This paper examines the relationship between stock market(KSE-100), money market(M2 and 180 days T-bill rate), and foreign exchange market(ER:PKR/USD) in Pakistan by using monthly data covering the period from 2000:M1 to 2015:M12. The study investigates long-run equilibrium relationship between these three financial markets by employing Johansen and Juselius^[1] cointegration tests. Long-run and short-run causality relationship between stock market and other macroeconomic variables is also established by employing vector error correction model(VECM) and pairwise granger causality tests. The results of multivariate cointegration test(trace test) indicate a one cointegrating vector, and the significant normalized cointegrating coefficients are evident of long run equilibrium relationship between all the selected variables. Negative and significant ECT(?1) for all variables during full sample period witness the presence of long-run causality connection among variables, while during the military regime and democratic regime, significant difference of long-run causal connections are identified across the regimes. Moreover, the results of granger causality test also indicate that there are significant variations in the causality relationship among variables across the regimes. Therefore, it is essential for forecasting, planning and policy making to consider the importance of political governance system while analyzing the historical cointegration among financial market and make the necessary adjustments accordingly.

This paper studies the optimal consumption-investment strategy with Heston's stochastic volatility(SV) model under hyperbolic absolute risk aversion(HARA) utility criterion. The financial market is composed of a risk-less asset and a risky asset, whose price process is supposed to be driven by Heston's SV model. The risky preference of the individual is assumed to satisfy HARA utility, which recovers power utility, exponential utility and logarithm utility as special cases. HARA utility is of general framework in the utility theory and is seldom studied in the existing literatures. Legendre transform-dual technique along with stochastic dynamic programming principle is presented to deal with our problem and the closed-form solution to the optimal consumption-investment strategy is successfully obtained. Finally, some special cases are derived in detail.

After the reform and opening, the economic relationship between China and the world is strengthened heavily. Theoretically, international factors have impact on the domestic general price level through a set of channels. This paper employed a sample including monthly data of five representative indicators, to explore the influence of international factors on Chinese price level. The empirical results showed that there is an obvious lag for Chinese CPI reacting to international shocks, while the PPI reacts immediately. The impact of international factors on Chinese CPI and PPI usually lasts 12 months at least and they always exhibit a different transmission mechanism for international shocks. Besides, a further study revealed that some structure-breakpoints in the influence mechanism of international factors exist, and great changes of the impact direction and significance for different factors have taken place in the subsample periods.

It's well-known that change-point problem is an important part of model statistical analysis. Most of the existing methods are not robust to criteria of the evaluation of change-point problem. In this article, we consider "mean-shift" problem in change-point studies. A quantile test of single quantile is proposed based on saddlepoint approximation method. In order to utilize the information at different quantile of the sequence, we further construct a "composite quantile test" to calculate the probability of every location of the sequence to be a change-point. The location of change-point can be pinpointed rather than estimated within a interval. The proposed tests make no assumptions about the functional forms of the sequence distribution and work sensitively on both large and small size samples, the case of change-point in the tails, and multiple change-points situation. The good performances of the tests are confirmed by simulations and real data analysis. The saddlepoint approximation based distribution of the test statistic that is developed in the paper is of independent interest and appealing. This finding may be of independent interest to the readers in this research area.

This paper proposed the optimized three-stage strategy of orderly management of file stream in network printing workflow. In first stage the customer preflight was added to the conventional prepress preflight, which set quick-type, general-type, stable-type and comprehensive-type preflight scheme for customers by investigating the possibility of occurrence of errors of various preflight entries and customer relevancy. Based on four types of preflight schemes, four customer preflight applications were created by using Pitstop Pro and Connector You. Customers can select one of the appropriate applications for quick preflight before delivering to reduce the probability of returning the files back for correction when errors occur in preflight. Second stage is printing enterprise prepress preflight, which proposed the concept of the prepress preflight tolerance. In addition, according to the different requirements of printing technology and quality, this paper established the prepress preflight scheme based on the printing enterprises' tolerance for preflight error. Third stage is to manage the optimized sorting of prepress file stream. To achieve it, the SPT rule and the 0-1 programming model were adopted, time spend of preflight, printing process and post-press finishing was also taken into account. Moreover, Enfocus Switch software was applied to establish automated network printing workflow and complete the file stream sorting. Finally, the result of simulation analysis of the optimized strategy shows that the optimized three-stage strategy can effectively shorten the file processing time.

