Open Access

Destination websites, which are maintained by destination marketing/management organisations (DMOs), are a key source of information for tourists in the pre-trip phase. DMOs are increasingly applying experiential marketing on their websites to support positive pre-travel online destination experiences (ODEs) and make the vision of the holiday as vivid as possible. Thereby they aim to turn virtual visitors into physical visitors. However, research into technology-driven travel experiences is still in its infancy. In particular, a theoretical understanding of the nature of ODEs arising from destination websites is still lacking. Closing this knowledge gap is of great interest from a theoretical perspective; furthermore, it is of central importance for strategic marketing-controlling of destinations. Therefore, this dissertation is dedicated to an extensive investigation of ODEs on destination websites in the pre-travel phase. The aims were to analyse the influences of experiential design on ODEs, explore the ODE dimensions, and develop and validate a measurement tool for assessing the ODE values of destination websites. In the first qualitative multi-method study (eye-tracking, retrospective think-aloud protocols, semi-structured interviews, and video observations), the objective was to gain an in-depth understanding of the ODE facets in the travel inspiration phase. It was found that the experience dimensions adopted in previous research regarding the product-brand context (sensory, affective, intellectual, social, and behavioural dimensions) also occurred in the ODE context but exhibited some particularities, such as a future-oriented affective component (affective forecasting). Moreover, a supplementary spatio-temporal experience dimension was identified. An online field experiment was subsequently conducted and aimed at assessing the effects of applying experiential marketing on destination websites on ODEs in the travel inspiration phase. Based on the findings of Study 1, an initial attempt at developing an ODE measurement instrument was made and the ODE dimensionality tested. The results showed the theoretically relevant experience dimensions to be less differentiated compared to the product-brand context; instead, they merged into a holistic ODE encompassing several experience facets. Furthermore, it was shown that the application of experiential design enhanced ODEs; however, considering the subjectivity of experiences, the effect was rather small. Accordingly, complex multi-media elements do not automatically increase the experiential effect. In the third study, a quasi-online field experiment was conducted, simulating the travel information phase (higher involvement than Study 2) to re-assess the ODE dimensions and develop and validate a measurement instrument. The results showed the overall ODE to be reflected by two interrelated dimensions that aligned with the dual process theory: hedonic and utilitarian experiences. The facets identified in the first study were largely reflected in these two overarching components. Moreover, a reliable, valid, and parsimonious second-order measure for assessing ODEs was proposed. Overall, the results yielded by this dissertation enhance the scientific understanding of the technology-empowered tourist experience in the currently under-researched pre-travel experience phase. In addition, by proposing a new scale for the measurement of ODEs, this dissertation provides useful methodological advancements that can pave the way for further research in this field. The results will also be of great practical value for DMOs, as they yield a tool for controlling the experiential outcomes of websites as a base for strategic marketing decisions.

This thesis aims to develop a FE-based model of a dieless wire drawing process for wires made from magnesium alloys. To this end a general material model of pure magnesium and a model of the dieless wire drawing process are developed. Based on the general pure magnesium model an alloy specific model for AZ31 wire is developed. The performance of both models is assessed using experimental data generated on a dieless wire drawing prototype. The process model is conceptionally split into the thermal and mechanical response of the wire. The thermal model is validated by axial temperature profiles and the mechanical model is vali-dated by CSA-reduction and wire force. Both behaviours are validated separately before combin-ing the thus created models into a thermomechanical model of the dieless wire drawing process. The thermal material model is developed for pure magnesium. An initial assumption of limited correlation between content of alloying elements and thermal behaviour, was disproven. As a results in addition to alloy-specific mechanical data, thermo-electric data is recorded to achieve thermal validity of the model. This is done by identifying the experimental maximum temperature of the drawn wire for a given heating power and calculating the necessary input power of the in-duction heating device to achieve this temperature in simulation. The mechanic material model is based on experimental stress-strain curves recorded for each investigated wire materials in addi-tion to pure magnesium data, based on literature. Results show the thermomechanical magnesium models to be mostly valid, provided process parameters stay within the range of available data on the mechanic material performance. Where the model is forced to extrapolate material behaviour, simulation quality drops. This ap-plies for wire temperature and CSA-reduction. Estimations of wire force are shown to be invalid. For AZ31 wire the thermal model generated valid temperature profiles of the wire. The thermo-mechanical model for AZ31 is shown invalid as both CSA-reduction and wire force deviate from experimental results.

