Asymmetric importance-performance analysis: Measuring classification changes of destination attributes into basic,performance and excitement factors according to the segmentation criterion

Abstract

Studies combining Asymmetric Importance-Performance Analysis (AIPA) with segmentation are scarce and no study measures the magnitude of the changes in AIPA results when using different data sets: data sets belonging to general tourists and market segments. Consequently, no study evaluates whether one segmentation criterion produces greater changes in AIPA results than another. This study quantifies classification changes of destination attributes in AIPA results according to the previous visit and the origin of the visitors. Based on a sample of 409 tourists in Puerto López (Ecuador), results showed that “nature”, “adventure”, “sun and beach”, and “culture” were basic factors, while “grastronomy” was a performance factor. However, this classification differ considerably when different data sets are used, and especially, when considering segments by origin of the visitor.