In an effort to reduce exorbitant employee turnover, the hospitality industry has recently offered career development programs to their employees in pursuit of longer retention. Such educational human resource (HR) practices are expected to increase the skill flexibility of individual employees (i.e., individual skill breadth) across a wide range of skill categories, leading to lower turnover through improved job satisfaction. However, the empirical association between employee skill flexibility and turnover at the individual level has remained unexplored in the HR literature. This study fills in this research gap by drawing on the theoretical framework of employee skill flexibility in the field of strategic human resource management (SHRM). Building on a unique data set from over 10,000 LinkedIn profiles among hotel employees in major brands across the United States, we operationalize their skill flexibility and find its association with turnover. For this purpose, we first identify seven hotel employee-specific skill categories using an unsupervised machine-learning method and subsequently quantify skill flexibility at the individual level. Our results show that the association between skill flexibility and turnover is moderated by skill categories. This study contributes to the HR literature as a data-driven implementation of human capital analytics (HCA). / Doctor of Philosophy / Employee turnover has long been a critical issue in the hospitality industry. According to the US Bureau of Labor Statistics, the hospitality sector had a turnover rate of 86.3% in 2021, while the average of all industries is 47.2%. As the quality of customer service in hotels is directly linked to the competence of employees, it is essential to reduce the turnover rate and retain highly skilled workers for long-term competitiveness. One of the most effective ways to achieve this is by developing employees' skill sets through upskilling and reskilling practices (Deloitte, 2020), which can improve their flexibility and performance in the workplace. By analyzing the profiles of 10,560 hotel employees on LinkedIn, this study identified key skill categories using machine-learning-based text analytics, then, two main variables are operationalized: individual skill flexibility using the Herfindahl-Hirschman index and turnover frequency. This study found that the role of individual skill flexibility on turnover is contingent on specific skill categories employees have. Individual skill flexibility is negatively associated with turnover in employees with accounting and finance skills, but employees with software skills show a positive association between individual skill flexibility and turnover. The findings in this study suggest that hotel managers and HR practitioners need to implement customized skill training programs based on their employees' primary skill sets. By doing so, they can focus more specifically on individual career development, continuously reconfigure their workforce, and improve the company's resilience. By reducing turnover rates and retaining highly skilled employees, hotels can also enhance customer service quality and achieve a competitive advantage in the long run. Such findings are largely consistent with anecdotal evidence found in major hotel brands and operators.

No description available.

The thesis investigates the effects of industrial automation on post-secondary education enrollment. To assess the effects, we build linear regression models to estimate the impact of the surge in the stock of industrial robots on post-secondary enrollment across 50 U.S. states and 41 countries. Drawing upon these estimates and the literature documenting the structural shift in the labor market, we find that recent developments in the fields of automation and robotics have contributed to a shift in demand for post-secondary education, with panel data models that control for both country and time fixed unobservables indicating a significant decline in enrollment for 4-year degree programs internationally.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.