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The work presents a systematic analysis of a large-scale integration of electric and autonomously controlled vehicles with corresponding infrastructure in cities. A framework is formulated assessing transport-related, electrotechnical and economical parameters of the operation of a highly efficient but comfortable road traffic based on renewable energies. Simulation results show potential to replace local motorized individual transport entirely and to reach the targets of the energy transition.
Flottenbetrieb --- Autonomes Carsharing --- Elektromobilität
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This research is based on a prior study done by "Farajallah, Hammond and Penard" in 2016, and focuses on the Belgian market of the Peer-to-Peer platform BlaBlaCar. The intent of this research is to analyze, how the reputation of a driver influences his pricing behaviour and the amount of seats he sells for a trip in his car. The fi ndings show, that the results from the original study, which took place in France, could not be replicated with the Belgian data.
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Autonomous driving technology is classified as a key trend within the automotive industry and expected to revolutionize mobility behavior by boosting the usage of shared mobility programs. This master thesis addresses the transition path of premium manufacturers and raises the question of unique selling propositions of premium offers within the ‘shared’ and ‘autonomous’ mobility business. In consideration of literature research, premium characteristics and purchase reasons for premium vehicles within the ‘self-driven’ and ‘owned’ mobility business were identified. Based on an empirical online study, referring to 260 respondents, having their main residence in Germany, unique selling propositions of premium offers in the ‘shared’ and ‘autonomous’ mobility business were analyzed. Premium decision-making in the ‘shared’ and ‘autonomous’ mobility business was found to be more rational, more individual, and less emotional or status related as hitherto. Route length, time gains, interior characteristics, privacy, alternative time consumption, as well as personal innovativeness were found to positively affect a customer’s premium usage intention in the context of autonomous sharing. Managerial implications, promising areas for further research, as well as an ethical evaluation of results are included in this master thesis.
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Jens Kopp analyzes the potential of car sharing as a new mobility solution in light of progressive urbanization and researches factors influencing the use of car sharing to assess the growth outlook of car sharing services. He performs a regression analysis to identify statistically significant factors influencing the use and evaluation of car sharing services based on an empirical field research conducted in Germany (n=175). Key findings include that cost saving is the only researched factor relevant to influence the use of car sharing services as well as the evaluation of car sharing and the assessment of its future. The existing research shows that car sharing is a viable lever to address substantial ecological and economic mobility issues and the conducted research provides new insights into the factors influencing the use and evaluation of car sharing services. Contents The Transformation in the Automobile Industry State of the Automobile Industry: Porter’s Five Forces Research Design: Empirical Field Research on Potential Car Sharing Users Target Groups Researchers and students in the fields of strategic corporate management, marketing, and economics Market research specialists, strategy managers, marketing and sales experts in the automobile industry The Author Jens Kopp holds a Master’s Degree in Business Administration from the FOM in Essen with a focus on Strategic Corporate Management. .
Car sharing. --- Auto sharing (Car sharing) --- Automobile sharing --- Carsharing --- Automobile leasing and renting --- Marketing. --- Globalization. --- Management. --- Administration --- Industrial relations --- Organization --- Global cities --- Globalisation --- Internationalization --- International relations --- Anti-globalization movement --- Consumer goods --- Domestic marketing --- Retail marketing --- Retail trade --- Industrial management --- Aftermarkets --- Selling --- Marketing
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Modern societies demand high and varied mobility, which in turn requires a complex transport system adapted to social needs that guarantees the movement of people and goods in an economically efficient and safe way, but all are subject to a new environmental rationality and the new logic of the paradigm of sustainability. From this perspective, an efficient and flexible transport system that provides intelligent and sustainable mobility patterns is essential to our economy and our quality of life. The current transport system poses growing and significant challenges for the environment, human health, and sustainability, while current mobility schemes have focused much more on the private vehicle that has conditioned both the lifestyles of citizens and cities, as well as urban and territorial sustainability. Transport has a very considerable weight in the framework of sustainable development due to environmental pressures, associated social and economic effects, and interrelations with other sectors. The continuous growth that this sector has experienced over the last few years and its foreseeable increase, even considering the change in trends due to the current situation of generalized crisis, make the challenge of sustainable transport a strategic priority at local, national, European, and global levels. This Special Issue will pay attention to all those research approaches focused on the relationship between evolution in the area of transport with a high incidence in the environment from the perspective of efficiency.
