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Improving the Validity of Conjoint Analysis by Additional Data Collection and Analysis Steps

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Challenges at the Interface of Data Analysis, Computer Science, and Optimization

Abstract

Depending on the concrete application field and the data collection situation, conjoint experiments can end up with a low internal validity of the estimated part-worth functions. One of the known reasons for this is the (missing) temporal stability and structural reliability of the respondents’ part-worth functions, another reason is the (missing) attentiveness of the respondents in an uncontrolled data collection environment, e.g. during an online interview with many parallel web applications (e.g. electronic mail, newspapers or web site browsing). Here, additional data collection and analysis has been proposed as a solution. Examples of internal sources of data are response latencies, eye movements, or mouse movements, examples of external sources are sales and market data. The authors suggest alternative procedures for conjoint data collection that deal with these potential sources of internal validity. A comparison in an adaptive conjoint analysis setting shows, that the new procedures lead to a higher internal validity.

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Correspondence to Sebastian Selka .

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Selka, S., Baier, D., Brusch, M. (2012). Improving the Validity of Conjoint Analysis by Additional Data Collection and Analysis Steps. In: Gaul, W., Geyer-Schulz, A., Schmidt-Thieme, L., Kunze, J. (eds) Challenges at the Interface of Data Analysis, Computer Science, and Optimization. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24466-7_54

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