1. Introduction
The introduction of the Internet has been integral to information sharing. Before 1995, the Internet was predominantly used by large corporations and academia to exchange information in the form of research. The Internet has transfigured the world of computers and communication through its ability to transmit data, and as an instrument of information sharing [
1]. It took many years for the current variation of social networks to the to evolve. Some of the social networking sites (SNSs) took shape in the 1990s, like BlackPlanet, MoveOn, Six Degrees, Asian Avenue, etc. However, social media was fostered in 2000 when many SNSs flourished and revolutionized communication between individuals and groups who started sharing their social-network-based common interests in education, music, movies, and friendship [
2].
Mark Zuckerberg launched Facebook on 4 February 2004. Dustin Moskovitz, Chris Hughes, and Eduardo Saverin were co-founders of this venture. In September of the same year, they introduced ‘Facebook Wall’, where people could post messages for their friends. Following this, within a short period of three months, one million people were active [
3].
In contrast, the number of users of different social networking sites (SNSs) worldwide has also increased by 280 million since January 2018 [
4]. AlQadheeb and Alsalloum [
5] stated that 94% of Internet users had their accounts on at least one social media platform. Global Web Index [
6] reported that six of 10 global Internet users were connected continuously online in 2019. Facebook has been the most famous social networking site. The data shows that the number of monthly active Facebook users reached 2.5 billion globally as of the 4th quarter of 2019 [
7]. This number is exponentially increasing, and there were over 2.7 billion Facebook users globally, with an active account monthly as of 30 June 2020. This was an increase of 12 percent in Facebook monthly active users year-over-year [
8].
Almost every SNS is meant for sharing, uploading, viewing, downloading, and understanding the information. The common purposes for information sharing are to get others’ attention, develop social capital, strengthen relationships among individuals, attract like-minded people, and develop information and knowledge-based societies. The SNSs users usually create a profile and put their information on these sites, most of which are personal [
9]. This profile could require personal and/or private information, i.e., name, photos, e-mail, physical/mailing address, cellular phone numbers, gender, interests, etc. However, some users share this information by choice on these sites, as these sites have an option to add more personal information like photographs, videos, family information, preferences, events, stories, opinions, etc. [
10].
In postmodern times, the sharing of personal information on social media networks has become excessively simple. Many platforms are readily available for people willing to share their personal information on social media, particularly on the most popular platform, Facebook. The terms ‘self-disclosure’ and ‘personal information sharing’ are used interchangeably in the literature. Self-disclosure is defined as ‘the act of revealing personal information to others’ [
11]. In the context of business, personal information sharing behavior is described by the perception of information disclosure, which eventually refers to revealing consumers’ data, i.e., biographical and/or demographic attributes, way of living, shopping practices, likes of commercial organizations [
12,
13] In general, posting a picture, personal information, providing status updates, or revealing personal preferences and experiences while engaging in public communication with other online community members is known as self-disclosure [
14]. Certain factors impact personal information sharing behavior or self-disclosure, e.g., social trust, trust, enjoyment, ease of use, benefits [
15,
16,
17], and privacy concerns [
18,
19].
Self-disclosure is mostly associated with social capital development [
20] and interpersonal relationship building [
21]. Literature suggests that self-disclosure helps individuals to overcome feelings of loneliness [
22]. Thus, it can positively impact the individual’s well-being [
23,
24]. Lately, during the COVID-19 emergency, people were socially isolated, and at this time, social capital could help individuals feel connected with others and reduce loneliness. Nabity-Grover et al. [
25] found a significant positive impact of COVID-19 on individual’s self-disclosure behavior, and they were found involved in self-disclosure on social media. The research on this topic mostly comes from developed countries, i.e., United States [
16,
26,
27] (Saudi Arabia [
5], Dutch [
18], Turkey [
28], Germany and Norway [
29], Malaysia [
30], and Hong Kong [
31], etc. However, little is known from developing countries, i.e., Indonesia [
32], Brazil [
33], while no literature could be found from South Asian contexts regarding self-disclosure. Only one study based on Pakistani students’ self-disclosure behavior is reported recently from China. Developing countries usually lack resources and expertise in different areas; therefore, it is essential to research developing countries to identify the current status, challenges, and opportunities to devise viable frameworks. In the modern digital paradigm, the effective use of information technology can help developing countries deal with several challenges, particularly those concerning the current research. Technology adoption in terms of self-disclosure may help overcome anxiety, depression, and mental ill-being of individuals through social capital development and connectedness. The identified antecedents may be manipulated effectively to bring positive outcomes.
Considering this literature gap, the current research was carried out to explore Pakistani Facebook users’ self-disclosure behavior and the factors that encourage them to share their personal information. The findings may be helpful to understand the phenomena in the local context in a comprehensive way. The results will further help identify the antecedents that, if utilized in a planned way, can positively affect self-disclosure behavior, which may further positively affect an individual’s well-being and help them develop social capital.
