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Online marketing, especially Paid Search Advertising, has become one of the most important paid media channels for companies to sell their products and services online. Despite being under intensive examination by a number of researchers for several years, this topic still offers interesting opportunities to contribute to the community, particularly because of its large economic impact and practical relevance as well as the detailed and widely unfiltered view of consumer behavior that such marketing offers. To provide answers to some of the important questions from advertisers in this context, the author present four papers in his thesis, in which he extends previous works on optimization topics such as click and conversion prediction. He applies and extends methods from other fields of research to specific problems in Paid Search. After a short introduction, the dissertation starts with a paper in which the authors illustrates a new method that helps advertisers to predict conversion probabilities in Paid Search using sparse keyword-level data. They address one of the central problems in Paid search advertising, which is optimizing own investments in this channel by placing bids in keyword auctions. In many cases, evaluations and decisions are made with extremely sparse data, although anecdotal evidence suggests that online marketing is a typical "Big Data" topic. In the developed algorithm presented in this paper, the authors use information such as the average time that users spend on the advertiser's website and bounce rates for every given keyword. This previously unused data set is shared between all keywords and used as prior knowledge in the proposed model. A modified version of this algorithm is now the core prediction engine in a productive Paid Search Bid Optimization System that calculates and places millions of bids every day for some of the most recognized retailers and service providers in the German market. Next, the author illustrates the development of a non-reactive experimental method for A/B testing of Paid Search Advertising activities. In that paper, the authors provide an answer to the question of whether and under what circumstances it makes economic sense for brand owners to pay for Paid Search ads for their own brand keywords in Google AdWords auctions. Finally, the author presents two consecutive papers with the same theoretical foundation in which he applies Bayesian methods to evaluate the impact of specific text features in Paid Search Advertisements.
Entrepreneurship is an important means for economic development and poverty alleviation . Due to the relevance of entrepreneurship, scholars call for research that contributes to the understanding of successful business creation. In order to best understand new venture creation, research needs to investigate barriers of entrepreneurship. A barrier that has received wide attention in the literature on new venture creation is capital requirements. Scholars argue that capital requirements are an entry barrier for new venture creation, as most people who start businesses have difficulties in acquiring the necessary amount of capital needed for starting the businesses. Particularly in developing countries, scholars and practitioners regard improvements in access to capital as a major solution to support new venture creation. However, besides improving access to capital, there are alternative solutions that help to deal with the problems of capital requirements and capital constraints in the process of new venture creation. In this dissertation, I argue that a possible means to master capital requirements and capital constraints in business creation is action-oriented entrepreneurship training. I draw on actionregulation theory (Frese & Zapf, 1994), theories supporting an interactionist approach (Endler & Edwards, 1986; Terborg, 1981) and on theories about career development (Arthur, 1994; Briscoe & Hall, 2006) to reason that action-oriented entrepreneurship training allows for handling capital requirements and capital constraints with regard to business creation. Specifically, I argue that action-oriented entrepreneurship training helps to deal with financial requirements and capital constraints in two ways: First, the training reduces the negative effect of capital constraints on business creation through the development of financial mental models. Second, the training supports finding employment and receiving employment income, which enable businesses creation.
