Using ConJoint AnAlysis to deteCt disCriminAtion: reveAling Covert PreferenCes from overt ChoiCes

In an effort to continue the development of methods to understand social cognition, we adopt a technique called conjoint analysis that mathematically deduces preferences from the implied tradeoffs people make when choosing between sets of attributes at varying levels. We asked 101 students to make a series of choices between prospective teammates in a trivia contest who varied on three dimensions relevant to the decisions (education, IQ, experience) and one dimension that was irrelevant (body weight). Although participants stated explicitly that weight had little impact on their decisions, weight actually accounted for more than 25% of the variance in their revealed preferences. Additional analyses demonstrated that participants gave up about 11 IQ points to have a thin rather than overweight teammate. We suggest that conjoint analysis can be a valuable tool for detecting and quantifying the social costs of covert attitudes that are not in sync with overt values.

[1]  Maurice E. Schweitzer,et al.  Stretching the Truth: Elastic Justification and Motivated Communication of Uncertain Information , 2006 .

[2]  Bryan K. Orme,et al.  Which Conjoint Method Should I Use? , 2001 .

[3]  Timothy D. Wilson,et al.  Telling more than we can know: Verbal reports on mental processes. , 1977 .

[4]  R. Nisbett,et al.  Verbal reports about causal influences on social judgments: Private access versus public theories. , 1977 .

[5]  Michael I Norton,et al.  Casuistry and social category bias. , 2004, Journal of personality and social psychology.

[6]  P. Green,et al.  Thirty Years of Conjoint Analysis: Reflections and Prospects , 2001 .

[7]  Charles E. Cunningham,et al.  Providing Information to Parents of Children with Mental Health Problems: A Discrete Choice Conjoint Analysis of Professional Preferences , 2009, Journal of abnormal child psychology.

[8]  A. Greenwald,et al.  Measuring individual differences in implicit cognition: the implicit association test. , 1998, Journal of personality and social psychology.

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

[10]  Dolly Chugh,et al.  Societal and Managerial Implications of Implicit Social Cognition: Why Milliseconds Matter , 2004 .

[11]  Melissa Woodard Barringer,et al.  A Review and Analysis of the Policy-Capturing Methodology in Organizational Research: Guidelines for Research and Practice , 2002 .

[12]  Michael A. Olson,et al.  Implicit measures in social cognition. research: their meaning and use. , 2003, Annual review of psychology.

[13]  R. Luce,et al.  Simultaneous conjoint measurement: A new type of fundamental measurement , 1964 .

[14]  H. Timmermans,et al.  Testing the external validity of hierarchical conjoint analysis models of recreational destination choice , 1992 .

[15]  Charles E. Cunningham,et al.  Adaptive Choice-Based Conjoint Analysis , 2010, The patient.

[16]  Vithala R. Rao,et al.  Conjoint Measurement- for Quantifying Judgmental Data , 1971 .

[17]  D. Dunning.  On the Motives Underlying Social Cognition , 2007 .

[18]  B. Orme.  Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing Research , 2005 .

[19]  K. Brownell,et al.  Bias, discrimination, and obesity. , 2001, Obesity research.

[20]  Lynda Aiman-Smith,et al.  Conducting Studies of Decision Making in Organizational Contexts: A Tutorial for Policy-Capturing and Other Regression-Based Techniques , 2002 .

[21]  Lesley Cunningham,et al.  Modeling the Bullying Prevention Program Preferences of Educators: A Discrete Choice Conjoint Experiment , 2009, Journal of abnormal child psychology.

[22]  J. Dovidio,et al.  Aversive Racism and Selection Decisions: 1989 and 1999 , 2000, Psychological science.

[23]  Eric T. Bradlow.  Current issues and a ‘wish list’ for conjoint analysis , 2005 .

[24]  Brian A. Nosek,et al.  The Implicit Association Test at Age 7: A Methodological and Conceptual Review , 2007 .