Magister Economicae - MEcon / The main objective of this study was to identify ways in which transaction costs can be lowered to improve small-scale farmers’ participation in and returns from agricultural output markets, with specific reference to small-scale mango farmers in Limpopo province. This study hypothesizes that transaction costs are lower in informal spot markets and increase when small-scale farmers sell in more structured markets (formal markets). This study builds on transaction cost economics (TCE) to demonstrate how to overcome transaction cost barriers that small-scale mango farmers face in the agro-food markets. The approach to collect primary information was sequenced in two steps: first, key informant and focus group interviews were conducted and, secondly, a structured survey instrument was administered in two districts of Limpopo. A total of 235 smallscale mango farmers were interviewed. A binary logistic regression model was used to estimate the impact of transaction costs on the likelihood of households’ participation in formal (=1) and informal (=0) agro-food markets. STATA Version 10 was used to analyse the data. This study found that a larger proportion of male than female farming households reported participation in the formal markets, suggesting deep-seated gender differentiation in market participation. The average age of small farmers participating in formal markets is 52, compared to 44 for those in informal markets, implying that older farmers might have established stronger networks and acquired experience over a longer period. Farmers staying very far from the densely populated towns (more than 50 km) participate less in the formal markets than those staying closer (0 – 25 km and 26 – 49 km), which implies that the further they are from the towns, the less the likelihood of farmers selling in the formal markets. Farmers who own storage facilities and a bakkie (transportation means) participate more in formal markets compared to those who do not own these assets, which suggests that these farmers are able to store mangoes, retaining their freshness and subsequently delivering them to various agro-food markets on time. Households that participate in formal markets have high mean values of income and social grants. However, this study found that the likelihood of a household’s participation in the markets is less as income and social grants increase. This suggests that households do not invest their financial assets in order to overcome market access barriers. A large proportion of households that own larger pieces of arable land participate in the formal markets, which implies that they are able to produce marketable surplus. Households that have a high mean value (in Rand) of cattle participate more in formal markets than in informal markets. However, this study found that the likelihood of a household’s participation in the markets does not change with an increase in the value of its livestock. These findings suggest that households do not sell their cattle in order to overcome market access barriers. Reduced transaction costs for small-scale mango farmers in Limpopo should improve their participation in and returns from the agro-food markets. Policy interventions to support this need to focus on: access to storage and transportation facilities, enforcement of gender equity requirements in existing policies, and better access to information about markets. / South Africa

The study's purpose was to identify demographics, educational background, finances, formal and informal education and experiences, reading habits, external environmental factors, psychological factors, and computer efficacy factors that predict a student's ability to successful complete an online (Web-based) distance learning community college course. Major student retention theories and student attrition and persistence research guided the study. Distance learners (N = 926) completed four surveys, which collected data for 26 predictor variables that included age, gender, marital status, ethnicity, support others, course load, first-time student, last semester attended, student type and location, financial stability, tuition payment, prior learning experiences, reading habits, family support, enrollment encouragement, study encouragement, time management, study environment, employment, extrinsic and intrinsic motivation, locus of control, self-efficacy, computer confidence and skills, and number of prior online courses. Successful or unsuccessful course completion was the dependent variable. Statistical analyses included Cronbach's alpha, Pearson chi-square, two-sample t test, Pearson correlation, phi coefficient, and binary logistic regression. Variables in each factor were entered sequentially in a block using separate binary logistic regression models. Statistically significant variables were course load, financial stability, prior learning experiences, time management and study environment, extrinsic motivation, self-efficacy, and computer skills. Selected predictor variables (N = 20) were entered hierarchically in a logistic regression model of which course load, financial stability, and self-efficacy were statistically significant in the final block. Correlation coefficients were computed for statistically significant predictor variables to determine whether the significance was confined to the control group or an overall level of significance. Findings were supported through cross-validation and forward stepwise entry of variables in logistic regression. Despite having two or more at-risk factors, distance learners who had high levels of self-efficacy, good computer and time management skills, financial stability, a favorable study environment, were enrolled in more than one course, and believed their prior learning experiences helped prepared them for their course were more likely to be successful.

