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      Gen Z's personalization paradoxes: A privacy calculus examination of digital personalization and brand behaviors

      1 , 2 , 2
      Journal of Consumer Behaviour
      Wiley

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          Abstract

          Employing privacy calculus theory, we examine why Gen Z consumers increasingly adopt ad blockers, use private browsers, or take other measures to limit data tracking. Specifically, we evaluate consumer behaviors related to personalized and non‐personalized digital marketing in light of two personalization paradoxes: privacy–benefits and avoidance–annoyance. Using structural equation modeling on a sample of 414 Gen Z consumers, our findings show that both the privacy–benefits paradox and avoidance–annoyance paradox strongly influence consumers' intentions to avoid brands that fail to personalize marketing efforts. We also explore the interaction effects of the two digital personalization tensions, showing that tradeoffs exist between the utilization of these two paradoxes. Our findings underscore key implications for marketers investing in personalized marketing efforts to enhance consumer–brand relationships.

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          Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives

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            Common method biases in behavioral research: A critical review of the literature and recommended remedies.

            Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how to control for them does not exist. Therefore, the purpose of this article is to examine the extent to which method biases influence behavioral research results, identify potential sources of method biases, discuss the cognitive processes through which method biases influence responses to measures, evaluate the many different procedural and statistical techniques that can be used to control method biases, and provide recommendations for how to select appropriate procedural and statistical remedies for different types of research settings.
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              Evaluating Structural Equation Models with Unobservable Variables and Measurement Error

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                Author and article information

                Contributors
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                Journal
                Journal of Consumer Behaviour
                J of Consumer Behaviour
                Wiley
                1472-0817
                1479-1838
                March 2024
                June 28 2023
                March 2024
                : 23
                : 2
                : 405-422
                Affiliations
                [1 ] University of Wisconsin‐Parkside Kenosha Wisconsin USA
                [2 ] College of Business & Economics, University of Wisconsin‐Whitewater Whitewater Wisconsin USA
                Article
                10.1002/cb.2199
                0e4a5198-7ac4-4e7e-96bf-b8ef818680e2
                © 2024

                http://creativecommons.org/licenses/by-nc-nd/4.0/

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