|
|
|
| Influence of Privacy Protection Technical Features on Users' Privacy Protection Behavior Intentions |
| Liu Bailing1,2, Lei Xiaofang1, Dong Jingli1 |
1.School of Information Management, Central China Normal University, Wuhan 430079
2.Center for Data Governance and Intelligent Decision-Making of Hubei Province, Wuhan 430079 |
|
|
|
|
Abstract To ensure the high-quality development of the digital economy, it is crucial to strengthen the protection of personal privacy in mobile applications. Privacy settings and permission request settings are two main privacy protection measures provided by mobile service providers, and their effectiveness is controversial. They are not widely used or adopted by users, probably because users cannot choose and control what personal information applications collect, what purpose it is used, and who it is shared with through privacy settings. Moreover, the operation process of permission request settings is complicated. To effectively exert the positive effects of privacy-protection technologies, we must pay attention to their technical features. In this study, we propose two technical features for existing privacy protection technologies from the perspective of providing users fine-grained control over personal information disclosure: the operability of privacy settings and the effectiveness of permission request settings. Based on signaling theory, we investigate the effect of these two technical features proposed in this study on users’ intentions to refuse to provide personal information and to provide false personal information (referred to as “privacy protection behavior intentions”). A total of 334 valid data points were collected using a scenario-based experimental method, and the PLS-SEM (partial least squares - structural equation modeling) method was applied for empirical analysis. The experimental results demonstrated that the operability of privacy settings and the effectiveness of permission request settings have significant direct negative effects on users’ privacy protection behavior intentions and indirect negative effects on users’ privacy protection behavior intentions through privacy concerns. Furthermore, the two technical features proposed in this study have significant positive interaction effects on users’ privacy protection behavior intentions. Our study enriches and expands the study of privacy protection technology design and user information behavior, and provides insights for mobile service providers to enhance their competitive advantages by designing effective privacy protection measures, thus promoting the high-quality development of the digital economy.
|
|
Received: 01 January 2023
|
|
|
|
1 中国互联网络信息中心. CNNIC发布第50次《中国互联网络发展状况统计报告》[EB/OL]. (2022-08-31) [2022-12-29]. http://www.cnnic.net.cn/n4/2022/0916/c38-10594.html.
2 奇安信在数博会发布《2021年App个人信息使用态势分析报告》[EB/OL]. (2021-05-27) [2022-12-29]. https://www.donews.com/news/detail/4/3152878.html.
3 Son J Y, Kim S S. Internet users’ information privacy-protective responses: a taxonomy and a nomological model[J]. MIS Quarterly, 2008, 32(3): 503-529.
4 Miltgen C L, Smith H J. Falsifying and withholding: exploring individuals’ contextual privacy-related decision-making[J]. Information & Management, 2019, 56(5): 696-717.
5 高锡荣, 杨康. 影响互联网用户网络隐私保护行为的因素分析[J]. 情报杂志, 2011, 30(4): 39-42, 80.
6 中国消费者协会. App个人信息泄露情况调查报告[R/OL]. (2018-08-29) [2022-12-29]. http://www.cca.org.cn/jmxf/detail/28180.html.
7 Lima J. Lying consumers could destroy big data[EB/OL]. (2015-06-10) [2022-12-30]. https://techmonitor.ai/technology/data/lying-consumers-could-destroy-big-data-4597794.
8 Meinert D B, Peterson D K, Criswell J R, et al. Privacy policy statements and consumer willingness to provide personal information[J]. Journal of Electronic Commerce in Organizations, 2006, 4(1): 1-17.
9 Liu B L, Pavlou P A, Cheng X F. Achieving a balance between privacy protection and data collection: a field experimental examination of a theory-driven information technology solution[J]. Information Systems Research, 2022, 33(1): 203-223.
10 Crossler R E, Bélanger F. Why would I use location-protective settings on my smartphone? Motivating protective behaviors and the existence of the privacy knowledge-belief gap[J]. Information Systems Research, 2019, 30(3): 995-1006.
11 Poikela M, Schmidt R, Wechsung I, et al. FlashPolling privacy: the discrepancy of intention and action in location based poll participation[C]// Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers. New York: ACM Press, 2015: 813-818.
12 Liu Y. User control of personal information concerning mobile-app: notice and consent?[J]. Computer Law & Security Review, 2014, 30(5): 521-529.
13 Al-Natour S, Cavusoglu H, Benbasat I, et al. An empirical investigation of the antecedents and consequences of privacy uncertainty in the context of mobile apps[J]. Information Systems Research, 2020, 31(4): 1037-1063.
14 Bansal G, Zahedi F M, Gefen D. Do context and personality matter? Trust and privacy concerns in disclosing private information online[J]. Information & Management, 2016, 53(1): 1-21.
15 梁晓丹, 李颖灏, 刘芳. 在线隐私政策对消费者提供个人信息意愿的影响机制研究——信息敏感度的调节作用[J]. 管理评论, 2018, 30(11): 97-107, 151.
