Computing unsegmented product maps from preference data by means of single ideal point models is commonly thought to be impossible because of indeterminacy problems. The authors show that this mathematical indeterminacy can be overcome by incorporating dependent sampling assumptions into a probabilistic multidimensional scaling (MDS) model. As a result, product space maps can be estimated for single markets from preference data alone. If desired, dissimilarity data can be combined with preference data to produce jointly estimated product space maps. The authors illustrate the advantages of the proposed approach with real and simulated data. They also make comparisons to both internal and external deterministic models. The results are favorable.
JMR publishes articles representing the entire spectrum of research in marketing, ranging from analytical models of marketing phenomena to descriptive and case studies.
Sara Miller McCune founded SAGE Publishing in 1965 to support the dissemination of usable knowledge and educate a global community. SAGE is a leading international provider of innovative, high-quality content publishing more than 900 journals and over 800 new books each year, spanning a wide range of subject areas. A growing selection of library products includes archives, data, case studies and video. SAGE remains majority owned by our founder and after her lifetime will become owned by a charitable trust that secures the company’s continued independence. Principal offices are located in Los Angeles, London, New Delhi, Singapore, Washington DC and Melbourne. www.sagepublishing.com