Yes / Although social innovation can help multinational enterprise (MNE) subsidiaries create social value for developing countries, they often encounter significant challenges in successfully implementing social innovation projects. This research applies the knowledge-based perspective to propose and test a theoretical framework to explain why MNE subsidiaries differ in their ability to pursue social innovation successfully in a developing country. The framework contends that MNEs’ relationship learning contributes to social innovation variability under varying levels of subsidiary autonomy and mode of entry. Analysis of primary data collected from 207 subsidiaries of MNEs operating in Ghana shows that relationship learning has a positive relationship with social innovation. Further analysis reveals that subsidiary autonomy enhances the positive association between relationship learning and social innovation, and that this moderating effect is stronger for subsidiaries with equity entry mode as opposed to non-equity entry mode. These insights advance the limited understanding of the antecedents of MNEs’ social innovation in developing countries and offer guidance on how MNE subsidiaries can successfully pursue social innovation interventions in a developing country. / The full-text of this article will be released for public view at the end of the twelve month publisher embargo.

The financial and environmental effects of traffic congestion and automobile-centric air pollution continue to be problems that must be addressed within the United States. In response, travel demand management (TDM) has emerged as a potential way to reduce automobile-based travel in order to minimize these effects. TDM strategies are highly dependent on specific urban form characteristics such as bicycle lanes, sidewalks, or transit facilities. A current gap exists in the analytical tools available to transportation planners when evaluating TDM projects. The standard transportation models do not take into account urban form characteristics in a systematic way. These characteristics play an import role in an individual's selection of walking, bicycling, or transit based travel modes. This gap needs to be filled in order to evaluate TDM projects with the same decision-making rigor that is applied to road expansion projects. The purpose of this project is to develop an enhanced transportation mode choice model that presents a systematic approach for incorporating urban form characteristics. This approach determines which elements of urban form have the strongest influence on transportation mode choice behavior. This work is being done in conjunction with the Roanoke Valley Allegheny Metropolitan Planning Organization as a way to evaluate the potential of TDM projects in promoting non-automobile forms of travel within the Roanoke region. This approach to developing an enhanced transportation mode choice model is a step forward in address the gap between TDM strategies and the tools needed to evaluate them. / Master of Urban and Regional Planning

Artificial intelligence techniques have produced excellent results in many diverse fields of engineering. Techniques such as neural networks and fuzzy systems have found their way into transportation engineering. In recent years, neural networks are being used instead of regression techniques for travel demand forecasting purposes. The basic reason lies in the fact that neural networks are able to capture complex relationships and learn from examples and also able to adapt when new data become available. The primary goal of this thesis is to develop mode choice models using artificial neural networks and compare the results with traditional mode choice models like the multinomial logit model and linear regression method. The data used for this modeling is extracted from the American Travel Survey data. Data mining procedures like clustering are used to process the extracted data. The results of three models are compared based on residuals and error criteria. It is found that neural network approach produces the best results for the chosen set of explanatory variables. The possible reasons for such results are identified and explained to the extent possible. The three major objectives of this thesis are to: present an approach to handle the data from a survey database, address the mode choice problem using artificial neural networks, and compare the results of this approach with the results of traditional models vis-à-vis logit model and linear regression approach. The results of this research work should encourage more transportation researchers and professionals to consider artificial intelligence tools for solving transportation planning problems. / Master of Science

The aim of this research was to construct a freight mode choice model, from the perspective of New Zealand freight shippers, identifying the possibility of mode substitution effects. Shipper’s freight modal choice depends on freight demand and infrastructure as well as the quality of service characteristics of alternative modes, such as transport cost, delivery time, reliability, damage and loss and frequency of service. Freight logistics characteristics, such as the attributes of the shipper, the attributes of the commodities to be transported, and the spatial attributes of shipments, strongly influence modal choice. In New Zealand, due to the heterogeneity of firms and issues of confidentiality and reliability of data, relatively little research has been done on modelling freight mode choice. This research involved revealed preference (RP) and stated preference (SP) surveys of representative freight shippers and agents. User-specific data make it possible to better identify the dependence between shipper’s mode shift behaviour and freight logistics in New Zealand circumstances. Moreover, by applying a discrete choice approach, the possibility of mode substitution effects was investigated. This research approach was prompted by substantial changes in New Zealand’s freight transport patterns due to the increasing use of logistic processes, and previously developed models using a four-stage approach fail to model elements of firms’ characteristics (i.e. size of shipments, delivery distance, export volume, product shelf-life, size and location of firm, number of road fleets, and relationship with contracted carriers). The outcomes of this research have shown that many of the operational and logistical influences that affect mode choice vary with the shipper and the industry. As a result, public policy makers should recognize that effective policy must consider both the needs of the transportation service provider and user. In particular, the public policy maker should recognize that freight transport mode choice results from an array of interactions among transportation characteristics, logistics characteristics and product characteristics.

