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

Effective policymaking requires understanding the causal effects of competing proposals. Relevant causal quantities include proposals' expected effect on different groups of recipients, the impact of policies over time, the potential trade-offs between competing objectives, and, ultimately, the optimal policy. This dissertation studies causal inference for public policy, with an emphasis on applications in economic development and education. The first chapter introduces Bayesian methods for time-varying treatments that commonly arise in economics, health, and education. I present methods that account for dynamic selection on intermediate outcomes and can estimate the causal effect of arbitrary dynamic treatment regimes, recover the optimal regime, and characterize the set of feasible outcomes under different regimes. I demonstrate these methods through an application to optimal student tracking in ninth and tenth grade mathematics. The proposed estimands characterize outcomes, mobility, equity, and efficiency under different tracking regimes. The second chapter studies regression discontinuity designs with multiple forcing variables. Leading examples include education policies where treatment depends on multiple test scores and spatial treatment discontinuities arising from geographic borders. I give local linear estimators for both the conditional effect along the boundary and the average effect over the boundary. For two-dimensional RD designs, I derive an optimal, data-dependent, bandwidth selection rule for the conditional effect. I demonstrate these methods using a summer school and grade retention example. The third chapters illustrate the central role of persistence in estimating and interpreting value-added models of learning. Using data from Pakistani public and private schools, I apply dynamic panel methods that address three key empirical challenges: imperfect persistence, unobserved student heterogeneity, and measurement error. After correcting for these difficulties, the estimates suggest that only a fifth to a half of learning persists between grades and that private schools increase average achievement by 0.25 standard deviations each year. In contrast, value-added models that assume perfect persistence yield severely downwardly biased and occasionally wrong-signed estimates of the private school effect.

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Structuralist theories of properties state that properties are individuated by their nomological or causal roles. It has previously been suggested that structuralism is incompatible with robust conceptions of qualia. In this paper, I argue that structuralism should be taken as a theory of de re representation, and under this formulation it is able to accommodate qualia as intrinsic, introspectable properties of experiences. I then turn to various thought experiments used by qualia theorists to expand the notion of qualia, and find the majority of these compatible with structuralism as well. I conclude that the structuralists and qualia theorists need not be at odds with each other.

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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

Given the difficulty in predicting outcomes in persons with stroke-induced aphasia (PWA), neuroimaging-based biomarkers of recovery could provide invaluable predictive power to stroke models. However, the neural patterns that constitute beneficial neural organization of language in PWA remain debated. Thus, in this work, we propose a novel network theory of aphasia recovery and test our overarching hypothesis, i.e., that task-specific language processing in PWA requires the dynamic engagement of intact tissue within a bilateral network of anatomically-segregated but functionally and structurally connected language-specific and domain-general brain regions. We first present two studies in which we examined left frontotemporal connectivity during different language tasks (i.e., picture naming and semantic feature verification). Results suggest that PWA heavily rely on left middle frontal gyrus (LMFG)-driven connectivity for tasks requiring lexical-semantic processing and semantic control whereas controls prefer models with input to either LMFG or left inferior frontal gyrus (LIFG). Both studies also revealed several significant associations between spared tissue, connectivity and language skills in PWA. In the third study, we examined bilateral frontotemporoparietal connectivity and tested a lesion- and connectivity-based hierarchical model of chronic aphasia recovery. Between-group comparisons showed controls exhibited stronger left intra-hemispheric task-modulated connectivity than did PWA. Connectivity and language deficit patterns most closely matched predictions for patients with primarily anterior damage whereas connectivity results for patients with other lesion types were best explained by the nature of the semantic task. In the last study, we investigated the utility of lesion classification based on gray matter (GM) only versus combined GM plus white matter (WM) metrics. Results suggest GM only classification was sufficient for characterizing aphasia and anomia severity but the GM+WM classification better predicted naming treatment outcomes. We also found that fractional anisotropy of left WM association tracts predicted baseline naming and treatment outcomes independent of total lesion volume. Finally, results of a preliminary multimodal prediction analysis suggest that combined structural and functional metrics reflecting the integrity of regions and connections comprise optimal predictive models of behavior in PWA. To conclude this dissertation, we discuss how multimodal network models of aphasia recovery can guide future investigations. / 2020-10-23T00:00:00Z

Los desafíos ecológicos contemporáneos están insertos en el contexto de la sociedad del riesgo, escenario que emergió de la modernidad en la transición para la posmodernidad. Este período se caracteriza por la complejidad y la incertidumbre, lo que hace frágil la estabilidad que hasta entonces se imponía a los vínculos causales. Pero, las incertidumbres del conocimiento científico no pueden utilizarse como excusa contra la responsabilidad por daños ambientales y tampoco pueden atribuir responsabilidad a quien no dio causa alguna al hecho nocivo. Por lo tanto, en situaciones de complejidad, en el ámbito probatorio, es posible establecer indicadores de probabilidad para establecer niveles de responsabilidad. De hecho, abordar las demandas de responsabilidad ambiental no se limita a esbozar una nueva teoría del nexo causal, calzada únicamente en las instituciones tradicionales del derecho material, exigiéndose un análisis conjugado del derecho probatorio pertinente. En este contexto, la causalidad fundada en probabilidades posibilita una solución que trasciende los modelos estancos de responsabilidad total o de plena exoneración, admitiéndose valores que flotan entre esos extremos en un ambiente de causalidad probable, indicativo de grados de incertidumbre. Además, las medidas preventivas que se adopten deben incidir en el resultado final de la responsabilidad, o sea: cuanto un agente aporte de pruebas que coloquen en evidencia la minimización de riesgos de causar daño ambiental es inversamente proporcional a su parte de responsabilidad. Por otro lado, daños de alta magnitud o elevada diseminación, respecto de que los responsables no sean adecuadamente determinables, pueden ser colocados en evidencia por medio de estudios científicos. Aquí no se busca algo al respecto de la causalidad para el caso concreto y es posible, entonces, dispensar de la prueba de pericia, a partir de una presunción de causalidad. Tal presunción solamente será invertida si el operador comprueba que adoptó las medidas preventivas de daños fundadas técnicamente en la mejor tecnología disponible. La propuesta, por lo tanto, es que la solución conjugue teoría de la causalidad, repercusión procesal de medidas preventivas y contexto probatorio del caso concreto.

Sports organisations must continuously assess how better to meet or exceed consumer expectations and perceptions of their experience in order to maintain and increase the number of spectators and loyal fans attending their sporting events. This study aims to enhance our understanding of which characteristics of a service attribute will best define its quality and impact on spectator behaviour by understanding the causal relationship between perceived service quality (PSQ) and satisfaction.