Edinburgh Napier University

  We demonstrate a method of using SAS® 9.4 to supplement the interpretation of dimensions of a Multidimensional Scaling (MDS) model, a process that could be difficult without SAS®. In our paper, we examine why do people choose to drive to work (over other means of travel),' a question that transportation researchers need to answer in order to encourage drivers to switch to more environmentally-friendly travel modes. We applied the MDS approach on a travel survey data set because MDS has the advantage of extracting drivers' motivations in multiple dimensions.To overcome the challenges of dimension interpretation with MDS, we used the logistic regression function of SAS 9.4 to identify the variables that are strongly associated with each dimension, thus greatly aiding our interpretation procedure. Our findings are important to transportation researchers, practitioners, and MDS users.