Combining Sources of Preference Data for Modeling Complex Decision Processes

Jordan J. Louviere, Robert J. Meyer, David S. Bunch, Richard Carson, Benedict Dellaert, W. Michael Hanemann, David Hensher, Julie Irwin

Research output: Contribution to journalArticleAcademicpeer-review

73 Citations (Scopus)


We review current state-of-the-art practices for combining preference data from multiple sources and discuss future research possibilities. A central theme is that any one data source (e.g., a scanner panel source) is often insufficient to support tests of complex theories of choice and decision making. Hence, analysts may need to embrace a wider variety of data types and measurement tools than traditionally have been considered in applied decision making and choice research. We discuss the viability of preference-stationarity assumptions usually made when pooling data, as well as random-utility theory-based approaches for combining data sources. We also discuss types of models and data sources likely to be required to make inferences about and estimate models that describe choice dynamics. The latter discussion is speculative insofar as the body of literature on this topic is small.

Original languageEnglish
Pages (from-to)205-217
Number of pages13
JournalMarketing Letters
Issue number3
Publication statusPublished - 1999


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