The Moderating Effect of Gender in Urgent Care Service Satisfaction

Abstract

The objective of this study is to investigate the extent to which gender serves as a moderator in the relationships between healthcare service quality, patient satisfaction, and behavioral intention in the urgent care industry. Using the data collected from 253 male and 209 female urgent care patients, the moderating effect of gender was examined through partial least square structural equation modeling. Gender was found significant in the relationship between urgent care quality and patient satisfaction. To improve patient satisfaction among males, urgent care providers should focus on reducing negative emotions among male patients. This can be done by reducing the gap between their expectations and their perceptions, creating a warm environment in the urgent care facility, and alleviating patients' emotional vulnerability. The female community is more willing to pay a premium price and recommend the urgent care providers if they are satisfied. The practical implication is that urgent care providers should employ different strategies across gender to improve their perceptions of care quality and satisfaction level.

• behavioral intention
• gender
• partial least square structural equation modeling
• patient satisfaction
• urgent care service quality

Additional information

Notes on contributors

G Qin

Hong Qin is an associate professor at The University of Texas Rio Grande Valley. Her teaching and research specializations are in the areas of business analytics, decision making, and quality management. Qin is a peer reviewer for numerous leading journals in her field. She can be reached by email at [email protected].

Kittipong Boonme

Kittipong Boonme is an assistant professor in the School of Management at Texas Woman's University. Boonme has more than 15 years of management experience in the food service and hospitality industry with expertise in single-unit and multi-unit restaurant operations. His major research interests include consumer decision-making, service quality, and logistics and supply chain.

Benjamin George

Benjamin T. George is an assistant professor of business analytics at the University of South Dakota. He received his doctorate in management science from the University of North Texas in 2016. His current research interests include data and text analytics, the development of methodology in the new generation of statistical platforms, and consumer driven e-commerce analysis. He has published research in multiple fields including top academic journals such as Decision Science and Journal of Electronic Commerce Research. Prior to embarking on a career in academia, George focused within several production and operation management areas with extensive work in the fields of automated production lines and large-scale commercial and industrial construction.

Victor Prybutok

Victor Prybutok is a Regents professor of decision sciences and vice provost of the Toulouse Graduate School at the University of North Texas. He received his bachelor's degree from Drexel University, a master's degree in bio-mathematics, a master's degree in environmental health, and a doctorate in environmental analysis and applied statistics. Prybutok is an ASQ Certified Quality Engineer (CQE), Quality Auditor (CQA), Manager of Quality/Organizational Excellence (CMQ/OE), and an accredited professional statistician by the American Statistical Association. He authored more than 180 journal articles and 200–plus conference presentations.