The establishment of the China Pilot Free Trade Zone(FTZ) has significantly promoted international trade, financial development, and economic growth. Building international financial centers(IFCs) satisfies the demand for FTZs to facilitate financial development, as well as promoting economic growth. Thus, successfully predicting the next IFC in China under the FTZ framework is an important issue. In this study, we applied grey relational analysis combined with entropy method to predict potential IFCs among seven FTZ cities. According to the results, our interesting findings include:1) the "total stock turnover", "total value of imports and exports", and "Foreign Direct Investment(FDI)" are key indicators for determining future IFCs; 2) among seven cities, Shenzhen and Tianjin are highly likely to become the next IFCs, while Shanghai is already an IFC.

In the pallet pool system, the differentiation of palletized freight volumes in different regions and seasonal transport of certain goods lead to the imbalance of pallets distribution among regions. It is necessary to improve the utilization of pallets through dispatching. The paper analyzes the factors which affect empty pallets dispatching, it includes carbon emission, transportation time and pallet type based on the pallet pool mode of enterprise alliance. On this basis, the optimization model is established with the goal of minimum total dispatching cost. Then, according to the different influences of railway and highway in transportation cost, the dispatching scheme is analyzed and the transportation mode of empty pallets dispatching is determined. Considering the characteristics of model, Cplex is used to solve it. Finally, a case is used to verify the feasibility and superiority of reasonable empty pallets dispatching in different transportation modes, and the transport characteristics of two transportation modes are analyzed. Moreover, the costs of pallets leasing and dispatching are compared.

In this paper, regulatory and optimum programming model has been adopted. Considering the costs of emission reduction, supervision and penalty, we went all out to analyze the optimal decision of cost efficiency of regulators when implementing these three policy instruments: carbon emission standards, carbon emission trading permissions, and carbon taxes as well. Its result has indicated: In strict accordance with control target of total carbon emissions, regulators are willing to render social and economic cost able to achieve the goal of optimal cost efficiency by regulating carbon emission standards and supervising marginal cost caused by variations in the probability; fortunately, under the conditions of low supervisory cost and certain criteria which is met, the implementation of carbon emission trading permissions could provide social and economic cost with opportunities to realize that objective; through comparative analysis, carbon emission trading permissions have the advantages of higher efficiency than carbon emission standards on the premise of incomplete information. During the implementation of carbon taxes strategy, when there exists uncertainty information in the enterprises reduction behaviors, the condition which enterprises can fully comply with is the tax rate level is not higher than marginal penalty function; the tax rate level of enterprises perfect compliance ought not to be lower than the division of marginal penalty cost and marginal supervisory cost. The optimal strategy of enterprises imperfect compliance is that regulators varying the marginal cost of emission standards is equal to varying that of supervisory probability.

The analytic hierarchy process (AHP) is used widely for analyzing decisions made in various real-world applications. Its basic idea is to construct a hierarchy of concepts encountered in a given decision problem and to choose the best alternative according to pairwise comparison matrices given by the decision maker. Under the assumption of fully rational economics, a reasonable decision should be consistent. It becomes an important issue on how to analyze and ensure the consistency of comparison matrices together with the judgments of the decision maker. The main objectives of the present paper are threefold. First, we review the basic idea and methods used to define the consistency and the transitivity of multiplicative reciprocal matrices, additive reciprocal matrices and comparison matrices with fuzzy interval and triangular fuzzy numbers. The existing controversy behind the applications of fuzzy set theory to the AHP in the literature is presented. Second, the consistency of the collective comparison matrices in group decision making based on AHP and fuzzy AHP is further analyzed. We point out that the weak consistency of preference relations with fuzzy numbers in fuzzy AHP and group decision making should be investigated comprehensively. Third, under the consideration of the vagueness in the process of evaluating the judgements, a new concept of fuzzy consistency of comparison matrices in the AHP is given.