Millions of children travel to and from school each day as part of their daily routine. A large percentage of children make this journey by car, and the numbers are steadily rising and this is leading to many environmental and health implications for children. The current economic climate has persuaded the British Government to look again at policies relating to all school travel funding to highlight areas where savings and cuts can be made. This is interesting because the home-to-school transport provision policy has been in place since the Education Act 1944 and this policy costs local authorities in England over £1 billion a year. Therefore, the focus of this thesis is threefold. Firstly, it seeks to determine the main issues within school travel and reports on the views of current professionals in the school travel industry. Structured in-depth interviews were carried out with 16 UK and US school travel experts. The questions focused on the current stakeholders of school travel, issues regarding school travel, bus use in school travel, and the challenges faced by transport planners to ensure school pupils have a safe and pleasant journey to school. Secondly this thesis quantifies the traffic and environmental impacts of the school choice policy in England. It achieves this by analysing School Census data from 2009 from the Department for Education. Multinomial logit modelling and mixed multinomial logit modelling are used to illustrate the current travel behaviour of English children in their journey to school and examine how there can be a significant reduction in vehicle miles travelled, CO2 emissions and fuel consumption if the school choice policy is removed. The results suggest that if all children attended their nearest school, this would result in reductions in their personal mobility, vehicle miles travelled and CO2 emissions. Finally, this thesis examines the policies relating to the funding criteria of home-to-school public school transport provision. Specifically, the paper employs a multilevel modelling technique to develop a series of relationships between bus usage by school and the level of spending by local education authorities on home-to-school bus travel provision while controlling for other factors such as school quality, land-use patterns and various proxies for household incomes. The results suggest that there is a significant effect of funding on the total school-level bus passenger mileage for primary (aged less than 11), secondary (aged 11 to 16) and Post 16 schools.

The carhops and drive-ins of the 1950s are symbolic of the freedom that the automobile has granted Americans. What the general public has gained from the automobile, however, may come at the expense of independent mobility and choices for today's adolescents, particularly those not yet old enough to drive or those from lower income families. Sprawl land use development patterns and limited transportation choices in most American cities often hold teenagers and their chauffeuring parents captive to the automobile. At the same time, information and communication technology is fast evolving and changing the ways in which teenagers live, interact, and communicate with others; easier transportation coordination is one potential outcome. This study seeks to examine teenagers' travel behavior for their most common destination ' going to and from school ' and how the use of technology influences this behavior. Survey data from five high schools, three in Northern California and two in Vermont, are used to identify the mode choice to and from school, socio-demographic characteristics, and technology use of the sampled teenagers. The built environment of the teenagers' home surroundings is determined by data obtained from the 2010 Census. Logistic regression analysis is used to describe the most significant variables influencing both mode choice to and from school, and the factors associated with the use of technology. Those variables with a family income component, such as high family education, access to a car and smartphone ownership have a positive effect on teenagers driving more to and from school. Similarly, those teens who travel longer distances depend more on rides and choose active modes of transportation than teens living in more populated neighborhoods. When it comes to technology use for transportation among teenagers, those living farther away from school, in worse connected neighborhoods are more likely to depend more on technology for arranging transportation, whereas those teens who choose active transportation modes to school depend less on. High density development policies seem the right recommendation to ensure teenagers choose active transportation alternatives to school and depend less on their parents, family, and friends to move around. Due to the strong influence of attitudes in teenagers' behavior, social education and culture adaptation programs could be suggested to encourage teens to become more confident on active transportation modes, as well as promote safe routes to school for both genders.

