thoughts on systems engineering. These achievements have important value on science, great practical meaning and present significance.
Based on investigating the forecast power of the potential predictors for realized volatility of four agricultural commodity futures by employing the high-frequency data from Chinese markets, we propose a HAR model with time-varying sparsity (TVS-HAR) to consider the time-varying regression coefficients and the time-varying forecasting models simultaneously, which is constructed by utilizing the independent normal-gamma autoregressive processes priors for the regression coefficients of a time-varying HAR model, and then we use MCS test to evaluate and compare out-of-sample forecasting performance of proposed model and other HAR type models. Our results indicate that the proposed model can adequately account for the time-varying effect of the regression coefficients and identify predictors that are most relevant over time, and the jumps have some forecast power for realized volatility forecast. Furthermore, the proposed model appears to be the most effective models for forecasting the realized volatility of agricultural commodity futures.
China's regional carbon emissions trading price is a nonlinear, non-stationary, and multi-frequency time series due to trading system, heterogeneous environment, and policy. With the highlighted risk of carbon emissions trading, the method research of carbon price forecast is important for carbon market risk management. In order to solve the problem that single model cannot fully describe the characteristics of carbon price fluctuation, this paper establishes a multi-frequency combination forecast model. First, extreme-point symmetric mode decomposition (ESMD) is used to decompose the original nonlinear and non-stationary carbon price series into several uncoupling intrinsic mode functions (IMFs). Then, IMFs are divided into three different frequencies:high, medium, and low frequency. Third, non-linear autoregressive (NAR), wavelet neural network (WNN), and support vector machine (SVM) are adopted to forecast each frequency data. Finally, PSO-SVM is used to integrate predicted results. Compared with NAR, WNN, SVM, and GARCH models, the empirical results show that the multi-frequency composite model can improve the model accuracy. Besides, the proposed integrated model proves more efficient and consistent.
In this paper, we calculated the impact on Hong Kong's economy due to the establishment of Hong Kong-Zhuhai-Macao bridge. First, the amount of exports/imports between the pearl river delta cities and Hong Kong, the GDP and per capita GDP of the pearl river delta cities, the GDP and per capita GDP of Hong Kong, the distance of the pearl river delta cities to Hong Kong are chosen as indexes. The change of imports and exports amount due to the change of the distance between Hong Kong and the pearl river delta cities in 2017, 2020, 2025 and 2030, are measured by using the gravity model. And then, based on Cobb Douglas model, import/export trade indicators are introduced and scientific research level is added to the index of technological change, we measured the influence of import and export trade on Hong Kong's economy with the ridge regression estimation method. So we obtain the economic effect due to the establishment of Hong Kong-Zhuhai-Macao bridge. At last, we put forward some suggestions.
Based on the optimal growth model, the constant utility discount factor hypothesis was relaxed and population aging could change the time preference thus influence the balanced growth path of the economic system. Without considering technological progress, the representative's attention to the future would be lower with the degree of population aging, resulting in a reduction in the steady consumption. With technological progress in economic system, although population aging process could reduce consumption by time preference, it might promote the technological progress, thereby improving the per capita consumption level. Using the CHARLS 2013 national research data, this article verified the hypothesis proposed by theoretical analysis. Empirical research showed that family financial situation would be positive related to consumption level which means higher income and family assets could raise the consumption level. The relationship would hold in the packet robustness test, personal assets robustness test and comparisons effect robustness test. Age should be negative related to consumption level, but this may not be significant for those who are very old. The elderly who may be healthier tend to consume less while those who were highly educated would have higher consumption level.
In a dual-channel supply chain consisting of a manufacturer, an e-tailer and a brick-and-mortar retailer with bidirectional free riding and price competition, we study the optimal pricing and sales effort decisions under centralized and decentralized supply chains. We find that in the centralized supply chain, the optimal retail price and sales effort are only dependent on the effort cost. Both retailers take efforts only if the cost is lower than a certain threshold. Otherwise, neither retailer takes effort. In the decentralized supply chain, retailers' optimal sales effort depends on wholesale price, effort cost and the coefficient of free riding. In details, with a high or low enough cost, the manufacturer offers the same wholesale price to both retailers so that both retailers take effort or neither one takes effort. Consequently, the sales effort level and supply chain profit are independent with the coefficient of free riding. Otherwise, the manufacturer executes wholesale price discrimination which strengthens with the coefficient of free riding. In addition, the manufacturer's profit decreases with the coefficient of free riding, while the profit of the retailer and the supply chain increases.
