To achieve Sustainable Development Goal 3 in developing countries, Good health and wellbeing for all, the health workforce is vital however the unpopularity of rural medical practice results in widening healthcare inequalities between urban and rural areas. This study determined the heterogeneity in valuations for rural facility attributes by final year medical students at one South African public university to inform cost-effective recruitment policy recommendations. Focus groups conducted identified facility attributes, a D-efficient design was generated with 15 choice sets, each with two rural hospital alternatives and no opt-out option. An online, unlabelled discrete choice experiment (DCE) was conducted, the results effects coded, and mixed logit models applied. The final sample size was 193 (86,16% of the class), majority female 130 (66.33%), with urban origins 176 (89.80%), unmarried 183 (93.37%) and without children 193 (98.47%). Most had undergraduate rural medicine exposure 110 (56.12%) and intended to specialise 109 (55.61%). The main-effects mixed logit found advanced practical experience, hospital safety, correctly fitted personal protective equipment (PPE) and availability of basic resources the highest weighted attributes with their mean utilities increasing by 0.82, 0.64, 0.62 and 0.52 respectively (p=0.000). In contrast, increases in rural allowance and the provision of housing provided smaller mean utility increases of 0.001 (p<0.01) and 0.09 (p<0.05) respectively. The interaction terms; female, general practise and prior rural medicine exposure, were associated with higher weighting for hospital safety, mean utility increases 1.59, 1.82, 1.42 respectively (p=0.000). Participants were willing to pay ZAR 2636.45 monthly (95%CI: 1398.55;3874.355) to gain advanced practical experience (equivalent to 65.91% of current rural allowance). Medical students’ facility preferences have been found to be influenced by their gender, career aspirations and prior experienced with rural medicine. The policy recommendations derived from this research include publicising rural health facility “draw-cards” among medical graduates, such as the opportunity to gain practical experience, improving the physical and occupational safety at rural health facilities and providing greater transparency about rural facility attributes to medical graduates.

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This study employed a stated choice experiment survey to identify southeastern U.S. farmers’ preferences for contracts to produce Giant Miscanthus. We developed a more theoretically consistent framework which takes into account risk preference and perception information and also accounts for heterogeneous status-quo alternatives. Results from our Random Parameter Logit model indicated that price per ton of harvested Giant Miscanthus, biorefinery harvest, and establishment cost-share all had significant positive effects on the probability of a producer accepting a contract to produce Giant Miscanthus, whereas contract length had a significant negative effect. Our analysis also found evidence of significant preference heterogeneity in producers’ preferences for biorefinery harvest, yield insurance, and contract length. We also found that incorporating risk perception and risk preference information, as well as accounting for heterogeneous status-quo alternatives in the decision framework improved overall model performance even though the respective individual coefficients for these variables were not statistically significant.

While the southeastern United States, including the state of Mississippi, has a strong natural resource base, woody biomass is not fully utilized to produce bioenergy in this region. This study intended to explore opportunities, issues, and the economic potential of wood-based bioenergy in the state of Mississippi. Realizing the importance of private forest landowner decisions in sustaining a bioenergy feedstock supply, one aim of this study was to understand their choices for preferred harvesting methods of supplying woody biomass for wood-based bioenergy industries. Study results indicated that landowners were interested in optimizing revenue from woody biomass utilization while minimizing damage to the surrounding environment and facilitating less site preparation. Similarly, by administering a survey instrument, total and unused volumes of residues in primary and secondary mill operations were also estimated. Availability of woody residue was higher in the primary wood processing industry. Similarly, the likelihood of getting feedstock would be higher if a wood-based bioenergy generating facility could be located near a larger, year round operational forest product industry. This study further accounted for the potential direct, indirect, and induced economic impacts of a state wood-based bioenergy industry. Three potential wood-based bioenergy industries namely wood-pellet, bio-oil and methanol-based gasoline facilities were considered for an economic analysis. Study results revealed that operation of a wood-pellet industry would contribute 82 full- and part-time jobs to the economy with $12 million worth of economic output to the Mississippi economy. Likewise, the operation of a bio-oil industry would generate 165 new full- and part-time jobs and provide an economic output of $17 million. Also, $96 million in economic output and 795 full- and part-time more jobs would be added by establishing a methanol-based gasoline industry. Clearly, these impacts are substantial and are likely to draw the attention of policy makers and investors towards wood-based bioenergy in Mississippi.