This paper proposes a group decision making method based on entropy of neutrosophic linguistic sets and generalized single valued neutrosophic linguistic operators. This method is applied to solve the multiple attribute group decision making problems under single valued neutrosophic liguistic environment, in which the attribute weights are completely unknown. First, the attribute weights are obtained by using the entropy of neutrosophic linguistic sets. Then three generalized single valued neutrosophic linguistic operators are introduced, including the generalized single valued neutrosophic linguistic weighted averaging (GSVNLWA) operator, the generalized single valued neutrosophic linguistic ordered weighted averaging (GSVNLOWA) operator and the generalized single valued neutrosophic linguistic hybrid averaging (GSVNLHA) operator, and the GSVNLWA and GSVNLHA operators are used to aggregate information. Furthermore, similarity measure based on single valued neutrosophic linguistic numbers is defined and used to sort the alternatives and obtain the best alternative. Finally, an illustrative example is given to demonstrate the feasibility and effectiveness of the developed method.

Asset allocation is an important issue in finance, and both risk and return are its fundamental ingredients. Rather than the return, the measure of the risk is complicated and of controversy. In this paper, we propose an appropriate risk measure which is precisely a convex combination of mean semi-deviation and conditional value-at-risk. Based on this risk measure, investors can trade-off flexibly between the volatility and the loss to tackle the incurring risk by choosing different convex coefficients. As the presented risk measure contains nonsmooth term, the asset allocation model based on it is nonsmooth. To employ traditional gradient algorithms, we develop a uniform smooth approximation of the plus function and convert the model into a smooth one. Finally, an illustrative empirical study is given. The results indicate that investors can control risk efficiently by adjusting the convex coefficient and the confidence level simultaneously according to their perceptions. Moreover, the effectiveness of the smoothing function proposed in the paper is verified.

This paper deals with a discrete-time Geo/Geo/1 queueing system with working breakdowns in which customers arrive at the system in variable input rates according to the states of the server. The server may be subject to breakdowns at random when it is in operation. As soon as the server fails, a repair process immediately begins. During the repair period, the defective server still provides service for the waiting customers at a lower service rate rather than completely stopping service. We analyze the stability condition for the considered system. Using the probability generating function technique, we obtain the probability generating function of the steady-state queue size distribution. Also, various important performance measures are derived explicitly. Furthermore, some numerical results are provided to carry out the sensitivity analysis so as to illustrate the effect of different parameters on the system performance measures. Finally, an operating cost function is formulated to model a computer system and the parabolic method is employed to numerically find the optimum service rate in working breakdown period.

The generalized autoregressive conditional heteroskedasticity (GARCH) type models are used to investigate the volatility of Bangladesh stock market. The findings of the study demonstrate that the index volatility characteristics changes over time. The article shows that the data are divided into three sub-periods: pre crisis, crisis, and post crisis. Accordingly, the results of the findings indicate changes in the GARCH-type models parameter, risk premium and persistence of volatility in different periods. A significant “low-yield associated with high-risk” phenomenon is detected in the crisis period and the “leverage effect” occurs in each periods. The investors are irrational which is based on assumption of risk and return characteristics of assets. Consequently, the market is not as mature as developed market. It is found in the article that the threshold generalized autoregressive conditional heteroskedasticity (TGARCH) model is more accurate for the model accuracy. Additionally, statistic error measurements indicate that GARCH model is more efficient than others and it has also more forecasting ability.

In this paper, we investigate the disparities of China's insurance market from the viewpoint of geography and enterprise by using the monthly data from January 2006 to December 2015. We divide the whole insurance market into two parts, namely property insurance and personal insurance. By constructing and analyzing minimum spanning trees of insurance market, we obtain the results as follows: (i) The connections between provinces are much closer than those of firms, and there are regional links between neighboring provinces in the minimum spanning tree (MST); and (ii) the domestic funded firms and foreign funded firms form two explicit clusters in the MSTs of property and personal insurance market.

This paper studies a dynamic mean-variance portfolio selection problem with random liability in the affine interest rate environment, where the financial market consists of three assets: one risk-free asset, one risky asset and one zero-coupon bond. Assume that short rate is driven by affine interest rate model and liability process is described by the drifted Brownian motion, in addition, stock price dynamics is affected by interest rate dynamics. The investors expect to look for an optimal strategy to minimize the variance of the terminal surplus for a given expected terminal surplus. The efficient strategy and the efficient frontier are explicitly obtained by applying dynamic programming principle and Lagrange duality theorem. A numerical example is given to illustrate our results and some economic implications are analyzed.

