Journal of Urban Planning and Development

This study analyzes a broad range of data in Jordan on people’s housing and customer attitudes using a questionnaire to measure the factors that influence people’s choice of housing and to decide upon the choice that best satisfies customers’ needs by using the semantic differentials technique. The questionnaire contains 45 attributes for the housing units constructed in several cities in Jordan. The main finding indicates a serious shortcoming in the new housing: a lack of cultural relevance in the design. Citizens have little or no voice in making decisions as to where and what types of housing should be built. The designers have placed their main emphasis on mass housing production with little attention to quality of design, customers’ needs, and cultural relevance. The key to establishing a successful housing sector appears to be the ability of developers to identify these issues adequately. Therefore, program managers and developers must understand the sources of competitive advantage in the housing sector that can make a difference in gaining and retaining customers. The customers’ expectations reflect a pressure toward changes in housing design and construction. An effective design and superior performance in meeting a market’s unique requirements may lead to a significant competitive advantage.

This paper analyzes the economic impact of an earthquake on transportation network that contains more detail for the Midwest states. Two aspects of cost are considered in the paper: final demand loss and transport cost increase. The 1812 New Madrid earthquake is used to develop a scenario for the analysis. The modeling system includes a transportation network loss function, a final demand loss function, and an integrated commodity flow model. After running the earthquake scenario, the analysis identifies the most significant link on the network in an economic sense as well as the link with the greatest physical disruption. The results reveal that the links with greater physical disruption are not always the ones exhibiting the greater economic damage. The resulting outputs can provide information to perform a cost-benefit analysis as well as to support a decision-making process on the optimal retrofit priority of bridges and links on the transportation network.

This paper introduces a quantitative methodology to model the way that the number, locations, and types of buildings in a region change over time, specifically in order to understand how those changes affect hurricane risk. The methodology is intended ultimately to be incorporated into regional risk-assessment models so they can more accurately estimate expected future hurricane losses. Current regional risk-assessment models assume that a region’s building inventory remains static over time. The methodology begins with population projections, transforms them into household projections, then housing-unit projections, and finally projections of the number of buildings with different structural characteristics. The final output is the number of buildings of a certain type in each census tract and each future year, where the building type is based on units in structure, year built, value, type of roof covering, predominant roof shape, and number of stories. A case study is presented for residential buildings in 15 counties in North and South Carolina. An uncertainty analysis examines the effect of modeling assumptions and data uncertainty on the results.