We explore the optimal advance selling strategy considering consumer valuation uncertainty and seeking cost. We build a two-period model and consider a seller that sells a single product to strategic consumers, who make purchasing decisions to maximize their consumer utility. The seller needs to set the prices in both selling periods and the capacity level for the advance period. We show that the capacity level for the advance period depends on the cost of unit product. Specifically, when the cost of unit product exceeds a specific threshold, the seller should always adopt the advance selling strategy. In this case, the discount advance selling strategy is optimal. Otherwise, the regular selling strategy is the best choice for the seller. In addition, we find that when the risk cost index is relatively low, a higher consumer seeking cost leads to lower advance selling price and total profit. Otherwise, the higher the seeking cost is, the higher is the advance selling price and the larger are the total profits.
In view of the common problem that the existing studies pay little attention to the different market powers of the authorized and unauthorized distributors, we consider a global supply chain composed of one manufacturer and two distributors in different countries, and we assume that one of the distributors will be the gray market entrant. The paper constructs a Stackelberg model where the authorized distributor is the leader and the unauthorized distributor is the follower. Firstly, the paper derives equilibrium strategies. We find that, in a gray market, the authorized distributor can obtain a higher profit in a sequential-decision setting, as compared to the simultaneous-decision setting. We derive that the manufacturer can obtain a higher profit in a sequential-decision setting, as compared to the simultaneous-decision setting. We also demonstrate that the sales volume of gray-market goods and profit from selling gray-market goods will be decreased when the authorized distributor makes decision first. Finally, we show that the node enterprises can achieve Pareto improvement by setting reasonable parameters in the two-part tariff contract.
With the constraint of carbon emission reduction, investigate how fairness and carbon coefficient may affect the retail price, the product carbon emission degree, and the profits of the manufacturer, the retailer, and the entire supply chain by establishing game theoretical models of a low-carbon supply chain. The results show that:1) both product carbon emission degree and supply chain profit in a centralized supply chain are higher than those in a decentralized supply chain, with manufacturer fairness concern, product carbon emission degree and supply chain profit will further reduce, and the manufacturer's behavior of fairness concerns is not only harmful to the retailer's profit and total channel profit, but also harmful to itself profit. Interestingly, although the manufacturer's profits are coming down, the relative share of manufacturer's profit in the total channel are rising; 2) in three different decision-making models, the retail price of low-carbon product, carbon emission degree and supply chain profit will increase with the increase of carbon coefficient; 3) carbon reduction investment cost sharing contract can contribute to the implementation of increasing demand of low-carbon products and decreasing retail price. Regardless of whether the manufacturer's fairness is concerned about or not, carbon reduction investment cost sharing contract could increase the overall efficiency of the supply chain and expand the supply chain profits.
We investigate the impact of carbon tax and the consumers' environmental awareness on the manufacturer's optimal emission reducing level and the optimal contractual parameters in a supply chain, which consists of both a retailer who faces uncertain demand and a manufacturer who exerts costly effort to reduce the carbon emission of a product during manufacturing to increase its retail price under a wholesale price contract (WPC) and a revenue-sharing contract (RSC). We show that the RSC can coordinate the supply chain with and without emission reduction and improve the two players' profits. Moreover, there exists a unique optimal reducing level for the manufacturer under WPC and for the supply chain coordinated with RSC, respectively, and a unique threshold of reducing level for the manufacturer and the retailer under WPC, and the supply chain coordinated with RSC to benefit from emission reduction, respectively. Furthermore, the variation of optimal wholesale price with reduction depends on the incremental unit cost of production, and the variation of the range of sharing proportion that can achieve Pareto improvement and coordinate the supply chain depends on the efficiency of the supply chain. The variation narrows when the increasing rate of the price that the consumers are willing to pay for environmental products is greater than that of the unit production cost, otherwise it broadens.
