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| Title: | Exploring the Antecedents and Consequences of Privacy Concerns: A Comparison of Humanoid Robot to Tablet |
| Authors: | 簡士鎰
Chien, Shih-Yi;Lin, Yi-Ling;Luo, Jing-Ting;Chan, Yao-Cheng |
| Contributors: | 資管系 |
| Keywords: | data sensitivity;human-robot interaction;information disclosure;personality traits;privacy concerns;social presence |
| Date: | 2025-10 |
| Issue Date: | 2025-11-14 |
| Abstract: | The emergence of AI-driven technologies often necessitates the collection of private user information to deliver personalised services and enhance the overall user experience. Given the recurring incidents of data breaches, awareness of privacy risks and concerns about disclosing personal information to AI-driven applications has significantly increased. Privacy concerns have become a critical issue, heavily influencing users' intentions to interact with such systems. To appropriately investigate the antecedents and consequences of disclosing private information, this study examines the influence of social presence (humanlike vs. non-humanlike media) on privacy concerns and information disclosure across different types of data sensitivities (including retail, financial, and medical data). An online survey (N = 282) and a lab experiment (N = 70) were conducted, incorporating multiple experimental tasks under various conditions. The results reveal that both social presence and data sensitivity significantly impact privacy concerns and information disclosure. Additionally, a privacy paradox is observed: while participants express concern about privacy, their attitudinal and behavioural intentions shift, indicating a willingness to trade sensitive information for enhanced services. The findings also show that individual personality traits strongly influence one's intention to disclose personal information when interacting with humanlike media. Furthermore, when investigating privacy concerns, it is essential to move beyond task-driven assessments. Instead, identifying the specific types of private information involved and adopting a data-driven perspective provides a more accurate understanding of privacy-related behaviours. |
| Relation: | Expert Systems, Vol.42, No.10, e70132, pp.1-22 |
| Data Type: | article |
| DOI 連結: | https://doi.org/10.1111/exsy.70132 |
| DOI: | 10.1111/exsy.70132 |
| Appears in Collections: | [資訊管理學系] 期刊論文
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