Technology: general issues --- History of engineering & technology --- Environmental science, engineering & technology --- optimization models --- timetable --- passenger waiting time --- vehicle occupancy ratio --- intelligent transportation systems --- demand prediction --- taxi recommendation --- vehicle social network --- ride-hailing --- urban rail transit (URT) --- exploratory data analysis (EDA) --- data envelopment analysis (DEA) --- sustainable transport systems --- intelligent transportation systems (ITS) --- big-data applications --- dynamic bus travel time prediction --- wide and deep --- data fusion --- attention --- recurrent neural network --- deep neural networks --- intelligent transportation --- railway --- CPS --- security --- safety --- critical infrastructure --- carsharing --- data analysis --- delays --- demand --- public transit --- taxi --- complex network analysis --- centrality measures --- network robustness --- ridership patterns --- clustering analysis --- passenger flow --- Barcelona underground --- artificial intelligence --- Big Data analytics --- forecasting systems --- recommender system --- Fintech --- passenger traffic --- artificial neural network --- regression analysis --- reputation algorithm --- users' reputation --- transport --- software application --- deep learning --- energy consumption --- sustainable cities --- transfer learning --- wastewater treatment plants --- unmanned aerial vehicles (UAVs) --- multi-objective optimization --- integer programming --- GLPK --- variable neighborhood search --- search and rescue --- learning recommender system --- learning object --- learning videos --- content-based --- collaborative filtering --- users' profiling --- data extraction --- natural language processing --- mapping application --- time series forecasting --- HTM --- regression --- machine intelligence --- cyber-attack detection --- IoT --- trust --- energy trading --- trusted negotiations --- optimization models --- timetable --- passenger waiting time --- vehicle occupancy ratio --- intelligent transportation systems --- demand prediction --- taxi recommendation --- vehicle social network --- ride-hailing --- urban rail transit (URT) --- exploratory data analysis (EDA) --- data envelopment analysis (DEA) --- sustainable transport systems --- intelligent transportation systems (ITS) --- big-data applications --- dynamic bus travel time prediction --- wide and deep --- data fusion --- attention --- recurrent neural network --- deep neural networks --- intelligent transportation --- railway --- CPS --- security --- safety --- critical infrastructure --- carsharing --- data analysis --- delays --- demand --- public transit --- taxi --- complex network analysis --- centrality measures --- network robustness --- ridership patterns --- clustering analysis --- passenger flow --- Barcelona underground --- artificial intelligence --- Big Data analytics --- forecasting systems --- recommender system --- Fintech --- passenger traffic --- artificial neural network --- regression analysis --- reputation algorithm --- users' reputation --- transport --- software application --- deep learning --- energy consumption --- sustainable cities --- transfer learning --- wastewater treatment plants --- unmanned aerial vehicles (UAVs) --- multi-objective optimization --- integer programming --- GLPK --- variable neighborhood search --- search and rescue --- learning recommender system --- learning object --- learning videos --- content-based --- collaborative filtering --- users' profiling --- data extraction --- natural language processing --- mapping application --- time series forecasting --- HTM --- regression --- machine intelligence --- cyber-attack detection --- IoT --- trust --- energy trading --- trusted negotiations
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Modern societies demand high and varied mobility, which in turn requires a complex transport system adapted to social needs that guarantees the movement of people and goods in an economically efficient and safe way, but all are subject to a new environmental rationality and the new logic of the paradigm of sustainability. From this perspective, an efficient and flexible transport system that provides intelligent and sustainable mobility patterns is essential to our economy and our quality of life. The current transport system poses growing and significant challenges for the environment, human health, and sustainability, while current mobility schemes have focused much more on the private vehicle that has conditioned both the lifestyles of citizens and cities, as well as urban and territorial sustainability. Transport has a very considerable weight in the framework of sustainable development due to environmental pressures, associated social and economic effects, and interrelations with other sectors. The continuous growth that this sector has experienced over the last few years and its foreseeable increase, even considering the change in trends due to the current situation of generalized crisis, make the challenge of sustainable transport a strategic priority at local, national, European, and global levels. This Special Issue will pay attention to all those research approaches focused on the relationship between evolution in the area of transport with a high incidence in the environment from the perspective of efficiency.