This study aims to answer four main research questions regarding the roles, strategies, barriers, and representation of the media and environmental nongovernmental organisations (ENGOs) in environmental communication in Malaysia. From a theoretical lens, this study has incorporated the essential concepts of media, ENGOs, and environmental communication from both Western and Asian, particularly Malaysian perspectives as primary points of reference. For the purpose of this study, a total of 13 interviewees from Media A and Media B and 11 interviewees from ENGO A and ENGO B were chosen for the qualitative interview while 2,050 environmental articles were collected as samples from Media A´s and Media B´s newspapers along with ENGO A´s and ENGO B´s newsletters from the period 2012 to 2014 for the quantitative content analysis. Specifically, the findings from interview confirmed that both the Malaysian media and ENGOs have shared quite similar roles in environmental communication, particularly in environmental legitimacy (creating trust, credibility, and relationships with the public), in democracy (acting as a watchdog and mobilising the public sphere), and in constructing public mind about environmental problems. Pictures undoubtedly were one of the most vital tools in social construction, especially for presenting the reality of the environmental problems to the public. This was in harmony with the results of the quantitative content analysis, where more than 60% of pictures were found on environmental articles in media newspapers and ENGOs newsletters. Malaysian media and ENGOs have shared two common strategies in environmental communication, namely campaigning and collaboration with other stakeholders, while the ENGOs have two extra strategies: advocacy and lobbying strategies. Malaysian media and ENGOs also have collaborated with each other and the level of collaboration between them was at the coordination (medium) level. Both social actors especially the media were also relied heavily on their sources for environmental articles and the result of quantitative content analysis showed that the government was the main source for media newspapers, whereas other ENGOs and laypersons were the main sources for ENGOs´ newsletters. There are also colossal barriers faced by both Malaysian media and ENGOs throughout the process of environmental communication and some of the barriers faced by both media and ENGOs include the problem with limited knowledge of the environment, while some other barriers, like media laws and ownership, were only faced by the media; other barriers such as funding problems were specifically faced by the ENGOs. In terms of representation of environmental information, the Malaysian media make more presentations on environmental problems, especially on topics like floods, wildlife and water crises in their newspapers, while ENGOs have given more attention to environmental effort topics such as conservation and sustainable living in their newsletters. Surprisingly, not only the media but also the ENGOs used the same (news) values like timeliness, proximity, and impact as criteria for the selection of environmental issues for their publications. Other factors such as the background of the organisation and the interest of journalists or editors also influence the selection of environmental issues. It is hoped that the proposed theoretical framework of this study can serve as a crucial guideline for the development of environmental communication studies, especially among the media and ENGOs not only in Malaysia but also in other (Southeast) Asian regions that share a similar background.
Air quality models are important tools which are utilized for a large field of application. When combined with data from observations, models can be employed to create a comprehensive estimation of the past and current distribution of pollutants in the atmosphere. Moreover, projections of future concentration changes due to changing emissions serve as an important decision basis for policymakers. For the determination of atmospheric concentrations of air pollutants by means of numerical modelling it is essential to possess a model which is able to create anthropogenic and biogenic emissions with a temporally and spatially high resolution. The emission data is needed as input for a chemistry transport model which calculates transport, deposition, and degradation of air pollutants. To evaluate the impact of changing emissions on the environment a flexible emission model with the capability to create diverse emission scenarios is needed. Further, it is important to always take into account a variety of different species to properly represent the major chemical reactions in the atmosphere (e.g. ozone chemistry, aerosol formation). Currently there are only a few high resolution emission datasets available for Europe. The amount of substances included in these datasets, however, is limited. Moreover, they can not be used as basis for the creation of new emission scenarios. To enable the creation of emission scenarios in the course of this doctoral thesis the American emission model SMOKE was adopted and modified. On the basis of a multitude of different georeferenced datasets, official statistics, and further model results the newly created emission model “SMOKE for Europe” is capable of creating hourly emission data for the European continent with a spatial resolution of up to 5x5km2. In order to demonstrate the universal applicability of the emission model the carcinogenic species benzo[a]pyrene (BaP) was exemplarily implemented into the model. BaP belongs to the group of polycyclic aromatic hydrocarbons. Because of its high toxicity the European Union introduced an annual target value of 1 ng/m3 in January 2010. SMOKE for Europe was used to create a variety of emission scenarios for the years 1980, 2000, and 2020. These emission scenarios were then used to determine the impact of emission changes on atmospheric concentrations of BaP and to identify regions which exceed the European target value. Additionally the impact of different legislation and fuel use scenarios on the projected atmospheric concentrations in 2020 was investigated. Furthermore, additional use cases for a flexible emission model are pointed out. The SMOKE for Europe model was used to simulate the transport of volcanic ash after the eruption of the Icelandic volcano Eyjafjallajokull in March 2010. By comparison of modelled concentrations for different emission scenarios with observations from remote sensing and air plane flights distribution and concentration of the volcanic ash over Europe was estimated. The results of this thesis have been presented in four scientific papers published in international peerreviewed journals. The papers are reprinted at the end of this thesis.
