Thesis (Ph. D.)--Harvard University, 1994. / Includes bibliographical references (leaves 156-160).

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<p> Maslow's hierarchy of needs identifies shelter (specifically safety and security) as a basic need that motivates people to continue through life. Many Americans are at risk of losing this basic need, yet we continue to stigmatize specific groups of people based on their inability to secure permanent housing. The integration of crisis intervention, resource networking, education, and empowerment into a supportive housing strategy in Washington, DC could reduce chronic homelessness. </p><p> Homelessness is a major issue that does not receive adequate attention in most cities. As gentrification continues, affordable housing is rapidly declining, placing longtime residents at risk of being displaced. An issue that can't be overlooked, homelessness contributes to social issues such as crime and violence. There are several stages of homelessness; therefore, multiple approaches must be developed to combat the issue at different points in the cycle. While an intervention may be successful in only one stage of the cycle, it could potentially provide the answers to questions surrounding other stages of homelessness. </p><p> This thesis will explore the causes of homelessness and only its associated problems. By identifying some of these problems and shedding light on some of the causes of homelessness (and realizing that those issues are present throughout society), this thesis will identify why it is important to create supportive housing and how this type of approach will help end chronic homelessness. </p><p> To develop a solution to this problem this thesis will use correlational research, observational research, qualitative data and quantitative data to identify the current homeless population, and the potential growth of the population within specific geographic areas. This information will help me identify a site and develop a replicable housing solution that will reduce the number of destitute residents, as well as potentially provide strategies for reducing the homeless population. </p><p> It has been determined that supportive housing, along with consideration for sustainability and several factors that affect the human psyche, will help end homelessness, which is costly in a small city such as Washington, DC. This thesis will explore supportive housing as one solution to chronic homelessness.</p><p>

This D.Phil, thesis undertakes a theoretical analysis of the microeconomic incentives for scientific and technical knowledge-creating activities at the firm-level, the channels by which these activities impinge on industrial change and economic growth, and the effectiveness of governmental policies formulated to influence these systemic linkages. The motivation for this work is explained in Chapter 2, which reviews the state of the art in new growth theory and puts forward a typology of privately sponsored RandD activities and knowledge resources defining the premises on which the thesis rests. Chapters 3 and 4 investigate the RandD allocation and output decisions of a profitmaximising monopolist investing in exploratory- and applications-oriented research, dealing separately with product and process innovations. The characteristic properties of the optimal time paths are ascertained by means of formal and numerical optimal control methods, including comparative dynamics. The complementarity between the two modes of research is shown to generate increasing returns, but these turn out to be short-lived. The model is extended in Chapter 5 to study the development of multiple product lines. Knowledge spillovers and demand-side externalities across successive product lines can provide the basis for continued spending on RandD, allowing sustained output growth and profitability. Chapters 6 to 8 turn to the challenges of modelling the irreducible elements of uncertainty in the innovation process and their bearing upon the dynamics of market competition and industry structure. In the sequential game theoretic model introduced, firms can invest in fundamentally uncertain "innovative-RandD," or wait until the uncertainty surrounding original innovation is dispelled and invest in certain but costly "imitative-RandD." These decisions are taken in a vertically and horizontally differentiated market where noninnovating firms can compete with a "traditional" product. The industry-wide scale of RandD investments and the related evolution in market structure are determined endogenously. To do so, a symmetric equilibrium concept is defined and its uniqueness established. The model can support Schumpeterian industry evolutions, in which surges of innovative entry are followed by waves of imitation, and ensuing "creative destruction" in which traditional producers are driven out of the industry and innovators' rents are eventually eroded. Numerical simulations are employed in Chapter 7 to provide further insights into the evolution of product development, market structure, pricing, firm growth, profitability, and consumer welfare. The final chapter considers the implications of this game theoretic approach for competition and innovation policies.

Thesis (M.A.)--Carleton University, 2001. / Includes bibliographical references (p. 111-117). Also available in electronic format on the Internet.

Thesis (Ph. D.)--University of California, Berkeley, 1988. / Includes bibliographical references (leaves 216-225).

Thesis (PhD) -- Macquarie University, Division of Environmental and Life Sciences, Graduate School of the Environment, 2008. / Typescript. Bibliography: p. 370-395.

This research develops a combined qualitative and quantitative activity based analysis methodologies framework for integrated fixed activity chaining schedules (IFACS). What is central to my dissertation is the extent to which the type, sequence, duration, and timing of fixed activities influence trip chaining. The goal is to improve the practice of travel behavior forecasting by modeling the activity patterns and chaining behavior of individuals with restricted schedules. Cluster analysis methods are applied to narrow down the endless possibilities of individual trip decision-making into a manageable group. Then space-time prism concepts are applied to locate unique activity travel patterns. Qualitative examples show that aggregate and individual trip-chaining behaviors are not easy to model. Informed by the qualitative analysis results, the framework incorporates both discrete choice and time-to-event models as quantitative analysis tools. The quantitative models cover two levels of chaining: trip link and whole journey. Logit models are used to analyze the choice to make a chained link right after the completion of an activity, and the decision to conduct a chained journey. Poisson models are used to examine the decision to make a number of chained links on a journey. Hazard-based duration models are used to analyze time of chaining events by studying the duration of a chained journey, then the duration of time elapsed till a chained link is made right after a fixed activity with the goal of defining a time threshold to the occurrence of trip chaining. Integrating results from qualitative and quantitative methods leads to a better understanding of how people make their trip-chaining and travel behavior decisions. Data from the 1998 Mobidrive six-week travel diary survey is used in the analyses. This framework focuses on the effects of five types of fixed activities on trip-chaining behavior: work, work-related, school, further education, and club/group meetings. Understanding factors influencing a person's decision to participate in a trip chain allows motivations behind trip-chaining behavior to become more tangible. One of the highlights of the analysis results of the modeling framework is discovering that the chaining behavior of individuals is influenced in different ways among different population subgroups.