Date of Conferral
2019
Degree
Ph.D.
School
Management
Advisor
Steven Tippins
Abstract
Many managers of Puerto Rican corporations have not been able to assist employees in their recovery from the devastation left by Hurricane Maria. This lack of assistance has resulted in high employee attrition rates, low productivity, anxiety, isolation, anguish, despair, panic attacks, and depression. Scholarly literature lacks research on emotional intelligence and learning in corporate, postdisaster contexts; both capacities may mitigate employee stress due to the uncertainty inherent in postdisaster conditions and motivate employees to persevere in the face of adversity. The purpose of this quantitative study was to assess the relationship between employee learning, emotional intelligence, and organizational performance. The theoretical framework applied was human capital theory. The research questions focused on how employee learning and emotional intelligence are related to organizational performance. The sample was 90 full-time employees of multinational corporations in Puerto Rico. Data were collected through SurveyMonkey using the Workplace Learning Scale, the Trait Meta-Mood Scale, and the Organizational Performance Scale. Regression analysis was used to analyze the data, and both employee learning and emotional intelligence were found to have a statistically significant positive relationship with organizational performance (β = .563, p = .000; β = .348, p = .000). To more fully capture participants' thoughts and feelings, a mixed methodology is recommended for future research. The results of this study could assist human resources managers in their selection of training that enables employees to gain the skills needed to support business continuity and personal welfare in postdisaster environments.
Recommended Citation
Lopez-Martinez, Jose A., "Relation between Employee Learning, Emotional Intelligence, and Organizational Performance" (2019). Walden Dissertations and Doctoral Studies. 7485.
https://scholarworks.waldenu.edu/dissertations/7485