Viable communication systems
(2020)
Society has come to the point that it requires a "Great Transformation" towards sustainability to ensure the viability of the planet for a vital society. The energy transition plays a central role for this transformation. For transforming the patterns of energy production and use in an energy transition as part of the "Great Transformation", this process of change now needs to strengthen its focus on information, communication, and knowledge systems. Human society needs to establish a knowledge system that has the potential to create usable knowledge for sustainability solutions. This requires organizing a communication system that is sufficiently complex, interconnected, and, at the same time, efficient for integrating reflexive, open-ended, inter- and transdisciplinary learning, evaluation, and knowledge co-production processes across multiple levels. This cumulative dissertation contributes to research in this direction by applying a systemic sustainability perspective on the content and organization of communication in the field of research on sustainable energy and the operational level of municipal climate action as part of the energy transition. Regarding sustainability, this thesis uses strong sustainability and its principles as a frame for evaluating the content of communication. Regarding the systemic perspective, the thesis particularly relies on the following theories: (i) the human-environment system model by R. Scholz as an overarching framework regarding interactions between humans and nature, (ii) social systems theory by N. Luhmann to reflect the complexity of society, (iii) knowledge management to consider the human character of knowledge and a practice-oriented perspective, and (iv) management cybernetics, in particular, the Viable System Model by S. Beer as a framework to analyze and assess organizational structures. Furthermore, the thesis leverages the potential of text mining as a method to identify and visualize patterns in texts that reflect prevalent paradigms in communication. The thesis applies the above conceptual and methodological basis in three case studies. Case Study 1 investigates the measures proposed in 16 municipal climate action plans of regional centers in Lower Saxony, Germany. It uses a text mining approach in the form of an Summary interpretation network analysis. It analyzes how different societal subsystems are connected at the semantic level and to what extent sustainability principles can be recognized. Case Study 2 analyzes and reflects paradigms and discursive network structures in international scientific publications on sustainable energy. The study investigates 26533 abstracts published from 1990 to 2016 using a text mining approach, in particular topic modeling via latent Dirichlet allocation. Case Study 3 turns again to the cases of municipal climate action in Lower Saxony examined in Case Study 1. It examines the involvement of climate action managers of these cities in multilevel knowledge processes. Using design principles for knowledge systems, it evaluates to what extent knowledge is managed in this field across levels for supporting the energy transition and to what extent local innovation potential is leveraged or supported. The three case studies show that international research on sustainable energy and municipal climate action in Germany provide promising contributions to achieve a transformation towards sustainability but do not fully reflect the complexity of society and still support a growth paradigm, in contrast to a holistic sustainability paradigm. Further, the case studies show that research and local action are actively engaging with the diversity of energy technologies but are lagging in dealing with the socio-epistemic (communication) system, especially with regard to achieving cohesion. Using the example of German municipalities, Case Studies 1 and 3 highlight the challenges of achieving coherent local action for sustainability and bottom-up organizational learning due to incomplete or uncoordinated multilevel knowledge exchange.
Collaborative governance is a promising approach to address the difficult challenges of sustainability through global public and private partnerships between diverse actors of state, market and civil society. The textile and clothing industry is an excellent example where a variety of such initiatives have evolved to address the wicked sustainability challenges. However, the question arises whether collaborative governance actually leads to transformation. In this dissertation, the author therefore questions whether and how collaborative governance in the textile sector provides space for, or pathways to, sustainability transformation. In three scientific articles and this framework paper, the author uses a mixed-methods research approach and follows scholars of sustainability science towards transformation research. First, he conducts a systematic literature review on inter-organizational and governance partnerships before diving into a critical case study on an interactive collaborative governance initiative, the German Partnership for Sustainable Textiles (Textiles Partnership). The multi-stakeholder initiative (MSIs) was initiated by the German government in 2015 and brings together more than 130 organizations and companies from seven stakeholder groups. It aims at improving working conditions and reducing environmental impacts in global textile and clothing supply chains. In two empirical articles, the author then explores learning spaces in the partnership and the ways in which governance actors navigate the complex governance landscape. For the former, he uses a quantitative and qualitative social network analysis based on annual reports and qualitative interviews with diverse actors from the partnership. Then, he uses qualitative content analysis of the interviews, policy documents and conducts a focus group discussion to validate assumptions about the broader empirical governance landscape and the social interactions within. Finally, in this framework paper, he uses theories of transformation to distinguish forms of change and personal, political and practical spheres of transformation, and reflects on the findings of the three articles in this cumulative dissertation.