MENVSC / Department of Geography and Geo-Information Sciences

This exploratory study assessed attitudes and perceptions of smallholder farmers towards agricultural technologies in Kakamega County, Kenya. Through a mixed-methods sequential design, the study evaluated the key variables predicting farmer adoption of agricultural innovations. While social sciences provide a clear human-driven pattern explaining the process of choices and behaviors regarding technology use, there is still little clarity on the influences of adoption decisions among smallholder farmers in rural Kenya. Using the diffusion of innovations theory, the study explored the attitudes and perceptions of smallholder farmers toward technology adoption in seven sub-counties of Kakamega County (Lurambi, Ikolomani, Shinyalu, Mumias East (Shianda), Malava Butere, and Khwisero). The study design utilized a quantitative survey of 245 smallholder heads of households, followed by focus group discussions to further probe attitudes, values and practices that could influence technology adoption. The survey questionnaire tested two hypotheses: (H1) socio-demographic characteristics are related to agricultural technology adoption; and, (H2) farmer access to extension services was related to agricultural technology adoption. A binary logistic regression model was used to quantitatively estimate socio-demographic variables presumed to influence the adoption of agricultural innovations. Subsequently, four informal focus group discussions of 28 discussants was conducted across representative sub-counties (Lurambi, Shianda, Malava and Ikolomani), to elicit an in-depth understanding of farmers’ perspectives on technology adoption. The focus group participants included farmers recruited from among survey participants. The qualitative research instrument sought to answer three questions, (RQ1) what are farmer attitudes and perceptions towards agricultural technologies; (RQ2) what socio-cultural values influence farmers’ choice of agricultural technologies; and, (RQ3) what sources do farmers use for obtaining information on agricultural technology? Quantitative results included a principal component analysis (PCA) in which 14 attitudes questions were reduced to five conceptual clusters. These clusters included: challenges in accessing modern agricultural technologies (explained 19.09% of the total variance); effectiveness of agricultural technologies (11.88%); enjoyment of agricultural technologies (10.02%); social influence in use of technology (9.47%); and experience with agricultural technologies (8.13%). A logistic regression model indicated that independently age (.07), education (.10), and off-farm income (.08) were significantly associated with adoption of technology at the 90% confidence level when controlling for all other variables in the model. However, agricultural extension (.42) was not a significant predictor of agricultural technology adoption in this model. Qualitative results provided rich insights which enhanced findings from the survey data. Key insights in the thematic analysis included: farmers’ ambivalence about agricultural technologies; lack of trust in agricultural agents; low levels of agricultural technology knowledge; extension services as the main source of information dissemination to farmers; predominance of gender in determining agricultural technology adoption; and gender inequity in agricultural decision-making. In conclusion, the study results suggested that a mixed-methods approach was valuable in probing the nuances of farmers’ perceptions of agricultural extension and technology adoption among smallholder farmers. The results supported the following recommendations: the agricultural extension efforts could be more effectively structured in order to support the dissemination of agricultural information; the issue of gender should be adequately addressed by engaging male and female in collaborative agricultural efforts to help break the barrier of gender inequity; and future research would benefit from disaggregating public and private extension services as a more robust method for determining their individual effects in the promotion of agricultural innovations among smallholder farmers.

In 2014, 32,675 deaths were recorded in vehicle crashes within the United States. Out of these, 51% of the fatalities occurred in rural highways compared to 49% in urban highways. No specific crash data are available for the built-up areas along rural highways. Due to high fatalities in rural highways, it is important to identify the factors that cause the vehicle crashes. The main objective of this study is to determine the factors associated with severities of crashes that occurred in built-up areas along the rural highways of Nevada. Those factors could aid in making informed decisions while setting up speed zones in these built-up areas. Using descriptive statistics and binary logistic regression model, 337 crashes that occurred in 11 towns along the rural highways from 2002 to 2010 were analyzed. The results showed that more crashes occurred during favorable driving conditions, e.g., 87% crashes on dry roads and 70% crashes in clear weather. The binary logistic regression model showed that crashes occurred from midnight until 4 a.m. were 58.3% likely to be injury crashes rather than property damage only crashes, when other factors were kept at their mean values. Crashes on weekdays were three times more likely to be injury crashes than that occurred on weekends. When other factors were kept at their mean value, crashes involving motorcycles had an 80.2% probability of being injury crashes. Speeding was found to be 17 times more responsible for injury crashes than mechanical defects of the vehicle. As a result of this study, the Nevada Department of Transportation now can take various steps to improve public safety, including steps to reduce speeding and encourage the use of helmets for motorcycle riders.