Algorithmic distribution has fundamentally altered the news industry and has led to conflicts over regulatory issues. Focusing on the introduction of European ancillary copyright, this chapter addresses an earlier international reform around algorithmic news distribution. Based on an in-depth thematic analysis of key documents from the policy formulation phase, the chapter maps the arguments for and against the ancillary copyright reform put forward by Google and news publishers in Germany. While we provide a detailed analysis of the underlying rationales of two key actors primarily affected by the regulation, we also place ancillary copyright in the context of competing private property and public policy visions, which allows for a better understanding of how and why different actors take particular positions on copyright reform and algorithmic regulation.

Beginning with the theology of Martin Luther and drawing on a selection of feminist theologians, this thesis proposes a relational, agential model of human flourishing. It is rooted in Luther’s doctrines of the hiddenness of God and of God’s alien and proper work in the lives of believers. Such an approach gives rise to questions concerning human freedom and agency, sin, and the nature of our relationship with God and with other persons. Many feminist theologies provide an inadequate account of sin and its effects on the person and their relationships. This thesis asserts that taking sin and its effects seriously is essential to developing a secure and healthy self, and a healthy relationship with God and other persons. It therefore proposes a reworked understanding of religious incurvature as a relational model of sin which supports the goal of human flourishing. This concept of the self curved either inwards, or towards another, speaks to the nature of sin in its traditional understanding of sin as pride, as well as addressing feminist criticisms that the notion of sin as pride is not relevant to the needs and experiences of women. The model of human flourishing proposed here is specifically Christian in its assertion that we do not exist as persons, are not fully human, without our being in relationship with the triune God and other created persons. We flourish in community. Further, it supports the idea that true Christian freedom consists of a life dedicated to service of God and others.

Environmental perception is one of the biggest challenges in autonomous driving to move inside complex traffic situations properly. Perceiving the road's condition is necessary to calculate the drivable space; in manual driving, this is realized by the human visual cortex. Enabling the vehicle to detect road conditions is a critical and complex task from many perspectives. The complexity lies on the one hand in the development of tools for detecting damage, ideally using sensors already installed in the vehicle, and on the other hand, in integrating detected damages into the autonomous driving task and thus into the subsystems of autonomous driving. High-Definition Feature Maps, for instance, should be prepared for mapping road damages, which includes online and in-vehicle implementation. Furthermore, the motion planning system should react based on the detected damages to increase driving comfort and safety actively. Road damage detection is essential, especially in areas with poor infrastructure, and should be integrated as early as possible to enable even less developed countries to reap the benefits of autonomous driving systems. Besides the application in autonomous driving, an up-to-date solution on assessing road conditions is likewise desirable for the infrastructure planning of municipalities and federal states to make optimal use of the limited resources available for maintaining infrastructure quality. Addressing the challenges mentioned above, the research approach of this work is pragmatic and problem-solving. In designing technical solutions for road damage detection, we conduct applied research methods in engineering, including modeling, prototyping, and field studies. We utilize design science research to integrate road damages in an end-to-end concept for autonomous driving while drawing on previous knowledge, the application domain requirements, and expert workshops. This thesis provides various contributions to theory and practice. We design two individual solutions to assess road conditions with existing vehicle sensor technology. The first solution is based on calculating the quarter-vehicle model utilizing the vehicle level sensor and an acceleration sensor. The novel model-based calculation measures the road elevation under the tires, enabling common vehicles to assess road conditions with standard hardware. The second solution utilizes images from front-facing vehicle cameras to detect road damages with deep neural networks. Despite other research in this area, our algorithms are designed to be applicable on edge devices in autonomous vehicles with limited computational resources while still delivering cutting-edge performance. In addition, our analyses of deep learning tools and the introduction of new data into training provide valuable opportunities for researchers in other application areas to develop deep learning algorithms to optimize detection performance and runtime. Besides detecting road damages, we provide novel algorithms for classifying the severity of road damages to deliver additional information for improved motion planning. Alongside the technical solutions, we address the lack of an end-to-end solution for road damages in autonomous driving by providing a concept that starts from data generation and ends with servicing the vehicle motion planning. This includes solutions for detecting road damages, assessing their severity, aggregating the data in the vehicle and a cloud platform, and making the data available via that platform to other vehicles. Fundamental limitations in this dissertation are due to boundaries in modeling. Our pragmatic approach simplifies reality, which always distorts the degree of truth in the result. This affects the model building of the quarter-vehicle and deep learning. Further limitations occur in the end-to-end concept. This represents the integration of road damages in the autonomous driving task but does not detail the aggregation modules and interfaces of the subsystems. The completion of this work does not conclude the topic of road damage detection and assessment in autonomous driving. Research must continue to optimize the proposed solutions and test them on a widespread basis in the real world. Furthermore, the sensor fusion of different approaches is fascinating in order to combine the advantages of individual systems. Integrating the end-to-end concept into the ecosystem of an autonomous vehicle is another fascinating field, taking interfaces and cloud platforms into account.