Predictor Analysis in Group Decision Making

Priority vectors in the Analytic Hierarchy Process (AHP) are commonly estimated as constant values calculated by pairwise comparison ratios elicited from an expert. For multiple experts, or panel data, other data with varied characteristics of measurements, priority can be built functions auxiliary predictors. example, multi-person decision making, priorities obtained regression modeling demographic and socio-economic properties. Then predicted for individual respondents, profiled each predictor, forecasted time, studied predictor importance, characteristic significance, fit quality well-known modeling. Numerical results show that suggested approaches reveal useful features behavior, noticeably extend AHP abilities applications numerous multiple-criteria making problems. The considered methods segmentation respondents finding optimum managerial solutions specific segment. It help to makers focus on respondents’ increase customer satisfaction, their retention loyalty promoted brands products.