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Journal ArticleDOI

Internet privacy concerns: an integrated conceptualization and four empirical studies

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TLDR
In this article, the authors identify alternative conceptualizations of Internet privacy concerns (IPC) based on multidimensional developmental theory and a review of the prior literature and examine the various conceptualizations with four online surveys involving nearly 4,000 Internet users.
Abstract
Internet privacy concerns (IPC) is an area of study that is receiving increased attention due to the huge amount of personal information being gathered, stored, transmitted, and published on the Internet. While there is an emerging literature on IPC, there is limited agreement about its conceptualization in terms of its key dimensions and its factor structure. Based on the multidimensional developmental theory and a review of the prior literature, we identify alternative conceptualizations of IPC. We examine the various conceptualizations of IPC with four online surveys involving nearly 4,000 Internet users. As a baseline, study 1 compares the integrated conceptualization of IPC to two existing conceptualizations in the literature. While the results provide support for the integrated conceptualization, the second-order factor model does not outperform the correlated first-order factor model. Study 2 replicates the study on a different sample and confirms the results of study 1. We also investigate whether the prior results are affected by the different perspectives adopted in the wording of items in the original instruments. In study 3, we find that focusing on one's concern for website behavior (rather than one's expectation of website behavior) and adopting a consistent perspective in the wording of the items help to improve the validity of the factor structure. We then examine the hypothesized third-order conceptualizations of IPC through a number of alternative higher-order models. The empirical results confirm that, in general, the third-order conceptualizations of IPC outperform their lower-order alternatives. In addition, the conceptualization of IPC that has the best fit with the data contains a third-order general IPC factor, two second-order factors of interaction management and information management, and six first-order factors (i.e., collection, secondary usage, errors, improper access, control, and awareness). Study 4 cross-validates the results with another data set and examines IPC within the context of a nomological network. The results confirm that the third-order conceptualization of IPC has nomological validity, and it is a significant determinant of both trusting beliefs and risk beliefs. Our research helps to resolve inconsistencies in the key underlying dimensions of IPC, the factor structure of IPC, and the wording of the original items in prior instruments of IPC. Finally, we discuss the implications of this research.

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Students' Information Privacy Concerns in Learning Analytics: Towards a Model Development.

TL;DR: In this article, the authors propose a theoretical model to understand the information privacy concerns of students in relation to learning analytics in higher education, and explore the IPC as a central construct between its two antecedents: perceived privacy vulnerability and perceived privacy control, and its consequences, trusting beliefs and self-disclosure behavior.
Journal ArticleDOI

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Trading Friendship for Value: An Investigation of Collective Privacy Concerns in Social Application Usage Research-in-Progress

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TL;DR: This article offers a theoretical framework on the dimensionality of collective privacy concerns (CPC) and proposes to operationalize the three dimensions of CPC using a second-order reflective construct, and plans to develop a scale for it.
Book ChapterDOI

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References
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Book

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Accounting for common method variance in cross-sectional research designs.

TL;DR: A model is presented that allows partial correlation analysis to adjust the observed correlations for CMV contamination and determine if conclusions about the statistical and practical significance of a predictor have been influenced by the presence of CMV.
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Structural Equation Modeling With Lisrel, Prelis, and Simplis: Basic Concepts, Applications, and Programming

TL;DR: This paper presents a meta-modelling framework for testing the factorial Validity of a Theoretical Construct and the Invariant Factorial Structure of a theoretical construct using LISREL, PRELIS, and SIMPLIS through Windows.
Journal ArticleDOI

Internet Users' Information Privacy Concerns (IUIPC): The Construct, the Scale, and a Causal Model

TL;DR: The results of this study indicate that the second-order IUIPC factor, which consists of three first-order dimensions--namely, collection, control, and awareness--exhibited desirable psychometric properties in the context of online privacy.
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