In the presence of carbon-sensitive consumers, this paper studies the procurement strategies for two competitive manufacturers and develops four models in which the two manufacturers can choose the low-carbon procurement strategy or to make by themselves. With the study, we derive the optimal sales price and wholesale price, and the optimal profits for the respective supply chain partners. The studies show that those two manufacturers will choose the make regime and fall into the prisoner's dilemma when the carbon sensitivity level of the consumers is relatively low. While when the carbon sensitivity level is moderate for the consumers, those two manufacturers will adopt the low-carbon procurement strategy and attain Pareto optimality for the case where difference in the carbon emission is large for the two manufacturers. However, when the carbon sensitivity level of the consumers is high enough and the difference in carbon emission is small for the two manufacturers, the differentiated procurement strategy will be the equilibrium.
Based on the consumers' willingness to pay to the characteristics of product, which are composed of physical property and environmental quality, we establish a dual-channel closed-loop supply chain decentralized decision-making model. On this basis, we compare three conditions:no subsidies, subsidies are given to manufacturer and subsidies given to consumers, and analyze the influences of government subsidies and consumers' preferences on the dual-channel closed-loop supply chain. The research indicates:the higher recognition to the physical property of the remanufactured products, the more beneficial (detrimental) to their sales and profit (environment); when consumers hold a low recognition, the manufacturer can simply enter the access to remanufacturing to promote the sales by the improvement of the environmental quality of remanufactured products, leading to a low environmental impact and profit for the decreasing new products; government-subsidized remanufacturing is beneficial (possibly detrimental) to their sales and profit (environment) while subsidies to manufacturers are the same to those to consumers; when consumers hold a high (low) recognition, the government should subsidize (tax).
This paper addresses the problem of product positioning of competing firms with consumer returns. Considering two typical return policies:Full-refund and no-refund return policy, we establish four noncooperative models of price and product positioning under the framework of Hotelling methodology. The subgame perfect Nash equilibrium of each model is derived by the backward induction approach. Moreover, based on the comparative analysis of equilibrium profits in each scenario, we derive the Nash equilibrium strategies of the game of the selection of return policy and explicitly propose the conditions for guaranteeing these equilibria. We find that consumer returns plays an important role in firms' decisions of pricing and product positioning. However, the degree of product differentiation does not change because of consumer returns. Furthermore, we prove that the salvage value and the consumer return cost have direct impact on firms' choice of return policy.
Under supply and demand uncertainty, this paper develops blood supply chain models that incorporate option contracts. And this paper provides insights into the effect of the option contracts and the supply and demand uncertainty on blood supply chain decisions. Firstly, under supply and demand uncertainty, we derive the hospital's optimal procurement policies, as well as the blood centre's optimal production policy in the presence of options contracts. Secondly, the blood supply chain coordination conditions are derived, which are not related to the unit wholesale price, but depend on the blood production random yield rate of raw blood. Finally, we show that there always exists a Pareto contract as compared to the non-coordinating contracts when the blood supply chain is coordinated.
By easing the consistency hypothesis of alternative or complementary auction items for bidders, this paper establishes a combinational auction model according to bidders' bid on the basis of combinatorial auction mechanism design. In order to efficiently obtain the optimal allocation of multiple items, particle swarm optimization (PSO) algorithm is used to simulate the optimization process of allocation, and then the combinatorial auction model based on PSO algorithm is constructed. The paper designs and implements the combinatorial auction model based on PSO algorithm on swarm simulation platform, and verifies the simulation validation through a specific combinational auction example. The analysis of simulation results shows that the combinatorial auction model based on PSO algorithm can effectively solve the problem of the distribution of multiple items, and can maximize the benefit of the vendor. The parameter analysis of learning ability shows that compared with self-learning ability, social learning ability is more important to the optimization of seller's return. This paper will have certain reference value to both the theoretical research and practical application of combinatorial auction.
