A hybrid combination of analytic hierarchy process and best-worst method: simulation and application
Thanh NgoPurpose
Among various multi-criteria decision-making (MCDM) methods, the best-worst method (BWM) is acknowledged as an improvement of the analytic hierarchy process (AHP). However, data collected from AHP surveys could not be used in BWM studies and vice versa because the two require different questionnaire structures. This article proposes a hybrid AHP-BWM approach to apply BWM to AHP data that can improve the AHP results.
Design/methodology/approach
We propose a new way to pre-process AHP data so that it can be used with BWM: for a certain alternative in the AHP data, one can determine the best and worst criteria using the total preference degree. We then used simulation and application to verify the usefulness of the proposed method.
Findings
Based on 5,130,000 pairwise comparison matrices of a Monte Carlo simulation, we suggest that the AHP-BWM performs better than AHP alone. Based on an empirical application using AHP data from farmers in the Northern region of Vietnam, we verify the importance of the Economic dimension in sustainable agricultural development in Vietnam.
Research limitations/implications
More empirical studies are needed when more data is available to confirm and extend our method.
Originality/value
The article proposed and verified a novel (hybrid) method to combine AHP data and BWM analysis.