The aim of this thesis is to study the effect of smoking and drinking on wages in Sweden. The data used in this study is the Swedish Level-of-living survey (LNU) from 1991. A multinomial logit model and the marginal effects from the estimated model are used to study the effect of smoking and drinking on wages in Sweden. The empirical results conclude that medium drinking increases the probability of having a high income, i.e. there is a positive significant relationship between medium drinking and wages in Sweden. Also concluded from the empirical results is that there is not a significant relationship between smoking and wages in Sweden.

<p>The aim of this thesis is to study the effect of smoking and drinking on wages in Sweden. The data used in this study is the Swedish Level-of-living survey (LNU) from 1991. A multinomial logit model and the marginal effects from the estimated model are used to study the effect of smoking and drinking on wages in Sweden. The empirical results conclude that medium drinking increases the probability of having a high income, i.e. there is a positive significant relationship between medium drinking and wages in Sweden. Also concluded from the empirical results is that there is not a significant relationship between smoking and wages in Sweden.</p>

Fethiye-G&ouml / cek area is one of the nine coastal Specially Protected Area (SPA) in Turkey. Since mid-80&rsquo / s G&ouml / cek town has developed to be a yachting center, and the bays of G&ouml / cek have acquired a well-earned international fame as a paradise for boating vacations. However, the uncontrolled yachting in this bay area presents a growing pressure on the environment, and the coastal and marine ecosystem. In this thesis a computer model for simulating the movements of yachts in G&ouml / cek Bays is developed. The computer model uses the Multinomial Logit Model (MNL) to find the probabilities for the boaters to select the next bay to visit. The model predicts the number of boats in each bay at the end of a day, the number of boats visited each bay during the day and the distribution of boater categories among the bays throughout the simulation time. In order to get the data needed for the inputs, a questionnaire was formed, and a detailed survey was carried out in G&ouml / cek Bays. In addition to the questionnaires, the number of the boats anchored were also observed in the field studies. The model is applied to the G&ouml / cek Bays and the results obtained are compared with the data obtained in the field. In the following years, the yacht movements and distributions at various anchor locations can be predicted with this model. These predictions will be useful in a future management plan that aims to control of yacht movement and anchoring.

Reflecting the growing interest from both consumers and policymakers, and building on recent developments in Willingness to Pay (WTP) methodologies, we evaluate consumer preferences for an archetypal traditional food product. Specifically we draw on stated preference data from a discrete choice experiment, considering the traditional Hungarian mangalitza salami. A WTP space specification of the generalized multinomial logit model is employed, which accounts for not only heterogeneity in preferences but also differences in the scale of the idiosyncratic error term. Results indicate that traditional food products can command a substantial premium, albeit contingent on effective quality certification, authentic product composition and effective choice of retail outlet. Promising consumer segments and policy implications are identified. (authors' abstract)

E-Commerce research shows that existing studies on online consumer choice behavior has focused on comparative studies of channel or store choice (online or offline), or online store choice (different e-tailers). Relatively less effort has been devoted to consumers’ online brand choice behavior within a single e-tailer. The goal of this research is to model online brand choice, including generating loyalty variables, setting up base model, and exploring the effects of Internet-specific attributes, i.e., order delivery, webpage display and order confirmation, on online brand choice at the SKU level. Specifically, this research adopts the Multinomial Logit Model (MNL) as the estimation methods. To minimize the model bias, the refined smoothing constants for loyalty variables (brand loyalty, size loyalty, and SKU loyalty) are generated using the Nonlinear Estimation Algorithm (NEA). The findings suggest that SKU loyalty is a better predictor of online brand choice than brand loyalty and size loyalty. While webpage display has little effect on the brand choice, order delivery has positive effect on the choice. Online order confirmation turns out to be helpful in choice estimation. Moreover, online consumers are not sensitive to net price of the alternatives, but quite sensitive to price promotion. These results have meaningful implications for marketing promotions in the online environment and suggestions for future research.

The transportation sector is considered one of the major contributors to greenhouse gas (GHG) emissions in metropolitan areas, and any efforts to reduce these emissions requires strategic management of multiple transportation modes. This paper presents a method to identify opportunities to reduce GHG emissions by expanding commuter bus services and incentives to shift commuters from private cars to transit. The approach uses a nested multinomial logit model for mode choice in a region that includes driving alone, carpooling, walking, cycling, and using four possible transit modes (ferry, commuter rail, rapid transit and bus) by walk access or driving access. A model of existing conditions was calibrated with data from the Boston metropolitan area. Using an emission factor model based on average speeds from the California Air Resources Board (CARB), the net effect of new commuter bus service on GHG emissions from transportation was estimated. Potential GHG reductions are weighed against the capital and operating costs of new transit services to quantify the cost-effectiveness of a new commuter bus service for isolated origin-destination pairs. This modeling framework is used to optimize fares and bus frequency in order to identify the corridors with the most cost-effective potential for GHG reduction. Results are presented for the Boston region, demonstrating the feasibility of implementation and the potential magnitude of benefits for cost-effectively reducing GHG emissions associated with transportation. The method is general and can be applied in other cities around the world.

