This study determines consumer demand for staple food crops biofortified with micronutrients in three sub-Saharan African countries. Specifically, the study investigates how the choice of a valuation technique for a nonmarket good or new product, and gender, influence acceptance of biofortified food crops. Biofortification, a new public health intervention for alleviating micronutrient deficiency problems in developing countries, is achieved by enhancing the micronutrient content of staple food crops using conventional plant breeding or biotechnology. The rural poor in developing countries are likely to benefit most from biofortification, for two main reasons. Firstly, their diets are primarily comprised of staple foods that are usually poor sources of micronutrients. Secondly, they have limited access to fortified food products, mineral and vitamin supplements. The novel property of biofortification, however, has been associated with changes in the intrinsic properties of staple food crops that may not be familiar to consumers. Thus, knowing consumers’ attitudes and potential reactions to such changes in their staple food crops has been important to researchers and marketers alike. The study employs hedonic evaluations and incentive-compatible economic experimental data from HarvestPlus that aimed at determining consumer acceptance of micronutrient biofortified staple food crops in three sub-Saharan countries, i.e., Nigeria, Rwanda, and Zambia. The first objective compares the Becker–DeGroot–Marschak (BDM) mechanism to the non-hypothetical choice experiment (nHCE) in revealing the willingness to pay (WTP) for a new maize variety biofortified with vitamin A, under a field setting in Zambia. A mixed logit model was used to determine consumers’ WTP for the biofortified orange maize, relative to the two local maize varieties in the nHCE. While a symmetrically censored least square (SCLS) model was used to determine consumers’ WTP for the biofortified orange maize in the BDM experiment. The results show that the nHCE yielded significantly higher WTP estimates than that from the BDM mechanism. The second objective, related to the first, explored potential reasons for the WTP disparity between the BDM and the nHCE. The results indicate that accounting for additional training in the BDM experiment and lexicographic behaviour in the nHCE, together resulted in a decrease by half in the WTP estimates difference between the two methods. This difference, however, remains statistically significant. The third objective determined whether the gender of the decision-maker is important in determining consumer’s attitudes and behaviour towards biofortified food crops. Specifically, the study explores gender differences in hedonic preferences and consumer valuations of food products made from biofortified food crops. Emphasis was placed on the statistical analysis methods that incorporate gender while fully accounting for sources of both the observed and unobserved heterogeneity across gender. Results suggest that the gender of the decision-maker may be an important factor in both hedonic preferences and WTP for biofortified food crops, although the results varied across three countries. In Zambia and Rwanda, gender differences were observed in hedonic preferences for vitamin A-biofortified orange maize and biofortified iron beans respectively, while no evidence of gender differences was observed in hedonic preferences for vitamin A biofortified cassava in Nigeria. On the other hand, gender differences in WTP for biofortified foods were observed across the three countries in the respective biofortified food crops. While it is not yet clear how the BDM and the nHCE can result in significantly different empirical estimates under similar conditions, these results suggest the solution could lie in controlling for design effects from the two techniques. Similarly, controlling for gender differences not only in the outcome variable but also in its determinants may be necessary to attain valid estimates of consumer acceptance of biofortified foods. / Thesis (PhD)--University of Pretoria, 2019. / Agricultural Economics, Extension and Rural Development / PhD / Unrestricted

Integration is a core concept of calculus. As such, significant work has been done on understanding how students come to reason about integrals, including both the definite integral and the accumulation function. A path towards understanding the accumulation function first, then the definite integral as a single point on the accumulation function has been presented in the literature. However, there seems to be an accessible path that begins first with understanding the definite integral through an Adding Up Pieces (AUP) perspective and extending that understanding to the accumulation function. This study provides a viable hypothetical learning trajectory (HLT) for beginning instruction with an AUP perspective of the definite integral and extending this understanding to accumulation functions. This HLT was implemented in a small-scale teaching experiment that provides empirical data for the type of student reasoning that can occur through the various learning activities. The HLT also appears to be a promising springboard into developing the Fundamental Theorem of Calculus. Additionally, this study offers a systematic framework for understanding the process- and object-level thinking that occurs at different layers of integration.

Economists are still searching for methods to reduce/eliminate Hypothetical Bias (HB). Different methods have been previously applied some with success and others without. In this study, we aimed to further test the cognitive dissonance approach (CD) through a learning design method to estimate the WTP for five beef attributes: Non-quality, Kentucky Proud, Appalachian, Grass Fed and a mix of 25% Non-quality and 75% Kentucky Proud, using a one and one half bounded model. To test the CD, 881 participants from the University of Kentucky, were randomly assigned to a real/hypothetical market for a battery recycling project at first and afterwards to a hypothetical market for beef. For the battery recycling, participants were asked to donate $1, $2 or $3. For the beef market, participants were randomly assigned to a $4 or $6 for the non-quality attribute patty. Participants assigned to a $4 were afterwards randomly assigned to a $4.5, $5, $5.5 or $6 and the ones assigned to a $6 were afterwards assigned to a $6.5, $7, $7.5 and $8 for the other attribute patties. From this study, we found that the learning design was effective in reducing the cognitive dissonance or conflicts between what consumers say and their actions.

