Predictors of Chinese Users’ Location Disclosure Behavior: An Empirical Study on WeChat

Abstract

Location disclosure behavior on social network sites (SNS) has developed rapidly. However, the influencing factors have not been adequately studied. Based on social cognitive theory and the concept of face, this study developed a research model to explain the factors with uniquely Chinese characteristics that predict WeChat users’ location disclosure. Using survey data collected from WeChat users in China (N = 545), the model is tested by a structural equation modeling (SEM). The results show that a desire to gain face, a fear of losing face, social norms, trust in SNS members and trust in an SNS provider positively influence WeChat users’ intention to disclose location information. Moreover, trust in SNS members can also boost trust in an SNS provider. Finally, both theoretical contributions and practical implications are discussed.

1. Introduction

Social network sites (SNSs) refer to “the web-based services that allow individuals to (1) construct a public or semi-public profile within a bounded system, (2) articulate a list of other users with whom they share a connection, and (3) view and traverse their list of connections and those made by others within the system” [1]. The integration of location-based services (LBS) and SNSs via mobile devices has bridged users’ physical and social worlds [2]. Hence, location-based social network services (LBSNS) have emerged, such as “check-in” services, providing individuals opportunities to communicate their location with others on social network sites and to maintain social relations with geographically distant friends [2]. On the one hand, location disclosure is of great importance to SNS users. Location disclosure on SNSs could be perceived as socially desirable, since disclosure is a key strategy of identity construction. Location disclosure allows users to consciously show their social life and present themselves in a desirable manner by selectively revealing some locations over others [2]. On the other hand, location disclosure behavior on SNSs has become a natural vehicle for SWOM (social word of mouth) for the locations at which users check in [3], such as restaurants and stores. The locations’ names and other related information disclosed by users are inadvertently exposed to SNS friends. This valuable spatiotemporal information disclosed by users not only helps businesses to improve mobile strategies but also has important implications for SNS providers. However, a study from a consulting firm revealed that 13% of SNS users disclosed their locations on Foursquare or Facebook, but only 6.5% of Chinese users engaged in check-in behavior [4]. Although location disclosure behavior is obviously an important issue, few studies have investigated the factors that drive Chinese users to check in to SNSs.

WeChat is the most popular social network in China [5]. “Moments” (Chinese pinyin: péngyǒu quān) is an important feature of WeChat, in which users can disclose their emotions, thoughts, and locations by posting text or pictures. More than 90% of users visit WeChat every day. A total of 61.4% of users browse “Moments” when they open WeChat [6]. Different from other SNSs, WeChat is uniquely characterized by intimacy among members: most WeChat “friends” know each other in real life [5]. The location-related information disclosed by users on SNSs can be viewed as a free and natural vehicle for SWOM [3]. The more intimate relationships are, the more likely WOM recipients will regard the information as important and change their attitudes and intentions [7]. In view of the characteristically strong ties on WeChat, the location disclosure behavior on that site may have a stronger impact on readers. Therefore, WeChat was investigated in this study.

SNSs in China have developed very quickly in recent years. For example, the WeChat-driven information economy reached 209.7 billion Chinese yuan (RMB) in 2017, making up for 4.7% of China’s total information consumption [8]. Prior research showed that Chinese users disclosed less personal information on SNSs than Western users, which can be explained by cultural characteristics [9]. However, most previous studies on check-in behavior were conducted in a Western context [2,3]. Influencing factors based on Chinese characteristics have received little attention. In China, a collectivistic society, face consciousness, and social influence are more salient [10,11]. In addition, general trust is lower in China [12]. Social cognitive theory (SCT) shows that people’s behavior is influenced by individual and environmental factors [13]. Moreover, prior research summarized that the influencing factors on users’ information disclosure on SNSs could be divided into three aspects: individual factors, platform related factors, and social influence factors [14]. Therefore, we explore the predictors of Chinese users’ check-in behavior on WeChat from individual (face consciousness), social (social norms), and platform-related perspectives (trust).

Moreover, it is difficult for individuals to trust social network providers, since they believe that providers are more likely to misuse their information [15]. Trust transfer theory indicates that trust in systems could be derived from interpersonal trust [16]. Even though China is a low-trust society, in close relationships, Chinese people show higher interpersonal trust [12]. Close relationships among users are a unique characteristic of WeChat [5]. Less is known about whether providers could benefit from interpersonal trust in the context of WeChat.

