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- Genre: Academic theses
Description
Unrestricted Mexican exports of sugar into the U.S. is considered the most pressing issue facing the U.S. sugar industry. The goal of this dissertation is to analyze the trade of sugar between Mexico and the U.S. as well as analyze additional primary issues confronting the U.S. sugar industry. Chapters 1 and 2 provide an introduction to the U.S. sugar industry. Chapters 3 through 6 develop trade models which analyze sugar trade between Mexico and the U.S. The trade models estimate how NAFTA, USDA sugar forecast errors and Mexican ownership of twenty percent of the Mexican sugar industry each impact U.S. producer surplus and Mexican welfare. Results validate that U.S. producer surplus and in some instances Mexican welfare were decreased by full implementation of NAFTA. U.S. producer surplus and Mexican welfare were decreased due to USDA sugar production forecasting errors. U.S. producer surplus would be increased if the Mexican government did not own twenty percent of Mexican sugar production. Using an online choice experiment, Chapter 7 assesses U.S. consumers' preferences and willingness to pay (WTP) for imported and genetically modified (GM) labeled sugar and sugar in soft drinks. Results indicate that consumers prefer bags of sugar and soft drinks labeled as "Not GM". Furthermore, consumers prefer sugar from Canada and the U.S. over sugar from Mexico, Brazil and the Philippines. Evidence is also provided that participants are more likely to choose actual products in the choice set rather than the "none of these" options when controlling for hypothetical bias by using consequentiality techniques. A non-hypothetical experimental auction was used in Chapter 8 to determine consumers' WTP for soft drinks labeled with sweetener and calorie information and analyzed the role of taste panels in an experimental auction. Results indicate that sugar is consumers' most preferred sweetener and calorie labeling is ineffective at influencing consumers to choose healthier soft drinks. Including taste in an experimental auction caused significant reductions in consumers' WTP for all soft drinks. Chapter 9 concludes by summarizing the results of this dissertation and discussing the future challenges facing the U.S. sugar industry.
ContributorsLewis, Karen Elizabeth (Author) / Schmitz, Troy (Thesis advisor) / Grebitus, Carola (Committee member) / Manfredo, Mark (Committee member) / Ketcham, Andrea (Committee member) / Arizona State University (Publisher)
Created2014
Description
The Dodd-Frank Act was created to promote financial stability in the United States. However, no one is quite sure what it is yet. While action had to be taken and Dodd-Frank has some positives, Dodd-Frank, as it is deciphered today, has severe drawbacks. Since Dodd-Frank is only in its infancy, it is difficult to form an interim conclusion about its effects on agricultural lending at this point. After passing Dodd-Frank in 2010, the government began trying to figure out what it means. Four years later, they are still trying and are about half way through making the rules. This law essentially replaces Glass-Steagall, which was repealed several years ago. Many believe repealing Glass-Steagall was a big reason for the financial collapse of 2008. While Glass-Steagall was a short, easily understood document, Dodd Frank adds many more regulations and pages. This creates a long, bulky, confusing law that seems to be extremely tough to comprehend legally or as a banker. In this study, I try to balance the positives and negatives of Dodd-Frank to understand if it is more detrimental or beneficial to agricultural lending. While we find that Dodd-Frank does help keep banks from some of the risky investments that many believe led to the financial crisis, the added paperwork, compliance costs, and strain it puts on small banks can be worrisome. I interviewed several agriculture-lending professionals who regularly deal with the rules and regulations of Dodd-Frank to discover the impact the new law has on banks, their customers, and the economy as a whole. These interviews give insight into what Dodd-Frank means to the agriculture-lending market and what changes have had to occur since the law was passed. These interviews demonstrate that Dodd-Frank is largely looked down upon by the banking industry. The professionals interviewed are very experienced. After the extensive research, interviews, and discoveries that came of this study, it was concluded that Dodd-Frank seems to hurt the lending industry much more than it helps. One major concern is the strain Dodd-Frank puts on small banks and how it makes "too big to fail" banks even bigger.