4. Data Analysis
A total of 400 Pakistani Facebook users responded to the questionnaire with valid responses. The distribution of age groups in
Table 2 shows that young people aged between 21 to 30 years participated in this study enthusiastically. In contrast, teenagers did not take much interest in filling out the questionnaire. The possible reason for being the largest age group (21–30 years) would be that this age group takes research seriously. Another reason could be that this age group considered students at the undergrad or graduate level, so they responded well as they might understand the importance of research. Additionally, as students, they were not attending their academic institutions due to COVID-19, so they might have had enough time to respond to this study.
The educational background distribution revealed that the largest group of participants in this study had an MA/MSc/BS degree. The reason behind this might be that the majority of the respondents belonged to the age group of 21–30 years. In Pakistan, students usually complete their master’s degree (after 16 years of education in Pakistan) in the same age group [
85]. (Previously, Kanwal et al. [
86] also reported that the Pakistani younger generation and most students were SNSs addicts. This could be a reason for the high participation of people having a MA/MSc/BS degree.
Furthermore, in Pakistan, Mphil/MS/Ph.D. degree holders are smaller in number as compared to the MA/MSc/BS degree holders. On the contrary, the smallest group of contributors had a Matric/O-Level education. This might be because the research cannot expect a holder of a 10-years education to participate in a research study, as they do not have enough knowledge and exposure to understand the importance of participation in research studies in the Pakistani context.
The people who were employed in a job made up the largest group of participants in this study. The reason for this might be that they have more opportunities and time to take part in such research activities. On the other hand, unemployed people might not have computing and internet facilities.
4.1. Analysis of Measurements and Structural Model
All the study constructs were reflective in nature. The structural equation model was employed using partial least squares (PLS) analysis to assess the measurement and structural model for reflective constructs.
4.1.1. Estimation of the Outer Measurement Model
Reliability
To investigate the reliability of the constructs, the study adopted the suggestion of Hair et al. [
87] in that the reliability of the constructs should be measured in two ways, first by measuring Chronbach’s alpha and second by the composite reliability against the threshold value >0.70 [
87]. Data in
Table 3 show that for all constructs, Chronbach’s alpha values and the composite reliability values were above the threshold >0.70. Therefore, it can be safely concluded that all constructs were reliable.
Convergent Validity
The convergent validity of the constructs was measured by the average variance extracted (AVE). AVE measures the average variance shared between the construct and its indicators. AVE’s threshold value is 0.5 (50%) or higher [
88]. The results in
Table 3 confirm that all constructs’ convergent validity was above the accepted threshold value, i.e., 0.5 or higher.
Multi Collinearity
To examine the values of collinearity, variance inflation factor (VIF), the significance of outer weights, and the significance of item loadings were examined [
89]. VIF values for all items of constructs were between 1–5 and were within the range of threshold value (
Table 4). The results in
Table 4 further indicate that for all the construct items, outer weights were significant. Secondly, outer loadings for all construct items were higher (>0.6) than the threshold value and were significant.
Discriminant Validity
If the average variance shared between the construct and its individual indicators was higher than 0.5, the next step was to measure the constructs’ distinctiveness. Henseler et al. [
90] suggested applying the heterotrait-monotrait ratio of correlations (HTMT). Hair Jr. [
88] encouraged application of HTMT 0.85 cutoff scores to interpret the HTMT results to verify the distinctiveness of the constructs. All the constructs’ values were lower than 0.85, which proved that all constructs were distinctive in nature (
Table 5).
4.1.2. Confirmatory Factor Analysis
For confirmatory factor analysis, PLS-SEM was applied as it is suitable to measure complex models with endogenous and exogenous constructs and indicators. Furthermore, the sample size was reasonably large for PLS analysis, as Hair et al. [
91] suggested. PLS-SEM analysis suggested a good model fit (SRMR = 0.097, NFI = 0.806) as the SRMR value was less than 0.10, and the NFI value was close to 1 [
92].
Figure 2 revealed that the item loadings were within the threshold value i.e., 0.5 as recommended by Awang [
93], and t values (depicted in the constructs’ relationship paths) and
p values were all accepted and significant. Furthermore,
Table 3 depicts that the composite reliability values for all constructs were more than 0.7, the average variance extracted values confirmed the convergent reliability i.e., >0.5 [
88], and Rho_A reliability coefficients were above 0.7, which was an acceptable range [
94]. The discriminant validity was measured through HTMT, and the values for all constructs met the criteria of HTMT 0.85 cutoff scores suggested by Hair Jr. [
88] (
Table 5).
