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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Predicting bicycle ownership and usage among university campus residents

Maynard, David Robert January 1900 (has links)
Master of Regional and Community Planning / Department of Landscape Architecture/Regional & Community Planning / Gregory Newmark / Concerns about climate change, environmental impacts and resources needed for transportation infrastructure, require new and different approaches to planning, designing, and operating transportation solutions on a global scale. College campuses are prime locations to focus on various methods of sustainable transportation, specifically walking and bicycling and the related infrastructures needed for these systems. The necessary infrastructures for these modes of transportation are different than the conventional road system utilized by automobiles. As a result, cities, planners, campuses, and the individuals who will be traveling must understand why changes to transportation infrastructures are important. This may require a mindset change before it becomes incorporated in their everyday lives. Universities can play a large role in this by offering increased infrastructure for bicycling. This paper examines the travel behaviors of students that live on campus at Kansas State University Campus in Manhattan and examines their bicycle ownership and usage habits, through the use of a survey. The survey results suggest that the Jardine Apartments is the area most used for bicycle travel. The survey provides the most perceived prevalent impediments to cycling more often as well as the top elements the University could utilize to promote cycling. This report conducted three binomial logistic regression models to predict bicycle ownership and usage. It was found that being male, residing in the Jardine Apartments, and having a high bicycle comfort level are all important factors.

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