ContributorsBettencourt, Bradley D (Author) / Thor, Eric (Thesis advisor) / Manfredo, Mark (Committee member) / Englin, Jeff (Committee member) / Arizona State University (Publisher)
Created2014
Descriptionyour words
ContributorsWang, Dan, M.S (Author) / Grebitus, Carola (Thesis advisor) / Schroeter, Christiane (Committee member) / Manfredo, Mark (Committee member) / Hughner, Renee (Committee member) / Arizona State University (Publisher)
Created2014
Description
The global demand and trade for fruits and vegetables is increasing at national and international levels. The fresh fruits and vegetables supply chain are highly vulnerable to contamination and can be easily spoiled due to their perishable nature. Due to increases in fresh fruit and vegetable trade shipment volume between countries, the fresh food supply chain area is the highly susceptible and frequently prone to food contamination. The inability of firms in the fresh food business to have a good supply chain visibility and tracking system is one of the prominent reasons for food safety failure. Therefore, in order to avoid food safety risk and to supply safe food to consumers, the firms need to have an efficient traceability system in their supply chain. Most of the research in the food supply chain area suggests the implementation of a highly efficient tracking system called RFID (Radio frequency identification) technology to firms in the food industry. The medium scale firms in the fresh food supply chain business are skeptical about implementing the RFID technology equipped traceability system due to its high cost of investment and low margins on fresh food sales. This research developed two methods to measure the probability of food safety risk in food supply chain. These methods use the information gain from RFID traceability systems as a tool to measure the amount of risk in the fresh food supply chain. The stochastic optimization model is applied in this study to determine the risk premium by investing in RFID technology over the electronic barcode traceability system. The results show that there is a reduction in buyer (Type II error) and seller risk (Type I error) for RFID technology employed traceability system compared to electronic barcode system. It is found from stochastic optimization results that there is a positive risk premium by investing in RFID traceability system over the current systems and suggests the implementation of RFID traceability system for complex medium scale fresh produce imports to reduce the food safety risks. This research encourages the food industries and government agencies to evaluate alternatives to update supply chain system with RFID technology.
ContributorsJanke, Deepak Kumar (Author) / Nganje, William (Thesis advisor) / Schmitz, Troy (Committee member) / Thor, Eric (Committee member) / Arizona State University (Publisher)
Created2011
Description
Consumers can purchase local food through intermediated marketing channels, such as grocery stores, or through direct-to-consumer marketing channels, for instance, farmers markets. While the number of farms that utilize direct-to-consumer outlets keeps increasing, the direct-to-consumer sales remain lower than intermediated sales. If consumers prefer to purchase local food through intermediated channels, then policies designed to support direct channels may be misguided. Using a variety of experiments, this dissertation investigates consumer preferences for local food and their demand differentiated by marketing channel. In the first essay, I examine the existing literature on consumer preferences for local food by applying meta-regression analysis to a set of eligible research papers. My analysis provides evidence of statistically significant willingness to pay for local food products. Moreover, I find that a methodological approach and study-specific characteristics have a significant influence on the reported estimates for local attribute. By separating the demand for local from the demand for a particular channel, the second essay attempts to disentangle consumers’ preferences for marketing channels and the local-attribute in their food purchases. Using an online choice experiment, I find that consumers are willing to pay a premium for local food. However, they are not willing to pay premiums for local food that is sold at farmers markets relative to supermarkets. Therefore, in the third essay I seek to explain the rise in intermediated local by investigating local food shopping behavior. I develop a model of channel-selection in a nested context and apply it to the primary data gathered through an online food diary. I find that, while some consumers enjoy shopping at farmers markets to meet their objectives, such as socialization with farmers, the majority of consumers buy local food from supermarkets because they offer convenient settings where a variety of products can be bought as one basket. My overall results suggest that, if the goal is to increase the sales of local food, regardless of the channel, then existing supply-chain relationships in the local food channel appear to be performing well.
ContributorsPrintezis, Iryna (Author) / Richards, Timothy J. (Thesis advisor) / Grebitus, Carola (Committee member) / Schmitz, Troy (Committee member) / Arizona State University (Publisher)
Created2018
Description
It is well understood that innovation drives productivity growth in agriculture. Innovation, however, is a process that involves activities distributed throughout the supply chain. In this dissertation I investigate three topics that are at the core of the distribution and diffusion of innovation: optimal licensing of university-based inventions, new variety adoption among farmers, and consumers’ choice of new products within a social network environment.
University researchers assume an important role in innovation, particularly as a result of the Bayh-Dole Act, which allowed universities to license inventions funded by federal research dollars, to private industry. Aligning the incentives to innovate at the university level with the incentives to adopt downstream, I show that non-exclusive licensing is preferred under both fixed fee and royalty licensing. Finding support for non-exclusive licensing is important as it provides evidence that the concept underlying the Bayh-Dole Act has economic merit, namely that the goals of university-based researchers are consistent with those of society, and taxpayers, in general.
