This study is to discuss the value of enterprise and the strategy formulated by system dynamics. For this field we trial to research the key activity factors that will effect the value of enterprise. This study will design a model and simulate the behavior of the key activity factors when the leader decided and executed the policy. From this model, the leader will anticipative understand the changes of the value of enterprise, know well the causal relationship and the feedback on the activities before decide, in addition become the strategy thinking, prevent the mistake and for the reference in management at the same time. The conclusions of this study are presented as follows: 1. From the thinking of strategic with the system dynamics, we build up 9 systems to simulate the operation of the enterprise and study the relationships with the variables are named Leader-Ship, Culture, Market, List, Technology, Stock, Operation Cost, Brand Value and Sum-profit. 2. From simulation, the logic design of the whole system and the relationships of the variables had been proved, that means it is the interdependence among the strategy, the capability of the management, and the value of the enterprise. 3. Compared with the simulating result and the strategies, the policies and the performance for 4 years in the case, there is a valid verification to pre-simulate and forecast the effects and the changes on the value of the enterprise before decided. The conclusions above are significant to the ¡§carrying capacity¡¨ of the corporate value that reflects to management in the following aspects. 1. Differentiation is the leader-ship and the managerial capacity. 2. Are the strategies making competitive advantage¡H 3. How about the resistance when the enterprise has been attacked by the competitors¡H

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Trip chaining and mode choice are two important travel behavior decisions in activity-based travel demand modeling system. The hierarchy of these two decisions influences models predictive capability and policy sensitivity. This thesis is aimed at investigating the hierarchical relationship between these decisions and also the effects of socio-demographic characteristics on them. Structural Equation Modeling (SEM) technique is used for this investigation. A six week travel diary data collected in Thurgau, Switzerland in 2003 is used for model estimation. Model estimation results show that for work-tour, trip chain and mode choice decisions are simultaneous and it remains consistent across the six weeks. For weekdays non-work tour, mode choice precedes trip chain whereas for weekends non-work tour trip chain precedes mode choice. The investigation of the effect of a number of socio-demographic characteristics on trip chaining and mode choice behaviors is also found useful for better understanding of these behaviors. / Transportation Engineering

This paper¡¦s purpose is to highlight the retribution of Taiwanese folktales and hope that through combining stories and religions together to educate people and encourage people to behave good and honest. This paper uses the view of Buddhism and Taoism to analysis 148 pieces of Taiwanese folktales by synthesis, induction and comparison. Hope that in using of the folktales and the religion theory to encourage people to behave good and honest instead of evildoing. Regulating their own behavior by following the good and ethical standards, to make sure that they can live their life safely and healthy. The first chapter includes research motives, methods, scope of the study and documents investigation. Second chapter defines the folk literatures and folk tales¡¦ ways and means of transmission for the relation between Fujian and Taiwanese folk tales and the process of Taiwanese folk tales development. Third chapter is the main part of this paper. First I sorted out Buddhist and Taoist ideas; which are retribution of good and evil, through their classic. Then I analyze the religious view through the pattern of the retribution which happens in the roles of Taiwanese folktales. The main focus is on Buddhism¡¦s causal concept, hell concept and the concept of reincarnation. Taoist concept of celestial theory, remain-sustain theory and Gods dominate over rewards and punishments theory. Fourth chapter discusses about retribution causes, methods and results of the role in the Taiwanese folk tales, as well as the meaning that folktales has on itself. Fifth chapter is to conclude the ideas and theory which were presented in this paper. Buddhism believes cause and effect cycle. Taoist believes that Gods dominate over reward and punishment. Buddhist theory of causation tells us that people who behave badly will become livestock or even fall into hell after death. People who behave good and honest will go to heaven or reincarnate to a good family after death. Taoism theory¡¦s judge system tells people that Gods record each person's words and deeds. People believe "What goes around, comes around" for over thousands of years and it has created a strong constraint among the people. Folktales also help build up this strong constraint force. Perhaps the constraint in people¡¦s mind has grown weaker in this emotionless modern generation. I hope this paper can recall people's minds and the goodness of the heart once again, in hoping that this emotion and believe will last along in the future.