This study aims to investigate the Chinese characteristics and factors that predict users’ intention to disclose location information to "Moments" on WeChat from the individual, social and platform perspectives. Moreover, we also examine the trust transfer theory in the context of SNSs. Our findings help to provide theoretical and practical implications for researchers, marketers, and advertisers.

This paper is structured as follows. First, we review previous related studies. Next, we propose our research hypotheses and develop a research model. Then, by using structural equation modeling, we verify the proposed model and discuss the results. Lastly, we conclude with the theoretical and practical implications and suggest directions for further research.

2. Theoretical Background and Hypotheses

2.1. Location Information Disclosure on SNS

Location information disclosure, i.e., check-in or tagging locations on status updates and posts, is defined as a record that users use to show and notify their friends about where they have been [3]. Social network services allow users not only to check in to specific locations but also to disclose location-related information such as experiences, thoughts, or photos by tagging locations on posts or status updates [17].

Social cognitive theory (SCT) shows a triadic reciprocal causation between personal factors, the external environment, and behavior [18], which has been examined in various topics such as mass communication, career development, and organizational management [19,20,21]. In this reciprocal causation, personal factors, environmental factors, and behavior influence each other bidirectionally [19]. It indicates that people’s behavior is influenced by individual and environmental factors [13]. This is confirmed by a review study, in which the influencing factors leading to information disclosure behavior on SNSs were summarized into three aspects: individual, platform-related, and social influence factors [14]. Both social and platform-related factors can be seen as environmental factors. However, prior research on location disclosure has mainly focused on individual aspects. For instance, previous studies found that extraversion and narcissism indirectly impact check-ins via attitudes towards self-disclosure and exhibitionism [2]. Furthermore, according to the privacy calculus model, people check in to SNSs after weighing the trade-off between perceived benefits and risks [22]. However, environmental factors received less attention.

Additionally, Chinese people tend to disclose less personal information compared to Western users [23], and this difference can be explained by cultural characteristics [24]. Therefore, more research is required to explain Chinese SNS users’ check-in behavior by exploring the effects of Chinese characteristics, such as face consciousness, social norms, and trust.

2.2. Face Consciousness

In self-presentation theory, face refers to maintaining a positive image in order to make positive impressions on others [25]. Bao et al. [26] have proposed a new concept—face consciousness, which refers to people’s desire to gain face and avoid losing face in their social lives. The concept of face is deeply rooted in Chinese culture and the daily social behavior of Chinese people [27]. Therefore, we inferred that face consciousness may also influence individuals’ location disclosure behavior on SNSs.

Face consciousness can be divided into two dimensions—“fear of losing face” and “desire to gain face” [10]. These two are not the opposite ends of the same dimension but two different aspects of the face consciousness construct. They may coexist, that is, an individual may not only want to gain face but also may fear losing face [10]. “Desire to gain face” reflects the extent to which an individual wants to gain face. In a Chinese context, individuals need not only to maintain good relationships with others but also need to maintain face [28]. This can be regarded as a typical impression management behavior, because individuals want to obtain better evaluations from others by presenting themselves in a positive light. Wang and Stefanone [2] have indicated that check-ins may be a tool of impression management. The higher one’s desire to gain face is, the more likely one is to present oneself on an SNS with the expectation of obtaining positive evaluations, and the more likely one is to disclose location. Thus, we propose the following hypothesis:

H1 “Desire to gain face” is positively associated with users’ disclosure of location information on WeChat.

“Fear of losing face” reflects the extent to which an individual has concerns about losing face. Individuals who do not maintain proper social performance may be out of line with social expectations, which may eventually lead to loss of face [10]. Therefore, “fear of losing face” may increase users’ susceptibility to the influence of social norms [29]. Users who are afraid of losing face may pay more attention to social norms because they are more concerned about whether their behavior is in line with social expectations. As a result, they may check in to WeChat when others think that they should do it. Thus, we propose the following hypotheses:

H2 “Fear of losing face” is positively associated with users’ intention to disclose location information on WeChat.

H3 “Fear of losing face” is positively associated with social norms.

2.3. Social Norms

In a collectivistic culture such as China, social influence is particularly salient. Social influence theory has been widely used to explain the effect of others on individuals [30]. This theory argues that an individual’s feelings, attitudes and behavior are influenced by others [31]. Compliance occurs when people want to obtain rewards from important others or avoid punishment [32]. From the perspective of social psychology and economics, social norms are a key factor in social influence [33].

