Using Choice Experiment to Estimate Consumer Valuation: the Role of Experiment Design and Attribute Information Loads

Zhifeng Gao, Xiaohua Yu and Lisa House

No 49406, 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin from Agricultural and Applied Economics Association

Abstract: With fixed dimensionality of choice experiments, previous simulation results shows that D-optimal design with correct priori information generates more accurate valuation. In the absence of prior information, random designs and designs incorporate attribute interactions result in more precise valuation estimates. In this paper, the Monte Carlo results demonstrate that the performances of different design strategy are affected by attribute information loads in choice experiments. Consumer valuation estimates in simulation settings varies with the number of attributes.

Keywords: Marketing; Research Methods/Statistical Methods (search for similar items in EconPapers)
Pages: 28
Date: 2009
New Economics Papers: this item is included in nep-cmp and nep-mkt
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:ags:aaea09:49406

DOI: 10.22004/ag.econ.49406

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