Non-symmetrical correspondence analysis of abbreviated hard laddering interviews

Abstract

Hard laddering is a kind of a semi structured interview in a quantitative means-end chain (MEC) approach that yields a summary implication matrix (SIM). The SIM is based on pairwise associations between attributes (A), consequences (C), and personal values (V), and constitutes a base for developing hierarchical value maps (HVM). A new summary data presentation of the A-C-V triplets that form a summary ladder matrix (SLM) is presented. The structure of the SLM is examined with the use of non-symmetrical correspondence analysis. This approach permits us to identify the dependence structure in the SLM as well as the ladders that contribute most to the system's inertia. © Springer International Publishing Switzerland 2013.