With the incorporation of spatial statistic method, this paper constructs a state-space model of housing market bubbles, discussing the spatial pattern of housing market bubbles in China, and identifying the dynamic evolution process. The results show that: The bubbles of housing market walked along a path from low level to high level and then downsized to a low level during the period of 2009 and 2014, and the highest level stayed at 2011. From overall, the level of housing market bubbles had shown significant spatial autocorrelation and spatial agglomeration. In detail, the direction of North-South in China showed the inverted U shape, i.e., Central region was with high bubbles, and two ends contained low bubbles; from East-West direction, the East had high bubbles and the West contained comparatively low bubbles. Local spatial test indicates that there were some approximate spatial features in housing market bubbles among the adjacent regions. Observed from the level of housing market bubbles, China contained 3 plates: The first was the plate with low bubble level, including 3 provinces in North-East China (provinces of Jilin, Heilongjiang and Liaoning were included, but Dalian in Liaoning province was excluded; the second was the Central andWest plate (the provinces of Yunnan, Guizhou, Sichuan, Guangdong, Guangxi, Hunan, Hubei, Gansu, Fujian, Jiangxi and Hainan were included in this plate), which was also featured with low bubble; and the third was Central East plate (provinces or provincial regions of Beijing, Tianjin, Hebei, Jiangsu, Zhejiang, Shanghai, Shandong, Anhui, Shanxi, Shaanxi and Inner Mongolia were included), which was characterized as high bubble region.

Due to the long operation cycle of maritime transportation and frequent fluctuations of the bunker fuel price, the refueling expenditure of a chartered ship at different time or ports of call make significant difference. From the perspective of shipping company, an optimal set of refueling schemes for a ship fleet operating on different voyage charter routes is an important decision. To address this issue, this paper presents an approach to optimize the refueling scheme and the ship deployment simultaneously with considering the trend of fuel price fluctuations. Firstly, an ARMA model is applied to forecast a time serials of the fuel prices. Then a mixed-integer nonlinear programming model is proposed to maximize total operating profit of the shipping company. Finally, a case study on a charter company with three bulk carriers and three voyage charter routes is conducted. The results show that the optimal solution saves the cost of 437,900 USD compared with the traditional refueling scheme, and verify the rationality and validity of the model.

This paper considers the two-part tariff licensing by an innovating firm to its potential competitor in a differentiated mixed duopoly, in which one firm sets a quantity and the other firm charges a price. Based on the development cost incurred by the rival, we derive the optimal behavior of the firms under full information case and partial information case respectively. Information difference on the equilibrium strategies is also investigated.

Based on the system dynamics (SD) model, this paper puts forward a quantitative method to evaluate the earthquake emergency plan in China. Firstly, we analyze the disaster system structure and the content of plan. Using the analysis results, we establish a system dynamics (SD) model and then carry out its simulation. According to the simulation results, the rescue effect using the plan of 2012 is better than that of 2006. From the policy level, in order to reduce loss, government should maintain communication smoothly, improve the ability of self and mutual help, strengthen the management of public opinion, and pay more attention to secondary disasters.

The purpose of this paper is to investigate the macroeconomic effect of pollution emission in an overlapping generation system. This is done through constructing an endogenous economy which generates pollution and environment deterioration. It shows how different level of pollution emission could cause complexity such as fold bifurcation in this system. In addition, numerical simulations are provided to show the emergency of complexity.

On the social network platform, complaints about the public policy formulation and implementation issues arise largely. Through the information aggregation, frequent interaction, word-ofmouth and emotional resonance on online social network, these information will lead to the outbreak of the network complaints. It brings difficulties and challenges in public management. China is under a period of social transformation, and there are various problems and contradictions. Emergency can easily arouse group complaints on online network, and it will lead to network public opinion through inducing social emotional resonance, which is harmful to social security and stability. This paper has built the evaluation index system from four dimensions with complaint text's quality, transmission timeliness, user interaction degree and emotional resonance excited by emergency. Then, we establish the dynamic influence measure model of online netizens complaint theme based on an entropy weight model. The measure model is proved to be reasonable and effective by the empirical research of Sina Weibo data. The model can effectively solve the measure problem of group complaints influence when the emergencies arouse social emotional resonance. It has important theoretical significance and practical value for public policy decision-maker on listening to online group complaints, understanding public opinion, and making public policy.

