Department of Sport Management
P.O. Box 118208
Gainesville, FL 32611-8208
(352) 294-1664 | email@example.com
Yonghwan Chang (Ph.D., University of Florida) is an Assistant Professor of Sport Management. Previously, Chang served as an Assistant Professor at the University of Minnesota and Texas Tech University from 2016 to 2020. For approximately three years, Chang worked at Kumho as a financial investment consultant. Chang has been named a North American Society for Sport Management (NASSM) Research Fellow. Chang has also been honored as an Emerging Scholar in Sport Marketing by the American Marketing Association’s (AMA) Sport and Sponsorship-Linked Marketing Special Interest Group.
Chang’s research interests are sport marketing and consumer behavior, with an emphasis on two lines of inquiry: (i) experiential consumption and (ii) sport sponsorship. Sport experiences are largely subjective, contextual, hedonic, and affective in nature, and thus he aims to provide an improved understanding of consumers’ decision-making processes as well as the benefits and values of sport experiences. He explores a variety of experiential consumption areas such as luxury services, spectator sports, and social media. The primary objective of his sport sponsorship research is to identify the complex network of brand associations stored in fans’ memory in order to optimize desirable consumption outcomes. He works toward expanding current sponsorship literature by integrating recent metacognitive accounts of consumers’ perception and assessment with the purpose of filling explanatory gaps in the existing research.
As a means to create innovative and impactful knowledge, Chang has a keen interest in adapting emerging technologies. He utilizes technologies in three ways: i) as a statistical tool, ii) as a measurement of consumer cognition and emotion, and iii) as a research context. He is proficient in the R programming language and open-source software for statistical analyses. Chang desires to improve and diversify existing methods in order to more accurately measure consumer cognition and emotions, thus overcoming response biases. In particular, he explores sport consumers’ unfiltered, natural, and real-life expression of their emotions by employing a combination of machine learning and Bayesian optimization techniques. Most recently, he utilizes entertainment technologies as research contexts in order to identify major industrial and academic trends. He explores the role of simulated environments in developing spectators’ emotional inertia and resilience.