A utilização majoritária da malha ferroviária brasileira para o transporte de cargas e a sua incompatibilidade para desenvolvimento de altas velocidades inviabiliza a oferta de serviços competitivos para o transporte intermunicipal de passageiros. A questão explorada nesta tese é sobre qual tecnologia ferroviária provê melhores resultados socioeconômicos no contexto de uma nova rede para o transporte intermunicipal de passageiros com operação exclusiva de Trens de Alto Desempenho (High Performance Trains - HPTs) ou Trens de Alta Velocidade (High Speed Trains - HSTs), caracterizados por velocidades médias de 150 km/h e 300 km/h respectivamente. Nesse sentido, a hipótese é que a diferença entre benefícios e custos socioeconômicos da oferta de serviços de HSTs resultam em valores positivos e maiores do que aquelas decorrentes da operação de HPTs, mediante parâmetros específicos de avaliação socioeconômica e uma configuração hipotética de rede na Região Sudeste do Brasil. Assim, o objetivo principal da tese é estimar e comparar os custos e benefícios socioeconômicos de uma rede ferroviária pela estimativa dos investimentos para a construção de novos traçados ferroviários, estimativa do número de viagens intermunicipais na Região Sudeste em um horizonte de planejamento estratégico e a propensão à escolha modal, estabelecimento de uma formulação de Análise Custo-Benefício (Cost Benefit Analysis - CBA) e aplicação dos modelos em cenários considerando a operação exclusiva de HPTs ou de HSTs. A resolução do problema de otimização de traçados ferroviários, com uma abordagem de computação paralela aplicada a um Algoritmo Genético, indica que os investimentos em infraestrutura variam majoritariamente em função da topografia, os custos de desapropriações são proporcionalmente pequenos e as restrições geométricas dos traçados não influenciam significativamente nesses resultados. Após a projeção do número de viagens intermunicipais por modelos analíticos, os dados coletados em uma pesquisa de preferência declarada são utilizados para modelagem da propensão à escolha modal. Finalmente, uma proposta de formulação para o cálculo dos principais itens de custos e benefícios de uma avaliação socioeconômica para o transporte ferroviário de passageiros viabiliza a análise de cenários em função de produtividade da construção da infraestrutura, variabilidade dos investimentos estimados e capacidade de atração de demanda reprimida. Os resultados dos cenários indicam que a diferença entre os benefícios estritamente econômicos (receita operacional e valor residual dos investimentos em infraestrutura) e os custos de construção e operacionais são negativos para qualquer tarifa ferroviária, apesar dos resultados para a rede de HSTs serem maiores do que para a de HPTs. Considerando os aspectos sociais, os benefícios totais da operação ferroviária sobrepõem-se aos seus custos em situações tarifárias específicas, novamente com resultados maiores para uma rede de HSTs, cuja tendência também é observada quando apenas os benefícios sociais são relacionados com custos totais através de uma Razão Benefício-Custo (Benefit-Cost Ratio - BCR). Portanto, segundo as premissas desta tese, há indícios que o investimento em uma infraestrutura ferroviária aparentemente não é uma decisão promissora em termos de viabilidade socioeconômica, apesar da operação de HSTs ser mais conveniente do que HPTs nas condições analisadas. / The major use of the Brazilian railway network for freight transport and its incompatibi-lity with high speed trains does not enable running competitive services of intercity passenger transport. The research question of this thesis is which rolling stock technology provides better socioeconomic results on a new intercity passenger network with exclusive operation of High Performance Trains (HPTs) or High Speed Trains (HSTs) with average speeds of 150 km/h and 300 km/h respectively. The hypothesis is that the difference between the socioeconomic benefits and costs of operating HSTs results in positive values and greater than those from the operation of HPTs given specific socioeconomic parameters and a hypothetical network in the Southeastern region of Brazil. The main goal of this research is to estimate and compare the