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Information privacy and correlates: an empirical attempt to bridge and distinguish privacy-related concepts

  • Research Article
  • Published:
European Journal of Information Systems

Abstract

Privacy is one of the few concepts that has been studied across many disciplines, but is still difficult to grasp. The current understanding of privacy is largely fragmented and discipline-dependent. This study develops and tests a framework of information privacy and its correlates, the latter often being confused with or built into definitions of information privacy per se. Our framework development was based on the privacy theories of Westin and Altman, the economic view of the privacy calculus, and the identity management framework of Zwick and Dholakia. The dependent variable of the model is perceived information privacy. The particularly relevant correlates to information privacy are anonymity, secrecy, confidentiality, and control. We posit that the first three are tactics for information control; perceived information control and perceived risk are salient determinants of perceived information privacy; and perceived risk is a function of perceived benefits of information disclosure, information sensitivity, importance of information transparency, and regulatory expectations. The research model was empirically tested and validated in the Web 2.0 context, using a survey of Web 2.0 users. Our study enhances the theoretical understanding of information privacy and is useful for privacy advocates, and legal, management information systems, marketing, and social science scholars.

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Author information

Authors and Affiliations

  1. Department of Information Technology & Operations Management, College of Business, Florida Atlantic University, Boca Raton, USA

    Tamara Dinev & Paul Hart

  2. College of Information Sciences and Technology, Pennsylvania State University, University Park, USA

    Heng Xu

  3. Department of Decision Sciences and Management Information Systems, Farmer School of Business, Miami University, Oxford, USA

    Jeff H Smith

Authors
  1. Tamara Dinev
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  2. Heng Xu
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  3. Jeff H Smith
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  4. Paul Hart
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Appendices

Appendix A

Measurement items (measured on 7-point Likert-type scale)

Perceived privacy (PRIV)

When you answer the following questions about your privacy, please think about the limited access the Web sites have to your personal information

  1. 1

    I feel I have enough privacy when I use these Web sites.

  2. 2

    I am comfortable with the amount of privacy I have.

  3. 3

    I think my online privacy is preserved when I use these Web sites.

Perceived information control (PCTL)

  1. 1

    I think I have control over what personal information is released by these Web sites.

  2. 2

    I believe I have control over how personal information is used by these Web sites.

  3. 3

    I believe I have control over what personal information is collected by these Web sites.

  4. 4

    I believe I can control my personal information provided to these Web sites.

Perceived privacy risk (RISK)

  1. 1

    In general, it would be risky to give personal information to Web sites.

  2. 2

    There would be high potential for privacy loss associated with giving personal information to Web sites.

  3. 3

    Personal information could be inappropriately used by Web sites.

  4. 4

    Providing Web sites with my personal information would involve many unexpected problems.

Anonymity (ANYT)

  1. 1

    I believe I can hide my true identity on these Web sites.

  2. 2

    I believe I can stay anonymous and do everything I want on these Web sites.

  3. 3

    I can keep my information anonymous on these Web sites.

Secrecy (SCRT)

  1. 1

    I believe, I can conceal some information from these Web sites when I want to.

  2. 2

    I feel I can falsify some of my personal information if it is asked for by these Web sites.

  3. 3

    I believe, I can refuse to give my personal information to these Web sites when I think it is too personal.

Confidentiality (CFDT)

  1. 1

    I believe my personal information provided to these Web sites remains confidential.

  2. 2

    I believe these Web sites will prevent unauthorized people from accessing my personal information in their databases.

  3. 3

    I believe my personal information is accessible only to those authorized to have access.

Information sensitivity (IS)

When visiting Web sites that collect information, many people find there is some information that they generally feel comfortable providing, some information they feel comfortable providing only under certain conditions, and some information is too personal that they never or rarely feel comfortable providing. Please indicate how much you agree with the following statements:

  1. 1

    I do not feel comfortable with the type of information these Web sites request from me.

  2. 2

    I feel that these Web sites gather highly personal information about me.

  3. 3

    The information I provide to these Web sites is very sensitive to me.

Perceived benefits of information disclosure (BEN)

  1. 1

    Revealing my personal information on these Web sites will help me obtain information/products/services I want.

  2. 2

    I need to provide my personal information so I can get exactly what I want from these Web sites.

  3. 3

    I believe that as a result of my personal information disclosure, I will benefit from a better, customized service and/or better information and products.

Importance of information transparency (TR)

Please specify the importance of …

  1. 1

    whether these Web sites will allow me to find out what information about me they keep in their databases;

  2. 2

    whether these Web sites tell me how long they will retain information they collect from me; and

  3. 3

    the purpose for which these Web sites want to collect information from me.

Regulatory expectations (LAW)

  1. 1

    I believe that the law should protect me from the misuse of my personal data by online companies.

