AN ALTERNATING LEAST‐SQUARES PROCEDURE FOR ESTIMATING MISSING PREFERENCE DATA IN PRODUCT‐CONCEPT TESTING

S. DeSarbo, Paul E. Green, J. Douglas Carroll

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

Product‐concept testing is a popular activity in marketing research. Often the number of new product/service concepts under study far exceeds the time available for any single respondent. Respondents therefore may receive only a subset of the concepts comprising the total design. Researchers are interested in making plausible imputations for the missing evaluations of any given respondent. This paper proposes a model and an iterative estimation procedure to impute missing entries for each evaluator. The model and the procedure incorporate (1) the internal structure of the response matrix and (2) an ancillary matrix of (nonmissing) respondent background data; they also (3) allow for individual differences in respondents' uses of the numerical rating scale. The model is applied to both real and synthetic data. Suggestions also are given on how the data imputations may be used in market segmentation and product‐line decisions.

Original languageEnglish (US)
Pages (from-to)163-185
Number of pages23
JournalDecision Sciences
Volume17
Issue number2
DOIs
StatePublished - Apr 1986

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting(all)
  • Strategy and Management
  • Information Systems and Management
  • Management of Technology and Innovation

Fingerprint Dive into the research topics of 'AN ALTERNATING LEAST‐SQUARES PROCEDURE FOR ESTIMATING MISSING PREFERENCE DATA IN PRODUCT‐CONCEPT TESTING'. Together they form a unique fingerprint.

  • Cite this