Zhang Changqing, Cui Changqi, Yao Qi
School of Economics and Business Administration, Chongqing University, Chongqing, 400030, People's Republic of China.
School of Economics and Management, Chongqing Jiaotong University, Chongqing, 400074, People's Republic of China.
Psychol Res Behav Manag. 2021 Dec 2;14:1929-1945. doi: 10.2147/PRBM.S336223. eCollection 2021.
In the big data era, many institutions (ie, hospitals) and firms use various methods to encourage people to disclose more personal information to gain competitive advantages in many businesses, such as healthcare and the Internet of Things (IoT) devices. Discussions on antecedents of individuals' willingness to reveal private data from individual differences perspective are limited. Drawing on information boundary theory, we examine how self-construal prompts a different regulatory focus (promotion focus versus prevention focus), thus, affects individuals' willingness to disclose private data.
A mixed-method approach was used to examine our hypothesis. Study 1 (N = 93, participants in China) manipulated self-construal in lab experiments and examined participants' actual disclosure behavior in the emerging IoT context of connected cars. Study 2 (an online survey, N = 200, participants in US) measured chronic self-construal in another disclosure context (healthcare app), replicating the preliminary effect and examined the mediating effect of the regulatory focus. Study 3 (an online experiment, N = 284, participants in US) tested the moderating effect of message framing.
Study 1 showed that participants primed an independent self-construal were more willing to share private information, whether it is real driving data or private identity information. Study 2 showed that independent (interdependent) self-construal individuals tend to have promotion focus (prevention focus), thus leading to higher (lower) willingness to disclose personal health information. Study 3 demonstrated that independent (interdependent) self-construal individuals are more willing to share information when presented with gain-framing (loss-framing) information.
Independent (interdependent) self-construal positively (negatively) affects individuals' willingness to disclose and these effects will be mediated by regulatory focus and moderated by message farming. Our study provides a theoretical paradigm that is new to the willingness to disclose literature, and offers an effective, actionable strategy on how institutions and firms can facilitate individuals' personal information disclosure.
在大数据时代,许多机构(如医院)和公司采用各种方法鼓励人们披露更多个人信息,以便在医疗保健和物联网(IoT)设备等众多业务中获得竞争优势。从个体差异角度对个人披露私人数据意愿的前因进行的讨论有限。借鉴信息边界理论,我们研究了自我建构如何引发不同的监管焦点(促进焦点与预防焦点),进而影响个人披露私人数据的意愿。
采用混合方法来检验我们的假设。研究1(N = 93,中国参与者)在实验室实验中操纵自我建构,并在联网汽车这一新兴物联网背景下考察参与者的实际披露行为。研究2(一项在线调查,N = 200,美国参与者)在另一个披露背景(医疗保健应用程序)中测量长期自我建构,复制初步效应并考察监管焦点的中介作用。研究3(一项在线实验,N = 284,美国参与者)测试信息框架的调节作用。
研究1表明,启动独立自我建构的参与者更愿意分享私人信息,无论是真实驾驶数据还是私人身份信息。研究2表明,独立(相互依赖)自我建构的个体倾向于具有促进焦点(预防焦点),从而导致更高(更低)的披露个人健康信息的意愿。研究3表明,当呈现收益框架(损失框架)信息时,独立(相互依赖)自我建构的个体更愿意分享信息。
独立(相互依赖)自我建构对个人披露意愿产生积极(消极)影响,这些影响将通过监管焦点介导,并受到信息框架的调节。我们的研究为披露意愿文献提供了一个新的理论范式,并为机构和公司如何促进个人信息披露提供了一种有效、可操作的策略。