Although most previous studies focused on the static effect of relational ties, egocentric network or a whole network on key inventors' creativity, few have explored the dynamic impact of network cut-vertices that combine above three levels. Based on patent data of 46 domestic firms from 1995 to 2010, we use negative binomial regression model to analyze the effect of occupying past and current cut-vertices positions on key inventors' creativity. The analysis is conducted at a group level and time dimension. The results show that for a long time, the more cut-vertices key inventors occupy in the past collaborative networks, the lower his creativity is. But there is an inverted U-shaped relationship between the occupation numbers of cut-vertices positions in the current collaborative networks and the key inventors' creativity, for both long time and short time. The results confirm the importance of occupying the current cut-vertices positions and time factor in considering the role of network dynamic.
Decision-making for sustainable development is inseparable for the integrating of material flow cost accounting (MFCA) and life cycle assessment (LCA). Literature review indicates that the current extension of MFCA on the life cycle perspective does not yet exist a relatively mature method system. Theory of constraints (TOC) indicates that cost accounting boundary and object are the logical starting point for MFCA extension form a life cycle perspective. Furthermore, definition of life cycle phase, full life cycle flow structure model, and coexistence of monetary and non-monetary information are the core content for MFCA extension. In this view, the paper build a set of methodology system which including MFCA-LCA model and accounting methods, and then introduced a case to present the details of environmental damage value accounting, cost accounting, and the process of MFCA-LCA comprehensive evaluation. This study contributes to the theories and literatures of MFCA and also provides application notes for enterprises to implement MFCA.
For the location inventory routing problem in the establishment and optimization for shipping logistics system of remote islands, we analyzed the operation mechanism and characteristics of the logistics system with special background combining islands' natural environment and geographical structure. This paper developed an optimization model considering the elements of the logistics' node locations, port layouts, warehouse plans and route configurations. The model can keep the supply among remote islands any time, and the goal of the model is the lowest logistic cost. According to the characteristics of the problem, this paper suggested a hybrid algorithm based on genetic algorithm and plant growth simulation algorithm. The rationality and effectiveness of the model and algorithm were respectively proved by the the practical case of shipping logistics system for certain remote islands in the South China Sea and comparison of algorithms. Finally, through sensitivity analysis, this paper points out that the decision should be more focused on transportation system optimization. The model and algorithm provide a theoretical support and optimization method for the construction of remote islands' shipping logistics system, which has a great theoretical significance and practical value for construction decision and logistics system establishment of the South China Sea Islands.
To improve the performance of urban multi-modal transportation systems and the conditions of daily trips, it is of great importance to investigate the integrated optimization of fares and transfer pricing discounts for subway and bus services that both serve the same passenger corridor. Generally, in modeling a passenger choice of transit modes, it is essential to take into account the passenger subjective evaluation of the delay risk due to her or his mode choice as well as the objective conditions affecting the choice of travel routes. For this purpose, a bi-level program is formulated, of which the upper level maximizes the social welfare and the lower level is a variable-demand stochastic user equilibrium assignment model. A genetic algorithm is applied to solve the bi-level program while the method of successive averages is adopted to solve the lower-level model. Finally, a series of numerical experiments is carried out to illustrate the performance and applications of the model. The results show that the effects of the passenger subjective evaluation of the delay risk on travel behavior are significant and that the implementation of transfer pricing discount can reduce the passenger transfer cost and increase the social welfare of public transit system.
Taking account of the fact that the dynamics of influences has been ignored in the most research of opinion propagation with network, this paper introduces the factor of dynamic influences to the research. With the idea of Krause bounded confidence model, this paper introduces Festinger's cognitive dissonance theory to improve interaction conditions of opinions and has a different understanding of the confidence threshold, this threshold isn't the critical value that whether individuals have interactions or not, it is the critical value that whether the influence between individuals are increased or decreased. And then, it introduces the short-term memory and punitive mechanism to give a further study for the dynamic influence. Accordingly, this paper builds an opinion propagation model under dynamic influence, then conducts a series of analysis based on computational experiments. The results show that, when group's confidence threshold increased, individuals' differentiation degree will reduce. And the initial influence distribution affect the opinion differentiation, a higher influence would lead to a more stable opinion and the convergence speed is faster. The effect of the influencer has a negative relationship with the confidence threshold, but has a positive relationship with the influencers' proportion.