This thesis investigates the factors that are associated with annual changes in the share price of Johannesburg Stock Exchange (JSE) listed companies. In this study, an increase in value of a share is when the share price of a company goes up by the end of the financial year as compared to the previous year. Secondary data that was sourced from McGregor BFA website was used. The data was from 2004 up to 2011. Deciding which share to buy is the biggest challenge faced by both investment companies and individuals when investing on the stock exchange. This thesis uses binary logistic regression to identify the variables that are associated with share price increase. The dependent variable was annual change in share price (ACSP) and the independent variables were assets per capital employed ratio, debt per assets ratio, debt per equity ratio, dividend yield, earnings per share, earnings yield, operating profit margin, price earnings ratio, return on assets, return on equity and return on capital employed. Different variable selection methods were used and it was established that the backward elimination method produced the best model. It was established that the probability of success of a share is higher if the shareholders are anticipating a higher return on capital employed, and high earnings/ share. It was however, noted that the share price is negatively impacted by dividend yield and earnings yield. Since the odds of an increase in share price is higher if there is a higher return on capital employed and high earning per share, investors and investment companies are encouraged to choose companies with high earnings per share and the best returns on capital employed. The final model had a classification rate of 68.3% and the validation sample produced a classification rate of 65.2% / Mathematical Sciences / M.Sc. (Statistics)

In the present study, I analyze adolescent girls’ smoking through a unique combination of a quantitative survey of impressions and a theoretical analysis based on new elaborations of Bourdieu’s concept symbolic capital. The method of the study is three-fold. First, focus-group interviews elicit relevant impressions of adolescents in the eyes of peers. Second, a questionnaire survey distributed to adolescent peers quantitatively investigates how impressions of a girl on a picture differ depending on whether or not she has a cigarette. Third, a theoretical analysis based on elaborations of Bourdieu’s theories scrutinizes the results of the questionnaire survey. The results of the questionnaire survey indicate that smoking adolescent girls generate impressions of being significantly less likable, more popular, more conceited, less kind, less shy, more liable to bully, less funny, more deceitful, and less compassionate than non-smoking adolescent girls. In the elaborations of Bourdieu’s theories, I introduce a division of symbolic capital into two forms: symbolic virtue capital, generated through impressions of virtues, and symbolic power capital, generated through intimidating impressions of destructive power. According to the theoretical analysis of the results, smoking adolescent girls have relatively much symbolic power capital but relatively little symbolic virtue capital compared to adolescent girls that do not smoke.

Doctor of Philosophy / Department of Physics / Dean Zollman / As part of a collaborative study of the science preparation of elementary school teachers, we investigated the quality of students’ reasoning and explored the relationship between sophistication of reasoning and the degree to which the courses were considered inquiry oriented. To probe students’ reasoning, we developed open-ended written content questions with the distinguishing feature of applying recently learned concepts in a new context. We devised a protocol for developing written content questions that provided a common structure for probing and classifying students’ sophistication level of reasoning. In designing our protocol, we considered several distinct criteria, and classified students’ responses based on their performance for each criterion. First, we classified concepts into three types: Descriptive, Hypothetical, and Theoretical and categorized the abstraction levels of the responses in terms of the types of concepts and the inter-relationship between the concepts. Second, we devised a rubric based on Bloom’s revised taxonomy with seven traits (both knowledge types and cognitive processes) and a defined set of criteria to evaluate each trait. Along with analyzing students’ reasoning, we visited universities and observed the courses in which the students were enrolled. We used the Reformed Teaching Observation Protocol (RTOP) to rank the courses with respect to characteristics that are valued for the inquiry courses. We conducted logistic regression for a sample of 18 courses with about 900 students and reported the results for performing logistic regression to estimate the relationship between traits of reasoning and RTOP score. In addition, we analyzed conceptual structure of students’ responses, based on conceptual classification schemes, and clustered students’ responses into six categories. We derived regression model, to estimate the relationship between the sophistication of the categories of conceptual structure and RTOP scores. However, the outcome variable with six categories required a more complicated regression model, known as multinomial logistic regression, generalized from binary logistic regression. With the large amount of collected data, we found that the likelihood of the higher cognitive processes were in favor of classes with higher measures on inquiry. However, the usage of more abstract concepts with higher order conceptual structures was less prevalent in higher RTOP courses.

