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Data Analysis and Knowledge Discovery  2024, Vol. 8 Issue (3): 63-76    DOI: 10.11925/infotech.2096-3467.2023.0035
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Emotion and Context’s Impact on Users’ Engagement in Defensive Privacy Protection Behaviors
Liu Bailing1,2(),Lei Xiaofang1,Xu Yang1
1School of Information Management, Central China Normal University, Wuhan 430079, China
2Center for Data Governance and Intelligent Decision-Making of Hubei Province, Wuhan 430079, China
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Abstract  

[Objective] This study explores the mechanism of threat assessment on users’ willingness to engage in defensive privacy protection behaviors. It helps companies make reasonable privacy management decisions and foster a healthy corporate digital ecosystem. [Methods] Based on the protection motivation theory and focusing on threat assessment, we introduced “information privacy anxiety” as an emotional mediating variable. Then, we used the information sensitivity of the context as a moderating variable to construct a model for the impact mechanism of threat assessment on users’ defensive intentions. We used the SEM-PLS to empirically analyze 183 financial and 200 e-commerce context datasets. [Results] Information privacy anxiety is a critical emotional factor influencing users’ willingness to defensive privacy protection behaviors. It plays a partial mediating role between perceived threats and defensive intentions. The information sensitivity of the context positively moderates the relationship between information privacy anxiety and defensive willingness. The information sensitivity of the context only has a moderating effect on the relationship between perceived vulnerability and threat. In contrast, it did not moderate the relationship between perceived severity and threat. [Limitations] This study explores willingness rather than actual behaviors. Regarding information sensitivity comparison, we only chose representative finance and e-commerce contexts. [Conclusions] This study advances the protection motivation theory, providing theoretical guidance for business to adopt appropriate management measures to reduce users’ defensive privacy protection behaviors.

Key wordsProtection Motivation Theory      Defensive Privacy Protection Behaviors      Emotion      Context     
Received: 13 January 2023      Published: 12 April 2024
ZTFLH:  C931  
Fund:National Social Science Fund of China(22&ZD324);Ministry of Education of Humanities and Social Science Project(23YJA630057);Fundamental Research Funds for the Central Universities(CCNU22QN017)
Corresponding Authors: Liu Bailing,ORCID:0000-0001-7825-5263,E-mail: bl_liu@ccnu.edu.cn。   

Cite this article:

Liu Bailing, Lei Xiaofang, Xu Yang. Emotion and Context’s Impact on Users’ Engagement in Defensive Privacy Protection Behaviors. Data Analysis and Knowledge Discovery, 2024, 8(3): 63-76.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2023.0035     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2024/V8/I3/63

A Model of Threat Appraisal on Users’ Defensive Privacy Protection Behavior Intentions
变量 类别 数量 百分比/%
性别 181 47.26
202 52.74
年龄(岁) <18 2 0.52
18~21 75 19.58
22~25 187 48.83
26~30 85 22.19
30~35 18 4.70
>35 16 4.18
职业 在校学生 242 63.19
企业员工 103 26.89
其他 38 9.92
教育背景 高中及以下 19 4.96
大专 17 4.44
本科 171 44.65
硕士 164 42.82
博士及以上 12 3.13
使用金融/电子商务
网站时间(年)
<1 6 1.57
1~2 26 6.79
2~3 50 13.06
3~4 50 13.06
4~5 43 11.23
>5 208 54.31
Demographic Characteristics
因子 金融 电子商务
容差 方差膨胀
因子
容差 方差膨胀
因子
自变量 信息隐私焦虑 0.493 2.028 0.423 2.364
感知威胁 0.300 3.339 0.467 2.143
感知脆弱性 0.303 3.304 0.721 1.387
感知严重性 0.344 2.906 0.621 1.610
因变量 防御性隐私保护行为意愿
Multicollinearity Diagnosis Results
因子 测量项 因子载荷 Cronbach’s α CR AVE
防御性隐私保护行为意愿(PP) PP1 0.894(0.897) 0.919(0.924) 0.943(0.947) 0.804(0.816)
PP2 0.888(0.889)
PP3 0.904(0.917)
PP4 0.901(0.910)
信息隐私焦虑(IPA) IPA1 0.888(0.908) 0.917(0.934) 0.942(0.953) 0.803(0.836)
IPA2 0.889(0.908)
IPA3 0.910(0.926)
IPA4 0.897(0.915)
感知威胁(PT) PT1 0.922(0.917) 0.917(0.916) 0.948(0.948) 0.860(0.859)
PT2 0.927(0.929)
PT3 0.933(0.934)
感知脆弱性(PV) PV1 0.892(0.839) 0.904(0.867) 0.933(0.907) 0.777(0.709)
PV2 0.882(0.821)
PV3 0.866(0.835)
PV4 0.885(0.872)
感知严重性(PS) PS1 0.918(0.909) 0.883(0.863) 0.927(0.917) 0.810(0.787)
PS2 0.880(0.889)
PS3 0.901(0.863)
Results of Confidence and Convergent Validity Tests
因子 PP IPA PT PV PS
PP 0.897(0.903)
IPA 0.815(0.624) 0.896(0.914)
PT 0.638(0.601) 0.688(0.722) 0.927(0.927)
PV 0.554(0.292) 0.618(0.425) 0.787(0.392) 0.881(0.842)
PS 0.548(0.332) 0.631(0.535) 0.739(0.457) 0.776(0.509) 0.900(0.887)
Results of Discriminant Validity Test
A Structural Model Test of Users’ Willingness to Adopt Defensive Privacy Protection Behaviors
类别 信息隐私焦虑 防御性隐私保护行为意愿
β 95%的置信区间 β 95%的置信区间
下限 上限 下限 上限
自变量 感知威胁 0.561*** 0.474 0.648 0.123* 0.027 0.220
中介变量 信息隐私焦虑 0.723*** 0.605 0.841
间接效应 0.406*** 0.302 0.515
Intermediation Effect Test: Finance
类别 信息隐私焦虑 防御性隐私保护行为意愿
β 95%的置信区间 β 95%的置信区间
下限 上限 下限 上限
自变量 感知威胁 0.675*** 0.584 0.765 0.256*** 0.131 0.381
中介变量 信息隐私焦虑 0.348*** 0.215 0.482
间接效应 0.235*** 0.107 0.390
Intermediation Effect Test: E-Commerce
假设 金融(m=183) 电商(n=200) β t 假设支持
H1(2):IPAPP 0.707 0.393 0.314 2.445*** 支持
H2(2):PTPP 0.142 0.327 -0.185 1.436ns 不支持
H3(2):PTIPA 0.688 0.722 -0.034 0.457ns 不支持
H5(2):PVPT 0.537 0.215 0.322 2.492** 支持
H6(2):PSPT 0.322 0.347 -0.025 0.189ns 不支持
Comparing Assumptions in Finance and E-Commerce Contexts
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