Distance measures are used to describe the difference between two sets. In view of the intuitionistic multiplicative set, which uses an unsymmetrical scale (Saaty's 1/9-9 scale), we define some universal distances based on the famous Minkowski distance. Then we give several numerical examples to illustrate and compare our results. Furthermore, to apply distance measures into decision-making problems, a practical application about the effect of rain attenuation for satellite communication link is provided, which helps to provide the alternative for building satellite earth stations.
The polygonal fuzzy number can determine a class of fuzzy information with the help of the orderly representation of real numbers. It can not only approximate a general fuzzy number according to arbitrary precision, but also it overcomes the complexity the arithmetic operations of fuzzy numbers based on Zadeh's extended principle. In this article, we first introduce the definition of the polygonal fuzzy number and its orderly representation, and its extended arithmetic operations and the metric formula are given. Secondly, the multiple attribute index information of clustering objects are described through the orderly representation of polygonal fuzzy numbers, and then, the optimal fuzzy partition (matrix) and clustering centers are obtained by the objective function, and a fuzzy c-means (FCM) clustering algorithm is put forward based on the pattern of polygonal fuzzy numbers to describe multiple attribute index information. Finally, try to prove that algorithm is prior to trapezoidal fuzzy number to describe index information through a numerical example.
Teaching informatization is an important part of talent cultivation in colleges and universities. There have a lot of problems for further research in the process of system development. This paper determines level-rate system including 9 level-rate variables based on 8 major problems to be solved in the process of system development and level ascension, establishes feedback simulation flow diagram model using stepwise setting up and recovering parameter combination simulation testing technology of rate fundamental in-tree method, builds 9 rate variable fundamental in-trees, 86 simulation equations and 14 regulation interval control parameter equations, confirms the reliability of each tree combination model using a certain value of each control parameter range, establishes complex flow graph model. Then, based on the control parameter range, designs fixed assets and software resources increasing input at the same time under the condition of the most satisfied and the most unsatisfied control parameter combination plan, fixed assets and software resources focus on input in stages under the condition of the most satisfied and the most unsatisfied control parameter combination plan, analysis of results of improving simulation experiments. Finally, close ties to the actual, this paper proposes seven pieces of countermeasures, in order to provide references for developing and implementing management measures of teaching information level ascension.
The collaborative filtering (CF) is the most widely used recommendation technology in personalized recommender systems. However, it has one-sidedness in determining the common preferences between users because the traditional CF calculates user similarities only according to user-item ratings, and thus reduces the quality of searching neighbor. Besides, many context-based CF methods ignore the differences of the effect of varieties contexts to user preferences, and thus affect the recommendation effectiveness. To address these problems, this paper proposes an improve CF model based on contextualized user preferences. Firstly, the proposed model analyses the importance of the effect of different contexts to user preferences based on the theory of information entropy, and searches nearest neighbors according to user-commodity ratings and user preferences to commodity attributes. And then, the weight of context importance is introduced in the process of recommendation generation to obtain the recommendation results. To evaluate the performance of the proposed model, a set of the experiments on MovieLens dataset are conducted, and the results show that the proposed model has low MAE value than other CF methods, thus it enhances the prediction accuracy and improves the quality of context-based personalized recommendation.
In order to solve the problem about multi factors, high dimensional data, small samples and incomplete information when analyzing unconventional flood emergency evolution risk, in the knowledge element layer by granularity decomposition, model of unconventional flood emergency evolution risk analysis is built based on projection pursuit and information diffusion theory. The evolution risk between emergency events is transferred to the risk that the change of status attributes of hazard bearing body in current situation result in the mutation of output attributes based on knowledge element theory. The rules of emergency events evolution are established based on status attributes threshold of hazard bearing body, risk information in the observed data is diffused into the control point of the risk index universe on the output attributes by projection pursuit and information diffusion theory, then the emergency events evolution probability, and the unconventional flood emergency evolution risk is calculated. Taking Taoqupo reservoir as an example, the evolution risk is analyzed between water level rising and dam overtopping at the scenario of serious rainstorm in the upstream. The results show that the model of events evolution risk analysis could sequential and quantitative analyze and evaluate risk probability distribution according to the risk grade level and few monitoring data, and help the emergency management decision makers grasp the development of the event and emergency response in real time, reduce the losses caused by secondary events.