Refine
Document Type
- Doctoral Thesis (4)
Language
- English (4)
Has Fulltext
- yes (4)
Is part of the Bibliography
- no (4)
Keywords
- Accident Research, Allocative Efficiency, Benefit Cost, Cost Benefit, Cost Effectiveness, Transport Safety, Transportation Safety Regulations (1)
- Mobility, transportation, passenger transportation, intelligent transportation systems (ITS), infrastructure, technology, regulatory frameworks, public authorities, socio-economic cost-benefit analysis, society (1)
- Retail, Innovation, Emerging Technology (1)
- autonomous driving, artificial intelligence, automotive industry, mobility, COVID-19, supplier risks, process optimisation (1)
Today, transportation is a central element of a society’s welfare in terms of economic, political and social success. It creates jobs, allows international cooperation between firms and countries, contributes to firms’ productivity, and enables social participation and interaction. It has become an essential intermediate. Consequently, changes in transportation affect many more sectors. Therefore, transportation of goods and persons has been growing immensely within the past decades. Against this background, intelligent transportation systems (ITS) gain importance in improving and changing transport. Technology can cover all modes (e.g. advanced driving systems, cooperative vehicle systems as vehicle-to-vehicle or vehicle-to-infrastructure communication, or mobile and multimodal information and ticketing systems). The deployment of ITS substantially changes our transportation system. These changes concern several elements and stakeholders of mobility, e.g. infrastructure, technology, users, providers, public institutions, or regulatory frameworks. Up to now, research on ITS strongly focused on technical aspects, i.e. technical development and feasibility. However, these aspects can only represent part of a comprehensive analysis of ITS. This dissertation gives systematic analysis of elements that in the end have a strong impact on the successful market introduction of ITS. It discusses different aspects of intelligent transportation systems providing a view on the framework conditions for intelligent transportation systems. This work, hereby, focuses on passenger transportation. It shows that the successful deployment of ITS requires multiple actors. Each of them can positively or negatively influence the success of ITS-deployment. This work specifically analyses the investment decisions of public authorities on the example of socio-economic cost-benefit analysis, the users’ willingness to accept a multimodal information and ticketing system and its impact on modal choice, and finally the municipalities’ role in providing mobility for specific user groups on the example of immigrants showing the potential and limitations of ITS. The work picks up research questions that have not been addressed before and contributes to a deeper understanding of the interplay of ITS as a technology and the society.
For over 80 years the idea of self-driving cars has influenced our perception of the future transport mode. While in 1939 people were excited, they did not believe it would ever become reality. In 2021 we are now closer than ever to bringing these cars on the road. But the vast number of stakeholders and the various aspects that must be considered for the execution of self-driving cars makes it even more complex than at first glance. The creation of a proper artificial intelligence infrastructure, the integration of AI within the automotive industry and lastly, getting society to accept self-driving cars, are the focus of this dissertation. Through a literature review, a qualitative and a quantitative study these key aspects have been considered. At the centre is the over one century old German, and European, automotive industry. The European automotive manufacturers and suppliers need to act together, take risks, educate future self-driving car users and overall see the European automotive industries as allies. Europeans would benefit from pooling financial capabilities and data gathering to execute technological improvements faster and better. To bring autonomous vehicles on the road, and to create a transport mode capable of competing with Chinese, American and other competitors’ products, and to simply not be outsmarted by them, Europeans have to work together and become strategically bold. As the COVID-19 pandemic hit in 2020, integrating AI within our automotive industry may not be on companies’ minds, but we need it now more than ever. Through AI, processes, such as information gathering and handling, can be improved and machinery supporting workers can be introduced. In addition, the fundamental assumptions on which our future mobility world is based have changed and, as a result, strategies must be reassessed. While the introduction reflects on pre-COVID-19 times, the papers included in this dissertation highlight the changes and the opportunities the virus brought upon the industry and tries to encourage it to expand AI integration and self-driving vehicle execution. The pandemic may have resulted in lower financial capabilities for the research and creation of self-driving cars, but it has also allowed for an increased acceptance rate of this future transport mode. Overall, it is time for the automotive industry to reconsider its self-driving vehicle deployment approach drastically in order to reinvent itself and usher in a new era where AI within automobiles is not feared but preferred.
Road crashes play a substantial role in depressing GDP, especially in low- and
middle-income countries. The economic welfare of countries is adversely affected,
and governments must try to correct this market failure. The conditions that
obtain in Turkey, Costa Rica, and the European Union are conducive to analyzing
regulatory policies in the field of traffic accidents. Since Turkey and Costa
Rica introduced periodic technical inspections recently, data from before and
after their introduction is available and can be compared. I obtained exclusive
inspection data from Turkey for the analysis. For Costa Rica, I derived cost-unit
rates that had not been calculated before, which allowed me to rank and evaluate
regulatory measures that may be adopted in the future. The Covid-19 pandemic
made it possible to study another set of policy interventions. That study
complements the first two papers. The observed effects are examined in the
context of the efforts of the European Union to reduce deadly traffic accidents
over the last few decades. By analyzing data from before and after government
interventions, I show the impact as well as the shortcomings of specific policies
in different countries or regions and discuss their welfare effect. Furthermore,
this dissertation provides evidence for the claim that introducing periodic technical
inspections, a policy intervention that can tackle the problem of frequent
traffic accidents, is cost effective and thus exerts a positive effect on the economy.
The retail industry is continuously confronted with new challenges and experiences a transformation from a supplier’s market to a buyer's market. It is, thus, essential for the retail industry to consequently focus on, anticipate and fulfil consumer’s demands. Technologies and innovative business solutions can help to support to establish a required customer experience and, thereby, gain a competitive advantage. A multitude of new services and products, channels as well as players can already be identified which drive the transformation. Therefore, retailers need to understand current trends and technologies and identify as well as implement relevant solutions for their transformation since otherwise, new players will dominate the market.
Hence, this dissertation aims to review and analyse new technologies which are coupled with innovative business activities in order to provide customer-centric retailing. For this purpose, this dissertation consists of five articles and derives four major contributions which introduce different approaches to establishing consumer satisfaction. Firstly, a core technology for retail is artificial intelligence (AI) which can be meaningful applied along the entire value chain and improve retailers’ positions. Two focus areas have been identified in this context which are (i) the optimisation of the entire retail value chain with the help of AI with the aim to derive transparency and (ii) the improvement of consumer satisfaction and relationship. Secondly, focussing on the consumer-retailer relationship in the digital era, a concept with a data architecture is proposed based on a real use case. The outcome was that a specific customer orientation based on data can increase the brand value and sales volume. Thirdly, the work presents that new shopping concepts, named unmanned store concepts, gain continuous growth. Unmanned store concepts employ a variety of new technologies, are characterised by attributes of speed, ease, as well as comfort, and are deemed to be the new ideal of the expectations of modern buyers. Two different directions have been deeper analysed: (i) walk-in stores and (ii) automated vending machines. The critical success factors for the usage of unmanned store solutions are distance as well as high consumer affinity for innovations. In times of the COVID-19 pandemic, which has a huge impact on retail, a continuous innovation capability still needs to be established. Finally, this work introduces a tool for systematic innovation management considering the current circumstances. Taken as a whole, this dissertation with its five articles deals with significant research questions which have not been approached so far. Thereby, the literature is extended by the introduction of novel insights and the provision of a deeper understanding of how retailers can transform their business into a more consumer-oriented way.
