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.

Different types of business incubators have been established worldwide in the last decade. As the latest generation of incubation models, the accelerator provides a mix of services including mentorship, office space, access to the latest technology and a network of investors, with an aim to help ventures survive in the market. Meanwhile, startups are important to the society because they help balance the labor market and make contributions to the economic growth. The aim of this paper is to find the factors which best predict the success of new ventures based on characteristics of entrepreneurs and ventures. This research utilizes a case study of TechStars Accelerator and includes 640 startups from all industries and geographical regions which participated in the programs between 2007 and 2015. The analysis employs two statistical models, namely the Logit Model and the Ordinary Least Squares (OLS) Model. This study finds that technology intensive ventures founded by a team of entrepreneurs are more likely to succeed. Also, other variables such as the amount of funding, previous industry experience and location have a positive effect on the success of accelerator backed startups.

No description available.

The purpose of this thesis was to evaluate the impact of dynamic message signs (DMS) on the Orlando-Orange County Expressway Authority (OOCEA) toll road network using the Pre-Deployment DMS Survey (henceforth referred to as "pre-deployment survey"). DMS are electronic traffic signs used on roadways to give travelers information about travel times, traffic congestion, accidents, disabled vehicles, AMBER alerts, and special events. The particular DMS referred to in this study are large rectangular signs installed over the travel lanes and these are not the portable trailer mount signs. The OOCEA is currently in the process of adding several fixed DMS on their toll road network. Between January 2007 and February 2008, approximately 30 DMS are planned on their network. It is important to note that there was one DMS sign on the OOCEA network before this study started. Since most of the travelers on OOCEA toll roads are from Orange, Osceola and Seminole counties, this study is limited to these counties. This thesis documents the results of pre-deployment analysis. The instrument used to analyze the travelers' perception of DMS was a survey that utilized computer aided telephone interviews. The pre-deployment survey was conducted during early November of 2006. Questions pertaining to the acknowledgement of DMS on the OOCEA toll roads, satisfaction with travel information provided on the network, formatting of the messages, satisfaction with different types of messages, diversion questions (Revealed and Stated preferences), and classification/socioeconomic questions (such as age, education, most used toll road, and county of residence) were asked to the respondents. The results of the pre-deployment analysis showed that 54.4% of the OOCEA travelers recalled seeing DMS on the network. The respondents commonly agreed that the DMS are helpful for providing information about hazardous conditions, and that the DMS are easy to read. The majority of the travelers preferred DMS formats as a steady message for normal traffic conditions, and use of commonly recognized abbreviations such as I-Drive for International Drive. The results from the binary logit model for "satisfaction with travel information provided on OOCEA toll road network" display the significant variables that explain the likelihood of the traveler being satisfied. The results from the coefficients show that infrequent travelers are more likely to be satisfied with traveler information on OOCEA toll roads. In addition, the provision of hazard warnings, special event information, and accuracy of information on DMS are associated with higher levels of satisfaction with traveler information. The binary logit model for "Revealed Preference (RP)" diversion behavior showed that Seminole County travelers were likely to stay on the toll road, and SR 408 travelers were likely to divert off the toll road. The travelers who acknowledged DMS on the OOCEA network were also likely to divert off the toll road, but those who learned of the congestion by DMS were likely to stay on the toll road. Learning of congestion by DMS could encourage travelers to stay, since when they are on the toll roads, diversion at times could be difficult with no access to exits or little knowledge of alternate routes. But it is also possible that travelers stayed because their perception was that the toll roads are faster, especially when messages on DMS show travel times that confirm the travelers' belief. Travelers who were not satisfied with travel information on the network were more likely to divert off the toll road. The implications for implementation of these results are discussed in this thesis. DMS should be formatted as a steady message for normal traffic conditions. Commonly recognized abbreviations, such as I-Drive for International Drive, must be used for roadway identification when possible. DMS messages should be pertained to information on roadway hazards when necessary because it was found that travelers find it important to be informed on events that are related to their personal safety. Accuracy of information provided on DMS was important for traveler information satisfaction because if the travelers observe inaccurate travel times on DMS, they may not trust the validity of future messages. DMS information that led to the travelers canceling their intended stops led to a higher likelihood of them being dissatisfied with traveler information. It is important to meet the travelers' preferences and concerns for DMS.

No description available.

