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This doctoral thesis is concerned with two separate but intertwined topics in the field of financial econometrics: (i) the measurement and relevance of new sources of information on financial markets in the form of online investor sentiment and attention and (ii) nonlinearities in financial time series in the form of structural breaks. According to classical finance theory, competition among rational investors, often called arbitrageurs, leads to an equilibrium in which prices on capital markets equal the present value of expected future cash flows. Under this theoretical lens, the trading decisions of irrational investors have no significant impact on prices since their demands are offset by rational investors. However, the classical finance theory fails to fit the extreme levels of and changes in stock prices corresponding to events such as the Great Crash of 1929 or the Dot.com bubble of the 1990s, which are difficult to align with any rational explanation. Akin to the notion of "animal spirit" first coined by Keynes (1936), behavioral finance theory sets out to augment the classical model by explicitly taking into account two assumptions: Firstly, trading activities of investors are thought of to be partially influenced by subjective beliefs about investment risks and future cash flows, generally referred to as investor sentiment. Secondly, there are limits to arbitrage in the sense that betting against sentiment-driven investors is associated with higher risks and costs. Thus, inconsistent with predictions of the classical finance theory, arbitrageurs do not aggressively force prices to fundamentals. On this basis, irrational (collective) investor behavior has moved into the focus of modern finance theory and corresponding empirical applications. The widespread internet access and usage of social media platforms in recent years have led to new sources of information - and with them new sources and types of data that can be used by researchers and practitioners alike - pertaining to this collective investor behavior and corresponding financial market outcome: Short messages published on social media platforms such as Twitter or StockTwits on the one hand and online search queries on the other. The first part of this thesis makes use of such data in empirical financial applications, also from a high-frequency intraday perspective, in order to assess its impact on predictions of financial variables and to unravel new relationships. In general, it is reasonable to assume that many relationships in economics and finance are nonlinear. Thus, several kinds of nonlinearities can arise when considering financial markets and time series of financial variables that are not necessarily approximated well by simple linear models. Relating to the behavioral finance literature, the model of De Long et al. (1990) proposes that in the presence of sentiment-prone noise traders the price of a risky asset evolves as a nonlinear function of these noise traders' average bullishness (i.e., their mean misperception of the expected price) and its variance. Though being of a different philosophical nature than sentiment-induced noise trader theories, some other models of trade based on noninformational reasons, such as changes in risk aversion or liquidity needs, also involve nonlinear relations. The second part of the thesis focuses on one often overlooked kind of nonlinearity that entails potentially more severe implications, namely structural breaks in financial time series. Structural breaks, also referred to as change-points, in the data generating process underlying a given univariate time series do not only constitute a source of nonlinearity that can be modeled but also a more subtle source of nonstationarity. Given that endeavors of time series model building and prediction usually demand some stationarity assumption to be made, the latter poses a common problem in the analysis of univariate economic and financial time series. Matters are complicated by the fact that the exact number and timing of structural breaks are usually unknown ex-ante. Therefore, the consistent estimation of structural breaks, or change-points, has been studied extensively in the related literature. This thesis adds to the ongoing discussion by proposing a two-step model selection procedure for the detection and timing of change-points in structural break autoregressive models. A similar methodology is then used to investigate the effect of Box-Cox transforms on the estimation of structural breaks in realized volatility time series.