16 Xu H, Teo H H, Tan B C Y, et al. The role of push-pull technology in privacy calculus: the case of location-based services[J]. Journal of Management Information Systems, 2009, 26(3): 135-174.
17 Zhao L, Lu Y B, Gupta S. Disclosure intention of location-related information in location-based social network services[J]. International Journal of Electronic Commerce, 2012, 16(4): 53-90.
18 李凯, 黄敬尧, 王晓文. LBS用户信息公开意愿影响因素分析——基于交换理论的实证研究[J]. 情报学报, 2016, 35(1): 84-97.
19 Yang Q W, Gong X, Zhang K Z K, et al. Self-disclosure in mobile payment applications: common and differential effects of personal and proxy control enhancing mechanisms[J]. International Journal of Information Management, 2020, 52: 102065.
20 刘百灵, 夏惠敏. 隐私反馈技术特征对用户隐私保护行为影响研究[J]. 科研管理, 2020, 41(11): 182-192.
21 朱侯, 李佳纯. 社交媒体用户隐私设置行为实证研究——以微信平台为例[J]. 现代情报, 2020, 40(3): 169-177.
22 朱侯, 张明鑫. 移动APP用户隐私信息设置行为影响因素及其组态效应研究[J]. 情报科学, 2021, 39(7): 54-62.
23 程慧平, 郑雨霏, 闻心玥. 基于扎根理论的社交媒体用户隐私设置意愿影响因素研究[J]. 现代情报, 2021, 41(10): 130-139, 176.
24 赵雪芹, 吴鹏. 基于控制代理理论的移动APP用户隐私信息披露行为研究[J]. 现代情报, 2022, 42(4): 143-152, 167.
25 Lipford H R, Besmer A, Watson J. Understanding privacy settings in Facebook with an audience view[C]// Proceedings of the 1st Conference on Usability, Psychology, and Security. Berkeley: USENIX Association, 2008: Article No.2.
26 Stern T, Kumar N. Improving privacy settings control in online social networks with a wheel interface[J]. Journal of the Association for Information Science and Technology, 2014, 65(3): 524-538.
27 Fang S W, Rajamanthri D, Husain M. Facebook privacy management simplified[C]// Proceedings of 12th International Conference on Information Technology-New Generations. Piscataway: IEEE, 2015: 719-720.
28 沈洪洲, 汤雪婷, 周莹. 我国移动社会化媒体隐私保护功能的可用性研究[J]. 图书情报工作, 2017, 61(4): 23-30.
29 Gu J, Xu Y J, Xu H, et al. Privacy concerns for mobile app download: an elaboration likelihood model perspective[J]. Decision Support Systems, 2017, 94: 19-28.
30 Liu Z L, Wang X Q, Li X H, et al. Protecting privacy on mobile apps: a principal-agent perspective[J]. ACM Transactions on Computer-Human Interaction, 2022, 29(1): Article No.7.
31 Zhang B, Xu H. Privacy nudges for mobile applications: effects on the creepiness emotion and privacy attitudes[C]// Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing. New York: ACM, 2016: 1676-1690.
32 Spence M. Job market signaling[J]. The Quarterly Journal of Economics, 1973, 87(3): 355-374.
33 Mavlanova T, Benbunan-Fich R, Koufaris M. Signaling theory and information asymmetry in online commerce[J]. Information & Management, 2012, 49(5): 240-247.
34 Song Y, Wu H, Ma J D, et al. Exploring the dynamic influences and interaction effects of signals on backers’ investment in the crowdfunding market[J]. Information Technology & People, 2020, 33(2): 792-812.
35 Cheung C M K, Xiao B S, Liu I L B. Do actions speak louder than voices? The signaling role of social information cues in influencing consumer purchase decisions[J]. Decision Support Systems, 2014, 65: 50-58.
36 Liu F Z, Lai K H, Wu J, et al. How electronic word of mouth matters in peer-to-peer accommodation: the role of price and responsiveness[J]. International Journal of Electronic Commerce, 2022, 26(2): 174-199.
37 Hsieh G, Tang K P, Low W Y, et al. Field deployment of IMBuddy: a study of privacy control and feedback mechanisms for contextual IM[C]// International Conference on Ubiquitous Computing. Heidelberg: Springer, 2007: 91-108.
38 刘百灵, 孙文静. 隐私管理技术特征对移动用户信息披露意愿的影响[J]. 系统管理学报, 2020, 29(6): 1113-1123.
39 刘百灵, 杨世龙, 李延晖. 隐私偏好设置与隐私反馈对移动商务用户行为意愿影响及交互作用的实证研究[J]. 中国管理科学, 2018, 26(8): 164-178.
40 钟越, 付迪阳. Android应用程序隐私权限安全研究[J]. 信息安全研究, 2021, 7(3): 287-292.
