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Data has become a necessary resource for firm operations in the modern digital world, explaining their growing data gathering efforts. Due to this development, consumers are confronted with decisions to disclose personal data on a daily basis, and have become increasingly intentional about data sharing. While this reluctance to disclose personal data poses challenges for firms, at the same time, it also creates new opportunities for improving privacy-related interactions with customers. This dissertation advocates for a more holistic perspective on consumers’ privacy-related decision-making and introduces the consumer privacy journey consisting of three subsequent phases: pre data disclosure, data disclosure, post data disclosure. In three independent essays, I stress the importance of investigating data requests (i.e., the first step of this journey) as they represent a largely neglected, yet, potentially powerful means to influence consumers’ decision-making and decision-evaluation processes. Based on dual-processing models of decision-making, this dissertation focuses on both consumers’ cognitive and affective evaluations of privacy-related information: First, Essay 1 offers novel conceptualizations and operationalizations of consumers’ perceived behavioral control over personal data (i.e., cognitive processing) in the context of Artificial Intelligence (AI)-based data disclosure processes. Next, Essay 2 examines consumers’ cognitive and affective processing of a data request that entails relevance arguments as well as relevance-illustrating game elements. Finally, Essay 3 categorizes affective cues that trigger consumers’ affective processing of a data request and proposes that such cues need to fit with a specific data disclosure situation to foster long-term decision satisfaction. Collectively, my findings provide research and practice with new insights into consumers’ privacy perceptions and behaviors, which are particularly valuable in the context of complex, new (technology-enabled) data disclosure situations.
In the ongoing 21st century, low- and middle-income countries will face two health challenges that are thoroughly different from what these countries have been dealing with in preceding centuries. First, they are confronted with surging rates of non-communicable diseases (NCDs), and second, climate change will take its toll and is predicted to cause catastrophic health impairments and exacerbate chronic health conditions further. Both will pose a disproportionate health and economic burden on low- and middle-income countries, which are also the countries least able to cope with them. By threatening individual health and socioeconomic improvements, and by putting an immense burden on already constrained health care systems, they impede the progress in poverty reduction and widen health inequities between the rich and the poor.
Against this background, this thesis investigates the potential of NCD prevention and treatment measures in the context of Southeast Asia, with case studies in Indonesia. Specifically, it seeks to understand what kind of health interventions have the potential to be (cost-)effective considering the cultural background, lifestyle, health literacy and health system capacities in the region. Further, this thesis analyzes the interplay between NCDs and climate change and assesses the financial burden that both might pose in the decades to come. Hence, this thesis contributes to a better understanding of how the two health challenges of the 21st century, NCDs and climate change, can be addressed in the context of Southeast Asia and offers insights into what type of health policies and interventions can play a supportive role.
Abstract 1: This paper investigates whether market quality, uncertainty, investor sentiment and attention, and macroeconomic news affect bitcoin price discovery in spot and futures markets. Over the period December 2017 – March 2019, we find significant time variation in the contribution to price discovery of the two markets. Increases in price discovery are mainly driven by relative trading costs and volume, and by uncertainty to a lesser extent. Additionally, medium-sized trades contain most information in terms of price discovery. Finally, higher news-based bitcoin sentiment increases the informational role of the futures market, while attention and macroeconomic news have no impact on price discovery.
Abstract 2: We investigate whether local religious norms affect stock liquidity for U.S. listed companies. Over the period 1997–2020, we find that firms located in more religious areas have higher liquidity, as reflected by lower bid-ask spreads. This result persists after the inclusion of additional controls, such as governance metrics, and further sensitivity and endogeneity analyses. Subsample tests indicate that the impact of religiosity on stock liquidity is particularly evident for firms operating in a poor information environment. We further show that firms located in more religious areas have lower price impact of trades and smaller probability of information-based trading. Overall, our findings are consistent with the notion that religiosity, with its antimanipulative ethos, probably fosters trust in corporate actions and information flows, especially when little is known about the firm. Finally, we conjecture an indirect firm value implication of religiosity through the channel of stock liquidity.
Abstract 3: This study shows that higher physical distance to institutional shareholders is associated with higher stock price crash risk. Since monitoring costs increase with distance, the results are consistent with the monitoring theory of local institutional investors. Cross-sectional analyses show that the effect of proximity on crash risk is more pronounced for firms with weak internal governance structures. The significant relation between distance and crash risk still holds under the implementation of the Sarbanes-Oxley Act, however, to a lower extent. Also, the existence of the channel of bad news hoarding is confirmed. Finally, I show that there is heterogeneity in distance-induced monitoring activities of different types of institutions.