In this study, social norms are the extent to which one perceives that other people believe he/she should behave in some way [34,35,36]. Many studies on information disclosure have examined the positive effect of social norms on users’ disclosure behavior [35]. Koohikamali et al. [36] have suggested that social norms indirectly influence location disclosure through attitude. Less is known about if social norms have a direct effect on users’ location disclosure intention. People comply with social norms because they can bring a sense of social identity [11]. Therefore, WeChat users may disclose their location on “Moments” to comply with the expectations of friends and relatives and avoid being isolated. Thus, we propose the following hypothesis:

H4 Social norms are positively associated with users’ intention to disclose location information on WeChat.

2.4. Trust

Trust refers to “the willingness of a party to be vulnerable to the actions of another party based on the expectation that the other will perform a particular action important to the trustor, irrespective of the ability to monitor or control that other part” [37]. China is a low-trust society [38]. However, trust is an important platform-related factor in predicting online information disclosure [39,40]. However, the effect of trust has not been discussed in previous studies on check-in behavior.

Previous studies divided trust into two forms according to target: interpersonal trust and system trust [15]. Interpersonal trust refers to “one’s confidence in others’ reliability and integrity” [41]. System trust is defined as the perceived reliability of an information system [42]. In virtual communities, trust in members and trust in the system positively influenced individuals’ stickiness [16]. Many studies have confirmed that both trust in the SNS provider [43] and trust in SNS members [40] were positively associated with users’ information disclosure behavior on SNSs. Privacy risk has a significantly negative effect on people’s intention to disclose locations [22,36]. Trust significantly reduces the negative effect of privacy risk [44]. Therefore, both trust in the SNS provider and trust in SNS members may also positively impact WeChat users’ check-in behavior. Thus, we propose the following hypotheses:

H5 Trust in an SNS provider is positively associated with users’ intentions to disclose location information on WeChat.

H6 Trust in SNS members is positively associated with users’ intentions to disclose location information on WeChat.

Users may place less trust in social media if they believe that SNS providers have a stronger motive to abuse information without authorization than other members of an SNS [15]. However, according to the trust transfer theory, trust in the platform provider can be derived from trust in the SNS members. An individual’s trust in an unknown person or object may be transferred from his trust in a known person or object [45]. Previous studies confirm that interpersonal trust can be transferred to system trust through communication or cognitive process, such as trust in users of a website to trust in the website or community [46]. In virtual communities, trust in members positively influences trust in systems [16]. Therefore, trust in WeChat can benefit from trust in WeChat friends. Thus, we propose the following hypothesis:

H7 Trust in SNS members is positively associated with trust in the SNS provider.

Figure 1 shows the research framework of this study.

3. Method

3.1. Measures

We conducted an online survey through WeChat to ensure that the respondents were WeChat users in China. This study recruited 652 participants by using the snowball method to obtain a convenience sample in July 2016. According to Tencent [6], young people aged 18–35 are the main users of WeChat (86.2%). Therefore, ten undergraduates and graduate students (18–35; five males and five females) from a university in southwestern China were first recruited and asked to share the questionnaire with their friends and family. We asked them to transmit links in WeChat groups and “Moments” because of the diversity and wider coverage of samples and to ensure that participants were WeChat users. We did not limit specific transmitted objects to ensure the sample randomness. The responses with excessively short answering times (<120 s) or with the same scores for all items were regarded as invalid and deleted. We produced 545 validated questionnaires.

The questionnaires contained two sections. The first section consisted of six constructs (desire to gain face, fear of losing face, social norms, trust in SNS providers, trust in SNS members, and location disclosure intentions). The second section included the demographics of subjects (like gender, age, and education), usage of WeChat, and their experiences with location disclosure. There were nine measurement items for each of the two trust constructs, which were adapted from Contena et al. [47] and Krasnova et al. [15]. The measurement of face consciousness included 10 items that were adapted from Zhang et al. [10]. The social norm scale (three items) was adapted from Hsu and Lu [33] and Li et al. [11]. Check-in on WeChat is equal to location-tagging on updates or posts. Therefore, the concept of location disclosure in this study was the same as check-in. There were two measurement items regarding location disclosure intention, which were adapted from Luarn et al. [3]. Our survey contained 24 items total (see Appendix A) and used a seven-point Likert scale ranging from “strongly disagree = 1” to “strongly agree = 7”.

