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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.
Sustainability transitions research proposes fundamental changes of societal systems' organisation to overcome persistent societal challenges, such as climate change or biodiversity loss, and allowing systems to become more sustainable. This thesis adresses an underlying tension in sustainability transitions research: between transitions as an open-ended process of fundamental change and the normative direction of this change: sustainability. In doing so, three themes are in the focus of the research: individual agency, normativity and transdisciplinary collaboration. Thereby, the thesis aims to strengthen process-oriented and potentially transformative approaches to sustainability transition research, in contrast to primarily descriptive-analitical approaches. Transition management as a recent and salient example of transdisciplinary transition research is chosen to provide research framework and application context. Based on conceptual-theoretic, empirical case study and reflexive work, three main results are contributed: First, a psychologically enriched understanding of individual and sustainability related agency in conceptual and empirical understandings of transition management is developed. This builds on two perspectives: a psychologically enriched capability approach as well as the analysis of social effects (social learning, empowerment and social capital development) of transition management to capture sustainability oriented agency increases. As second main result, normative considerations, namely sustainability, are included into transition management on conceptual and empirical levels. Therein, substantive, procedural and intentional aspects of sustainability are combined: Substantive aspects are covered by proposing capabilities, behavioral freedoms to live a valuable life, as normative yardsticks to measure developments. Procedural aspects include a detailed understanding of facilitating a learning journey towards making sustainability meaningful in the local transition management cases and setting up experiments for its realiziation. Intentional aspects are addressed by linking social effects of transition management to awareness, motivations and feelings of responsibility towards sustainability. As a third main result, the transdisciplinary collaboration in transition management of creating an arena as an interactive learning space is conceptualized and explored, as well as the roles of the researchers therein. Key issues of this learning space, the community arena, are drawn out and ideal-type roles and activities of researchers in addressing these issues are proposed and empirically analysed. As synthesis of thesis results, ten principles of sustainability transition management are proposed.