Analytic Hierarchy Process for Survey Data in R

The Analytic Hierarchy Process (AHP), introduced by Thomas Saaty, is a versatile multi-criteria decision-making tool that allows individuals to rationally weigh attributes and evaluate alternatives presented to them. While most applications of the AHP are focused on implementation at the individual or small-scale, the AHP was increasingly adopted in survey designs, which involve a large number of decision-makers and a great deal of heterogeneity in responses. The tools currently available in R for the analysis of AHP data, such as the packages ahp by Gluc (2018) and Prize by Dargahi, are excellent tools for performing the AHP at a small scale and offers are excellent in terms of interactivity, user-friendliness, and for comparing alternatives.

However, researchers looking to adopt the AHP in the analysis of survey data often have to manually reformat their data, sometimes even involving dragging and copying across Excel spreadsheets, which is painstaking and prone to human error. There are no good ways of computing and visualising the heterogeneity amongst AHP decision-makers, which is common in survey data. Inconsistent choices are also prevalent in AHP conducted in the survey format, where it is impractical for enumerators to identify and correct for inconsistent responses on the spot when the surveys are delivered in paper format. Even if an electronic version that allows immediate feedback of consistency ratio is used, respondents asked to repeatedly change their answers are likely to be mentally fatigued. Censoring observations with inconsistency is likely to result in a greatly decreased statistical power of the sample, or may lead to unrepresentative samples and nonresponse bias.

The ahpsurvey package provides a workflow for researchers to quantify and visualise inconsistent pairwise comparisons that aids researchers in improving the AHP design and adopting appropriate analytical methods for the AHP.

Full source code: CRAN, Github

Peer reviewed publication produced: Cho et al. (2019) Validating Citizens’ Preferences for Restoring Urban Riverscape: Discrete Choice Experiment versus Analytical Hierarchy Process link