Bakgrund: Logotypförändringar har blivit alltmer vanliga och logotyperna blir allt enklare. Hur ser konsumenterna på denna förändring? Syfte: Syftet med denna studie är att undersöka hur logotypers komplexitet samt igenkänning kan påverka konsumenters preferenser. Metod: Datainsamlingen gjordes med hjälp av en webbenkät som spreds via Facebook med en svarsfrekvens på 134 respondenter. Enkäten bestod av ett valexperiment där, av två svarsalternativ, det föredragna alternativet valdes. I del två svarade respondenterna också på om de kände igen logotyperna eller inte. Resultat: Resultatet samanställdes i frekvenstabeller och bearbetades med hjälp av en logistisk binominal regressionsanalys. Inget statiskt signifikant resultat uppnåddes. Slutsatser: Studien visar ingen statistisk evidens för i vilken utsträckning logotypers komplexitet, samt konsumenters igenkänning av en logotyp, påverkar konsumenters preferenser. I specifika fall påvisas dock belägg för att individer som känner igen en logotyp föredrar den komplexa (gamla) och individer som inte känner igen en logotyp föredrar den enkla (nya). / Background: Logo changes have become increasingly common, and the logos themselves are becoming simpler. How do consumers perceive this transformation? Aim: The purpose of this study is to examine how the complexity and recognizability of logos can influence consumer preferences. Method: The collection of data was conducted using a web survey distributed via Facebook, resulting in a response rate of 134 participants. The survey employed a choice experiment, where respondents were presented with two response options and asked to select their preferred alternative. In the second part, participants also indicated whether they recognized the logos or not. Results: The results were compiled into frequency tables and analyzed using logistic binomial regression analysis. However, no statistically significant results were obtained. Conclusions: The study does not provide statistical evidence regarding the extent to which the complexity of logos and consumers' recognition of a logo influence consumer preferences. However, in specific cases, there is evidence that individuals who recognizea logo prefer the complex (old) one, while individuals who do not recognize a logo prefer the simple (new) one.

Water-recycling technologies have been developed to reduce water consumption and surface runoff in horticultural operations. However, WRT may increase risk of disease from water-borne pathogens such as Pythium and Phytophthora. More information is needed about producers' management practices and attitudes regarding irrigation runoff containment and recycling. A mail survey was administered in February 2013 to horticultural nursery growers in Virginia, Maryland, and Pennsylvania. Collected were respondents' demographic characteristics plus irrigation and disease management practices. The survey incorporated a choice experiment quantifying willingness to adopt water recycling given hypothetical disease outbreak, water shortage probabilities, and percentage cost increases via a conditional logit model. Two hundred and sixty respondents provide valuable insight into horticultural production in the Mid-Atlantic region. We were unable to calculate the implicit price of water or disease for adoption because the sample of 91 respondents for the choice experiment yielded a flat distribution of operations ranging in $100 to $7 million in nursery cost. However, findings did support the hypothesis that producers will be more likely to adopt selected WRT when cost decreases, probability of disease decreases. Only 33% chose to adopt. Cost is the biggest factor as the majority of producers are not equipped to handle water recycling or capture and would go out of business due to the expense. Disease is also significant factor inhibiting growers from adopting. Until mandatory environmental regulations in place to force producers to contain runoff, or until incentivized cost sharing programs are implemented, wide spread adoption of water recycling technologies is unlikely to occur. / Master of Science

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Background and Objectives: Understanding patient and public values and preferences is essential to healthcare and policy decision making. Discrete choice experiments (DCEs) are a common tool used to capture and quantify these preferences. Recent technological advances allow for a variety of approaches to create and analyze DCEs. However, there is no optimal DCE design, nor analysis method. Our objectives were to (i) survey DCE simulation studies to determine what design features affect statistical efficiency, and assess their reporting, (ii) further investigate these findings with a de novo simulation study, and (iii) explore the sensitivity of individuals’ preference of attributes to several methods of analysis. Methods: We conducted a systematic survey of simulation studies within the health literature, created a DCE simulation study of 3204 designs, and performed two empirical comparison studies. In one empirical comparison study, we determined addiction agency employees’ preferences on knowledge translation attributes using four models, and in the second, we determined elementary school children’s choice of bullying prevention programs using nine models. Results and Conclusions: In our evaluation of DCE designs, we identified six design features that impact the statistical efficiency of a DCE, several of which were further investigated in our simulation study. The reporting quality of these studies requires improvement to ensure that appropriate inferences can be made, and that they are reproducible. In our empirical comparison of statistical models to explore the sensitivity of individuals preferences of attributes, we found similar rankings in the relative importance measures of attributes’ mean part-worth utility estimates, which differed when using latent class models. Understanding the impact of design features on statistical efficiency are useful for designing optimal DCEs. Incorporating heterogeneity in the analysis of DCEs may be important to make appropriate inferences about individuals’ preferences of attributes within a population. / Thesis / Doctor of Philosophy (PhD) / This thesis focuses on the design and analysis of preference surveys, which are referred to as discrete choice experiments. These surveys are used to capture and quantify individuals’ preferences on various characteristics describing a product or service. They are applied in various health settings to better understand a population. For example, clinicians may want to further understand a patient population’s preferences in regards to multiple treatment alternatives. Currently, there is no optimal approach for designing or analyzing preference surveys. We investigated what factors help improve the design of a preference survey by exploring the literature and conducting our own simulation study. We also investigated how sensitive the results of a preference survey were based on the statistical model used. Overall, we found that (i) increasing the amount of information presented and reducing the number of variables to explore will maximize the statistical optimality of the survey; and (ii) analyzing the data with different statistical models will yield similar results in the ranking of individuals’ preferences of the variables explored.