It is sometimes said that money speaks louder than words, and in a world where financial decisions are a major driving force, it is interesting to explore how monetary incentives influence our decision making. Some argue that intrinsic motivation is sufficient to be able to measure prosocial decision-making, but what happens when we add monetary incentives to experiments that might otherwise be conducted with hypothetical scenarios? In this study, we conduct an online experiment with 1002 participants to explore if decision making changes when monetary incentives are introduced. The experiment includes five different social dilemmas involving distributions of money between participants. There are two conditions where one group makes hypothetical decisions and the other group receives money based on their decisions (i.e., is incentivized). Furthermore, we investigate if income, age and gender affect prosocial behavior. Our results suggest that both conditions show similar effects on prosocial behavior which implies that usage of either one of the two conditions will generate an equivalent outcome. The effects from household income, age and gender were significant in some social dilemmas, but the effect was not practically relevant for this study. We believe our results may be useful to include in the discussion of whether or not monetary incentives and hypothetical decisions generate similar results when studying prosocial behavior in decision making in experiments.

Hypothetical bias continues to be a challenge for practitioners of the contingent valuation method (CVM). This study compared the effect of three hypothetical bias mitigation techniques in a CVM survey focused on estimating maximum willingness to pay for a beach conditions monitoring service among U.S. Gulf Coast beachgoers. Beach conditions information is known to affect beach patronage but no valuation study has yet estimated its value. The two techniques tested are: budget and substitutes cheap talk treatments and certainty follow-up. We presented a theoretically consistent model of budget-constrained utility maximization which accounts for the respondents’ subjective probability of a good beach trip with and without the beach conditions information. Interval regression was used to estimate respondents WTP for beach conditions monitoring service. Both mitigation treatments were unable to mitigate HB. The mean WTP was $3.39 and the net benefit for the program was between $188,531,063 and $391,474,452.

This paper explores the impact of political responses against terrorism and how they are linked to hypothetical voting intention. After September 11, 2001, terrorism became a major concern of democratic governments and their residents. Terrorism poses a constant unseen threat that people want to feel protected from. The goal of the current study was to examine whether the way political candidates communicate responses to terrorist actions affect the way people vote. The findings indicate that offensive portrayals of terrorism brought in more hypothetical votes than defensive ones. These data have the potential to help the general public better understand political messages related to the subject of terrorism along with facilitating communication during future possible crisis caused by terrorist attacks.

Lesson study is a form of professional development for teachers adopted in recent years from Japan. Introducing lesson study to U.S. teachers and researchers has been the focus of most of the literature on this subject. Much of the literature outlines how lesson study works and describes its essential features. One of the features of lesson study is anticipating student responses, also known as anticipating student thinking. Anticipating student responses is passingly described in lesson study literature. This research was conducted to understand what it means to anticipate student responses for preservice mathematics teachers in a lesson study group. Lesson study literature indicates that anticipating student responses is to anticipate conceptual development from the students' perspective, and the purpose is to be prepared to have meaningful discussions and questions to enable students to develop the understanding. Anticipating student responses is highly related to the hypothetical learning trajectory described by Simon (1995), the self directed anticipative learning model described by Christensen and Hooker (2000) and the expert blind spot discussed by Nathan and Petrosino (2003). While their work does not stem from lesson study, they add theoretical perspective to the idea of anticipating student responses. Their work indicates that anticipating student responses is difficult, valuable, that one gets better at it through experience, and that it is very useful in refining lessons. Participants were enrolled in the mathematics education methods class of a large private university in the U.S. A characterization of anticipating student responses was developed as the participants met in group meetings to create a lesson. They anticipated student responses in ways that facilitated lesson planning and task design. Participants did not anticipate student responses toward students' conceptual development. This research reports five particular ways that anticipating student responses was used as a tool to define and refine the lesson so that it ran smoothly toward lesson goals. These ways are related to: goals, tasks and materials, procedural mathematical reasoning, successful student efforts, and emotional responses. It is believed that anticipating student responses towards task design is a necessary precursor to anticipating student responses toward students' conceptual development.

There is an overemphasis on procedures and manipulation of symbols in calculus and not enough emphasis on conceptual understanding of the subject. Specifically, students struggle to understand and correctly apply concepts in calculus such as the chain rule, implicit differentiation, and related rates. Students can learn mathematics more deeply when they make connections between different mathematical ideas. I have hypothesized that students can make powerful connections between the chain rule, implicit differentiation, and related rates through the mathematical concept of nested multivariation. Based on this hypothesis, I created a hypothetical learning trajectory (HLT) rooted in nested multivariation for students to develop an understanding of these three concepts. In this study, I explore my HLT through a small-scale teaching experiment with individual first-semester calculus students using tasks based on the HLT.Based on the teaching experiment, nested multivariational reasoning proved to be critical in understanding how the variables within a function composition change together and in developing intuition and understanding for the multiplicative nature of the chain rule. Later, nested multivariational reasoning was mostly important in recognizing the existence of a nested relationship and the need to use the chain rule in differentiation. Overall, through the HLT, students gained a connected and conceptual understanding for the chain rule, implicit differentiation, and related rates. I also discuss how the HLT might be adjusted and improved for future use.

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