Purpose

The purpose of the current research is to present an explanatory framework for how people selectively attend to privacy-related news information about LBA depending on the extent to which they know about LBA already as well as their appraisals of privacy threats and efficacy.

Design/methodology/approach

The proposed model was tested using structural equation modeling based on a total of 522 useable responses obtained from an online survey.

Findings

The results revealed two different approaches to information exposure: (1) people choose to seek out privacy-related news articles when their persuasion knowledge and perceived threat level are high, whereas (2) they tend to avoid such information when perceived threats accompany fear as well as psychological discomfort, or when they believe that they are knowledgeable about LBA practices and highly capable of protecting their privacy.

Originality/value

With the development of real-time location-tracking technologies, the practice of LBA is becoming increasingly popular. As such, however, concerns about data collection and privacy are also on the rise, garnering a great deal of media attention. Despite the importance and constant stream of news reports on the subject, a comprehensive understanding of consumers' privacy assessments and information consumption remains underexamined. By incorporating the persuasion knowledge model and extended parallel process model, the current research presents an explanatory framework for consumers' privacy perceptions and information choice.

中文翻译：

---

消费者对基于位置的广告 (LBA) 和选择性暴露隐私相关在线信息的评估框架

目的

当前研究的目的是提出一个解释框架，说明人们如何根据他们对 LBA 的了解程度以及对隐私威胁和功效的评估，选择性地关注有关 LBA 的隐私相关新闻信息。

设计/方法论/途径

使用结构方程模型对所提出的模型进行了测试，该模型基于从在线调查中获得的总共 522 个可用响应。

发现

结果揭示了两种不同的信息暴露方式：（1）当人们的说服知识和感知威胁水平较高时，他们选择寻找与隐私相关的新闻文章，而（2）当感知到的威胁伴随着恐惧时，他们倾向于避免此类信息以及心理不适，或者当他们认为自己了解 LBA 实践并且非常有能力保护自己的隐私时。

原创性/价值

随着实时位置跟踪技术的发展，LBA的实践变得越来越流行。然而，因此，对数据收集和隐私的担忧也在增加，引起了媒体的广泛关注。尽管有关该主题的新闻报道很重要且源源不断，但对消费者隐私评估和信息消费的全面理解仍然不够充分。通过结合说服知识模型和扩展并行过程模型，当前的研究为消费者的隐私感知和信息选择提供了一个解释框架。