41 Tan J, Nguyen K, Theodorides M, et al. The effect of developer-specified explanations for permission requests on smartphone user behavior[C]// Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. New York: ACM Press, 2014: 91-100.
42 Mousavi R, Chen R, Kim D J, et al. Effectiveness of privacy assurance mechanisms in users' privacy protection on social networking sites from the perspective of protection motivation theory[J]. Decision Support Systems, 2020, 135: 113323.
43 Connelly B L, Certo S T, Ireland R D, et al. Signaling theory: a review and assessment[J]. Journal of Management, 2011, 37(1): 39-67.
44 Gratch J, Marsella S. A domain-independent framework for modeling emotion[J]. Cognitive Systems Research, 2004, 5(4): 269-306.
45 The White House. Consumer data privacy in a networked world: a framework for protecting privacy and promoting innovation in the global digital economy[J]. Journal of Privacy & Confidentiality, 2013, 4(2): 95-142.
46 刘百灵, 徐伟, 夏惠敏. 应用特征与个体特质双重视角下移动购物持续使用意愿研究[J]. 管理科学, 2018, 31(2): 59-70.
47 刘百灵, 夏惠敏, 李延晖. 移动购物用户信息披露意愿影响因素的实证研究——基于公平理论和理性行为理论视角[J]. 情报理论与实践, 2017, 40(5): 87-93.
48 Xu H, Teo H H, Tan B C Y, et al. Effects of individual self-protection, industry self-regulation, and government regulation on privacy concerns: a study of location-based services[J]. Information Systems Research, 2012, 23(4): 1342-1363.
49 陈雄强, 罗锦艺, 孙心仪, 等. 手机App权限索取风险评估与改进策略[J]. 中阿科技论坛(中英文), 2021(2): 111-113.
50 Cohen B D, Dean T J. Information asymmetry and investor valuation of IPOs: top management team legitimacy as a capital market signal[J]. Strategic Management Journal, 2005, 26(7): 683-690.
51 Aguinis H, Bradley K J. Best practice recommendations for designing and implementing experimental vignette methodology studies[J]. Organizational Research Methods, 2014, 17(4): 351-371.
52 Alexander C S, Becker H J. The use of vignettes in survey research[J]. Public Opinion Quarterly, 1978, 42(1): 93-104.
53 Sharma S, Crossler R E. Disclosing too much? Situational factors affecting information disclosure in social commerce environment[J]. Electronic Commerce Research and Applications, 2014, 13(5): 305-319.
54 Choi B C F, Kim S S, Jiang Z J. Influence of firm's recovery endeavors upon privacy breach on online customer behavior[J]. Journal of Management Information Systems, 2016, 33(3): 904-933.
55 Davis F D. Perceived usefulness, perceived ease of use, and user acceptance of information technology[J]. MIS Quarterly, 1989, 13(3): 319-340.
56 Xu H, Dinev T, Smith J, et al. Information privacy concerns: linking individual perceptions with institutional privacy assurances[J]. Journal of the Association for Information Systems, 2011, 12(12): 798-824.
57 中国互联网络信息中心. 第45次《中国互联网络发展状况统计报告》[EB/OL]. (2020-04-28) [2022-12-30]. https://www.cnnic.cn/n4/2022/0401/c88-1088.html.
58 艾媒网. 手机行业数据分析: 2021年中国网民智能手机操作系统为安卓的占比89.6%[EB/OL]. (2021-08-03) [2022-12-30]. https://www.iimedia.cn/c1061/79273.html.
59 Podsakoff P M, MacKenzie S B, Lee J Y, et al. Common method biases in behavioral research: a critical review of the literature and recommended remedies[J]. Journal of Applied Psychology, 2003, 88(5): 879-903.
60 Wang T E, Duong T D, Chen C C. Intention to disclose personal information via mobile applications: a privacy calculus perspective[J]. International Journal of Information Management, 2016, 36(4): 531-542.
61 Hair J F, Risher J J, Sarstedt M, et al. When to use and how to report the results of PLS-SEM[J]. European Business Review, 2019, 31(1): 2-24.
62 Im G, Rai A. Knowledge sharing ambidexterity in long-term interorganizational relationships[J]. Management Science, 2008, 54(7): 1281-1296.
63 Chin W W, Marcolin B L, Newsted P R. A partial least squares latent variable modeling approach for measuring interaction effects: results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study[J]. Information Systems Research, 2003, 14(2): 189-217.
64 Jiang Z J, Heng C S, Choi B C F. Privacy concerns and privacy-protective behavior in synchronous online social interactions[J]. Information Systems Research, 2013, 24(3): 579-595.
65 Lobel B. Quality of data suffers as consumers are reluctant to disclose personal information[EB/OL]. (2015-05-21) [2022-12-30]. https://smallbusiness.co.uk/quality-of-data-suffers-as-consumers-are-reluctant-to-disclose-personal-information-2485411/. |
|
|
|
