Design of Experiments for Eliciting Customer Preferences

In this chapter, the survey methods needed to elicit the customer preference data to estimate a DCA or OL model, are introduced. The survey methods are based upon established Design of Experiments methodologies, but adapted for the specific needs of stated preference experiments.

[1]  Bruce E. Ankenman,et al.  Optimal experimental design of human appraisals for modeling consumer preferences in engineering design , 2009, DAC 2008.

[2]  Peter Goos,et al.  A Comparison of Criteria to Design Efficient Choice Experiments , 2006 .

[3]  D. Hensher,et al.  Stated Choice Methods: Analysis and Applications , 2000 .

[4]  Peter Goos,et al.  Optimal designs for rating-based conjoint experiments , 2004 .

[5]  A. Tamhane,et al.  Statistics and Data Analysis: From Elementary to Intermediate , 1999 .

[6]  Kenneth E. Train,et al.  Discrete Choice Methods with Simulation , 2016 .

[7]  Genichii Taguchi,et al.  Introduction to quality engineering. designing quality into products a , 1986 .

[8]  John M. Rose,et al.  Applied Choice Analysis: List of tables , 2005 .

[9]  Deborah J. Street,et al.  The Construction of Optimal Stated Choice Experiments , 2007 .

[10]  M. Wedel,et al.  Designing Conjoint Choice Experiments Using Managers' Prior Beliefs , 2001 .

[11]  Jordan J. Louviere,et al.  Designing Discrete Choice Experiments: Do Optimal Designs Come at a Price? , 2008 .

[12]  Peter Goos,et al.  An Efficient Algorithm for Constructing Bayesian Optimal Choice Designs , 2009 .

[13]  Stuart R. Lipsitz,et al.  Analyzing bivariate ordinal data using a global odds ratio , 1995 .

[14]  John M. Rose,et al.  Applied Choice Analysis: A Primer , 2005 .

[15]  Peter Goos,et al.  Optimal designs for conjoint experiments , 2008, Comput. Stat. Data Anal..

[16]  Jordan J. Louviere,et al.  What You Don’t Know Might Hurt You: Some Unresolved Issues in the Design and Analysis of Discrete Choice Experiments , 2006 .

[17]  D. Street,et al.  The Construction of Optimal Stated Choice Experiments: Theory and Methods by STREET, D. J. and BURGESS, L. , 2007 .

[18]  R. J. O'Hara Hines,et al.  COMPARISON OF TWO COVARIANCE STRUCTURES IN THE ANALYSIS OF CLUSTERED POLYTOMOUS DATA USING GENERALIZED ESTIMATING EQUATIONS , 1998 .

[19]  John M. Rose,et al.  Applied Choice Analysis: List of tables , 2005 .

[20]  Mark J. Garratt,et al.  Efficient Experimental Design with Marketing Research Applications , 1994 .

[21]  R. McKelvey,et al.  A statistical model for the analysis of ordinal level dependent variables , 1975 .

[22]  R. J. O'Hara Hines,et al.  Analysis of Clustered Polytomous Data Using Generalized Estimating Equations and Working Covariance Structures , 1997 .

[23]  J. S. Hunter,et al.  Statistics for Experimenters: Design, Innovation, and Discovery , 2006 .

[24]  K. Train.  Discrete Choice Methods with Simulation , 2003 .

[25]  R. A. Fisher,et al.  Design of Experiments , 1936 .

[26]  Conrad A. Fung,et al.  An explanation and critique of taguchi's contributions to quality engineering , 1988 .

[27]  Vijay Mahajan,et al.  On the Creation of Acceptable Conjoint Analysis Experimental Designs , 1991 .

[28]  Jie Yu,et al.  Efficient Conjoint Choice Designs in the Presence of Respondent Heterogeneity , 2009, Mark. Sci..

[29]  P. Laycock,et al.  Optimum Experimental Designs , 1995 .

[30]  Madhan Shridhar Phadke,et al.  Quality Engineering Using Robust Design , 1989 .

[31]  Paul E. Green,et al.  Adaptive Conjoint Analysis: Some Caveats and Suggestions , 1991 .

[32]  S. S. Stevens,et al.  Psychophysics: Introduction to Its Perceptual, Neural and Social Prospects , 1975 .

[33]  Peter Goos,et al.  Outperforming Completely Randomized Designs , 2004 .

[34]  Jim Albert,et al.  Ordinal Data Modeling , 2000 .

[35]  Nanxin Wang,et al.  Design and Verification of a New Computer Controlled Seating Buck , 2006, DAC 2006.

[36]  S. Zeger,et al.  Longitudinal data analysis using generalized linear models , 1986 .

[37]  Peter Goos,et al.  The optimal design of blocked and split-plot experiments , 2002 .

[38]  Christopher Zorn.  Generalized Estimating Equation Models for Correlated Data: A Review with Applications , 2001 .

[39]  Paul E. Green,et al.  Rating Scales and Information Recovery—How Many Scales and Response Categories to Use? , 1970 .

[40]  Eli P. Cox,et al.  The optimal number of response alternatives for a scale: A review. , 1980 .

[41]  Douglas C. Montgomery,et al.  Response Surface Methodology: Process and Product Optimization Using Designed Experiments , 1995 .

[42]  B. Bowerman.  Statistical Design and Analysis of Experiments, with Applications to Engineering and Science , 1989 .

[43]  P. McCullagh.  Regression Models for Ordinal Data , 1980 .

[44]  Robert L. Mason,et al.  Statistical Design and Analysis of Experiments , 2003 .