This paper studies consensus of a class of heterogeneous multi-agent systems composed of first-order and second-order agents with intermittent communication. For leaderless multi-agent systems, we propose a distributed consensus algorithm based on the intermittent information of neighboring agents. Some sufficient conditions are obtained to guarantee the consensus of heterogeneous multi-agent systems in terms of bilinear matrix inequalities (BMIs). Meanwhile, the relationship between communication duration and each control period is sought out. Moreover, the designed algorithm is extended to leader-following multi-agent systems without velocity measurements. Finally, the effectiveness of the main results is illustrated by numerical simulations.

With the development of the electronic commerce, the electronic word-of-mouth (eWOM) has become important reference information for consumer shopping. EWOM has attracted considerable interest from researchers in the past decade. In this paper, a research review is conducted and an integrated framework is proposed on the effect of eWOM. The effect of eWOM are influenced by its characteristics, communicators, and other factors. The characteristics of eWOM include the source, the volume and the valence. The communicators of eWOM refer to the sender, the receiver and the relationship between them. In addition, dispersion and consistency, persistence and observability, anonymity and deception, and community engagement are related factors for the effect of eWOM.

Social media and consumer behavior are increasingly important in business nowadays. As a new form of advertising, social media do facilitate the increase in demand and bring a challenge to manufactures. While researchers demonstrated that insufficient capacity generates the loss in the process of sales, an opposite conclusion has been obtained that the profit is larger in insufficient capacity. This study investigates this situation of a manufacturer. We develop a multi period model of insufficient capacity concerning with social media and consumer behavior. An calculation of the model indicates that a great change appears in the demand of each period. To ensure the maximum profit, the capacity of each period is computed. And the profit is almost 8 times larger than that we do not consider social media and consumer behavior. We discuss the implications of our findings for both theory and practice.

Current researches on node importance evaluation mainly focus on undirected and unweighted networks, which fail to reflect the real world in a comprehensive and objective way. Based on directed weighted complex network models, the paper introduces the concept of in-weight intensity of nodes and thereby presents a new method to identify key nodes by using an importance evaluation matrix. The method not only considers the direction and weight of edges, but also takes into account the position importance of nodes and the importance contributions of adjacent nodes. Finally, the paper applies the algorithm to a microblog-forwarding network composed of 34 users, then compares the evaluation results with traditional methods. The experiment shows that the method proposed can effectively evaluate the node importance in directed weighted networks.

In this paper, the consensus problem for heterogeneous multi-agent systems composed of first-order and second-order agents is investigated with directed network topologies. Based on a system transformation method, this consensus problem is turned into a consensus problem for homogeneous multi-agent systems. With certain assumption on the control parameters, firstly, necessary and sufficient condition for consensus is proposed with fixed topology. Secondly, sufficient condition is proposed for heterogeneous multi-agent systems to achieve consensus with switching topologies. Finally, simulation examples are presented to verify the effectiveness of the theoretical results.

In the finance market, risk happened in two pattern. In one case, extreme volatility together with a short balance time leads to a great panic to the market. On the contrary, if the volatility is smaller, the time period will usually be longer. It will bring many infections to various related fields, which causes wider range influences to the economy. Both cases hurt financial market and the economy itself deeply. In this paper, we developed a novel market regulation method in which the conflict of fluctuation time and volatility will be balanced. It describes a way to compute a portfolio of relatively short time period together with smaller fluctuation volatility by using a general prediction algorithm based on overshoot in cybernetics. It can also give explanation to counter-cyclical supervision theory and macro-prudential regulation. Furthermore, it can provide numerical operation guide for countercyclical supervision theory and macro-prudential regulation.

