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From Contextualizing to Context Theorizing: Assessing Context Effects in Privacy Research

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  • Heng Xu

    (Kogod School of Business, American University, Washington, DC 20016)

  • Nan Zhang

    (Kogod School of Business, American University, Washington, DC 20016)

Abstract

Over the past two decades, behavioral research in privacy has made considerable progress transitioning from acontextual studies to using contextualization as a powerful sensitizing device for illuminating the boundary conditions of privacy theories. Significant challenges and opportunities wait, however, on elevating and converging individually contextualized studies to a context-contingent theory that explicates the mechanisms through which contexts influence consumers’ privacy concerns and their behavioral reactions. This paper identifies the important barriers occasioned by this lack of context theorizing on the generalizability of privacy research findings and argues for accelerating the transition from the contextualization of individual research studies to an integrative understanding of context effects on privacy concerns. It also takes a first step toward this goal by providing a conceptual framework and the associated methodological instantiation for assessing how context-oriented nuances influence privacy concerns. Empirical evidence demonstrates the value of the framework as a diagnostic device guiding the selection of contextual contingencies in future research, so as to advance the pace of convergence toward context-contingent theories in information privacy.

Suggested Citation

  • Heng Xu & Nan Zhang, 2022. "From Contextualizing to Context Theorizing: Assessing Context Effects in Privacy Research," Management Science, INFORMS, vol. 68(10), pages 7383-7401, October.
  • Handle: RePEc:inm:ormnsc:v:68:y:2022:i:10:p:7383-7401
    DOI: 10.1287/mnsc.2021.4249
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    References listed on IDEAS

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    1. Maria Iannario, 2010. "On the identifiability of a mixture model for ordinal data," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 87-94.
    2. Bearse, Peter M & Bozdogan, Hamparsum & Schlottmann, Alan M, 1997. "Empirical Econometric Modelling of Food Consumption Using a New Informational Complexity Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(5), pages 563-586, Sept.-Oct.
    3. Alessandro Acquisti & Curtis Taylor & Liad Wagman, 2016. "The Economics of Privacy," Journal of Economic Literature, American Economic Association, vol. 54(2), pages 442-492, June.
    4. Maria Iannario & Marica Manisera & Domenico Piccolo & Paola Zuccolotto, 2020. "Ordinal Data Models for No-Opinion Responses in Attitude Survey," Sociological Methods & Research, , vol. 49(1), pages 250-276, February.
    5. Sendhil Mullainathan & Marianne Bertrand, 2001. "Do People Mean What They Say? Implications for Subjective Survey Data," American Economic Review, American Economic Association, vol. 91(2), pages 67-72, May.
    6. Avi Goldfarb & Catherine Tucker, 2012. "Shifts in Privacy Concerns," American Economic Review, American Economic Association, vol. 102(3), pages 349-353, May.
    7. Bearse, Peter M & Bozdogan, Hamparsum & Schlottmann, Alan M, 1997. "Empirical Econometric Modelling of Food Consumption Using a New Informational Complexity Approach: Reply," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(5), pages 590-592, Sept.-Oct.
    8. Leslie K. John & Alessandro Acquisti & George Loewenstein, 2011. "Strangers on a Plane: Context-Dependent Willingness to Divulge Sensitive Information," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 37(5), pages 858-873.
    9. Alessandro Acquisti & Leslie K. John & George Loewenstein, 2013. "What Is Privacy Worth?," The Journal of Legal Studies, University of Chicago Press, vol. 42(2), pages 249-274.
    10. Johns, Gary, 1991. "Substantive and methodological constraints on behavior and attitudes in organizational research," Organizational Behavior and Human Decision Processes, Elsevier, vol. 49(1), pages 80-104, June.
    11. Domenico Piccolo & Rosaria Simone, 2019. "The class of cub models: statistical foundations, inferential issues and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 389-435, September.
    12. Marreiros, Helia & Tonin, Mirco & Vlassopoulos, Michael & Schraefel, M.C., 2017. "“Now that you mention it”: A survey experiment on information, inattention and online privacy," Journal of Economic Behavior & Organization, Elsevier, vol. 140(C), pages 1-17.
    13. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780199245291.
    14. Naresh K. Malhotra & Sung S. Kim & James Agarwal, 2004. "Internet Users' Information Privacy Concerns (IUIPC): The Construct, the Scale, and a Causal Model," Information Systems Research, INFORMS, vol. 15(4), pages 336-355, December.
    15. Maria Iannario, 2012. "Modelling shelter choices in a class of mixture models for ordinal responses," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 21(1), pages 1-22, March.
    16. Domenico Piccolo & Rosaria Simone, 2019. "Rejoinder to the discussion of “The class of cub models: statistical foundations, inferential issues and empirical evidence”," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 477-493, September.
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