After licensing, new products enter the diffusion process. Using a case study of small holders in Mozambique, I observe substantial geographic clustering of new-variety adoption decisions. Controlling for the other potential factors, I find that information diffusion through space is largely responsible for variation in adoption. As predicted by a social learning model, spatial effects are not based on geographic distance, but rather on neighbor-relationships that follow from information exchange. My findings are consistent with others who find information to be the primary barrier to adoption, and means that adoption can be accelerated by improving information exchange among farmers.
Ultimately, innovation is only useful when adopted by end consumers. Consumers’ choices of new products are determined by many factors such as personal preferences, the attributes of the products, and more importantly, peer recommendations. My experimental data shows that peers are indeed important, but “weak ties” or information from friends-of-friends is more important than close friends. Further, others regarded as experts in the subject matter exert the strongest influence on peer choices.
University researchers assume an important role in innovation, particularly as a result of the Bayh-Dole Act, which allowed universities to license inventions funded by federal research dollars, to private industry. Aligning the incentives to innovate at the university level with the incentives to adopt downstream, I show that non-exclusive licensing is preferred under both fixed fee and royalty licensing. Finding support for non-exclusive licensing is important as it provides evidence that the concept underlying the Bayh-Dole Act has economic merit, namely that the goals of university-based researchers are consistent with those of society, and taxpayers, in general.
After licensing, new products enter the diffusion process. Using a case study of small holders in Mozambique, I observe substantial geographic clustering of new-variety adoption decisions. Controlling for the other potential factors, I find that information diffusion through space is largely responsible for variation in adoption. As predicted by a social learning model, spatial effects are not based on geographic distance, but rather on neighbor-relationships that follow from information exchange. My findings are consistent with others who find information to be the primary barrier to adoption, and means that adoption can be accelerated by improving information exchange among farmers.
Ultimately, innovation is only useful when adopted by end consumers. Consumers’ choices of new products are determined by many factors such as personal preferences, the attributes of the products, and more importantly, peer recommendations. My experimental data shows that peers are indeed important, but “weak ties” or information from friends-of-friends is more important than close friends. Further, others regarded as experts in the subject matter exert the strongest influence on peer choices.
ContributorsFang, Di (Author) / Richards, Timothy J. (Thesis advisor) / Bolton, Ruth N (Committee member) / Grebitus, Carola (Committee member) / Manfredo, Mark (Committee member) / Arizona State University (Publisher)
Created2015
Description
Three demand systems were estimated to examine demand sensitivity and welfare changes for each commodity under study. In the first essay, a Quadratic Almost Ideal Demand System (QUAIDS) was used to examine the effect of the Fukushima Daichi nuclear disaster on the demand for imported pelagic fish in the domestic Japanese market. The effect of the Fukushima Daichi nuclear disaster was measured using changes in demand after the disaster as well as measures of changes in social welfare changes caused by the disaster. A significant effect of the disaster on demand sensitivity measures was found, but no significant changes in welfare. In the second essay, a differential demand system examined the effect of exchange rate fluctuations on the demand for fresh tomatoes in the U.S. Market. It was found that the U.S. Dollar-Mexican Peso exchange rate had a significant positive effect on the demand for Mexican fresh tomatoes. In the third essay, a Hurdle Negative Binomial demand system was estimated for recreational trips to the Boundary Waters Canoe Area Wilderness. This model was estimated using Bayesian methods to obtain parameter estimates that could not be obtained by maximum likelihood. The parameters were used to calculate recreational welfare measures for trips to seventy-two entry points.
ContributorsValdez Lafarga, Octavio (Author) / Englin, Jeffrey (Thesis advisor) / Schmitz, Troy (Committee member) / Abbott, Joshua (Committee member) / Arizona State University (Publisher)
Created2017
Description
Celiac Disease (CD) is now widespread as one in 133 people are currently diagnosed, while there were only one in 150 in 2006. Much of the research concerning CD is still in the early stages, as formal epidemiological studies are relatively recent. CD is aggravated by the consumption of gluten, which is found mainly in wheat, rye, oats, and barley. Not surprisingly, the rising prevalence of CD has created a significant business opportunity for food manufacturers in developing products that are tailored to CD sufferers. While the entire Gluten-Free (GF) industry has been experiencing double digit growth rates, the expansion in available snack foods has outstripped all others. Observation of GF snack food prices suggests that food manufacturers are responding to high retail prices associated with GF foods. However, GF foods are often also advertised with other attributes that generally sell for a premium over conventional foods. Therefore, whether the high retail price for GF snack foods can be attributed specifically to the GF attribute is an empirical question. The objective of this research is to determine whether there is a retail-price premium for GF snack foods and, if there is, to estimate its magnitude. A hedonic pricing model is used to answer this question. Specifically, a hedonic pricing model was applied to a unique dataset of snack food products in order to estimate the marginal value for the GF attribute, while controlling for a number of other important attributes. Results show that the GF attribute is both economically and statistically significant, implying a premium of nearly $1.86 above gluten-containing products. Production costs for smaller manufacturers can be two to three times higher for GF foods relative to non-GF foods, but this still implies an excess premium of over $0.50 (assuming 40% margins). However, high premiums may not last as large retailers are utilizing their influence over suppliers to keep retail margins low. Therefore, the primary implication of the research is that the rapid growth in recent years can easily be explained on economic grounds for large agribusinesses, as this implies a major profit opportunity.
