Data Quality, Level of Aggregation, and Nonmetric Multidimensional Scaling Solutions - Day, George S.; Deutscher, Terry; Ryans, Adrian B. (Journal of marketing research, 1976)
AS THE RELATIVE EMPHASIS IN NONMETRIC MULTIDIMENSIONAL SCALING RESEARCH SHIFTS FROM TECHNIQUES TO APPLICATIONS, INCREASING ATTENTION IS BEING PAID TO THE QUALITY OF INPUT DATA AND THE EXTENT OF AGGREGATION OF INDIVIDUAL DATA FOR ANALYSIS PURPOSES. THE THEORETICAL FRAMEWORK DEVELOPED IN THIS STUDY SHOULD ASSIST A MARKETING-RESEARCHER WHO HAS NONMETRIC SCALING DATA FROM A LARGE SAMPLE OF RESPONDENTS TO DECIDE WHETHER HE SHOULD SEGMENT HIS SAMPLE, OR WHETHER HE SHOULD SIMPLY WORK WITH THE FULLY AGGREGATED DATA SET. IF HE HAS A VERY LARGE SAMPLE OR HIGHLY RELIABLE DATA BUT HIGH ERROR IN THE AGGREGATE DATA THEN IT WOULD APPEAR THAT THE SAMPLE OF SUBJECTS IS VERY HETEROGENEOUS. IN THIS CASE, SEGMENTATION SHOULD BE TRIED IN AN ATTEMPT TO UNCOVER MORE HOMOGENEOUS SEGMENTS FOR ANALYSIS. THE IMPORTANCE OF COLLECTING RELIABILITY INFORMATION IS DEMONSTRATED WHEN ANY SIMILARITY DATA ARE GATHERED AND ESPECIALLY WHEN AGGREGATION OF THE DATA IS BEING CONSIDERED.