Authors: Fahri Karakaya; Abhrawashyu Awasthi
Addresses: University of Massachusetts Dartmouth, Charlton College of Business, Department of Marketing, Dartmouth, MA 02747-2300, USA ' Dr. Fresh LLC, 6645 Caballero Blvd, Buena Park, CA 90620, USA
Abstract: This study compares the robustness of conjoint analysis versus multiple linear regression when using orthogonal data. The explained variance (R²) by four independent variables was utilised to test the robustness of the regression analysis while Pearson's R and Kendall's tau were used for testing conjoint method. The results indicate that the two methods produce somewhat different results and conjoint analysis is more robust compared to regression.
Keywords: conjoint analysis; sensitivity analysis; multiple linear regression analysis; robust statistics; orthogonal data; robustness.
International Journal of Data Analysis Techniques and Strategies, 2014 Vol.6 No.2, pp.121 - 136
Available online: 08 Jun 2014 *Full-text access for editors Access for subscribers Purchase this article Comment on this article