Quantitative risk assessments are a fundamental part of economic analysis and natural hazard risk management models. It increases the objectivity and the transparency of risk assessments and guides policymakers in making efficient decisions when spending public resources on risk reduction. Managing hazard risks calls for an understanding of the relationships between hazard exposure and vulnerability of humans and assets.   The purpose of this thesis is to identify and estimate causal relationships between hazards, exposure and vulnerability, and to evaluate the applicability of systematically collected data sets to produce reliable and generalizable quantitative information for decision support.   Several causal relationships have been established. For example, the extent of lake flood damage to residential buildings depends on the duration of floods, distance to waterfront, the age of the house and in some cases the water level. Results also show that homeowners private initiative to reduce risk, prior to or during a flood, reduced their probability of suffering building damage with as much as 40 percent. Further, a causal relationship has been established between the number of people exposed to quick clay landslides and landslide fatalities.   Even though several relationships were identified between flood exposure and vulnerability, the effects can only explain small parts of the total variation in damages, especially at object level. The availability of damage data in Sweden is generally low. The most comprehensive damage data sets in Sweden are held by private insurance companies and are not publicly available. Data scarcity is a barrier to quantitative natural hazard risk assessment in Sweden. More efforts should therefore be made to collect data systematically for modelling and validating standardized approaches to quantitative damage estimation. / Natural hazard damages have increased worldwide. Impacts caused by hydrological and meteorological hazards have increased the most. An analysis of insurance payments in Sweden showed that flood damages have been increasing in Sweden as well. With climate change and increasing populations we can expect this trend to continue unless efforts are made to reduce risk and adapt communities to the threats. Economic analysis and quantitative risk assessments of natural hazards are fundamental parts of a risk management process that can support policymakers' decisions on efficient risk reduction. However, in order to develop reliable damage estimation models knowledge is needed of the relationships between hazard exposure and the vulnerability of exposed objects and persons. This thesis has established causal relationships between residential exposure and flood damage on the basis of insurance data. I also found that private damage-reducing actions decreased the probability of damage to buildings with almost 40 percent. Further, a causal relationship has been established between the number of people exposed to quick clay landslides and fatalities. Even though several relationships have been identified between flood exposure and vulnerability, the effects can explain only small parts of the total variation in damages, especially at object level, and more effort is needed to develop quantitative models for risk assessment purposes.

Many highway maintenance agencies are facing an increased pressure to utilize their limited resources while still achieving the optimum winter highway maintenance outcome. Also there is a tendency to privatize maintenance operation, in order to improve the road user's satisfaction by bringing more competition to winter maintenance operations. Given this context the purpose of this research is to develop an effective performance measurement system that can evaluate how well agencies have conducted winter maintenance activities to meet the road user's expectations of safety and mobility. Though there have been performance measurement studies conducted in the winter maintenance area, few of them are comprehensive enough to evaluate winter maintenance outcomes, while at the same time taking storm severity, road system characteristics, and maintenance effort together into consideration. To address this deficiency, several particular challenges must be considered: first, how to evaluate the storm severity for individual storms; second, how to evaluate maintenance outcomes using a series of quantitative measures; and third, what are the appropriate targets that maintenance outcomes can be compared with, considering outcomes are sensitive to maintenance input, weather severity, road classifications, and traffic specifications. To address these questions: A storm severity index is developed; studies on effects of weather were quantitatively synthesized by meta-analysis; effects of weather and maintenance on road surface conditions are estimated by MLR; SEM (Structural Equation Modeling) is applied to estimate the direct and indirect effects of maintenance on mobility and Multiple Classification Analysis (MCA) was applied to estimate the contribution of winter maintenance to safety. The final result of this research is an applicable winter maintenance performance measurement system. It informs maintenance agencies where they excel at and where improvements are needed for the specified goals. Further, the developed road surface condition prediction model can be used as a predictive tool to allow agencies to conduct "what if" experiments that will lead to optimization of maintenance practice over time. The relative magnitudes of the effects of different maintenance methods on mobility and safety that is estimated by the models will enable agencies to assign priorities, and to compare maintenance outcomes based on the input resources.