This doctoral thesis contains four empirical studies analysing the personal accountability of prime ministers and the electoral presidentialisation of parliamentary elections in European democracies. It develops the concept of presidentialised prime ministerial accountability as a behavioural element in the chain of accountability in parliamentary systems. The ongoing presidentialisation of parliamentary elections, driven by changes in mass communication and erosion of societal cleavages, that fosters an increasing influence of prime ministers' and other leading candidates' personalities on vote choices, has called performance voting – and the resulting accountability mechanism of electoral punishment and reward of governing parties – into question. This thesis analyses whether performance voting can be extended to the personal level of parliamentary governments and asks whether voters hold prime ministers personally accountable for the performance of their government. Furthermore, it explores how voters change their opinion of prime ministers and how differences in party system stability and media freedom between Western and Central Eastern Europe contribute to higher electoral presidentialization in Central Eastern European parliamentary elections. This thesis relies on several national data sources: the "British Election Study", the "German Longitudinal Election Study" and other German election surveys, the "Danish Election Study", as well as, data from the "Forschungsgruppe Wahlen". In addition, it utilises cross-national data from the "Comparative Study of Electoral Systems".
Internet- and mobile technologies are increasingly used to deliver mental health care. E-Mental Health is promising for the prevention and treatment of mental disorders. However, while E-Mental Health was shown to be an effective treatment tool, fewer studies investigated the prevention of mental health problems with E-Mental Health approaches. In a series of three studies, this dissertation examines internet- and mobile-based approaches for the early monitoring and supporting of mental health. First, a pilot study investigates the use of smartphone data as collected by daily self-reports and sensor information for the self-monitoring of bipolar disorder symptoms. It was found that some, but not all smartphone measurements predicted clinical symptoms of mania and depression, indicating that smartphones could be used as an earlywarning system for patients with bipolar disorder. Second, a randomized controlled trial evaluates the effectiveness of an internet-based intervention among persons with depression and sickness absence. The intervention was found to be effective in reducing depressive symptoms compared to a control group, suggesting that the internet can provide effective support for people with sickness absence due to depression. Third, a study protocol proposes to combine self-monitoring with a mobile intervention to support mental health in daily life. Supportive self-monitoring will be evaluated in a fully mobile randomized controlled trial among a sample of smartphone users with psychological distress. If supportive self-monitoring on the basis of a smartphone application is effective, it could be widely distributed to monitor and support mental health on a population level. Finally, the contribution of the presented studies to current research topics in E-Mental Health is discussed.
The wide accessibility of the Internet and web-based programs enable an increased volume of online interventions for mental health treatment. In contrast to traditional face-to-face therapy, online treatment has the potential to overcome some of the barriers such as improved geographical accessibility, individual time planning, and reduced costs. The availability of clients' treatment data fuels research to analyze the collected data to obtain a better understanding of the relationship among symptoms in mental disorders and derive outcome and symptom predictions. This research leads to predictive models that can be integrated into the online treatment process to assist clinicians and clients. This dissertation discusses different aspects of the development of predictive modeling in online treatment: Categorization of predictive models, data analyses for predictive purposes, and model evaluation. Specifically, the categorization of predictive models and barriers against the uptake of mental health treatment are discussed in the first part of this dissertation. Data analysis and predictive modeling are emphasized in the second part by presenting methods for inference and prediction of mood as well as the prediction of treatment outcome and costs. Prediction of future and current mood can be beneficial in many aspects. Inference of users' mood levels based on unobtrusive measures or diary data can provide crucial information for intervention scheduling. Prediction of future mood can be used to assess clients' response to the treatment and expected treatment outcome. Prediction of the expected treatment costs and outcomes for different treatment types allows simultaneous optimization of these objectives and to increase the cost-effectiveness of the treatment. In the third part, a systematic predictive model evaluation incorporating simulation analyses is demonstrated and a method for model parameter estimation for computationally limited devices is presented. This dissertation aims to overcome the current challenges of predictive model development and its use in online treatment. The development of predictive models for varies data collected in online treatment is demonstrated and how these models can be applied in practice. The derived results contribute to computer science and mental health research with client individual data analysis, the development ofpredictive models, and their statistical evaluation.
Strong sustainability, according to the common definition, requires that different natural and economic capital stocks have to be maintained as physical quantities separately. Yet, in a world of uncertainty this cannot be guaranteed. To therefore define strong sustainability under uncertainty in an operational manner, we propose to use the concept of viability. Viability means that the different components and functions of a dynamic, stochastic system at any time remain in a domain where the future existence of these components and functions is guaranteed with sufficiently high probability. We develop a unifying and general ecological-economic concept of viability that encompasses the traditional ecological and economic notions of viability as special cases. It provides an operational criterion of strong sustainability under conditions of uncertainty. We illustrate this concept and demonstrate its usefulness by applying it to livestock grazing management in semi-arid rangelands.