major socioeconomic costs and benefits of a hypothetical railway network by first estimating the required investments of new alignments. Furthermore, the number of trips among cities in the Southeastern Region over a strategic planning horizon and the mode choice are estimated and a Cost-Benefit Analysis formulation is provided to be applied to scenarios of exclusive operation of HPTs or HSTs. The solution of the railway alignment optimization problem with a parallel computing approach applied to a Genetic Algorithm shows that the infrastructure investments vary mainly due to the topography, whereas the expropriation costs are proporti-onally small and the railway geometric constraints do not significantly affect the results. The number of trips by transport mode over a planning horizon is expanded analytically and the collected data of a stated preference survey is applied to a mode choice modeling approach. Finally, a formulation for the major items of costs and benefits of a socioeconomic assessment for a rail passenger transport project is proposed and it is applied to specific scenarios where the effects of the infrastructure building productivity, variability of the estimated investments, and the ability to attract new passengers are analyzed. The results from these scenarios show that the difference between the operating income and the net residual value of investments in infrastructure, construction and operating costs are negative for any rail fare, despite the results for the network of HSTs being higher than for HPTs. Furthermore, the overall benefits of the railway operation outweigh the costs in specific pricing policies with better results for a network operating HSTs. This trend is also noticed when only the social benefits are compared to the total costs by a Benefit-Cost Ratio (BCR). Therefore, there is evidence that the investment in railway infrastructure for passenger transport apparently is not a promising decision in terms of socioeconomic feasibility under the assumptions of this thesis, despite the operation of HSTs being more attractive than HPTs under the specified conditions.

A utilização majoritária da malha ferroviária brasileira para o transporte de cargas e a sua incompatibilidade para desenvolvimento de altas velocidades inviabiliza a oferta de serviços competitivos para o transporte intermunicipal de passageiros. A questão explorada nesta tese é sobre qual tecnologia ferroviária provê melhores resultados socioeconômicos no contexto de uma nova rede para o transporte intermunicipal de passageiros com operação exclusiva de Trens de Alto Desempenho (High Performance Trains - HPTs) ou Trens de Alta Velocidade (High Speed Trains - HSTs), caracterizados por velocidades médias de 150 km/h e 300 km/h respectivamente. Nesse sentido, a hipótese é que a diferença entre benefícios e custos socioeconômicos da oferta de serviços de HSTs resultam em valores positivos e maiores do que aquelas decorrentes da operação de HPTs, mediante parâmetros específicos de avaliação socioeconômica e uma configuração hipotética de rede na Região Sudeste do Brasil. Assim, o objetivo principal da tese é estimar e comparar os custos e benefícios socioeconômicos de uma rede ferroviária pela estimativa dos investimentos para a construção de novos traçados ferroviários, estimativa do número de viagens intermunicipais na Região Sudeste em um horizonte de planejamento estratégico e a propensão à escolha modal, estabelecimento de uma formulação de Análise Custo-Benefício (Cost Benefit Analysis - CBA) e aplicação dos modelos em cenários considerando a operação exclusiva de HPTs ou de HSTs. A resolução do problema de otimização de traçados ferroviários, com uma abordagem de computação paralela aplicada a um Algoritmo Genético, indica que os investimentos em infraestrutura variam majoritariamente em função da topografia, os custos de desapropriações são proporcionalmente pequenos e as restrições geométricas dos traçados não influenciam significativamente nesses resultados. Após a projeção do número de viagens intermunicipais por modelos analíticos, os dados coletados em uma pesquisa de preferência declarada são utilizados para modelagem da propensão à escolha modal. Finalmente, uma proposta de formulação para