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Increased focus on sustainability and climate change has made reduction in CO2 emissions a priority across all industries. The construction equipment (CE) industry sees alternate powertrain technologies like battery electric and hydrogen fuel-cells as the solution to the climate problem and has therefore started investing in this domain. However, with their niche application, the demand on construction equipment is unique and this indicates that it is important to understand the customer preferences when introducing new technologies in this market. This presents the research question answered in thisthesis - do customers prefer non-fossil based alternate powertrain in construction equipment?. In order to answer this question, extensive literature review is carried out and parallelsare drawn with passenger vehicle and commercial truck industry. Based on previous workin this area, the first step is to calculate the total cost of ownership of the four different alternatives - diesel, bio-diesel, battery electric and fuel-cell electric. This information is then used to establish a discrete choice experiment, which is designed to gauge thes tated preference of the customers. A survey was conducted to this effect, where CE customers were provided with multiple choice scenarios and asked to choose between fouralternatives, differentiated by varying attributes such as total investment cost, total variablecost, operation range, refill duration and technology maturity. The survey responsewas then used to build a random utility model using logistical models like MultinomialLogit, Mixed Logit and Nested Logit. The utility coefficients were estimated in these three models and compared against each other and the most significant attributes were identified. Out of 54 respondents, even though majority 62% preferred a conventional diesel machine in the stated preference choices, an overwhelming 38% had opted for the sustainable alternatives which was more than expected, specially since such machines are not available in the mainstream market. The mixed multinomial logit model showed the best fit among the model alternatives tested and attributes like fixed cost, variable cost and market share showed statistical significance with this model. The results indicate that the market preferenceis still in favour of diesel machinery but the perception towards sustainable poweredmachinery looks positive and better than expected. Original Equipment Manufacturers(OEMs) need to target smaller fleet owners for adoption of sustainable alternatives like Battery Electric and Fuel Cell electric machines. Even though Sustainable powered machines show a lot of promise, they are still not competitive in terms of cost as the discrete choice analysis shows that variable cost significantly influence purchase decision.

A thorough understanding of transit customers’ preferences and travel behaviour is fundamental to offering a high-quality urban transportation system. The dominant approach in transit quality literature is rooted in understanding current transit users’ preferences. However, disregarding the heterogeneity in transit customers’ desired quality yields suboptimal conclusions regarding their preferences. Therefore, an effective transit system should strive to understand the broad spectrum of transit and non-transit users’ preferences to increase transit ridership. Towards that end, this research aims at deciphering the heterogeneity associated with transit customers’ service desired quality. The research utilized a primary dataset elicited from an online survey that was part of Hamilton Street Railway (HSR) Public Engagement efforts in Hamilton, Ontario, Canada. The research employed state-of-the-art discrete choice models (e.g., error components logit models, latent class choice models, nested logit models) along with multivariate statistical and spatial analysis. In this respect, this dissertation quantified and unveiled latent heterogeneity in transit customers’ preferences and its implications on their willingness to pay for service improvements through various techniques and specifications. Unlike the conventional classifications for transit customers, our research classifies transit customers into three latent segments: Direct Trip Enthusiastic (DTE), Cost-Sensitive (CS), and Real-time Information Supporter (RIS). The dissertation also investigated and further quantified the influence of subjective psychological factors in shaping transit customers’ preferences towards service attributes. For instance, environmental consciousness is found to be associated with less sensitivity to walking time while higher appreciation to at-stop real-time information provision. Furthermore, the research highlighted how the built environment and its contextual effects influence customers’ travel behaviour while accounting for variations in socioeconomic characteristics. The spatial analysis concluded that the built environment's influence is not equally efficacious over geography. Overall, this research presents a unique contribution to the knowledge of public transit research for practitioners, policymakers, and academia. / Dissertation / Doctor of Philosophy (PhD)

