Conjoint Analysis Task

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A conjoint analysis task is an statistical analysis task that requires a ranking model of person preferences based on surveys.



References

2010

  • http://en.wikipedia.org/w/index.php?title=Conjoint_analysis_%28marketing%29&action=edit
    • Conjoint analysis is a statistical technique used in market research to determine how people value different features that make up an individual product or service.
    • The objective of conjoint analysis is to determine what combination of a limited number of attributes is most influential on respondent choice or decision making. A controlled set of potential products or services is shown to respondents and by analyzing how they make preferences between these products, the implicit valuation of the individual elements making up the product or service can be determined. These implicit valuations (utilities or part-worths) can be used to create market models that estimate market share, revenue and even profitability of new designs.
    • Conjoint originated in mathematical psychology and was developed by marketing professor Paul Green at the Wharton School of the University of Pennsylvania and Data Chan. Other prominent conjoint analysis pioneers include Richard Johnson (founder of Sawtooth Software) who developed the Adaptive Conjoint Analysis technique in the 1980s and Jordan Louviere who invented and developed Choice-based approaches to conjoint analysis and related techniques such as MaxDiff.

2009

1978

  • (Green & Srinivasan, 1978) ⇒ P. E. Green, and V. Srinivasan. (1978). “Conjoint Analysis in Consumer Research: issues and outlook.” In: Journal of Consumer Research, 5(2). doi:10.1086/208721