Binsawad Muhammad, Abbasi Ghazanfar Ali, Sohaib Osama
Department of Computer Information Systems, King Abdulaziz University, Jeddah, Saudi Arabia.
Labuan Faculty of International Finance, Universiti Malaysia Sabah, Malaysia.
PeerJ Comput Sci. 2022 Mar 16;8:e926. doi: 10.7717/peerj-cs.926. eCollection 2022.
Big data and machine learning technologies facilitate various business intelligence activities for businesses. However, personal data collection can generate adverse effects on consumers. Big data collection can compromise people's sense of autonomy, harming digital privacy, transparency and trust. This research investigates personal data collection, control, awareness, and privacy regulation on people's autonomy in Saudi. This study used a hybrid analytical model that incorporates symmetrical and asymmetrical analysis fuzzy set qualitative comparative analysis (fsQCA) to analyze consumer sense of autonomy regarding big data collection. The symmetrical shows that 'Control' had the most significant influence on people's autonomy, followed by 'Big data collection' and 'Awareness'. The fsQCA shows 84% of the variation, explaining the people's autonomy.
大数据和机器学习技术推动了企业的各种商业智能活动。然而,个人数据收集可能会给消费者带来不利影响。大数据收集可能会损害人们的自主感,损害数字隐私、透明度和信任。本研究调查了沙特阿拉伯个人数据收集、控制、意识以及隐私监管对人们自主性的影响。本研究使用了一种混合分析模型,该模型结合了对称和不对称分析——模糊集定性比较分析(fsQCA),以分析消费者对大数据收集的自主感。对称分析表明,“控制”对人们的自主性影响最大,其次是“大数据收集”和“意识”。fsQCA显示出84%的变异,解释了人们的自主性。