This paper addresses the supply chain engineering and its application in China's retailing industry. Based on the approaches of systems engineering, we propose the concept of supply chain engineering, which applies the idea of supply chain management to the engineering practices through the advanced information and management technology, to integrate the supply chain system and optimize its operations. We then illustrate the application of the supply chain engineering in China's retailing industry. In such practices, we developed the virtual retailing enterprise mode and the FROM-SCM system, and designed the sales assistant etc. Such theory and practices are successfully applied in Meiyijia, which has transformed Meiyijia from a traditional retailer to a modern service enterprise, and the profits are resulted from the service fees rather than the traditional surplus between buying and selling prices. Now Meiyijia has built an ecosystem with the retailer in the core, the headquarter as the service platform. The success of Meiyijia in recent years shows the effectiveness of the supply chain engineering.

In this paper, a game model composed of three subjects-government, manufacturer and consumer has been built by using Evolutionary Game Theory on the basis of analyzing the trilateral game strategy of waste mobile reverse supply chain based on ECP; an evolutionary equilibrium model is to be sought for by utilizing the replication dynamic differential equation method; and the trilateral game strategy's revolutionary trend and consistency have been analyzed by means of SD simulation method when government implements the static or dynamic reward and punishment strategy. The finding results reveal that, under the static reward and punishment strategy, the revolutionary process of trilateral game strategy is always unstable whether the initial behavior strategy is unitary or mixed. Therefore, it is more reasonable for the government to adopt the strategy of dynamic reward and punishment, and it is also stable and reciprocal for all the stakeholders when implementing this strategy.

Current literatures assume that a consumer's willing to pay (WTP) for a bundle is equal to the sum of his or her separate reservation prices for the component goods and concludes that mixed bundling is superior to pure components in a monopoly market. However, full mixed bundling is a discount conduct in order to attract more consumers, and the price of the bundle must be lower than the sum of the prices of two products, which must be considered in a consumers' WTP for the bundle. Then, if consumers' reservation prices are heterogeneous and subject to the uniform distribution, we can draw opposite conclusions:Full mixed bundling is disadvantageous to firms when Stackelberg pricing. The profit under full mixed bundling is less than that under pure components.

In this paper, we analyze the 180 stocks which have the potential influence on the Shanghai Stock Exchange (SSE). First, we use the stock closing prices from January 1, 2005 to June 19, 2015 to calculate logarithmic the correlation coefficient and then build the stock market model by threshold method. Secondly, according to different networks under different thresholds, we find out the potential influence stocks on the basis of local structural centrality. Finally, by comparing the accuracy of similarity index of the local information and path in the link prediction method, we demonstrate that there are best similarity index to predict the probability for nodes connection in the different stock networks.

In the analysis on economic growth factors, calculating the contribution rate of influencing factor to economic growth using the CES production function model is a common and important research field. The CES production function model has a variety of forms, and the superposition CES production function model proposed in the paper is a new model. With regard to the model's parameter estimation, the paper proposes a modified particle swarm optimization which has a fast convergence rate and a high precision. With regard to the calculation of factor contribution rate, the paper offers a new scientific calculation method with the superposition CES production function model. At last, the paper makes an empirical analysis on the contribution rate of Chinese economic growth factors and the result obtained consists with the reality.

A common feature of previous studies about the application of data envelopment analysis (DEA) to determine environmental and economic efficiencies is that the two were analyzed in separate models or frameworks. The purpose of this paper is to analyze the economic efficiency and environmental efficiency with a single model. This paper proposes an integrated DEA model, based on a modification of the directional distance function, which allows us to decompose the eco-efficiency (EE) into the economic efficiency (ECE) and environmental efficiency (ENE). The ECE characterizes the ability of gaining economic benefits while the ENE characterizes the ability to control pollutant emissions in production activities. Identification of ECE and ENE can help decision makers of different regions detect what kind of factor (economic inefficiency or environmental inefficiency) is the main source of eco-inefficiency. This can help decision makers more targeted to improve EE. To illustrate the feasibility of our approach, a case study of 30 regions in China is presented. The empirical results show that almost all regions have very high economic efficiencies. The environmental inefficiency is the main source of eco-inefficiency. The differences of environmental efficiencies lead to the differences of eco-efficiencies in the east, central and west areas, while the economic efficiencies do not have significant differences among these areas. The economic efficiencies showed an opposite "V" shape and the environmental efficiencies showed a decreasing trend during the period 2010-2014.

