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Economic aspects of household recycling behavior and attitudes in City of Bryan are examined to improve solid waste management policies in the city. Using survey data collected by mail and personal interviews, residents’ attitudes towards solid waste management are analyzed, in general, and specifically, the factors influencing recycling behavior examined using logistic regression. In addition, three alternative policies are presented to respondents. First, support for an additional drop-off recycling center (Policy I) is examined. Second, WTP for two different recycling programs, curbside recycling service (Policy II), and curbside recycling with a drop-off recycling center (Policy III), as a function of socio-economic factors thought to influence WTP are computed using contingent valuation method, an indirect valuation tool. Finally, preference for a particular policy among the three alternatives presented to the residents of Bryan is explored. Because of the different data collection modes and assumptions on the bid prices two logit models are estimated to examine recycling behavior, and Policy I and two multinomial logit models for the most preferred policy, whereas four logit models are estimated for Policy II and III. The estimated models are similar both within the Policies and between the Policies in terms of the affects of variables, significance of coefficients, and consistency with previous studies indicating a potential set of factors that can be used to explain WTP for recycling services. Bryan residents that are female, white, employed, have higher incomes, have children, own a house, and are self-perceived environmentalists tend to recycle more. Similarly, males, nonwhites, older respondents, students, non-environmentalists and non-recyclers are more likely to support an additional drop-off center. WTP for Policy II is positively influenced by males, whites, respondents who are employed, low-income respondents, environmentalists, non-recyclers, and those who support Policy I. In comparison, WTP for Policy III is positively influenced by females, whites, respondents who are employed, younger respondents, environmentalists, non-recyclers, and those who support Policy I. In the case of both Policies I and II, the bid price negatively influences WTP as expected. While the WTP for Policy II is slightly higher than the estimated cost of a curbside recycling service ($2.50), the WTP for Policy III is lower than the estimated cost. No consistent pattern emerges across most of the coefficients and the four possible alternatives, three proposed policies and the current situation. However, probabilities computed using the multinomial logit results is the highest for Policy II, followed by either Policy III or no change to the existing solid waste management policy.

The dawn of international banking has already sparked some of the most well known mergers in the financial industry. Following the recent merger waves of the major developed economies, Taiwan¡¦s industry also engages merger and acquisitions to pursue external growth. Firms may merge for various reasons and generates totally different result in shareholder¡¦s wealth. Thus, capture the factors which drive the merger activity is very critical issue to all the participants of Taiwan¡¦s equity market. The objective of this study is to analyze the determents of target selection in the merger and acquisition activity in Taiwan¡¦s financial industry. The subject what the research are going to study and development. There is acquired Cooperative Association what characteristics are owned. Logit regression is utilized to investigate a sample of 12 listed firms which engaged mergers after the government has passed the Financial Merger Institutions Law over the period from 2000 to 2007. Consistent with literature of merger and acquisitions, the empirical result suggests that the firms with weaker debt structure, good loan quality and Capital Adequacy, to become good targets.

The response surface methodology is a useful method to find the optimum response in an experiment. In this work, a new test statistic with only few replicates at the center point for curvature detection is discussed. The performance of the new statistic is investigated through simulation. In the second part of this work, when the response variable is of the proportional type taking only values between 0 and 1, some analysis methods are compared based on the predicted variances on the design region.

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Deposit insurance varies greatly across countries due to each country’s specific environment. The purpose of this study is to find what factors may affect coverage limit in deposit insurance. First, we implement panel data over the period of 1960 to 2008 including 78 countries’ political setting, bank industry’s structural differences and overall economic factors. The empirical results show that countries with lower saving rate, interest spread and government debt tend to have higher coverage. However, coverage tends to be lower in more political open countries. Second, we performed panel data logit model to find that increasing government debt would reduce the probability of increasing coverage limits. Third, the regression of variable changes shows strong negative significance in the relationship of interest spread and coverage over GDP per capita. The main contribution of this thesis is to identify significant influences to the coverage limit. This could provide reference factors when considering the setting of Deposit insurance scheme to insure financial stability.

The ginger industry is one of the key industries identified by the Fiji government in its diversification strategy to accommodate the remnants of the withdrawal of the European Union’s sugar preferences. There is considerable pressure on small industries such as ginger in search of ways in which they can be made to operate efficiently and sustain the economy. Expansion of commercial agriculture into marginal land which is unsustainable adds enormous pressure on land causing soil erosion. Coupled with this is the quality issue which is a serious problem of ginger production and has reduced its competitiveness over the years. This study focuses on two types of losses in ginger production to provide an integrated approach to policy making and computing production losses. One is the observable output loss at the farm site that is not sold due to sub-standard quality related to disease and the other is the unobserved output loss due to inefficient production. The research attempts to answer the question of whether the Fiji ginger farmers are producing efficiently, and at what levels. The relative importance of each input in ginger production is examined. The study undertakes to determine the effects of key variables on farm efficiency. Also examined is the overall farm profiles based on the efficiency rankings of the ginger producers. Furthermore, this research attempts to determine factors that influence soil erosion, and those that influence the observed ginger loss. Using cross-sectional data from a ginger farm survey conducted in June 2007, this research estimates a stochastic production frontier which incorporates soil erosion as an input in the framework. Very few studies have looked at the impact of soil erosion in this context; hence, this study fills the gap by incorporating land quality in the analysis. Farms were found to produce at 69% of their maximum potential output and soil erosion resulted in 6.8% loss in ginger output. This also implies that using the same resources, technology and farming techniques efficiently can lead to a 31% increase in output. While unobserved loss to farm income is a 27% (F$4.6m) increase over the observable loss at farm site, the revenue loss to the whole industry is at least 30% (F$5.07m). Profit was a key determinant of both losses, but staying on farm, slope of land, manure use and hot water treatment affected the observed but not unobserved loss. Although farmer education had no effect on both losses, it was important for undertaking soil conservation. Fiji is in a good position to increase production as education, age and experience of farmers were not significant determinants of efficiency. Thus, displaced farmers from sugar cane farming (given serious concerns of the viability of that industry) can be encouraged to move with ease into ginger as an alternative livelihood. Lastly, the study highlights some practical implication which calls for an integrated package of policies related to use of best farming techniques, land tenure and, agricultural extension and support services for sustainable agricultural growth.

