变革性隐私计算:社交媒体上的个性化-隐私悖论概念化

Julien Cloarec, L. Meyer‐Waarden, Andreas Munzel
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引用次数: 0

摘要

数字营销的快速发展凸显了个性化与隐私之间的重要矛盾,而数据技术和人工智能的进步又加剧了这一矛盾。本研究深入探讨了个性化与隐私之间的悖论,强调了消费者行为的两面性--既渴望定制化互动,又要保护个人数据。我们采用社会交换理论作为概念框架,探讨互联网幸福感(HWI)如何影响用户在社交媒体上披露个人信息的意愿。我们的研究开发并测试了一个概念模型,该模型研究了驱动社交媒体上信息共享行为的心理机制,包括信任信念和信息收集顾虑的调节作用。通过研究发布频率对幸福感指数和个性化信息披露之间关系的中介效应,我们的研究结果有助于理解幸福感、信任和隐私顾虑之间复杂的相互作用,这被称为 "变革性隐私计算"。我们的研究丰富了社会交换和隐私计算理论,为营销人员在个性化和隐私之间取得平衡提供了有价值的启示,提出了在不损害隐私标准的情况下提高用户参与度的策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Transformative privacy calculus: Conceptualizing the personalization‐privacy paradox on social media
The rapid evolution of digital marketing underscores a critical tension between personalization and privacy, exacerbated by advances in data technologies and artificial intelligence. This study delves into the personalization‐privacy paradox, emphasizing the dichotomy of consumer behavior—desiring customized interactions while guarding personal data. We explore how happiness with the internet (HWI) influences users' willingness to disclose personal information on social media, employing social exchange theory as our conceptual framework. Our research develops and tests a conceptual model that investigates the psychological mechanisms driving information‐sharing behaviors on social media, including the moderating roles of trust beliefs and information collection concerns. By examining the mediating effect of posting frequency on the relationship between HWI and information disclosure for personalization, our findings contribute to understanding the complex interplay between happiness, trust and privacy concerns, coined as transformative privacy calculus. Our study enriches social exchange and privacy calculus theories, providing valuable implications for marketers aiming to navigate the balance between personalization and privacy, suggesting strategies to enhance user engagement without compromising privacy standards.
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