IPCC於第四次報告書中，模擬氣候持續暖化預測未來海平面上升之情形，而海平面上升對於人口集中的台北都會區將產生莫大之衝擊，同時亦會造成土地利用變遷。本研究目的在於探討海平面上升對台北都會區土地利用變遷之影響，以及受淹沒地區之人口未來可能之遷移區位，主要係從社會經濟發展層面進行分析。運用二元羅吉斯迴歸模式並結合土地利用轉換與影響模型（CLUE-s），以四種不同情境模擬土地利用變遷之情況，其情境分別為海平面上升59公分管制農林地與不管制，以及海平面上升100公分管制農林地與不管制。 　　研究結果顯示，海平面上升之情形越嚴重，未來的都市建地發展會越趨向擴張的形式，對農林地產生變遷之壓力；而於同一海平面上升水平下，針對農林地進行管制，其建地之發展會較為集中於都市計畫地區範圍內，且多數人口亦將遷移至此，容易形成人口壓力。此外，土地利用變遷模擬所得之新增建地部分，於情境A、C下足以容納受影響之人口，但情境B、D則不足以容納，皆會對台北都會區產生容受力之問題，產生累計人口超過計畫人口之現象。因此，建議未來政府於都市發展上，可調整都市計畫內之土地使用強度或都市範圍，也可利用都市更新之方式減少新的土地開發；此外，從國家層級分析，未來的國土計畫法於立法上，亦可將更多氣候變遷相關影響因子納入四大功能分區，透過適宜性分析進行分類分級，以做為未來土地利用發展之引導。 / The 4th IPCC report simulated climate warming and predicted future sea-level rise scenarios. A sea level rise will have a great impact on the population of the Taipei metropolitan area, and it will also produce land-use changes. The purpose of this study is to research the impact of sea level change on land use changes and population migration in Taipei metropolitan, and the areas that will be immigrated by the flooded areas. The method used includes binary logistic regression model combined with Conversion of Land Use and its Effects Model (CLUE-s). Setting the sea-level rise and regulating agricultural land, forest land of the four simulated situations. The results show that the higher sea level rises, the more transformation towards urban development in the future, and the higher sea level will also pressure agriculture and forestry changes. As a result of population pressure on Taipei metropolitan area, the same level of sea-level rise for the regulation of agriculture and forestry land, the development of building sites and population migration will be more concentrated on urban planning areas. In addition, the simulation of land use change generated new building sites, sufficient enough to accommodate the affected population under A and C simulated situations, but B and D couldn’t generate such results. Instead, it will generate a carrying capacity issue. Therefore, this thesis suggests that the government adjust the intensity of land use in urban development, urban areas and urban renewal of urban planning. In addition, the analysis from the national level, the future legislation of Land Planning Act should include the relation of climate change impact factors as a consideration of future land use development.

2007年美國爆發次級房貸違約潮造成了其經濟、房市和股市的不景氣，也波及到持有美國房貸證券化商品的各國，使其承受重大的損失，因此房屋抵押貸款違約的影響因素和金融資產證券化機制對貸款違約風險的影響又再度成為不動產與金融市場上之重要議題。而以往針對美國次貸危機的研究多指出道德風險是造成此次危機的原因之一，但是較缺乏實證研究的支持。 有鑑於此，本研究以我國的台北市和新北市的房屋抵押貸款市場作為研究對象，探討逆選擇和道德風險這兩個資訊不對稱的問題對貸款違約率的影響。研究結果顯示「貸款成數高、貸款利率高、搭配信貸和設定二胎的貸款比較容易違約」，證實逆選擇和道德風險問題確實存在於房屋抵押貸款市場，而且會增加貸款違約的機率。為了降低違約機率，從降低資訊不對稱的角度來看，本研究建議：一、建立全國房貸資料庫；二、將信貸的金額納入房貸的貸款成數中考慮，以降低款人的道德風險。 再者，本研究認為造成次貸危機的根本原因是不當政策導致的保證機制浮濫，以及高風險的房貸證券化商品的氾濫。為了避免我國發生類似次貸危機的事件，從減少資訊不對稱的角度切入，本研究建議我國的金融資產證券化機制應該：一、將道德風險內部化，消除創始機構自利的動機以減少道德風險；二、使用外部信用增強的方式，以確實發揮分散證券風險的作用。 / The 2007 subprime mortgage crisis has severely struck the stability of the worldwide financial markets. Some researches indicate that moral hazard problems are the main factors causing the crisis. However, few studies support asymmetry problems existing in a mortgage market by empirical evidences. First, using the mortgage samples from Taipei City and New Taipei City this study would like to understand if the mortgage market are information asymmetry problems, adverse selection and moral hazard, and conduct the empirical analysis for these factors’ impact on mortgage default. The results show that mortgage default is influenced significantly by the Loan-to-Value （LTV） ratio, contract interest rates, the existence of second liens and credit loans, and jobs. It shows that adverse selection and moral hazard actually exist in the mortgage market. According to the empirical results, secondly, this study proposes suggestions for mortgage lending and financial asset securitization to reduce adverse selection and moral hazard problems and enhance the regulation environment and market’s stability. It is expected that the results of this study will be applied to avoid the occurrence of similar crisis in Taiwan.