Title of Paper

IPA Gap Scores and Travel Intentions

Author Bios (50 Words for each Author)

Dr. Bynum Boley is an Associate Professor of Parks, Recreation and Tourism Management at the University of Georgia. His research focuses on sustainable tourism and how the unique natural and cultural resources of tourism destinations jointly relate to resident quality of life and destination competitiveness.

Dr. Evan Jordan is an Assistant Professor in the Department of Health and Wellness Design in the School of Public Health at Indiana University. His research focuses on the impacts of tourism on the physical and mental health of residents of host communities. He is particularly interested in tourism’s impact on stress, emotions, and quality of life and their implications for public health.

Abstract (150 Words)

While the tourism literature has extended Importance Performance Analysis (IPA) in many ways, there has been little use of gap scores associated with the differences between performance and importance perceptions to see how these proxy measures of satisfaction influence intent to travel. With this gap in mind, we walk readers through how gaps scores associated with IPA can be calculated and subsequently used as independent variables within multiple regression equations to identify destination attributes that influence intent to travel. 21 destination-level attributes were administered to 1,653 international travelers from each of the U.S.’ top five markets (U.K., Canada, Mexico, Japan, and China) within an IPA format. Results revealed the gap scores associated with safety, price, national parks, food, scenery, and transportation were significant predictors of intent to travel. Pairing these results with traditional IPA graphs adds an extra layer of interpretation for managers seeking to improve their destination’s image.

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IPA Gap Scores and Travel Intentions

While the tourism literature has extended Importance Performance Analysis (IPA) in many ways, there has been little use of gap scores associated with the differences between performance and importance perceptions to see how these proxy measures of satisfaction influence intent to travel. With this gap in mind, we walk readers through how gaps scores associated with IPA can be calculated and subsequently used as independent variables within multiple regression equations to identify destination attributes that influence intent to travel. 21 destination-level attributes were administered to 1,653 international travelers from each of the U.S.’ top five markets (U.K., Canada, Mexico, Japan, and China) within an IPA format. Results revealed the gap scores associated with safety, price, national parks, food, scenery, and transportation were significant predictors of intent to travel. Pairing these results with traditional IPA graphs adds an extra layer of interpretation for managers seeking to improve their destination’s image.