This research examines a new methodology for prospectively estimating the willingness of travelers to use a toll road by combining travel time saved with the income of the prospective customer base. The purpose of the research is to facilitate network level planning by allowing some reasonable predictions of acceptable toll rates from readily available data and estimation techniques. Methods of estimating user benefit resulted in simulated distributions of value of user time. Values of time are linked to census tract income data for the user population to produce value of time as a percentage of income as an indicator. As relevant literature acknowledges the tendency toward increased toll road usage at higher income levels, it is hypothesized that linking estimates of value of time directly to household income would produce a more useful indicator of the travel market than do conventional indicators. Techniques for prospectively estimating the travelshed of a toll road are compared with the actual travelshed, as reflected in user home census tracts, as a means of evaluating the efficacy of those techniques in estimating the market area of a prospective toll road. Results show that considering value of time as a percentage of census tract median income provides an improved portrayal of the toll road market, as usage of the toll road increases with increasing income. Using census tract median income as the income parameter has shortcomings, in that it produces anomalous results at very low population levels. Of the two methods of estimating the travelshed, the visual estimation approach was not satisfactory, leaving the analyst to use select link analyses instead.

This research attempts to examine whether economic, social, political and institutional factors affected local public expenditures (per capita) in Taiwan. The panel data regression analysis, covering the period from 1989 to 2007, used statistics from the 21 prefectures (5 cities and 16 counties) of Taiwan by applying the median voter model and political business cycle (PBC) model. The findings from the empirical data suggest that the explanatory variable of the median income is significant and has a positive sign as predicted by the priori expectation, with the exception of economic development expenditure. The gap between the median income and average income variables has positive signs in the total, social welfare, police and economic development expenditures. The tax share variable and grant variable on all categories of spending are significant, but the positive sign of the tax share variable contrasts a priori expectations. The population variable and population density variable have negative signs in different expenditures, while the social welfare and the education, science, and culture expenditures have positive signs. Comparing the difference before and after the downsizing of the Taiwan Provincial Government, the significance of the latter is higher than the former, and the effects of various variables differ. The results of this research also indicated that the variables of the pre-election year, election year and post-election year demonstrated statistical significance with varying directional tendencies, and that the results are inconsistent with the traditional hypothesis of the election cycle. The incumbent magistrates or mayors, regardless of whether they do or do not intend on re-election, exhibit no significant influence on most expenditures, and thus this does not agree with a priori expectations. The administrative satisfactions of incumbent magistrates or mayors have statistically significant influence on the expenditures and deficits. Generally, the Pan-KMT incumbent magistrates or mayors have more motives to increase the total and capital expenditures and deficits than the Pan-DPP. Interestingly, the KMT party, which held the majority of seats in the county council, has a positive sign and statistically significant influence on the expenditure of grants to townships. The evidence has demonstrated that a unified government or divided government (horizontal type or vertical type) has no significant influence on most of the expenditure forms, although a negative sign on social welfare expenditure is evident in 21 counties and cities. The lagged deficit is significant with a positive sign, which implies that the insufficiency of local accountability and deficits are becoming a long-term problem. When comparing the power of the median voter model and political business cycle model in explaining the local public expenditure, a non-nested test was implemented. No model was found to hold an advantage over another model. In brief, the current research indicates that the factors of the majority voters' demands, elections and parties indeed have different influences on various expenditure forms in Taiwan.

This research study was designed to help illuminate if there is a relationship between the quality of career and technical education programs from centralized and decentralized-controlled systems in relation to the level of authority exerted by state governing/coordinating boards over the community college system. This study included data from the 50 states that are part of the United States of America. This study used a quasi-experimental, nonequivalent design. This study did not include randomly selected groups and was a nonequivalent control group design. The independent variables included: centralized or decentralized governance, median household income, the percent of community colleges that are rural, unemployment rate, and amount spent per full time enrolled community college student. The independent variable data that was collected came from the Bureau of Labor and Statistics, the United States Census Bureau, and the Integrated Post-Secondary Education Data System (IPEDS). The dependent variable was the mean score of Carl Perkins Act reporting data that each state is required to report to federal authorities every year. The states were divided in two separate groups, centralized or decentralized form of governance. A regression analysis was performed in order to analyze if a relationship exists between the independent and dependent variables for each group. The research indicated that the form of governance does impact Carl Perkins Act reporting scores in a decentralized form of governance in relation to median income, but overall the model is not a good predictor of overall scores. A significant difference was found in states that have a decentralized form of governance and median household income in relation to Carl Perkins Act reporting data. However, the model, as a whole, did not produce significant results in relation to the independent and dependent variables. Considerations for future research are discussed.

Major disasters such as wildfire, tornado, hurricane, tropical storm, flooding cause disruptions in infrastructure systems such as power outage, disruption to water supply system, wastewater management, telecommunication failures, and transportation facilities. Disruptions in electricity infrastructures have negative impacts on sectors throughout a region, including education, medical services, financial, and recreation sectors. In this study, we introduce a novel approach to investigate the factors which can be associated with longer restoration time of power service after a hurricane. Considering restoration time as the dependent variable and utilizing a comprehensive set of county-level data, we have estimated a Generalized Accelerated Failure Time (GAFT) model that accounts for spatial dependence among observations for time to event data. The model fit improved by 12% after considering the effects of spatial correlation in time to event data. Using GAFT model and Hurricane Irma's impact on Florida as a case study, we examined: (1) differences in electric power outages and restoration rates among different types of power companies: investor-owned power companies, rural and municipal cooperatives; (2) the relationship between the duration of power outage and power system variables; (3) the relationship between the duration of power outage and socioeconomic attributes. The findings of this study indicate that counties with a higher percentage of customers served by investor-owned electric companies and lower median household income, faced power outage for a longer time. This paper identifies the key factors to predict restoration time of hurricane-induced power outages, allowing disaster management agencies to adopt strategies required for restoration process.