Confidence judgments and decision making are part of everyday life. In an ideal world, people would assess their skills and knowledge accurately and base their decisions only on rational deliberations. Yet, this is often not the case. Confidence judgments in own skills or performance are often biased (e.g., Dunning, 2011; Moore & Healy, 2008; Moore & Schatz, 2017; Sanchez & Dunning, 2018; Pikulina, Renneboog, & Tobler, 2017; Michailova & Schmidt, 2016). Also, people tend to deviate from rational decision strategies (e.g., Achtziger & Alós-Ferrer, 2014; Alós-Ferrer, Hügelschäfer, & Li, 2016, 2017; Charness, Karni, & Levin, 2010; Erev, Shimonovich, Schurr, & Hertwig, 2008; Fiedler, Brinkmann, Betsch, & Wild, 2000; Tschan et al., 2009). Therefore, the research aim of the present dissertation was twofold. In the first chapter of the present dissertation I investigated confidence judgments in own skills and the confidence bias, the processes underlying these confidence judgments, and the influences of gender and monetary incentive on confidence judgments. The second aim was to investigate the influence of goal and implementation intentions on rational decision making and how this influence is reflected in the neural correlate of reinforcement learning. A common finding in research on confidence judgments is the confidence bias (e.g. Moore & Schatz, 2017; Moore & Healy, 2008; Pikulina et al., 2017; Sanchez & Dunning, 2018; Lebreton et al., 2018). In most cases, the confidence bias reflects overconfidence, which means that people’s subjective confidence exceeds their actual ability or performance (Fischhoff, Slovic, & Lichtenstein, 1977). In some cases, there is also evidence for underconfidence, suggesting that people underestimate their abilities (Kruger & Dunning, 1999; Kruger & Burrus, 2004). Gender is an important predictor of the confidence bias. Underconfidence is more prevalent in females, whereas males often display overconfidence (e.g., Barber & Odean, 2001; Hügelschäfer & Achtziger, 2014; Niederle & Vesterlund, 2007). In Study 1, I investigated the processes underlying confidence judgments and the confidence bias by means of response times, and I examined potential gender differences. Participants answered general knowledge questions and judged their confidence on the correctness of each answer. Participants had overall a good sense of whether their answer was correct or incorrect. This was reflected by higher confidence judgments on correct answers compared to incorrect ones. The analysis of response times on the confidence judgments revealed that male participants who took longer to judge their confidence were made more accurate judgments than males who responded quickly. This relationship was not found for females. In Study 2, half of the participants received a monetary incentive for good performance in the general knowledge test. The monetary incentive for performance increased the time invested in both tasks (the knowledge questions and the confidence judgments). However, this increased effort did not lead to better performance on the knowledge questions, nor did it yield more accurate confidence judgments. The response times suggested that males who invested more time in the confidence judgments were more accurate (as in Study 1). However, the opposite was true for females. The more time females invested in their judgment the more underconfident they were. This influence of the response time on the confidence bias was only found for incentivized participants. In Study 3, the accuracy of the confidence judgment was incentivized. Contrary to the expectations, the monetary incentive did not reduce the confidence bias but led both males and females to be overconfident. In this study, the response time on the confidence judgment did not predict the confidence bias. On the whole, the results demonstrate that (a) the processes of confidence judgments differ between females and males, and (b) the effectiveness of monetary incentives for improving the accuracy of confidence judgments depends strongly on the incentive being contingent on the performance in the task at hand. The second chapter of the present dissertation investigated the influence of goal and implementation intentions (P. M. Gollwitzer, 1999) on rational decision making (see also Hügelschäfer & Achtziger, 2017). The impact of intentions was examined by the neural correlate of reinforcement learning, i.e. the feedback-related negativity (FRN; Holroyd & Coles, 2002). Participants worked on a probability updating task in which the optimal strategy to maximize the expected payoff was to follow Bayes’ rule by integrating new information with prior probabilities (Bayes & Price, 1763). The optimal decision rule conflicted with a simpler suboptimal decision strategy, i.e. the reinforcement heuristic (see Achtziger & Alós-Ferrer, 2014; Charness & Levin, 2005). The goal and implementation intention manipulation was proposed to control the automatic process of the reinforcement heuristic and hence foster rational decision making. The results showed that the goal intention and the implementation intention had no influence on the number of reinforcement errors (in contrast to the findings of Hügelschäfer & Achtziger, 2017). However, both, the goal and implementation intentions increased the amplitude of the FRN which, on the neural level, indicated a stronger reliance on the reinforcement heuristic than in the control group. The findings shed some light on the impact of goal and implementation intentions on rational decision making. They demonstrate that careful consideration of the use of intentions as an intervention for improved decision making is required to avoid undesired side-effects. Taken together, the present dissertation provided new insights into the processes underlying confidence judgments, the confidence bias, rational decision making, and its neural correlates.