In September 2002, the Canadian Institute of Health Information, Health Canada and the National Task Force on Health Information created the Canadian Community Health Survey (CCHS) whose objective was to determine the status of the Canadian health care system and the health status of Canadians themselves. The CCHS was divided into two cycles (Cycle 1.1 and Cycle 1.2) of which CCHS Cycle 1.1 was general population health survey designed to provide information for 136 health regions covering all provinces and territories. For this particular report, data from Cycle 1.1 was analyzed in order to determine if Work stress, Type of Smoker, Body Mass Index (BMI) and Household Income were significant factors contributing to the general health of the population of Ontario. Each of the above mentioned variables was considered individually for a given age, gender and marital status of the respondents. Logistic Stepwise Regression was used to determine if these variables were significant predictors of general health and all the possible two way interactions were explored at the five percent level. Furthermore, a diagnostic check of the fitted models was conducted and the validity of the models was assessed once again after removing the influential points. In addition, the linearity of all the continuous variables was tested in the logit models followed by a comparison of the fitted models using weights. Overall, it was found that all of the potential predictor variables of concern were significant predictors of general health. The majority of two way interaction terms were included in the fitted models, however, the overall fit of some models was found to be poor. In some cases, upon removing the influential points, the overall fit improved significantly, while for others, the fit did not improve by much. Also, it was found that Household Income and Work stress were not linear in the logit model while Age was found to be linear. Upon comparing models with and without sampling weights, it was found that the model that included sampling weights consisted of the same main effects as the model without sampling weights, along with additional interaction terms which were not present earlier. KEY WORDS: CCHS, Sampling Weights, Logit Models, Fitted Models, Interactions, Stepwise Regression / Thesis / Master of Science (MS)

No / The existing empirical literature on foreign direct investment (FDI) entry strategies tends to allow a binary choice between wholly owned enterprises (WOEs) and equity joint ventures (EJVs) or between greenfield investment and acquisition only. The current study specifies a multinomial logit model for the choice from all four FDI entry modes in China. Five hypotheses are developed based on transaction cost economics and tested on a data set covering 10,607 foreign investment projects in China. A foreign investor seems to prefer the WOE mode given its large investment commitment, a high level of the host country's experience in attracting FDI, a good specific industrial location, and a high asset intensity in the host industry. If the conditions of host country experience and good specific location are not met, the EJV and the joint stock company (JSC) modes seem to be of greater use. A good specific location also makes the contractual joint venture (CJV) a preferable entry mode. Compared with overseas Chinese investors from Hong Kong, Macao, and Taiwan, other foreign investors prefer EJVs over WOEs and CJVs. The results have important implications for managers.

Establishing wetland gains and losses, delineating wetland boundaries, and determining their vegetative composition are major challenges that can be improved through remote sensing studies. In this study, we used the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) to separate wetlands from uplands in a study of 870 locations on the Virginia Coastal Plain. We used the first five bands from each of two ASTER scenes (6 March 2005 and 16 October 2005), covering the visible to the short-wave infrared region (0.52-2.185υm). We included GIS data layers for soil survey, topography, and presence or absence of water in a logistic regression model that predicted the location of over 78% of the wetlands. While this was slightly less accurate (78% vs. 86%) than current National Wetland Inventory (NWI) aerial photo interpretation procedures of locating wetlands, satellite imagery analysis holds great promise for speeding wetland mapping, lowering costs, and improving update frequency. To estimate wetland vegetation composition classs of the study locations, we generated a Classification and Regression Tree (CART) model and a Multinomial Logistic Regression (logit) model, and compared their accuracy in separating woody wetlands, emergent wetlands and open water. The overall accuracy of the CART model was 73.3%, while the overall accuracy of the logit model was 76.7%. Although the CART producer's accuracy (correct category classification) of the emergent wetlands was higher than the accuracy from the multinomial logit (57.1% vs. 40.7%), we obtained the opposite result for the woody wetland category (68.7% vs. 52.6%). A McNemar test between the two models and NWI maps showed that their accuracies were not statistically different. We conducted a sub-pixel analysis of the ASTER images to establish canopy cover of forested wetlands. The canopy cover ranged from 0 to 225 m2. We used visble-near-infrared ASTER bands, Delta Normalized Difference Vegetation Index, and a Tasselled Cap transformation in an ordinary linear regression (OLS) model. The model achieved an adjusted-R2 of 0.69 and an RMSE of 2.73% when the canopy cover is less than 16%. For higher canopy cover values, the adjusted-R2 was 0.4 and the RMSE was19.79%. Taken together, these findings suggest that satellite remote sensing, in concert with other spatial data, has strong potential for mapping both wetland presence and type. / Ph. D.

The number of elderly is increasing; to meet their transportation needs, it is important to clearly understand their travel patterns and preferences. Since travel patterns and preferences depend on socio-demographic and other factors, it is essential to identify these factors first to understand the travel behavior of the elderly. The main purpose of this thesis is to analyze the travel patterns and preferences of the elderly age 65 and above using 2009 National Household Travel Survey (NHTS) data. This thesis presents a detailed descriptive analysis of 2009 NHTS data to understand the travel patterns of the elderly. Along with a descriptive analysis, a multinomial logit model and a mixed- multinomial logit model are estimated to explore the factors associated with the overall travel preferences of the elderly and to identify individuals among the elderly who are the least mobile and at risk for social isolation. The analysis results indicate the differences in the trip characteristics between the elderly and non-elderly. Variation is found even among the different groups of the elderly. The model estimation results show the presence of different travel preferences among the elderly and identify those individuals among the elderly who are immobile for longer periods (e.g., a week) and at risk for social isolation. Elderly individuals with different travel preferences should be considered separately in research to determine the appropriate outcomes that can help transportation planners and policy makers improve planning and policy related to elderly individuals.