ContributorsSampson, Jed Philip (Author) / Richards, Timothy (Thesis advisor) / Manfredo, Mark (Committee member) / Pofahl, Geoffrey (Committee member) / Arizona State University (Publisher)
Created2010
Description
The difficulty of demonstrating a significant return on investment from the use of advanced data analytics has led to a lack of utilization of this tool. The most likely explanation for this phenomenon is the difficulty of incorporating non-financial metrics in the higher levels of analysis that are fully salient and derived in a manner that can be understood and trusted by organizational leaders. Another challenge that has confounded the use of advanced analytics by the leadership of organizations is the widely accepted belief that models are oftentimes developed with an insufficient number of variables that are expected to have an impact, which inhibits extrapolation of results for use in real-world decision making. This research identifies factors that contribute to the underutilization of analytics models in managerial decisions by leadership of the produce industry, and explores a variety of potential tools including descriptive analytics and dashboards that are able to provide predictive, prescriptive, and more advanced cognitive methods of decision making for use by organizational leadership. By understanding the disconnect between availability of the advanced data analysis tools and use of such tools by organizational leadership, this research assists in identifying the programs and resources that should be developed and presented as opportunities for support in the industrial decision-making process. This dissertation explores why managers within the produce industry underutilize higher levels of data analytics and whether it is possible to increase their levels of cognitive comfort. It shows that by providing leadership with digestible and rudimentary business experiments, they become more comfortable with more complex data analytics and then are better able to utilize dashboards and other tools within their decision-making models. As experiments are explained to managers, they become as comfortable with conducting experiments as they are with dashboards, thus becoming comfortable with evaluating their benefits.
ContributorsGlassman, Jeremy Britz (Author) / St. Louis, Robert (Thesis advisor) / Shao, Benjamin (Committee member) / Manfredo, Mark (Committee member) / Arizona State University (Publisher)
Created2020
Description
Decision-making is critical in the livestock supply chain. Understanding how producers and consumers make their decisions requires a sufficient understanding of the process of their decision-making behavior. Based on the processing resources, consumers or producers’ choices could be affected by different processes: affective process, cognitive process or both affective and cognitive processes simultaneously. Applying a variety of experiment methods, this dissertation investigates how producers and consumers make their choices by exploring how the product attributes, and the characteristics of the decision-maker, affect consumers and producers’ choice-making behaviors. In the first essay, I implemented a discrete choice experiment and estimated random parameter logit models with error component to analyze Chinese consumer willingness to pay (WTP) for domestic and imported beef flank labeled with the new quality grades and other relevant beef labels. Results suggest foreign beef producers could compete most closely with domestic beef if it was labeled as premium quality. In the second essay, I investigate Chinese consumer WTP for beef from different countries and the role of ethnocentrism, country image, and product image on the WTP. Results suggest that foreign beef exporters could promote their beef in China by advertising in accordance with positive country and product images.
In the third essay, I attempt to determine hog farmers’ motivations to adopt genomics for breeding hogs that are more resistant to the disease. In doing so I focus on the impact of their risk preferences and related peer effects that might influence potential adoption. This case study provides implications for local governments and companies trying to promote new technologies.
In the fourth essay, I investigate how social influence affects producers’ behavior under disease outbreak using social network analysis. In particular, I focus on how information flows during an epidemic such as African Swine Fever. Findings provide insights into how information flows and how actors communicate during a situation of crisis. This can be used by stakeholders (1) to disseminate information; and (2) to avoid the spread of rumors and false information.
ContributorsGao, Shijun (Author) / Grebitus, Carola (Thesis advisor) / DeLong, Karen (Committee member) / Schmitz, Troy (Committee member) / Arizona State University (Publisher)
Created2022