In this era of a data-driven society, useful data (Big Data) is often unintentionally ignored due to lack of convenient tools and expensive software. For example, web log files can be used to identify explicit information of browsing patterns when users access web sites. Some hidden information, however, cannot be directly derived from the log files. We may need external resources to discover more knowledge from browsing patterns. The purpose of this study is to investigate the application of web usage mining based on web log files. The outcome of this study sets further directions of this investigation on what and how implicit information embedded in log files can be efficiently and effectively extracted. Further work involves combining the use of social media data to improve business decision quality.

Chauffeured car service (CCS) has developed rapidly in recent years. Although CCS brings convenience and effectiveness, it also triggers some new problems like vicious competition. This work studies the duopoly competition between CCS company and taxi company, in terms of different average cost and number of vehicles of two companies. To find the solutions like the pricing scheme to ease the vicious competition, Hotelling model is introduced. The Hotelling-type model is used to present passengers' preferences to the companies. Besides, failing situation is taken into account in the Hotelling model to describe the situation where passenger's demand is not satisfied in reality. This work theoretically analyzes the price scheme and equilibrium market segmentation based on the average cost and number of vehicles of each company. Furthermore, companies' profits, passengers' utility and social welfare in equilibrium are revealed based on the game theory. The study shows that both of companies can get optimal profits by setting effective price scheme. The company which has higher price, definitely gets less market share. In addition, moderate competition can lead to positive influence on social welfare.

Major societal problems affect the social stability. It is necessary to understand the public opinion toward those issues to avoid social conflicts. Nowadays the social media become the major platform to track what the public is concerned about and which may be of the societal risk. However, it is very tough to capture the public attention in short time due to huge flow of user-generated contents. In this paper, we approach this problem by expanding the method of generating storyline with the result displayed by a multi-view graph. One real-world example is illustrated and evaluation is given to show the effectiveness of the proposed method.

The study of human mobility patterns is of both theoretical and practical values in many aspects. For long-distance travel, a few research endeavors have shown that the displacements of human travels follow a power-law distribution. However, controversies remain regarding the issue of the scaling laws of human mobility in intra-urban areas. In this work, we focus on the mobility pattern of taxi passengers by examining five datasets of three metropolitans. Through statistical analysis, we find that the lognormal distribution with a power-law tail can best approximate both the displacement and the duration time of taxi trips in all the examined cities. The universality of the scaling laws of human mobility is subsequently discussed, in view of the analysis of the data. The consistency of the statistical properties of the selected datasets that cover different cities and study periods suggests that, the identified pattern of taxi-based intra-urban travels seems to be ubiquitous over cities and time periods.

This paper focusses on the information asymmetry in crisis news after a serious incident in Tianjin, China, in 2015. The incident caused enormous damage and resulted in societal unrest because of the lack of reliable information from the formal media channels. Social media-micro blogs-played a major role in reporting on crisis situations. We divided netizens (i.e., the citizens of the net) into high and low types according to their information-critical level to the crisis news. The data shows information deterioration on the crisis news, related to the netizens' information-critical level. For the traditional media there is the opportunity to use information quality distortion to make more marginal profits. This is possible only if the citizens' information stays under a certain quality level. The result is overprovision of low quality news and high quality news driven out of the market, whereupon adverse selection (i.e., a lack of symmetric information) appears. However, by adopting a process view, we found self-correcting mechanism (i.e., dying out of rumors) of the social media communities in China. We provided a agent-base model and simulation to show that the more media exist in the market, the faster speed of the information deterioration, but also the capacity to ‘discuss’ rumors.

To simulate the rumor propagation process on online social network during emergency, a new rumor propagation model was built based on active immune mechanism. The rumor propagation mechanisms were analyzed and corresponding parameters were defined. BA scale free network and NW small world network that can be used for representing the online social network structure were constructed and their characteristics were compared. Agent-based simulations were conducted on both networks and results show that BA scale free network is more conductive to spreading rumors and it can facilitate the rumor refutation process at the same time. Rumors paid attention to by more people is likely to spread quicker and broader but for which the rumor refutation process will be more effective. The model provides a useful tool for understanding and predicting the rumor propagation process on online social network during emergency, providing useful instructions for rumor propagation intervention.