The global economy has gained momentum in recent years, with advances in technology and digitalization leading to shorter product life cycles, increased competition, and transformed industries. These circumstances call for the need for constant innovation. Organizations are required to act and adapt quickly to technological changes, dynamic markets, competitive threats, and rapidly altering customer needs, without losing focus of their established business. Two notions are important for organizations in this setting: (1) reaching ambidexterity and (2) structuring the front-end of innovation. Ambidextrous companies, which own the ability to balance between innovation activities that exploit current competencies (exploitation) and those that explore new competencies (exploration), are more successful than companies which concentrate on only one of these activities (Gibson & Birkinshaw, 2004; He & Wong, 2004; Jansen, Van Den Bosch, & Volberda, 2006; Katila & Ahuja, 2002; C. Kim, Song, & Nerkar, 2012). However, both exploration and exploitation require the allocation of resources, causing a trade-off, which makes it difficult to perform the combination of both (Greve, 2007; Levinthal & March, 1993). Previous research does not focus on how organizations can adapt their innovation activities in order to reach ambidexterity (Cantarello, Martini, & Nosella, 2012; Judge & Blocker, 2008; Z. Wei, Yi, & Guo, 2014). Managing innovations poses an increasingly daunting task for organizations, demanding different requirements regarding the innovation management process. Managing innovation through a structured innovation process facilitates the creation and planning of innovation to transform ideas into marketable products. The first stage of this process – the front-end of innovation – is of significant meaning, since activities in the front-end of innovation are strongly linked to innovation success (Dwyer & Mellor, 1991; Markham, 2013; Moenart, De Meyer, Souder, & Deschoolmeester, 1995; Reid & de Brentani, 2004). The creation of value and competitive advantage takes primarily place in the front-end of innovation, and the actual costs of mismanagement can only be discovered at later stages (Markham, 2013; Reid & de Brentani, 2004; P. Smith & Reinertsen, 1991). A concept to foster ambidexterity and structure the front-end of innovation described mainly by practitioners are so-called innovation fields (Cooper, Edgett, & Kleinschmidt, 2004; Crawford, 1980; Hambrick & Fredrickson, 2001; Khurana & Rosenthal, 1998; Reid & de Brentani, 2004; Talke, Salomo, & Rost, 2010). Innovation fields establish guidelines that determine search strategy, scope, depth, and locus of innovation search by setting search boundaries. Literature describes different types of applications for innovation fields such as strategic purposes, ideation, lifting synergies, technology intelligence and portfolio extension. With innovation fields, organizations (1) can structure the front-end of innovation and align corporate objectives to innovation activities and (2) have an instrument at hand to facilitate the shift of resources and to prioritize innovation activities according to the balance between exploitation and exploration, thereby fostering ambidexterity. However, research on innovation fields is scarce, thus, the objective of this dissertation is to examine how and why perceived contextual factors influence the intended application and perceived proficiency of innovation fields in the front-end of innovation. The theoretical foundation is based on the theory of organizational learning. A research framework is derived from acknowledged literature, focusing on (1) strategic orientation, (2) organizational context and (3) external environment as main contextual factors influencing the intended application of innovation fields. An explorative research design is followed, composed of an embedded single case study design using a mixed-methods approach. As a case, a corporate R&D division of a Germany-based company is selected. First, a qualitative study with semi-structured interviews is conducted, followed by a quantitative survey to get a more comprehensive picture of the role of perceived contextual factors influencing intended innovation field applications and proficiency. Based on the underlying empirical research, distinct differences regarding perceived contextual factors and their influence on intended innovation field applications and proficiency have been identified. Notably, the perceived contextual factors vary across the different types of applications for innovation fields. Overall, the strategic orientation and external environment have a strong influence on the intended innovation field applications and proficiency, while organizational context only play a minor role. Furthermore, the findings substantiate the use of different types of applications for innovation fields in the front-end of innovation. This study contributes to theory by creating a research framework linking perceived contextual factors to intended innovation field applications and proficiency. Finally, this dissertation delivers a comprehensive description of innovation field applications. The findings enhance the existing body of knowledge regarding innovation research, specifically regarding the front-end of innovation and innovation fields as well as organizational learning. Besides the advancement of scientific knowledge, managerial implications are drawn for the application of innovation fields in a corporate context.

Employees of public sector organizations serve as the backbone of democratic societies, making decisions that shape how and for whom vital public services are delivered. Public employees influence the realization of political goals and provide basic public goods as well as critical infrastructure. They are of high societal relevance as they represent the “human face of the state” and should incorporate public values to enable, serve, and protect the democratic system and the rule of law. According to the United Nations’ Sustainable Development Goal 16, effective public institutions must pay attention to employees as their most critical resource. The public sector––the largest or among the largest employers in most countries––faces a looming human resource crisis. Public employers face the need to replace a wave of baby boomers retiring and a decline in the number of people interested in working in the public sector. The COVID-19 pandemic highlights the shortage of professionals and leaders in the example of critical infrastructure such as public health authorities, hospitals, and social services. As a major field of research and practice, public human resource management (HRM) aims to understand these challenges and develop adequate coping strategies. However, the field faces relevant research gaps. Among other factors, the current scientific understanding is limited regarding the role of differences amongst organizational types in the public sector. Although previous research indicates the role of organizational goals and publicness dimensions for human resource practices in general, there is a lack of understanding to what extent the effects of motivation and pay dispersion differ, for example, between public administrations and state-owned enterprises (SOEs). The goal of this dissertation is to enhance the theoretical understanding of the role of motivation and pay dispersion for performance and recruitment focusing on differences amongst organizational types in the public sector, to derive theoretical perspectives on an integrated steering of human resources of public administration and SOEs. Overall, this dissertation highlights three contributions of the four included articles. First, it shows the important conceptual role of SOEs as research objects and offers approaches to further integrate SOEs as research objects in public HRM, taking into account the different institutional arrangements of public service provision, as organizational goals and publicness can be crucial and insightful determinants for motivation and pay dispersion. Second, the presented work offers new theoretical approaches and field-experimental insights for the under-researched public sector recruitment literature. Third, it derives theoretical perspectives on an integrated steering of human resources of public administration and SOEs as well as implications for future research on motivation and pay dispersion as major factors for performance and recruitment in public sector organizations.

