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Order in Product Customization Decisions: Evidence from Field Experiments

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  • Jonathan Levav
  • Mark Heitmann
  • Andreas Herrmann
  • Sheena S. Iyengar

Abstract

Differentiated product models are predicated on the belief that a product's utility can be derived from the summation of utilities for its individual attributes. In one framed field experiment and two natural field experiments, we test this assumption by experimentally manipulating the order of attribute presentation in the product customization process of custom-made suits and automobiles. We find that order affects the design of a suit that people configure and the design and price of a car that people purchase by influencing the likelihood that they will accept the default option suggested by the firm. (c) 2010 by The University of Chicago. All rights reserved.

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  • Jonathan Levav & Mark Heitmann & Andreas Herrmann & Sheena S. Iyengar, 2010. "Order in Product Customization Decisions: Evidence from Field Experiments," Journal of Political Economy, University of Chicago Press, vol. 118(2), pages 274-299, April.
  • Handle: RePEc:ucp:jpolec:v:118:y:2010:i:2:p:274-299
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    References listed on IDEAS

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    Cited by:

    1. James Agarwal & Wayne DeSarbo & Naresh K. Malhotra & Vithala Rao, 2015. "An Interdisciplinary Review of Research in Conjoint Analysis: Recent Developments and Directions for Future Research," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(1), pages 19-40, March.
    2. Peters, Jörg & Langbein, Jörg & Roberts, Gareth, 2016. "Policy evaluation, randomized controlled trials, and external validity—A systematic review," Economics Letters, Elsevier, vol. 147(C), pages 51-54.
    3. Novarese, Marco & Wilson, Chris M., 2013. "Being in the Right Place: A Natural Field Experiment on List Position and Consumer Choice," MPRA Paper 48074, University Library of Munich, Germany.
    4. Eric Johnson & Suzanne Shu & Benedict Dellaert & Craig Fox & Daniel Goldstein & Gerald Häubl & Richard Larrick & John Payne & Ellen Peters & David Schkade & Brian Wansink & Elke Weber, 2012. "Beyond nudges: Tools of a choice architecture," Marketing Letters, Springer, vol. 23(2), pages 487-504, June.
    5. John G. Matsusaka, 2016. "Ballot order effects in direct democracy elections," Public Choice, Springer, vol. 167(3), pages 257-276, June.
    6. Peter C. Reiss, 2011. "Structural Workshop Paper --Descriptive, Structural, and Experimental Empirical Methods in Marketing Research," Marketing Science, INFORMS, vol. 30(6), pages 950-964, November.
    7. Olivier Toubia & Eric Johnson & Theodoros Evgeniou & Philippe Delquié, 2013. "Dynamic Experiments for Estimating Preferences: An Adaptive Method of Eliciting Time and Risk Parameters," Management Science, INFORMS, vol. 59(3), pages 613-640, June.
    8. repec:eee:touman:v:33:y:2012:i:2:p:266-275 is not listed on IDEAS
    9. Altmann, Steffen & Falk, Armin & Grunewald, Andreas, 2013. "Incentives and Information as Driving Forces of Default Effects," IZA Discussion Papers 7610, Institute for the Study of Labor (IZA).
    10. Tiezzi, Silvia & Xiao, Erte, 2013. "Time Delay and Support for Taxation," MPRA Paper 51233, University Library of Munich, Germany.
    11. Garmann, Sebastian, 2017. "Election frequency, choice fatigue, and voter turnout," European Journal of Political Economy, Elsevier, vol. 47(C), pages 19-35.
    12. Shefrin, Hersh & Nicols, Christina M., 2014. "Credit card behavior, financial styles, and heuristics," Journal of Business Research, Elsevier, vol. 67(8), pages 1679-1687.
    13. Martijn G. de Jong & Donald R. Lehmann & Oded Netzer, 2012. "State-Dependence Effects in Surveys," Marketing Science, INFORMS, vol. 31(5), pages 838-854, September.

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