This study attempts a comparison between AHP(Analytic Hierarchy Process) in which the importance weight is structured by individual subjective values and regression model with importance weight based on statistical theory in determining the importance weight of casual model. The casual model is designed by for students’ satisfaction with university, and SERVQUAL modeling methodology is applied to derive factors affecting students’ satisfaction with university. By comparison of importance weights for regression model and AHP, the following characteristics are observed. 1) the lower the degree of satisfaction of the factor, the higher the importance weight of AHP, 2) the importance weight of AHP has tendency to decrease as the standard deviation(or p-value) increases. degree of decreases. the second sampling is conducted to double-check the above observations. This study empirically checks that the importance weight of AHP has a relationship with the mean and standard deviation(or p-value) of independence variables, but can not reveal how exactly the relationship is. Further research is needed to clarify the relationship with long-term perspective.

The purposes of this study are to identify assessment items to evaluate riverfront for amenity and recreation and to analyze the relative importance of the items using Analytic Hierarchy Process(AHP). Total 15 items of 5 categories were identified through literature review and panel discussion. Based on the AHP analysis results, a weighted value was set for each of the layers in the hierachy. ‘Ecological Characteristics’ (0.333) was rated with the highest weighted value. followed by ‘Landscape Characteristics’(0.190) and ‘Physical Characteristics’(0.166). Among the assessment items, ‘Water Quality’ (0.152) and ‘River Naturality’(0.118) had higher weighted values. With the set of assessment items field assessments were carried out for Gyung-An Stream of Gyeonggi-Do to exam its applicability. Total 6 segments and 31 reaches out of the 22.5 km long river were evaluated and the mean scores of the five categories were converted into a percentile score for comparison. Overall, the segments which had higher scores were located close to neighborhood areas and had better connections with other historical and cultural amenities. Also, existing facilities was an important factor and needs to be considered for waterfront development.