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On-Demand Mobility (ODM) is a concept to address congestion problems. Using electric aircraft and vertical take-off with limited landing (VTOL) capabilities, the ODM concept offers on demand transportation service between designated landing sites at a fraction of driving time. The purpose of this research is to estimate the potential ODM demand and understand the challenges of introducing ODM using the Northern California region (including major cities like San Francisco, Sacramento, and San Jose) as an area of study and a second, less rigorous analysis for the Washington-Baltimore region. A conditional logit model was developed to estimate mode choice behavior and to estimate ODM demand; presenting automobile and public transportation as the two competing modes to ODM. There are significant challenges associated with the service including ability to operate in bad weather, vehicle operating cost, siting and cost of landing sites, and overall public acceptance of small, remotely operated aircraft. Nine scenarios were run varying the input for a base fare, landing fare, cost per-passenger-mile, auto operational costs, and ingress (waiting) times. The results yielded sensitivity of demand to all these parameters and especially showed a great difference in demand when auto costs were decreased from the standard American Automobile Association (AAA) cost per mile to a likely, future auto operating cost. The challenge that aerospace engineers face is designing an aircraft capable of achieving lower operational costs. The results showed that in order for the ODM to be a competitive mode, the cost per passenger-mile should be kept at $1. / Master of Science

Metropolitan planning organizations (MPOs) have become increasingly interested in incorporating land use patterns and design ideas into transportation problems. Many design ideas under the umbrella of the New Urbanism; yet in practice they hardly get fully implemented in the standard transportation planning procedures. This research intends to contribute to the continuing debate on land use pattern-travel connection by adding further empirical evidence from the Austin, TX region. Also, it demonstrates ways to integrate land use patterns in transportation demand analysis. The study identifies 42 mixed use districts (MXD) in the Austin region and analyzes the following aspects of travel behavior in MXDs and non-MXDs: production trip rates, frequency of produced trips, network trip length, internal rate of capture, and person-miles of travel (PMT). The study contributes to transportation planning and policy making in Central Texas by providing local empirical evidence on urban form-travel connection. The study’s method and process can be of interest to a broad audience in academia and practice. / text

In this paper we first show that the gains achievable by integrating pricing and inventory control are usually small for classical demand functions. We then introduce reference price models and demonstrate that for this class of demand functions the benefits of integration with inventory control are substantially increased due to the price dynamics. We also provide some analytical results for this more complex model. We thus conclude that integrated pricing/inventory models could repeat the success of revenue management in practice if reference price effects are included in the demand model and the properties of this new model are better understood. (authors' abstract)

The historical underinvestment in power infrastructure and the poor performance of power delivery has resulted in extensive and regular power shortages in Nigeria. As Nigeria aims to bridge its power supply gap, the recent deregulation of its electricity market has seen the privatisation of its generation and distribution companies. Ambitious plans have also been put in place to expand the transmission network and the total power generation capacity. However, these plans have been developed with essentially arbitrary estimates for prevailing demand levels as the network and generation limits mean actual demand cannot be measured directly due to a programme of almost constant load shedding; the managed and intermittent distribution of inadequate energy allocation from the system operator. Network expansion planning and system reliability analysis require time series demand data to assess generation adequacy and to evaluate the impact of daily and seasonal influences on the energy supply-demand balance. To facilitate such analysis this thesis describes efforts to develop a credible time series electricity demand model for Nigeria. The focus of the approach has been to develop a fundamental bottom-up model of individual households accounting for a range of dwelling characteristics, socioeconomic factors, appliance use and household activities. A householder survey was conducted to provide essential inputs to allow a portfolio of household demand models which can account for weather-dependence and other factors. A range of national and regional socioeconomic and weather datasets have been employed to create a regionally disaggregated time series demand model. The generated demand estimates are validated against metered data obtained from Nigeria. The value of the approach is highlighted by using the model to investigate the potential for future load growth as well as analyse the impact of renewable energy generation on the Nigerian grid.

空氣污染防制費自民國84年7月1日開徵，希望能藉由空污費的徵收來減少污染的排放量，同時能透過空氣污染防制費的有效運用來改善空氣品質，而本文僅針對空氣污染防制迄今，對家計部門所產生的清潔效益進行估算。 首先，利用家計部門生產函數建立理論模型，接著以錢玉蘭、蕭代基(1996)，「台灣大都會地區改善空氣品質之經濟效益評估與酸雨風險認知調查」的問卷調查資料為樣本，對超對數及近似理想需求函數的實證模型進行配適比較。結果顯示：近似理想需求函數配適之判定係數較高，符合加總性、齊次性及對稱性限制條件，而價格變數與屬性變數之估計結果亦相當合理，因此，推論近似理想需求函數為解釋台灣清潔需求型態的較適模型。 由近似理想需求函數所推估之85及86會計年度空污費執行所帶來台灣地區家戶清潔效益分別為每戶2101元及651元，加總每戶效益後，台灣地區總清潔效益分別為128億元及39億元，與空污費實際執行的歲出相較，推論空污費執行迄今之效益大於成本。並由推算之各都會地區補償變量性質，建議政府以效率的觀點使用空氣污染防制費時，應將防制資源優先使用於改善都市化程度愈高，人口數愈多，污染程度愈嚴重地區的空氣品質。 / The Environmental Protection Agency of Taiwan launched the Air Pollution Emission Fees Program to levy emission fees on petroleum products, July 1, 1995. The purpose of such a program is to provide economic incentives to change peoples' behavior towards the consumption of fuels and to collect fees to be used for the improvement of air quahty. The objective of this study is to evaluate the effect of the emission fees program on household cleanness. In order to achieve this objective, we first employ a household production function in accordance with the theory of consumption behavior. Two models are utilized in this study, i.e., the translog firnction model and the almost ideal demand function model. We utilize cross-section data to fit into these models and find that the almost ideal demand model has more significant explanatory power. Therefore, we infer that this model is a better functional form for expressing the cleanness behavior of Taiwan's households. The estimated results of the total benefits for household cleanness resulting from the implementation of air pollution emission fees are NT$12.8 and NT$3.9 bilhon for the accounting years of 1996 and 1997, respectively. By comparing expenditure from the air pollution fees, which were designated for the purpose of improving air quality, i.e., NT$4.2 and NTS3.3 billion for the respective years 1996 and 1997, we can see that the pollution control program is conformable with the benefit-cost principle. Finally, based on the empirical results, pohcy recommendations are presented in the conclusion.

