“I” Am Willing to Disclose, but “We” are Unwilling: The Impact of Self-Construal on Individuals’ Willingness to Disclose

Figures & data

Table 1 Summary of Previous Research on Willingness to Disclose

Authors	Context	Theoretical Basis or Key Variables	Method	Main Findings
Belk (2013)^Citation31	Digital world		Conceptual	-The impetuses for confession and disinhibition have a positive effect on self-disclosure.
Berendt et al, (2005)^Citation32	Online store with an agent’s recommendations	Privacy attitudes and behavior	Experiment	-Individuals vary in their disclosure intention of private data and can be classified into privacy fundamentalists, profiling averse, marginally concerned, and identity concerned.
Cheng, Hou, and Mou (2021)^Citation13	IT-enabled ride-sharing	Disclosure intention	Interviews, Survey	-Privacy awareness positively affected perceived risks, and thus negatively correlated to the willingness to reveal personal information.
Ghose et al, (2020)^Citation33	Digital contact tracing	Location data	Secondary, Archival data	-High-income individuals and males were more privacy-conscientious and unwilling to disclose private information than low-income people and females.
Hann et al, (2007)^Citation34	Financial website	Information-processing theories	Experiment	-Websters can be classified into information sellers, convenience seekers, and privacy guardians based on their willingness to disclose information.
Karwatzki et al. (2017)^Citation3	Personalized event recommendation services	Information boundary theory, DTVP	Experiment	-A high (low) DTVP individuals are reluctant (willing) to reveal private information.
Li (2014)^Citation12	Websites	Information boundary theory	Survey	-DTVP positively impacts situational privacy concerns and individual’ disclosure intentions.
Li, Lin, and Wang (2015)^Citation28	Social network sites	Willingness to disclose	Survey	-Individuals who are more young, female, and self-confident are more likely to reveal their private data. -The disclosure of sensitive information negatively affects the breadth and depth of disclosure.
Thomaz et al, (2020)^Citation35	Websites in general		Conceptual	-People can be categorized into two distinct types:(1) those generally are prone to disclose their data with firms (Buffs), and (2) those who generally reject sharing personal data (Ghosts).
Treiblmaier and Pollach (2007)^Citation36	Purchase decision-making or advertisements	Users’ perceptions of benefits and costs of disclosure	Survey	-Individuals’ general attitude against private information (ie, their perceived level of risk related to the sharing of various information types) depends on their privacy valuation and the context.
Xu et al, (2011)^Citation37	Websites	DTVP	Survey	-DTVP positively impacts individuals’ privacy concerns and risks and then the resulting information disclosure, but is a rudimentary construct that needs further attention.
Own study	IoT and healthcare app	Information boundary theory, Self-construal, Message framing, Willingness to disclose	Survey, Experiment	-Independent (interdependent) self-construal individuals tend to be promotion focus (prevention focus), thus leading to higher (lower) willingness to share information. -The inhibiting impact of interdependent self-construal on willingness to disclose will be reversed when presented with loss-framing information and the facilitating impact of independent self-construal will be enhanced when presented with gain-framing messages.

Table 2 Demographic Information of Participants

	Study 1 N = 93 Car Driver Sample Recruited in China	Study 2 N = 200 ProA Members The U.S.	Study 3 N = 284 ProA Members The U.S.
Gender
Male	51.6	51	44.1
Female	48.4	49	55.9
Age
18–29	25.8	29	69.4
30–39	45.2	27	20.4
40–49	21.5	28.5	6.7
50–59	7.5	15.5	2.1
≥60	0	0	1.4
Education
Less than high school	0	3.5	2.5
High school graduate	9.6	9.5	31.7
College	14.0	20	19.4
Bachelor’s degree	72.0	52.5	29.9
Master	4.4	13	12.3
Professional degree	0	1.5	2.5
Doctorate	0	0	1.7
Annual household income
Less than $20,000	23.2	33	63.0
$20,000 to $39,999	44	29.5	21.1
$40,000 to $59,999	23	30.5	8.5
$60,000 to $79,999	8	5	4.6
$80,000 to $99,999	1.1	1.5	1.7
$100,000 or more	0.7	0.5	1.1

Figure 1 Effect of self-construal on sharing the driving data.

Note: ***p < 0.001.

Figure 2 Effect of self-construal on sharing the personal identity information.

Note: **p < 0.01.

Figure 3 The mediating role of regulatory focus (Study 2).

Note: ***p < 0.001; n.s. = not significant.

Figure 4 The interaction effect of self-construal and message framing on willingness to disclose.

Note: *p < 0.05; **p < 0.01.

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