o cálculo dos principais itens de custos e benefícios de uma avaliação socioeconômica para o transporte ferroviário de passageiros viabiliza a análise de cenários em função de produtividade da construção da infraestrutura, variabilidade dos investimentos estimados e capacidade de atração de demanda reprimida. Os resultados dos cenários indicam que a diferença entre os benefícios estritamente econômicos (receita operacional e valor residual dos investimentos em infraestrutura) e os custos de construção e operacionais são negativos para qualquer tarifa ferroviária, apesar dos resultados para a rede de HSTs serem maiores do que para a de HPTs. Considerando os aspectos sociais, os benefícios totais da operação ferroviária sobrepõem-se aos seus custos em situações tarifárias específicas, novamente com resultados maiores para uma rede de HSTs, cuja tendência também é observada quando apenas os benefícios sociais são relacionados com custos totais através de uma Razão Benefício-Custo (Benefit-Cost Ratio - BCR). Portanto, segundo as premissas desta tese, há indícios que o investimento em uma infraestrutura ferroviária aparentemente não é uma decisão promissora em termos de viabilidade socioeconômica, apesar da operação de HSTs ser mais conveniente do que HPTs nas condições analisadas. / The major use of the Brazilian railway network for freight transport and its incompatibi-lity with high speed trains does not enable running competitive services of intercity passenger transport. The research question of this thesis is which rolling stock technology provides better socioeconomic results on a new intercity passenger network with exclusive operation of High Performance Trains (HPTs) or High Speed Trains (HSTs) with average speeds of 150 km/h and 300 km/h respectively. The hypothesis is that the difference between the socioeconomic benefits and costs of operating HSTs results in positive values and greater than those from the operation of HPTs given specific socioeconomic parameters and a hypothetical network in the Southeastern region of Brazil. The main goal of this research is to estimate and compare the major socioeconomic costs and benefits of a hypothetical railway network by first estimating the required investments of new alignments. Furthermore, the number of trips among cities in the Southeastern Region over a strategic planning horizon and the mode choice are estimated and a Cost-Benefit Analysis formulation is provided to be applied to scenarios of exclusive operation of HPTs or HSTs. The solution of the railway alignment optimization problem with a parallel computing approach applied to a Genetic Algorithm shows that the infrastructure investments vary mainly due to the topography, whereas the expropriation costs are proporti-onally small and the railway geometric constraints do not significantly affect the results. The number of trips by transport mode over a planning horizon is expanded analytically and the collected data of a stated preference survey is applied to a mode choice modeling approach. Finally, a formulation for the major items of costs and benefits of a socioeconomic assessment for a rail passenger transport project is proposed and it is applied to specific scenarios where the effects of the infrastructure building productivity, variability of the estimated investments, and the ability to attract new passengers are analyzed. The results from these scenarios show that the difference between the operating income and the net residual value of investments in infrastructure, construction and operating costs are negative for any rail fare, despite the results for the network of HSTs being higher than for HPTs. Furthermore, the overall benefits of the railway operation outweigh the costs in specific pricing policies with better results for a network operating HSTs. This trend is also noticed when only the social benefits are compared to the total costs by a Benefit-Cost Ratio (BCR). Therefore, there is evidence that the investment in railway infrastructure for passenger transport apparently is not a promising decision in terms of socioeconomic feasibility under the assumptions of this thesis, despite the operation of HSTs being more attractive than HPTs under the specified conditions.