  2. 2

    I believe that the law should govern and interpret the practice of how online companies collect, use, and protect my private information.

  3. 3

    I believe that the law should be able to address violation of the information I provided to online companies.

Appendix B

Mediation tests

To obtain further insight into the potential mediating effects of perceived information control, we conducted a post hoc analysis following Baron and Kenny's (1986) recommendations for examining the mediating effects. In a mediation relationship, there is a direct effect between an independent variable (IV) and a DV and also indirect effects between an IV and a mediator variable, and between a mediator variable and a DV. Mediation is useful when we need to explain how the IV–DV relationship can be statistically explained by the IV–Mediator–DV relationship.

Baron and Kenny's (1986) argue that mediation is demonstrated if three conditions are fulfilled: the first condition stipulates that the IV must significantly affect the proposed mediator. As shown in Regression (1) in Table B1, the relationships between the proposed mediator (perceived information control) and the three IVs were all significant. The second condition requires the IV must significantly affect the DV. As shown in Regression (2) in Table B1, anonymity (ANYT) and secrecy (SCRT) were significantly related to perceived privacy (PRIV). But confidentiality (CFDT) was not significantly related to perceived privacy (PRIV). The last condition stipulates that the relationship between the IV and the DV should be weaker or insignificant when the proposed mediator is in the regression equation than when the proposed mediator is not in the equation. The results, shown in Regression (3) in Table B1 indicated that β for anonymity (β=0.285 compared with β=0.148) and β for secrecy (β=0.257 compared with β=0.151) were lower when perceived information control (PCTL) was included in the model. Table B1 summarizes the results for testing the mediating effect of perceived information control, which indicate partial mediation except for confidentiality, transparency, and regulatory expectations, which were not mediated.

Table B1 Testing the mediating effects of perceived information control (PCTL)
Full size table

Similarly, we conducted a post hoc analysis following Baron and Kenny's (1986) recommendations for examining the mediating effects of perceived risk (RISK). Table B2 summarizes the results, which indicated that RISK mediates the effects of perceived benefits of information disclosure (BEN) and information sensitivity (IS) on perceived privacy (PRIV). However, the results failed to demonstrate the mediation effect of RISK for the relationship between expectations of information transparency (TR) and perceived privacy (PRIV), as well as for the relationship between regulatory expectations (LAW) and perceived privacy (PRIV).

Table B2 Testing the mediating effects of perceived risk (RISK)
Full size table

In all, Baron and Kenny mediation tests provided above did not bring a conclusive argument about the extent of the partial mediation, especially the importance of the non-hypothesized relationships between the seven leftmost exogenous variables in our model, and the DV of perceived privacy. It is not known how much more explanatory power is brought into the model if these relationships are present in our model in the first place. To further investigate the mediation effects and empirically validate our model by SEM methods rather than the simpler multiple regression techniques, we ran the fully saturated PLS model, per the recommendations by Gefen et al (2011, p. viii) who discussed the importance of the saturated model in SEM validation. Per the authors:

This is rarely done in reported PLS research but it should. It is mainly needed to compare the theoretical model, which includes only the hypothesized paths, with the saturated model, which includes all possible paths in order to verify (1) that the significant paths in the theoretical model also remain significant in the saturated model, and (2) that adding the paths via the saturated model does not significantly increase the f2, a standard measure of effect size. By convention, f2 values of 0.02, 0.15, and 0.35 are labeled small, medium, and large effects, respectively, f2 is calculated as (R2 saturated model−R2 theoretical model/(1−R2 saturated model).

Table B3 presents the results from the saturated model and the comparison with the results from the hypothesized model. One can see that both conditions are met: first, all the significant paths in our theoretical model also remain significant in the saturated model; and second, with the only exception of information sensitivity, none of the leftmost variables have direct effect to perceived privacy. This result indicates full mediation for the six of the seven leftmost variables. Adding the additional paths in the saturated model changed the R2 from 52.2 to 56.1%, giving a small effect size of 0.089. This procedure validated our theoretical model. While the significance of the direct effect of Information sensitivity to perceived privacy is relatively small, possible theoretical underpinning of the relationship should be considered in future research.

Table B3 Theoretical and saturated structural models
Full size table

Finally, an additional insight about the mediation can be obtained by performing a pseudo F-test, per Burton-Jones and Straub (2006). Applying the test to our data yields a pseudo F-test of 16.198, which is not significant (16.198>0.05). This demonstrates that the saturated model did not explain significantly more R2 than did our original model.

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Dinev, T., Xu, H., Smith, J. et al. Information privacy and correlates: an empirical attempt to bridge and distinguish privacy-related concepts. Eur J Inf Syst 22, 295–316 (2013). https://doi.org/10.1057/ejis.2012.23

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  • DOI: https://doi.org/10.1057/ejis.2012.23

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