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Doctor of Philosophy / Department of Economics / Philip G. Gayle / This dissertation is composed of two essays in the field of Industrial Organization. Specifically, the empirical studies are conducted by focusing on the market structure and competition issues in the airline industry. The first essay investigates entry deterrence through incumbents’ pricing strategies in the airline industry. Recent research finds evidence that incumbent airlines tend to cut fares in response to the “threat” of entry by Southwest Airlines. Instead of focusing on the entry threat by a single carrier, this essay re-examines this issue by looking at incumbent airlines’ price response when entry is threatened by a wider variety of potential entrant airlines. Results show that incumbents’ response vary by the identity of the firm making the threat. As expected, incumbents cut fares in response to the threat of entry by some potential entrants; however, a new result is also found that incumbents may respond by raising their fare depending on who is making the threat. The second essay looks into an antitrust-relevant issue in the airline industry. Proper antitrust analysis often focuses on whether the concerned differentiated products are truly competing with each other. This essay uses a structural econometric model to investigate whether nonstop and connecting air travel products effectively compete with each other. Estimate results suggest that connecting products may be an attractive alternative to nonstop products for leisure travelers but less so for business travelers. If connecting products are counterfactually eliminated, the empirical model predicts small price changes for nonstop products. This suggests that the two product types only weakly compete with each other and can be treated as being in separate product markets for antitrust purposes.

No presente trabalho, é analisado o comportamento da demanda por transporte coletivo em quatro cidades de porte médio do interior do Estado de São Paulo (Araraquara, São Carlos, Jaú e São José do Rio Preto), visando a identificar os principais fatores que afetam o volume de passageiros, como: população, valor da tarifa, índice de motorização total e desagregada (automóveis e motocicletas), quantidade de empregos formais, produto interno bruto (PIB) per capita, etc. As análises efetuadas mostram que a demanda total por transporte coletivo urbano é influenciada principalmente pelas seguintes variáveis sócio-econômicas: população, índice de motorização e PIB per capita. Outros fatores que também influenciam são: tamanho da cidade, qualidade do transporte coletivo, cultura de utilização da bicicleta, etc.. São desenvolvidos dois modelos matemáticos simples, utilizando a técnica de regressão linear múltipla, que estabelecem relação entre a demanda por transporte coletivo e as principais variáveis sócio-econômicas que a afetam, como ferramenta para a previsão da demanda em diferentes cenários conformados pelas variáveis sócio-econômicas. Os resultados apresentados pelo modelo matemático que utiliza como índice de motorização, a relação entre a frota de veículos de duas rodas e a população refletem de maneira mais próxima a realidade que o modelo que utiliza a frota total. Este modelo é adequado para ser utilizado na previsão da demanda por transporte coletivo no universo das quatro cidades analisadas com erro máximo menor que 10%. / In this paper we analyzed the behavior of demand for public transportation in four mid-sized cities in the state of São Paulo (Araraquara, São Carlos, Jau and Sao Jose do Rio Preto), to identify key factors affecting the volume of passengers, such as population, amount of fare, motorization rate and total breakdown (automobiles and motorcycles), amount of formal employment, gross domestic product (GDP) per capita, etc. In general, the following conclusions can be inferred from the analysis performed: the total demand for transportation in a city depends mainly on the following parameters: population, motorization rate and GDP per capita. Other indirect factors such as quality public transport, culture, use of transport, etc. They also developed two simple mathematical models using multiple linear regression technique with the objective of establishing relations between the demand for public transportation and the following key social-economic variables that were identified as those that most influence the demand: population, motorization rate and GDP per capita, which is useful for predicting the demand for public transport in different scenarios conformed by social-economic variables. The results presented by the mathematical model show that uses such as motorization rate, the relation between the fleet of two-wheeled vehicles and the population, more closely reflect the reality that the model uses the total fleet. The model uses the rate of motorization in considering two vehicles suitable for use in forecasting demand for public transportation in the universe of the four cities analyzed maximum error <10%.