Master of Science / Department of Agricultural Economics / Amanor-Boadu, Vincent / Beans play a major role in addressing malnutrition and poverty in Africa. Hence, several studies have been conducted over the last two decades on beans attributes in various African countries, including Zambia. The similarity of these studies is their emphasis on the importance of including consumer preferences in the beans supply chain. This study attempts to contribute to informing the bean supply chain about bean attributes and consumer characteristics influencing beans consumption so that downstream stakeholders can effectively seize the embedded opportunities in the bean supply chain. Data used in this study were obtained from 900 surveyed households in Lusaka, Zambia and analyzed using a logit model. The study evaluated three attributes of beans: gravy quality; cooking time; and grain size. In addition, it assessed the price of beans associated with these attributes. The study sought to determine how these attributes influenced consumer preference for specific color beans. Results show that gravy quality, cooking time and price are important bean attributes influencing consumer preference for purple, mixed yellow and yellow bean while grain size has no statistically significant effect. The study also found that gender, education, and employment status of the household head or person purchasing food for the household, as well as the household’s child dependency ratio, dual household income, residential area and perception of the bean food group’s importance to consumers’ nutritional security were statistically significant in their effect on preference for purple, mixed yellow and yellow beans. The study’s results contribute to downstream stakeholders’ efforts to improve their own decisions in identifying the market segments to engage in. For example, bean breeders, producers, and traders might optimize limited resources available for their activities by investing in products that promise large markets to use volume to overcome any price disadvantage regarding profitability. Similarly, they may also invest in high-value low volume products that could also provide them with acceptable profitability. The option used would depend on their location and their own resource situation.

Master of Agribusiness / Department of Agricultural Economics / Kevin Dhuyvetter / Many companies use surveys to establish customer satisfaction metrics. This OEM has been using surveys to analyze customer satisfaction with their products, services, and distribution channel for several decades. Satisfaction metrics are established for the brand, product, and channel partners. The product metric is derived from a question on the survey asking customers how satisfied they are with the product. There are subsequent questions thereafter inquiring about satisfaction with specific functional areas of the product. It is common practice to use Partial Least Squares (PLS) regression analysis to evaluate what impacts the functional area questions have on the overall satisfaction question. The model results are used to understand what areas of the machine should be focused on to improve customers’ experiences with the machine. These results are compared to other data sources such as warranty, field reports, customer focus groups, etc. The results from these models are sometimes questioned based on what common intuition would suggest. Typically the top three drivers to the product metric are understandable, but there are often one or two key areas that do not make logical sense. The objective of this thesis was to understand whether PLS modeling is appropriate given the nature of customer survey data. Models were estimated using existing survey data on a specific model in the tractor product line. PLS models assume data are linear with no bounds. This in itself likely makes this type of model inappropriate for analyzing customer survey data. Responses are bounded on an 11 point scale from 0-10, however, the PLS model being non-bounded assumes there can be a score under 0 or over 10. The model also assumes a linear slope that would indicate each covariate answer 0-10 has the same level of effect on the response variable. This research has found that each covariate answer is in fact non-linear. For example, a customer answering a 2 to quality of manufacturing workmanship has a different impact on the overall satisfaction score than a customer who answers 8. Finally, this research discovered that the PLS models produce negative coefficients of significant value that are not reported to the enterprise. Binary and ordered logistic (logit) models were estimated as an alternative to PLS. Logistic models are non-linear and are commonly used to evaluate bounded data. Response data were separated into two groups based on Net Promoter Score (NPS) Methodology (Reicheld 2006). Using the NPS methodology, 0-6 scores are considered detractors, 7-8 scores are considered passives, and 9-10 scores are considered promoters. The logistic models demonstrate that the top two drivers to customer satisfaction scores are still quality of manufacturing workmanship and reliability/operational availability (similar to results of the PLS model). The unresolved problems question on the survey was included in the models and demonstrated that the predicted probability of a customer being a promoter is much higher in both binary and ordered logit models if no unresolved problems exist. Finally, the model found engine oil consumption remained negative and is statistically significant suggesting that even with the alternative modeling approach there still may be data issues related to the survey. It is recommended that the OEM implement logistic modeling for analyzing customer survey data. It is also recommended that a new survey design be constructed to eliminate issues with correlated data that can lead to spurious and unexplainable results.

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