[pt] Este artigo investiga o impacto da provisão pública na concorrência dentro do setor de ensino superior brasileiro. Desenvolvemos e estimamos um modelo empírico de demanda por ensino superior que incorpora instituições gratuitas e restrições de escolha do consumidor. Nosso modelo produz padrões de substituição mais realistas do que um modelo logit sem restrições, indicando que a seletividade é uma dimensão essencial da diferenciação de produtos. Mostramos que os programas públicos mais seletivos exercem pressão competitiva comparável aos programas privados mais seletivos, mas os programas públicos menos seletivos exercem mais pressão competitiva do que os programas privados menos seletivos. Nossas estimativas da resposta de oferta das instituições privadas sugerem que, na ausência de programas públicos, as mensalidades seriam cerca de 7 por cento mais altas. Esses resultados fornecem informações importantes sobre a dinâmica competitiva do ensino superior brasileiro e destacam o papel da provisão pública na promoção da concorrência nesse setor. / [en] This paper investigates the impact of public provision on competition within the Brazilian higher education sector. We develop and estimate an empirical model of demand for higher education that incorporates tuition-free institutions and consumer choice constraints. Our model produces more realistic substitution patterns than a logit model without constraints, indicating that selectivity is an essential dimension of product differentiation. We find that the most selective public programs exert comparable competitive pressure to the most selective private programs, but the least selective public programs exert more competitive pressure than the least selective private programs. Our estimates of the supply response of private institutions suggest that, in the absence of public programs, tuitions would be about 7 percent higher. These findings provide important insights into the competitive dynamics of Brazilian higher education and highlight the role of public provision in promoting competition in this sector.

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Yes / Background Recently, primary care in the United Kingdom has undergone substantial changes in skill mix. Non-medical prescribing was introduced to improve patient access to medicines, make better use of different health practitioners’ skills and increase patient choice. There is little evidence about value-based patient preferences for ‘prescribing nurse’ in a general practice setting. Objective To quantify value-based patient preferences for the profession of prescriber and other factors that influence choice of consultation for managing a minor illness. Design Discrete choice experiment patient survey. Setting and participants Five general practices in England with non-medical prescribing services, questionnaires completed by 451 patients. Main outcome measure Stated choice of consultation. Main results There was a strong general preference for consulting ‘own doctor’ for minor illness. However, a consultation with a nurse prescriber with positive patient-focused attributes can be more acceptable to patients than a consultation provided by a doctor. Attributes ‘professional’s attention to patients’ views’ and extent of ‘help offered’ were pivotal. Past experience influenced preference. Discussion and conclusion Respondents demonstrated valid preferences. Preferences for consulting a doctor remained strong, but many were happy to consult with a nurse if other aspects of the consultation were improved. Findings show who to consult is not the only valued factor in choice of consultation for minor illness. The ‘prescribing nurse’ role has potential to offer consultation styles that patients value. Within the study’s limitations, these findings can inform delivery of primary care to enhance patient experience and substitute appropriate nurse prescribing consultations for medical prescribing consultations. / Department of Health, Project 016/0108. NIHR, CDF/01/2008/009.

Background and Objectives: I investigated the use of sensitivity analyses in assessing statistical results or analytical approaches in three different statistical issues: (1) accounting for within-subject correlations in analyzing discrete choice data, (2) handling both-armed zero-event studies in meta-analyses for rare event outcomes, and (3) incorporating external information using Bayesian approach to estimate rare-event rates. Methods: Project 1: I empirically compared ten statistical models in analyzing correlated data from a discrete choice survey to elicit patient preference for colorectal cancer screening. Logistic and probit models with random-effects, generalized estimating equations or robust standard errors were applied to binary, multinomial or bivariate outcomes. Project 2: I investigated the impacts of including or excluding both-armed zero-event studies on pooled odds ratios for classical meta-analyses using simulated data. Five commonly used pooling methods: Peto, Mantel-Haenszel fixed/random effects and inverse variance fixed/random effects, were compared in terms of bias and precision. Project 3: I explored the use of Bayesian approach to incorporate external information through priors to verify, enhance or modify the study evidence. Three study scenarios were derived from previous studies to estimate inhibitor rates for hemophilia A patients treated with rAHF-PFM: 1) a single cohort of previously treated patients, 2) individual patient data meta-analysis, and 3) an previously unexplored patient population with limited data. Results and Conclusion: Project 1: When within-subject correlations were substantial, the results from different statistical models were inconsistent. Project 2: Including both-armed zero-event studies in meta-analyses increased biases for pooled odd ratios when true treatment effects existed. Project 3: Through priors, Bayesian approaches effectively incorporated different types of information to strengthen or broaden research evidence. Through this thesis I demonstrated that when analyzing complicated health research data, it was important to use sensitivity analyses to assess the robustness of analysis results or proper choice of statistical models. / Dissertation / Doctor of Philosophy (PhD)

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