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ItemTowards a Better Future of Work: Enhancing Efficiency, Promoting Fairness, and Upholding Labor Standards in the Contemporary Workplace(Georgia Institute of Technology, 2024-04-27) Ding, LiThe three essays in this dissertation examine critical issues at the intersection of the future of work and labor practices. As the nature of employment and the workplace continues to evolve, it is essential to consider how these changes might affect organizational efficiency, worker welfare, and broader societal implications. In the dissertation, I focus on three important contexts that shape the future of work, which are digital service platforms, gig economy platforms, and global supply chains, in each essay. I adopt empirical methodologies including structural estimation, policy simulations, online experiments, and econometric analyses to offer actionable insights for organizations and policymakers to navigate the complexities of the changing work landscape and work towards a better future of work.
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ItemEssays on Fintech, AI, and Innovation in Finance(Georgia Institute of Technology, 2024-04-25) Du, WendiThe dissertation consists of five essays on FinTech, AI and innovation in finance. These essays center around how innovation and capital market influence each other, and how to use cutting-edge technologies like machine learning and AI to address the economic questions that would otherwise remain unanswered. In the first essay, I investigate the redeployability channel of trademarks' collateral value. Using a novel court decision that exogenously weakens trademark redeployability, I find a 3.4 percentage point reduction in affected firms’ book leverage, equivalent to a 16.9\% decrease in their average book leverage. By using firm-level trademark portfolio data and employing natural language processing (NLP) techniques, including ChatGPT, I show that firms with more licensed trademarks (i.e., those more exposed to the court ruling), experience a stronger negative impact. Additionally, affected firms are less likely to pledge their registered trademarks as collateral afterward. When they do pledge, they pledge a greater number of trademarks, as well as more valuable ones. Affected firms also register fewer new trademarks in the future. In sum, my results highlight the value of trademark collateral in enhancing firms' debt capacity through its redeployability channel. In the second essay, we develop a text-based measure of firm-level inflation exposure from earnings calls. Our deep learning model identifies sentences discussing price changes, while distinguishing price increases from decreases and inputs from outputs. Our aggregate inflation exposure measure strongly correlates with official inflation measures. Firms with higher inflation exposure experience negative stock price reactions to earnings calls. The price reaction is attenuated when a firm has pricing power. Further, firms with higher inflation exposure have higher future costs of goods sold and lower operating cash flows. They perform worse on Consumer Price Index (CPI) release days when CPI exceeds the consensus forecast. In the third essay, we explore the area of emerging technologies which can potentially transform business and society but are difficult to identify and prone to hype and uncertainty. We construct a dictionary of emerging technology phrases from earnings calls using deep learning techniques and document an immediate positive stock market reaction to firms’ discussions of emerging technologies. We find that the positive reaction is more pronounced when firms discuss emerging technologies early in their life cycle. Firms with lower ex-ante credibility, such as a prior history of earnings management, innovate less ex-post and experience poorer long-term returns. Overall, our results highlight when firms' discussions of emerging technologies convey credible information to investors. The fourth essay examines whether managers walk the talk on the environmental and social discussion. We train a deep-learning model on various corporate sustainability frameworks to construct a comprehensive Environmental and Social (E\&S) dictionary. Using this dictionary, we find that the discussion of environmental topics in the earnings conference calls of U.S. public firms is associated with higher pollution abatement and more future green patents. Similarly, the discussion of social topics is positively associated with improved employee ratings. The association with E\&S performance is weaker for firms that give more non-answers and when the topic is immaterial to the industry. Overall, our results provide some evidence that firms do walk their talk on E\&S issues. In the final essay, we address the limitations of generic training schemes in the realm of financial language models. We propose a novel domain specific Financial LANGuage model (FLANG) which uses financial keywords and phrases for better masking. We further extend it to include span boundary objective and in-filing objective, utilizing the fact that many financial terminologies are phrases. Additionally, the evaluation benchmarks in the field have been limited. To this end, we contribute the Financial Language Understanding Evaluation (FLUE), an open-source comprehensive suite of benchmarks for the financial domain. These include new benchmarks across 5 NLP tasks in financial domain as well as common benchmarks used in the previous research. Experiments on these benchmarks suggest that our model outperforms those in prior literature on a variety of NLP tasks.
