Kim, Hyoeun2023-06-282023-06-282023-06-27vt_gsexam:37371http://hdl.handle.net/10919/115549In 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).ETDenIn CopyrightHotel Employee TurnoverEmployee Skill FlexibilityStrategic Human Resource ManagementHuman Capital AnalyticsLinkedInDissertation