個體選擇模式(discrete choice model)廣泛應用於國外的交通運輸及行銷領域，而國內交通運輸領域，也長期以此模式分析個體的運具選擇行為。反觀國內的行銷領域，因較難取得消費者的商品品牌購買紀錄，而鮮少應用個體選擇模式分析消費者的選擇行為。有鑒於此，本研究嘗試以問卷收集消費者對三個洗髮精品牌的選擇行為，以個體選擇模式中的多項邏輯模式(multinomial logit model)、巢狀邏輯模式(nested multinomial logit model)、混合多項邏輯模式(mixed logit model)進行分析，檢驗問卷設計中的促銷活動、消費者特性對選擇行為的影響性。 實證分析的結果發現，洗髮精的原價格及促銷折扣、贈品容量、加量不加價等促銷活動，皆對消費者的選擇行為有顯著的影響力，其中促銷折扣與贈品容量影響的程度較大，是較具有效果的促銷活動。而消費者的性別、年齡、職業及品牌更換的頻率，皆影響洗髮精的選擇行為。此外，消費者若固定選擇自己最常購買的洗髮精，此類型的消費者與其他人的品牌選擇行為，也有顯著的不同。 此外，根據本研究樣本，我們也發現海倫仙度絲與潘婷間的替代、互補性較強。 / Discrete choice model has been demonstrated to be a useful tool for analyzing consumers’ choice behavior data in the area of transportation and marketing research. However, since a complete data set containing consumers’ history of purchase behavior was rarely available to public, the model was less popular in the marketing research area than in the transportation research in Taiwan. Based on limited survey data on consumers’ choice among three different brands of shampoo, we applied multinomial logit model、nested multinomial logit model、mixed logit model in this study to understand promotion program’s effect on consumers’ choice behavior , the result showed that shampoos’ original price、discount、volume of hair conditioner bestowal、more volume with the same price all had significant impacts on consumers’ choice behavior, among them, discount and volume of hair conditioner bestowel influenced more .In addition, consumers’ gender、age、occupation and frequency of changing brands also affected consumers on choosing brands of shampoos. The study also found that a consumer who chose the same brand regularly behaved notably differently.

Vehicle ownership and utilization have a profound influence on activity-travel patterns of individuals, vehicle emissions, fuel consumption, highway capacity, congestion and traffic safety. The influence could be further skewed by the diversity of the vehicle fleet. This thesis presents a detailed analysis of the 2001 National Household Travel Survey data to understand the vehicle ownership patterns, fleet mix, allocation and utilization in the context of household and person socio-demographic characteristics. Along with a rich descriptive analysis, models of vehicle ownership and utilization are estimated to distinguish four vehicle types; cars, SUVs (sport utility vehicles), vans and pickup trucks based on their ownership by households and utilization patterns by household members. The primary driver level vehicle utilization analysis provides insights into the extent of allocation of a vehicle to a single person. In addition to confirming many perceptions about the ownership, acquisition and utilization patterns of different types of vehicles, this analysis brings out some subtle differences and similarities among the vehicle types. The analysis results indicate a greater propensity to acquire and use larger vehicles such as minivans, sports utility vehicles and pickup trucks among certain socio-demographic segments of population. Increased ownership and use of vans and SUVs, and their usage as personal vehicles rather than just work vehicles warrants a need to revise vehicle type specific policies, transportation planning and control measures.

[pt] A escolha do modo de transporte de carga é uma questão crítica na modelagem da demanda por transporte. Este estudo utiliza a técnica de preferência declarada no sentido de analisar o transporte de carga no Estado do Rio de Janeiro, visando identificar quais são os fatores relevantes na escolha de modo de transporte (rodovia e ferrovia) por parte das empresas com atuação no Estado, na categoria de produtos de Carga Geral. O estudo utilizou o modelo Logit Multinominal com o objetivo de verificar a importância de fatores (custo, tempo, serviço, confiabilidade, disponibilidade e risco de roubo de carga) na escolha de modo por parte das empresas, e apontar quais medidas que podem ser adotadas no sentido de fomentar a multimodalidade no transporte de carga no Estado do Rio de Janeiro. / [en] Freight mode choice is a critical part in modeling freight demand. This study uses the stated preference techniques to analyze cargo transportation in the State of Rio de Janeiro, aiming to identify the relevant factors in the mode choice (road and railroad) by companies operating in the State in the category of General Cargo products. The study used the Multinominal Logit model in order to verify the importance of factors (cost, time, service, reliability, availability and cargo theft risk) in the mode choice by the companies, and to indicate which measures may be adopted to promote multimodality in freight transport in the State of Rio de Janeiro.

The multinomial logit model (MNL) possesses a latent variable representation in terms of random variables following a multivariate logistic distribution. Based on multivariate finite mixture approximations of the multivariate logistic distribution, various data-augmented Metropolis-Hastings algorithms are developed for a Bayesian inference of the MNL model.