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Empirical Evidence and Measurement Results

  • Daniel EhlsEmail author
Chapter
Part of the Forschungs-/Entwicklungs-/Innovations-Management book series (FEIM)

Abstract

In order to analyze the DCE data, and in particular to apply the correlated mixed logit panel model, a specific econometric software is required. Despite the fact that the basic MXL model has been known for many years and is widely used, there is still a lack of suitable software supporting enhanced MXL model estimation. Chang and Lusk (2010) compare several econometric tools for estimating MXL models. STATA and NLOGIT are able to consider repeated choices from single individuals (panel data), but not SAS. In terms of accuracy, for example root mean square error, NLOGIT provides the most accurate results compared to SAS and STATA. Therefore, I work with NLOGIT version 4 for my model estimation. The following sections cover the descriptive, inferential and explorative statistics results. The discussion of the results, including hypotheses testing, follows in the next chapter for an enbloc evaluation of each research question, inclusion of further reports, and interpretation of the measurement results.

Keywords

Community Participation Preference Heterogeneity Content Community Taste Variation Random Parameter Logit Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Fachmedien Wiesbaden 2014

Authors and Affiliations

  1. 1.Technische Universität Hamburg-HarburgHamburgGermany

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