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ItemEmployee Evaluation and Performance Management(Georgia Institute of Technology, 2023-04-27) Green, Christopher M.The three essays in this dissertation focus on understanding how the structural policies and organizational procedures set by management may impact the performance of the workforce. Specifically, this dissertation: (i) employs analytical (e.g. game-theoretical and optimization models) and experimental techniques and (ii) encompasses the following three areas: performance management systems, rating systems, and sequential selection. Performance and Talent Management: The U.S. Army is at an inflection point with its talent management process. The Secretary of the Army has stated that a focused priority of the Army is to revolutionize the decades old process that was established in the 1980s under the Defense Officer Personnel Management Act (DOPMA) which has fallen woefully behind current talent and personnel management programs. One of the most promising areas for change is in the arena of performance management. To support this effort, I review performance management and evaluation systems studied in literature and currently in use within industry to identify how organizational and structural characteristics impact their effectiveness. I then apply this analysis to the unique case of the U.S. Army. The procedural limitations and legal constraints set on the military services make understanding and incorporating the factors of the external environment and organization structure critical to constructing a performance management system that meets the unique needs of these organizations. Rating Systems: Performance evaluation has long been a key mechanism for supervisors to grade the proficiency of employees at executing the tasks associated with their jobs. To conduct these evaluations firms often rate workers compared to their peers or against an objective standard. Which of these rating systems leads to higher workforce performance? To answer this question, I construct game-theoretic models of two performance rating systems. First, for a Relative rating system where workers compete with each other for a constrained number of high ratings. Second, for an Absolute rating system where workers are awarded high ratings by performing at or above a standard threshold. I derive the workers’ equilibrium performance as a function of their ability and the characteristics of the rating pool. From a firm’s perspective, I find that an Absolute rating system can lead to higher performance than a Relative rating system when the rating pool size is small or the workers’ cost of effort relative to their efficiency rate is low, and the reverse holds true otherwise. When considering the workers’ perspective, I find that higher ability workers prefer an Absolute system due to its predictable nature, while lower ability workers prefer a Relative system as it provides them an opportunity to outperform other workers. Sequential Selection: Enhancing workforce performance is the key to success for professional firms. Many firms employ competitive rating systems where supervisors can only award promotions or bonuses to a certain percentage of their subordinates. In many cases, such as the evaluation system of the U.S. Army, supervisors evaluate subordinates' performances over time and in sequence (e.g., based on employee’s work anniversary). As such, supervisors must make decisions based on incomplete information due to the temporal nature of the evaluation process. In this paper, I study how managers react under such sequential evaluation systems. I construct a theoretical model of a sequential selection problem to generate the optimal solution. I then conduct a set of experimental studies and evaluate the impact of pool size on the accuracy of each participant's decisions as compared to the state dependent optimal solutions. Despite theoretical increases in performance with larger pools, experimental performance did not yield an increase. Indeed, the average performance of subjects was the highest in the treatment that had the smallest pool size. I conduct multiple decision mechanism analyses to provide insights about the approaches subjects take and the nature of the behavioral traits leading to sub-optimal outcomes. Those comparisons suggest that the search fatigue mechanism may account for subjects’ sub-optimal behavior across treatments.
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ItemAm I Paranoid or Did I Just Receive Advice?: The Impact of Disability Status on Recipient Behavior Following Unsolicited Advice(Georgia Institute of Technology, 2023-04-17) Speach, Mary Eve PatriceAlthough advice in the workplace is associated with positive outcomes, employees tend not to seek out advice from coworkers. As such, organizations may be tempted to encourage unsolicited advice between employees to maximize benefits. However, little is understood regarding its detrimental effects for particular groups of employees. Therefore, I leverage the literature on advice and model of stigma-induced identity threat to assert that those with disabilities, due to their unique backgrounds, are more likely to perceive unsolicited advice as an identity threat. This dissertation posits that this heightened perception, also known as an identity threat appraisal, will influence levels of paranoid cognition and decrease daily work engagement. Furthermore, given that not all advice is equal I propose that the nature of the unsolicited advice offered (message and context) may operate as features of advice, impacting paranoid cognition levels. Results of Study 1 indicate that recipients of unsolicited advice experience greater levels of paranoid cognition than those in the control condition. Study 2 explores the features of unsolicited advice through a vignette experimental design. Findings illustrate that paranoid cognition varies as a function of context but not message. Using an ESM approach, Study 3 replicates the main effect findings of the previous studies and links paranoid cognition to daily work engagement. Finally, for the moderating effects those with a disability who received public unsolicited advice reported higher levels of paranoid cognition than those without a disability in the third study. Theoretical and practical implications of this model are discussed.
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ItemInnovation and Supply Networks(Georgia Institute of Technology, 2023-01-13) Palit, ShubhobrataThe three essays in this dissertation aim to improve our understanding of the influence of a firm’s network of buyers and suppliers as a source of external technological knowledge and, subsequently on its innovation performance. Such understanding is important for effectively managing technological knowledge, which involves managing not only the firm’s internal but also external technological knowledge. In the first essay (Chapter 2), I focus on the available technological knowledge in a firm’s supplier network and examine factors that accrue innovation benefits from such knowledge for a buyer firm. Specifically, I study technological distance, technological breadth, and extent of global sourcing, and how these factors interrelate in influencing a firm’s innovation performance. In the second essay (Chapter 3), I focus on a buyer as a source of technological knowledge for a supplier, and examine factors that make a supplier accumulate technological knowledge from the buyer. Specifically, I study how buyer innovation, technological similarity between a supplier and a buyer, a supplier’s dependence on a buyer, buyer-supplier size asymmetry, and the interrelationships between them influence the extent of supplier’s knowledge accumulation from the buyer. In the third essay (Chapter 4), I study the extent of a supplier’s knowledge accumulation from its buyers as a mechanism through which buyer innovation positively influences supplier innovation performance. Additionally, I demonstrate the moderating role of the supplier’s position within its supply network on the indirect effect of buyer innovation on supplier innovation performance.