Esta dissertação visa avaliar o padrão comportamental dos pedestres nos deslocamentos na cidade de Porto Alegre. É abordado a partir da base de dados provenientes da pesquisa de entrevistas domiciliares realizadas em 2003 em Porto Alegre. Para isto, caracterizaram-se os deslocamentos a pé na cidade e identificaram-se as regiões de maior e menor concentração de viagens a pé. A fim de determinar os fatores que influenciam a decisão de caminhar foram estimados modelos logit binomiais para as viagens menores que 2 km em cada uma das regiões identificadas anteriormente. As variáveis explicativas para os modelos analisados incluem características do domicílio (disponibilidade de automóvel e renda por domicílio), dos residentes (idade), das viagens (distância e motivo da viagem), da forma urbana (densidade de domicílios, densidade populacional, comprimento médio das quadras, padrão do sistema viário, tipo de uso do solo e estacionamento tarifado em área pública) e da disponibilidade de transporte coletivo na origem da viagem. Foram consideradas duas categorias de viagens: viagens por motivo trabalho/estudo e viagens por motivo não trabalho/estudo (motivos recreacionais, compras, saúde, assuntos pessoais e outros). Os resultados do estudo mostram que características sócio-econômicas dos residentes, características das viagens e da forma urbana influenciam a escolha do modo a pé. Analisando os valores de elasticidade obtidos para as duas categorias de viagens originadas em Petrópolis e no Centro pode-se inferir que as variáveis que exercem maior influência estão relacionadas principalmente a características da viagem (distância) e à configuração física da rede viária. A análise de sensibilidade evidenciou a sensibilidade do modelo frente a alterações das variáveis estudadas. Os resultados obtidos servem de apoio para um planejamento mais adequado da mobilidade e acessibilidade dos pedestres. / This thesis aims to evaluate the pedestrians’ behavior in Porto Alegre. The study was based on a Porto Alegre household survey of 2003. During the analysis, the pedestrian trips were characterized and the traffic zones with the larger and the smaller number of pedestrian trips were identified. In order to determine the influencing factors related to the walk choice, binomial logit models were developed for trips with less than 2km in each traffic zone previously identified. The explanatory variable used in the models included the characteristics of the household (auto availability and household income), of the household members (age), of the trip (distance and purpose of the trip), of the built environment (housing units density, population density, mean block size, street patterns, land use and public parking), and transit availability in the origin of the trip. Two types of pedestrian travel were considered: work and non-work trips (shopping, health, personal purposes and others). The study results showed that socio-economic characteristics, trip characteristics and local measures of the built environment influence walk modechoice. Elasticity results for the two types of trips, with origin in “Petrópolis” and Downtown, indicate that the most influence variables are connected with trip characteristics (distance) and street design. The sensibility analysis showed the model sensibility strength under the changes introduced in the variables studied. These analysis results may provide support for a better planning for pedestrians’ mobility and accessibility.

This thesis investigates the relationship between mode choice and the complexity of trip chaining patterns. An understanding of the causality between these two choice behaviors may aid in the development of tour-based travel demand modeling systems that attempt to incorporate models of trip chaining and mode choice. The relationship between these two aspects of travel behavior is represented in this thesis by considering three different causal structures: one structure in which the trip chaining pattern is determined first and influences mode choice, another structure in which mode choice is determined first and influences the complexity of the trip chaining pattern, and a third structure in which neither is predetermined but both are determined simultaneously. The first two structures are estimated within a recursive bivariate probit modeling framework that accommodates error covariance. The simultaneous logit model is estimated for the third structure that allows a bidirectional simultaneous causality. The analysis and model estimation are performed separately for work tour and non-work tour samples drawn from the 2000 Swiss Microcensus travel survey. Model estimation results show that the causal structure in which trip chaining precedes mode choice performs best for the non-work tour sample. For the work-tour sample, the findings were less conclusive because two causal structures, one in which trip chaining affects mode choice and the other in which both are determined simultaneously, gave virtually identical goodness-of-fit measures. But the structure in which mode choice precedes trip chaining pattern choice gave significantly inferior goodness-of-fit measures for the work tour sample. These findings should be reflected in the development of activity-based and tour-based modeling systems.