Technology: general issues --- History of engineering & technology --- Environmental science, engineering & technology --- optimization models --- timetable --- passenger waiting time --- vehicle occupancy ratio --- intelligent transportation systems --- demand prediction --- taxi recommendation --- vehicle social network --- ride-hailing --- urban rail transit (URT) --- exploratory data analysis (EDA) --- data envelopment analysis (DEA) --- sustainable transport systems --- intelligent transportation systems (ITS) --- big-data applications --- dynamic bus travel time prediction --- wide and deep --- data fusion --- attention --- recurrent neural network --- deep neural networks --- intelligent transportation --- railway --- CPS --- security --- safety --- critical infrastructure --- carsharing --- data analysis --- delays --- demand --- public transit --- taxi --- complex network analysis --- centrality measures --- network robustness --- ridership patterns --- clustering analysis --- passenger flow --- Barcelona underground --- artificial intelligence --- Big Data analytics --- forecasting systems --- recommender system --- Fintech --- passenger traffic --- artificial neural network --- regression analysis --- reputation algorithm --- users’ reputation --- transport --- software application --- deep learning --- energy consumption --- sustainable cities --- transfer learning --- wastewater treatment plants --- unmanned aerial vehicles (UAVs) --- multi-objective optimization --- integer programming --- GLPK --- variable neighborhood search --- search and rescue --- learning recommender system --- learning object --- learning videos --- content-based --- collaborative filtering --- users’ profiling --- data extraction --- natural language processing --- mapping application --- time series forecasting --- HTM --- regression --- machine intelligence --- cyber-attack detection --- IoT --- trust --- energy trading --- trusted negotiations --- n/a --- users' reputation --- users' profiling
Choose an application
Modern societies demand high and varied mobility, which in turn requires a complex transport system adapted to social needs that guarantees the movement of people and goods in an economically efficient and safe way, but all are subject to a new environmental rationality and the new logic of the paradigm of sustainability. From this perspective, an efficient and flexible transport system that provides intelligent and sustainable mobility patterns is essential to our economy and our quality of life. The current transport system poses growing and significant challenges for the environment, human health, and sustainability, while current mobility schemes have focused much more on the private vehicle that has conditioned both the lifestyles of citizens and cities, as well as urban and territorial sustainability. Transport has a very considerable weight in the framework of sustainable development due to environmental pressures, associated social and economic effects, and interrelations with other sectors. The continuous growth that this sector has experienced over the last few years and its foreseeable increase, even considering the change in trends due to the current situation of generalized crisis, make the challenge of sustainable transport a strategic priority at local, national, European, and global levels. This Special Issue will pay attention to all those research approaches focused on the relationship between evolution in the area of transport with a high incidence in the environment from the perspective of efficiency.
optimization models --- timetable --- passenger waiting time --- vehicle occupancy ratio --- intelligent transportation systems --- demand prediction --- taxi recommendation --- vehicle social network --- ride-hailing --- urban rail transit (URT) --- exploratory data analysis (EDA) --- data envelopment analysis (DEA) --- sustainable transport systems --- intelligent transportation systems (ITS) --- big-data applications --- dynamic bus travel time prediction --- wide and deep --- data fusion --- attention --- recurrent neural network --- deep neural networks --- intelligent transportation --- railway --- CPS --- security --- safety --- critical infrastructure --- carsharing --- data analysis --- delays --- demand --- public transit --- taxi --- complex network analysis --- centrality measures --- network robustness --- ridership patterns --- clustering analysis --- passenger flow --- Barcelona underground --- artificial intelligence --- Big Data analytics --- forecasting systems --- recommender system --- Fintech --- passenger traffic --- artificial neural network --- regression analysis --- reputation algorithm --- users’ reputation --- transport --- software application --- deep learning --- energy consumption --- sustainable cities --- transfer learning --- wastewater treatment plants --- unmanned aerial vehicles (UAVs) --- multi-objective optimization --- integer programming --- GLPK --- variable neighborhood search --- search and rescue --- learning recommender system --- learning object --- learning videos --- content-based --- collaborative filtering --- users’ profiling --- data extraction --- natural language processing --- mapping application --- time series forecasting --- HTM --- regression --- machine intelligence --- cyber-attack detection --- IoT --- trust --- energy trading --- trusted negotiations --- n/a --- users' reputation --- users' profiling
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