Modeling travel demand by time of day is gaining increasing attention in travel demand forecasting practice. This is because time of day choice has important implications for mode choice and for quantifying potential modal and time of day shifts in response to traffic congestion and peak period travel demand management strategies. In this context, understanding the causal relationship between time of day (departure time) choice and mode choice behavior would be useful in the development of time of day based travel demand modeling systems both within the four-step modeling paradigm and within newer tour-based and activity-based microsimulation paradigms. This thesis investigates the relationship between departure time choice and mode choice for non-work trips as work trips tend to be constrained with respect to time of day choice. Two alternative causal structures are considered in this thesis: one structure in which departure time choice is determined first and mode choice is subsequently influenced by departure time choice and a second structure in which mode choice is determined first and affects departure time choice. These two causal structures are analyzed in a recursive bivariate probit modeling framework that allows random error covariance. The estimation is performed separately for worker and non-worker samples drawn from the 1999 Southeast Florida Regional Household Travel Survey. For workers, model estimation results show that the causal structure in which departure time choice precedes mode choice performs significantly better. For non-workers, the reverse causal relationship in which mode choice precedes departure time choice is found to be a more suitable joint modeling structure. These two findings can be reasonably explained from a travel behavior perspective and have important implications for advanced travel demand model development and application.

How do land use characteristics affect individual and household travel behavior in a regional context? Can the investigation justify the land use policies to reduce automobile dependence and achieve the goals of sustainable development in the metropolitan areas? Previous research enhanced our understanding of the connections between land use and travel behavior. It also provided implications for managing automobile-dependent travel behavior. However, there are questions still left unanswered about the causal connections between them, and the effectiveness of the land use policies to manage travel demand. To address the issues, attention is focused on the effects of land use measures on travel behavior outcomes from different modeling perspectives. The travel demand modeling explores the associations between land use and travel behavior. In addition, the causal modeling helps clarify the causal connections between them. It includes the structural equation models (SEMs) and the directed acyclic graphs (DAGs). The study focuses on six counties of the Houston-Galveston Area Council (HGAC) area. Travel behavior outcomes contain individual mode choice, household automobile trip generation and household total vehicle miles traveled (VMT). Three dimensions (i.e., density, diversity and design) of six land use measures are considered, which are computed using quarter-mile buffers for both trip origins and destinations. Different travel outcomes and modeling strategies are examined for different travel purposes. The significance of land use measures in affecting travel behavior is found to be evident, while varying to a certain degree according to trip purposes, travel outcomes and methodologies. For individual model choice, multinomial logit (MNL) models, the SEMs and the DAGs for different trip purposes support the hypothesis that land use measures directly affect individual mode choice behavior when other factors are kept constant. There is also evidence from causal models that land use factors indirectly influence it through travel time. For household automobile trip generation, there is no evidence to assert that land use measures at origin significantly affect household automobile trip rates when travel cost and socioeconomic variables are controlled. However, it is confirmed that land use measures have indirect causal connections with automobile trips through travel costs for all trip purposes. For household total VMT, it is found that land use patterns around residential locations are not only significantly associated, but also causally connected with household VMT. To summarize, compact development with high density and improved network design generally contribute to the reduction in automobile dependent travel patterns in the HGAC region.

Each individual is both a consumer and an investor in the market. It is the common goal of every investor to achieve a high return on investment through the portfolio of profit maximization. As a result, the ratio of assets in a portfolio has become a hot topic. In China, real estate and the stock market are two main markets favoured by both individual and institutional investors. And there is a significant economic link between the two markets. Therefore, their mutual relationship and long-term and short-term causality can provide good guidance for investors. This paper studies the causality and correlation between stock trading volume and real estate trading volume in 31 provinces of mainland China. The empirical results in this paper is based on a panel data from 2000 to 2016 and divides 31 provinces into three different economic regions. The panel unit root test and the Pedroni co-integration test were carried out. The Hausman test was used to select among different estimation methods. Panel Mean Group is found the most suitable analysis method. It is found that the main industries in different provinces may affect the short-term causal relationship between real estate and the stock market. But in the long run, the causal relationship between real estate and the stock market is two-way and stable.

In the reasoning about actions community, causal relationships have been proposed as a possible approach for solving the ramification problem, i. e., the problem of how to deal with indirect effects of actions. In this paper, we show that causal relationships can be added to action formalisms based on Description Logics without destroying the decidability of the consistency and the projection problem.