Organizations that aim at delivering essential goods and services to low-income populations a the base of the pyramid increasingly blend the social welfare and the commercial logics in an effort to create financially sustainable solutions to social problems. Scholars have portrayed these cross-sectoral hybrid organizations as particularly agentic and resilient in institutionally complex settings, highlighting their ability to turn institutional voids into opportunity spaces. At the same time, the reconciliation of two antagonistic goals, namely poverty alleviation and financial value creation, as well as the multiple institutional voids that hybrid organizations face at the base of the pyramid (BoP) expose them to severe tensions. By investigating eight hybrid organizations in four countries, namely Colombia, Mexico, Kenya and South Africa, the present study contributes to a better understanding of cross-sectoral hybrid organizations in BoP settings in two ways. First, it shows that hybrid organizations not only face tensions between sector logics, but also between formal and informal, as well as between “Western-style” and “local style” strategic action fields. In settings which do not effectively provide guidance on the prioritization of social vs. financial objectives, these institutional voids manifest as tensions over goals and tensions over means in hybrid organizations. Second, the study sheds light on how field-level dynamics influence the ability of hybrid organizations to strategically employ factors that spur legitimacy advantages in an effort to turn institutional voids into opportunity spaces. Two different scenarios have been identified. One scenario refers to Colombia, Mexico and Kenya, which have been classified as fields that don’t effectively enforce a dominant sector logic concerning the legitimate way that health services should be provided to low-income populations. The present study has shown that in such fields, an organization’s logic of origin as well as the personal background of founders are factors that may spur legitimacy advantages in hybrid organizations. In effect, organizations which strategically employ these factors can select more freely from competing logics and ultimately overcome the prevailing tensions. This resonates with previous research, which has suggested that in fields with a dominant logic, hybrid organizations may take advantage of legitimacy advantages if their logic of origin corresponds to the dominant logic at the field level (Pache and Santos, 2012). However, the present study suggests that the factors leading to legitimacy advantages are more complex in fields with no effective dominant logic regarding social service provision. Here, the dominant logics among funding organizations, possible legitimacy spill-over effects from other market players, as well as the specifications of the commercial and the social welfare logics become important sources of possible legitimacy advantages. However, the study suggests that an organization’s ability to employ them strategically is dependent on their time of founding and their size. In addition to these findings, the study also provides insights on cross-sectoral hybridization in fields with a weakly enforced dominant logic, which is the second scenario that has been identified in South Africa. In particular, the study suggests that in such settings, hybrid organizations are more restricted to freely draw from competing logics, given that they face effective, normative imperatives about the goals they should pursue. However, the empirical investigation also indicates that an organization’s resource dependence structure is more influential than the encountered normative claims of audiences in health fields at the BoP. Further research is needed to refine these insights and explore cross-sectoral hybridization in social service provision fields in contexts of a weakly enforced dominant logic. Based on these findings, the author derives a range of practical recommendations that may themselves be interpreted as paradoxical. As the empirical study suggests, blended value creating hybrid organizations in Colombia, Mexico and Kenya currently face legitimacy advantages when originating from a commercial origin. The researcher is thus, on the one hand, inclined to recommend them to position themselves as commercially oriented organizations as to take advantage of the legitimacy advantages that the commercial logic currently entails. On the other hand, she cautions actors in the field of blended value creation, particularly funding entities, not to neglect the actual role of nonprofit organizations. The establishment of (health) markets that provide low-income populations in developing and emerging economies with affordable, high-quality products and services is likely to require significant unprofitable efforts. Finally, hybrid organizations in South Africa need to be more careful when adopting structures or practices from the commercial logic given the low legitimacy that this logic has in the health market at the BoP. There, organizations need to thoroughly analyze the institutional claims in the specific context of post-Apartheid South Africa.