846 resultados para SKY SURVEY DATA


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This dissertation comprises three individual chapters. Chapter Two examines how free riding across neighbors influenced the diffusion of color television sets in rural China. Chapter Three tests for asymmetric information between a firm’s management and other investors concerning its patent output. Chapter Four discusses how knowledge stocks influence a patenting firm’s later diversification. Chapter Two documents the existence of a type of network effects—free riding across neighbors—in the consumption of color television sets in rural China, which reduces the propensity of non-owners to purchase. I construct a model of the timing of the purchase of a durable good in the presence of free riding, and test its key implications using household survey data in rural China. Chapter Three tests for asymmetric information between a firm’s management and other investors about its patent output by examining insider trading patterns and stock price changes in R&D intensive firms. It demonstrates that management has considerable information about its patent output beyond what is known to investors. It also shows that the predictive power of insider trading patterns on patent output comes from purchases rather than sales. Chapter Four discusses two sequential channels through which knowledge stocks may influence a firm’s later diversification. One is that firms with more knowledge are more likely to enter a new industry. The other is that firms’ businesses have a better chance of surviving, conditional on being formed. By examining U.S. public patenting firms in manufacturing sectors for 1984-1996, I find that knowledge stocks predict the likelihood of new industry entry when controlling for firm size. However, this predictive power is weakened when diversification effects are included. On the other hand, a survival study of newly established segments shows that initial knowledge stocks have significant positive effects on segment survival, whereas diversification effects are insignificant.

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In what can rightly be said to be one of the most dramatic geopolitical shifts in modern times, the collapse of communist regimes in Central Europe and the former Soviet Union brought about dramatic changes in the entire region. As a consequence, wide ranging political, economic, and social transformations have occurred in almost all of these countries since 1989. The Slovak Republic, as a newly democratic country, went through the establishment of the electoral and party systems that are the central mechanisms to the formation of almost all modern democratic governments. The primary research purpose of this dissertation was to describe and explain regional variations in party support during Slovakia’s ten years of democratic transformation. A secondary purpose was to relate these spatial variations to the evolution of political parties in the post-independence period in light of the literature on transitional electoral systems. Research questions were analyzed using both aggregate and survey data. Specifically, the study utilized electoral data from 1994, 1998, and 2002 Slovak parliamentary elections and socio-economic data of the population within Slovak regions which were eventually correlated with the voting results by party in the 79 Slovak districts. The results of this study demonstrate that there is a tendency among voters in certain regions to provide continuous support to the same political parties/movements over time. In addition, the socio-economic characteristics of the Slovak population (gender, age, education, religion, nationality, unemployment, work force distribution, wages, urban-rural variable, and population density) in different regions tend to influence voting preferences in the parliamentary elections. Finally, there is an evident correlation between party preference and the party’s position on integration into European Union, as measured by perceived attitudes regarding the benefits of EU membership.

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Each disaster presents itself with a unique set of characteristics that are hard to determine a priori. Thus disaster management tasks are inherently uncertain, requiring knowledge sharing and quick decision making that involves coordination across different levels and collaborators. While there has been an increasing interest among both researchers and practitioners in utilizing knowledge management to improve disaster management, little research has been reported about how to assess the dynamic nature of disaster management tasks, and what kinds of knowledge sharing are appropriate for different dimensions of task uncertainty characteristics. ^ Using combinations of qualitative and quantitative methods, this research study developed the dimensions and their corresponding measures of the uncertain dynamic characteristics of disaster management tasks and tested the relationships between the various dimensions of uncertain dynamic disaster management tasks and task performance through the moderating and mediating effects of knowledge sharing. ^ Furthermore, this research work conceptualized and assessed task uncertainty along three dimensions: novelty, unanalyzability, and significance; knowledge sharing along two dimensions: knowledge sharing purposes and knowledge sharing mechanisms; and task performance along two dimensions: task effectiveness and task efficiency. Analysis results of survey data collected from Miami-Dade County emergency managers suggested that knowledge sharing purposes and knowledge sharing mechanisms moderate and mediate uncertain dynamic disaster management task and task performance. Implications for research and practice as well directions for future research are discussed.^

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Traffic from major hurricane evacuations is known to cause severe gridlocks on evacuation routes. Better prediction of the expected amount of evacuation traffic is needed to improve the decision-making process for the required evacuation routes and possible deployment of special traffic operations, such as contraflow. The objective of this dissertation is to develop prediction models to predict the number of daily trips and the evacuation distance during a hurricane evacuation. ^ Two data sets from the surveys of the evacuees from Hurricanes Katrina and Ivan were used in the models' development. The data sets included detailed information on the evacuees, including their evacuation days, evacuation distance, distance to the hurricane location, and their associated socioeconomic characteristics, including gender, age, race, household size, rental status, income, and education level. ^ Three prediction models were developed. The evacuation trip and rate models were developed using logistic regression. Together, they were used to predict the number of daily trips generated before hurricane landfall. These daily predictions allowed for more detailed planning over the traditional models, which predicted the total number of trips generated from an entire evacuation. A third model developed attempted to predict the evacuation distance using Geographically Weighted Regression (GWR), which was able to account for the spatial variations found among the different evacuation areas, in terms of impacts from the model predictors. All three models were developed using the survey data set from Hurricane Katrina and then evaluated using the survey data set from Hurricane Ivan. ^ All of the models developed provided logical results. The logistic models showed that larger households with people under age six were more likely to evacuate than smaller households. The GWR-based evacuation distance model showed that the household with children under age six, income, and proximity of household to hurricane path, all had an impact on the evacuation distances. While the models were found to provide logical results, it was recognized that they were calibrated and evaluated with relatively limited survey data. The models can be refined with additional data from future hurricane surveys, including additional variables, such as the time of day of the evacuation. ^

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This study investigated faculty library demand from an organizational culture perspective at one college where annual requests for library instruction are received from a mere six percent of faculty. Analysis of survey data revealed a statistically significant difference in academic discipline assignment of library research, with the English-Humanities faculty group far exceeding all other faculty groups including the Social Sciences.

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Indigenous people in Bolivia have historically been excluded from the social and political life of their country, where socioeconomic differences are highly correlated with ethnic identities. However, after a serious political crisis, in 2005 an indigenous leader was elected President in an unprecedented election, and the country has since faced aggressive social and political transformations. Using survey data that ranges from 1998 to 2010, this paper shows some relevant changes in the perceptions and attitudes of indigenous people towards the democratic regime, its political institutions, and other citizens. The trends shown suggest that the average relationship of indigenous citizens with the estate and its institutions has improved both in relative and in absolute terms. However, levels of political tolerance among indigenous Bolivians do not seem to have increased at the same rate as those of non-indigenous Bolivians.