4.1.3. Estimation of the Inner Measurement Model
Estimation of Path Coefficients (β) and T-Statistics
The path coefficients were estimated, and β denoted the expected variation in the dependent construct for a unit variation in the independent construct(s). The bootstrapping procedure was adopted to evaluate the significance of the hypothesis. To test the significance of the path coefficient and T-statistics values, a bootstrapping procedure using 5000 subsamples with no significant changes was carried out for this study, and the results are presented in
Table 6.
Data in
Table 6 show that all hypotheses were accepted at
p < 0.01. It was proved that individuals who find Facebook a medium that is easy to use agreed with the benefits of personal information sharing (B = 0.30, t = 6.16,
p < 0.00). Similarly, the people who agreed that personal information sharing behavior had its benefits considered Facebook a trustworthy medium (B = 0.31, t = 6.76,
p < 0.00). The data in
Table 6 show the negative impact of privacy concerns on Facebook’s trust (B = −0.20, t = 4.24,
p < 0.00).
However, it was confirmed that trust in the medium (Facebook) had a significant positive impact on developing social trust (B = 0.41, t = 7.99, p < 0.00). Further, social trust had a significant positive impact on personal information sharing behavior (B = 0.14, t = 3.40, p < 0.001).
Furthermore, a strong impact of the perceived benefits associated with personal information sharing practices on personal information sharing behavior was also witnessed (B = 0.49, t = 14.38,
p < 0.00). The graphical presentation of path analysis is referred to in
Figure 3.
4.1.4. Model Prediction
To examine the predictability power of the model, PLSpredict was applied. According to Shmueli et al. [
95], the precondition to applying this test is that Q2
predict for all the dependent constructs’ indicators should be more than 0. The MV prediction summary showed that PLS-SEM Q2
predict for all the dependent constructs’ indicators was above 0. Thus, on the second step, error histograms for the indicators were observed to find out if the distribution was symmetrical, PLS-SEM error plots were not normally distributed, and this was confirmed from the values of Skewness, Kurtosis, and Shapiro-Wilk test as well (
Table 7).
Therefore, it was decided to review the difference between PLS-SEM MAE and LM MAE values instead of RMSE values as per the guidelines of [
95]. Since the minority of the dependent construct’s indicators produced lower PLS-SEM prediction errors than the Naive LM benchmark (
Table 8), it could be concluded that the model had a low predictive power.
5. Findings and Discussion
Social media offers several opportunities to share and exchange personal information, i.e., opinions, pictures, videos. People use social media for self-disclosure [
96]. In particular, Facebook is the most popular social media platform. Self-disclosure relieves loneliness [
22], strengthens relational closeness [
97], expands the social network [
98], develops social capital [
20], increases the feeling of connectedness [
21], and improves subjective well-being [
23,
24]. A sense of self-expression [
99] and a feeling of familiarity with oneself [
100] are some other motives of self-disclosure. Individuals who express their thoughts, posts, hopes, and hobbies would essentially obtain more attention from friends and family members [
86]. Thus, it can be concluded that self-disclosure has several associated benefits, i.e., it satisfies individuals’ self-esteem, helps develop social capital, maintains relationships with friends and family members, and develops new relations.
This study provides several interesting findings in the field of information sharing behavior and self-disclosure. It highlights the antecedents of self-disclosure based on the technology acceptance model (TAM). The two main constructs of TAM were found to be correlated. It is confirmed from the findings of the current study that if technology and information systems cause no or little physical and mental exertion, people consider that technology or information system is useful. Earlier, Cho and Sagynov [
72] confirmed that online customers find shopping more beneficial if they can easily navigate through the online store. Similarly, Amin et al. [
65] suggested that mobile marketers should make users’ work easier if they intend to increase technology’s perceived usefulness and adoption.
The research discloses that the perceived usefulness/benefits of self-disclosure and the Facebook community’s trust significantly and directly impact personal information sharing behavior. If individuals are aware of personal information sharing benefits, they will share personal information more frequently. Thus, this study declared that the benefits of sharing personal information behavior are the most prominent antecedent among other antecedents under study. The people of Pakistan post their personal information considering that Facebook increases their popularity by sharing photos, ideas, activities, etc. This way, they present themselves before the members of their social network. Past studies also reported the same results as this study. Beldad [
15] revealed in his study, which was carried out in the Netherlands, that information sharing benefits were a strong predictor of young users’ decision to share personal information on Facebook. Similarly, the results of research by Kim and Kim [
73] conducted at Midwestern University, USA, showed that the benefits of personal information sharing on the web convinced users to publish their personal information. Considering the results obtained, we can conclude that the higher the benefits of self-disclosure that individuals perceive, the higher their volume of personal information sharing will be.
Similarly, people will share personal information more frequently if they trust those who have access to that information. Earlier studies have provided similar results to the current study. Salehan et al. [
16] uncovered that social trust is positively associated with personal information sharing behavior. Likewise, Hong and Hashim [
30] discovered in their study conducted in Northern Malaysia that social trust represented one of the positive features of Facebook relationships. Additionally, Dwyer et al. [
81] reported that Facebook members were trustworthy, so they were more willing to include personal information in their profiles.
