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- All Subjects: Civil Engineering
- Genre: Doctoral Dissertation
- Creators: Arizona State University
- Member of: Theses and Dissertations
- Status: Published
The activity-based approach to travel demand analysis and modeling, which has been developed over the past 30 years, has received tremendous success in transportation planning and policy analysis issues, capturing the multi-way joint relationships among socio-demographic, economic, land use characteristics, activity participation, and travel behavior. The development of synthesizing population with an array of socio-demographic and socio-economic attributes has drawn remarkable attention due to privacy and cost constraints in collecting and disclosing full scale data. Although, there has been enormous progress in producing synthetic population, there has been less progress in the development of population evolution modeling arena to forecast future year population. The objective of this dissertation is to develop a well-structured full-fledged demographic evolution modeling system, capturing migration dynamics and evolution of person level attributes, introducing the concept of new household formations and apprehending the dynamics of household level long-term choices over time. A comprehensive study has been conducted on demography, sociology, anthropology, economics and transportation engineering area to better understand the dynamics of evolutionary activities over time and their impacts in travel behavior. This dissertation describes the methodology and the conceptual framework, and the development of model components. Demographic, socio-economic, and land use data from American Community Survey, National Household Travel Survey, Census PUMS, United States Time Series Economic Dynamic data and United States Center for Disease Control and Prevention have been used in this research. The entire modeling system has been implemented and coded using programming language to develop the population evolution module named `PopEvol' into a computer simulation environment. The module then has been demonstrated for a portion of Maricopa County area in Arizona to predict the milestone year population to check the accuracy of forecasting. The module has also been used to evolve the base year population for next 15 years and the evolutionary trend has been investigated.
Nevertheless, some organizations understand the importance of risk management practices and have begun to measure their risk maturity in order to identify weaknesses and improve risk management practices. Risk maturity measures the organization's ability and perceptions towards risk management. It is possible that many of the barriers to improving risk management would not exist if increased risk maturity was found to have a positive correlation with successful project performance.
The comprehensive hypothesis of the research is that increased risk maturity improves project performance. An exploratory study was conducted on data collected to identify measurable benefits with risk management. Quantitative and qualitative data was collected on 266 construction projects over a seven year period. Multiple statistical analyses were performed on the data and found a positive correlations between risk maturity and project performance. A positive correlations was found between customer satisfaction and contractors risk maturity. Additional findings from the recorded data included the increased ability to predict risks during construction projects within an organization. These findings provide clear reasoning for organizations to devote additional resources in which improve their risk management practices.
This study finds that despite cultural differences, teachers are likely to share some commonalities with respect to their instructional decisions, understanding of student thinking and curricular knowledge. These similarities may reflect the convergence in teaching practice in the U.S. and China and the dedication the two countries make in improving math education. This study also finds the cross-country differences and cross-SES differences regarding teachers' PCK. On the one hand, the U.S. and Chinese math teachers of this study tend to diverge in valuing different forms of representations, explaining student misconceptions, and relating functions to other math topics. Teachers' own understanding of functions (and mathematics), standards, and high-stakes testing in each country significantly influence their PCK. On the other hand, teachers from the higher SES schools are more likely to show higher expectations for and stronger confidence in their students' mathematical skills compared to their counterparts from the lower SES schools. Teachers' differential beliefs in students' ability levels significantly contribute to their differences between socio-economic statuses.