Furthermore, social trust is an outcome of trust in the medium. The trust in the medium develops the trust in the community who is using that medium of information. The available literature discusses the impact of social norms on an individual’s trust in a medium, but little is known about the impact of trust in a medium on the trust of the community of that particular medium [
80], which is measured empirically in the current study. However, there is a need to test this impact further on different mediums and in different contexts.
Whereas privacy concerns are negatively associated with trust in the medium. If individuals have fewer privacy concerns, they will have more trust in the medium. Some previous studies also reported the same results. Higher privacy concerns are associated with weaker intentions to utilize online services [
78]. As individuals’ belief that accessing social networking sites over the internet is secure develops trust in the medium [
79]. Likewise, Paramarta et al. [
32] concluded that control over privacy protection positively impacted trust in social media among Indonesian people. Thus, the current study concludes that there was a negative impact of privacy concerns on trust in mediums, leading to self-disclosure through social trust.
6. Conclusions
The study concludes that self-disclosure behavior is dependent on multiple factors, i.e., individuals’ perceptions about the usefulness of personal information sharing, trust in the community to whom personal information is shared, trust in the medium, i.e., Facebook will keep its promises and will use personal information fairly. Although individuals’ perceived ease of use does not impact self-disclosure directly, it does, however, help them to understand the potential benefits of self-disclosure. Similarly, the people who consider personal information sharing riskier will have less trust in the medium and its community members, and, as a result, they will share personal information on Facebook less frequently.
It can be concluded that the perceived usefulness of self-disclosure practices and social trust impact directly whereas, perceived ease of use and privacy concerns indirectly impact the personal information sharing behavior. Likewise, trust in a medium and a community plays a mediating role. Furthermore, the impact of two independent variables borrowed from TAM proved stronger predictors of self-disclosure behavior, as compared to the other predictors. The study supports the theory of TAM.
7. Theoretical Contributions and Policy Implications
Theoretically, the study strengthens the literature on the use of SNSs and self-disclosure from developing countries. Furthermore, a handful of studies on the topic are based on the students’ data only, and little is known about the general public’s self-disclosure behavior. The current study somehow tries to bridge this gap in the literature. Additionally, the study extends TAM by including mediating variables, particularly by exploring the impact of “trust in the medium” on “social trust” that has rarely been explored previously.
The study offers several policy implications:
Ease of technology use positively impacts the individuals’ perceived usefulness of a medium/technology-related practice. It poses two types of implications; first, the SNSs administrators should try to develop user-friendly platforms for communication. Secondly, the government should devise policies to train individuals to use the technology effectively, and these policies should be implemented with the help of academic institutions (for students), employers (for employees), public libraries, and community centers through organizing training programs (for the general public). These training courses may be designed for different levels i.e., beginners and intermediate. The training contents may cover basic use to expert use of technology and social media for personal, professional, and economic benefits. In this way, individuals may find these kinds of mediums easy to use and may actively share personal information that will ultimately give them the associated benefits, i.e., social capital development, connectedness, self-esteem, etc.
It is also found that individuals with better awareness about the benefits of self-disclosure practice more frequently. Therefore, it is suggested that Facebook users should be guided about self-disclosure and its advantages. Particularly, psychiatrists and educators who want individuals to disclose their personal information with the purpose to connect them with others and reduce loneliness should consider that individuals will adopt this behavior if they consider it useful. Therefore, the potential benefits of self-disclosure must be communicated to the individuals by psychiatrists and educators.
In the current era, when SNSs have incorporated advanced privacy measures, individuals still show privacy concerns, and these negatively impact the trust in the medium of communication. Whereas trust in the medium has an indirect positive impact on self-disclosure behavior. As a matter of policy, SNSs providers should implement privacy policies and enhance an individual’s control over their personal information [
74]. Furthermore, users must be trained to manage their privacy settings, which will reduce their privacy concerns. In this way, individuals will have more trust in the medium that mitigates personal information sharing behavior. Similarly, social networking sites, especially Facebook, should attract baby boomers and generation X to join and use social media network sites, as they use this type of platform the least.
Social trust triggers self-disclosure; SNSs administrators should take such measures that enhance individuals’ trust in the SNSs community. For example, the fair use of information policy should be encouraged through a quick response to the users’ complaints. SNSs users may be guided on how and to whom they may contact if they find other members misusing their personal information. The national cyber-crime department should give cyber-crime awareness through seminars and training in liaison with academic institutions and public libraries.
These types of studies are conducted to potentially modify the users’ information sharing behavior by educating them through workshops, conferences, seminars, discussions, etc, as well as, help to address the negatively impacting variables, if found, for effective social networking sites’ use.