3.2. Sample Characteristics

Of the 545 participants, 60.7% of them were female. Most of these respondents were young users (82% were less than 30 years old), and most of them were well-educated (73% had a bachelor’s degree or above). The subjects tended to use WeChat for more than 1 hour per day (67.7%) (see

Table 1. Demographic statistics (N = 545).

Variables	Levels	Frequency	Percentage (%)
Gender	Male	214	39.3
	Female	331	60.7
Age	≤20	149	27.3
	21–25	223	40.9
	26–30	75	13.8
	31–50	81	14.9
	>50	17	3.1
Education	High school or below	29	5.3
	Two-year college	118	21.7
	Bachelor’s degree	254	46.6
	Master’s degree or higher	144	26.4
WeChat usage experience	None	0	0
	<1 year	92	16.9
	1–3 years	317	58.2
	4–5 years	103	18.9
	>5 years	33	6.1
WeChat usage/day	None	0	0
	<1 h	176	32.3
	1–3 h	207	38
	4–5 h	62	11.4
	>5 h	100	18.3
WeChat friends	None	0	0
	<50	144	26.4
	50–500	371	68.1
	500–1000	22	4
	>1000	8	1.5
Number of locations disclosed on WeChat during past half year	None	225	41.3
	1–3 times	157	28.8
	4–6 times	77	14.1
	7–9 times	36	6.6
	>=10 times	50	9.2

). Overall, this demographic information is consistent with that of WeChat users [6].

4. Results

4.1. Measurement Model

Table 2. Descriptive statistics, reliabilities, and correlations.

Constructs	Mean	SD	CR	AVE	Cronbach’s α	DG	FL	SN	TM	TP	LD
DG	4.328	1.033	0.866	0.565	0.853	0.752
FL	3.704	0.973	0.856	0.544	0.820	0.556	0.738
SN	3.630	1.342	0.911	0.773	0.926	0.234	0.233	0.879
TM	4.582	0.931	0.900	0.643	0.897	0.245	0.189	0.337	0.802
TP	4.389	1.014	0.890	0.671	0.901	0.240	0.140	0.341	0.596	0.819
LD	4.080	1.390	0.852	0.741	0.907	0.335	0.287	0.533	0.386	0.395	0.861

Notes: AVE = Average variance extracted, CR = Composite reliability, DG = Desire to gain face, FL = Fear of losing face, SN = Social norm, TM = Trust in SNS members, TP = Trust in SNS provider, LD = Location-information disclosure intention.

shows the results of absolute fit indices (χ²/df = 1.637 < 3; RMSEA = 0.033 < 0.08) and incremental fit indices (CFI = 0.982 > 0.9; GFI = 0.948 > 0.9; TLI = 0.979 > 0.9; IFI = 0.982 > 0.9), demonstrating a good model fit [48].

The Cronbach’s α values of these six constructs were greater than 0.8 (see Table 2), which implies that the measurement results of these six variables in the scale are reliable [49]. Composite reliabilities (CR) and average variance extracted (AVE) exceed the suggested threshold values of 0.6 and 0.5, respectively, showing adequate convergent validity [48,50]. In addition, the square roots of AVE (diagonal elements) are greater than the correlations between any two constructs (nondiagonal elements), indicating good discriminant validity [50]. Every within-construct item loads on the measured construct higher than on other constructs, also showing good discriminant validity [51], as shown in

Table 3. Loadings and cross-loadings.

	DG	FL	SN	TM	TP	LD
DG1	0.745
DG2	0.803
DG3	0.786
DG4	0.712
DG5	0.708
FL1		0.744
FL2		0.746
FL3		0.841
FL4		0.677
FL5		0.667
SN1			0.86
SN2			0.908
SN3			0.868
TM1				0.71
TM2				0.787
TM3				0.845
TM4				0.873
TM5				0.785
TP1					0.792
TP2					0.878
TP3					0.847
TP4					0.753
LD1						0.852
LD2						0.87

.

4.2. Structural Model

This study tested the structural model by using Amos 17.0 [52]. The analysis results showed that χ²/df = 2.662 < 3, RMSEA = 0.053 < 0.08, CFI = 0.952 > 0.9, GFI = 0.916 > 0.9; TLI = 0.946 > 0.9 and IFI = 0.952 > 0.9. All of those fit indices exceed the suggested threshold values, indicating an adequate fit.

The proposed hypotheses were examined by evaluating the structural model. The results showed that desire to gain face (β = 0.15, p < 0.001), fear of losing face (β = 0.09, p < 0.05), social norms (β = 0.42, p < 0.001), trust in SNS members (β = 0.13, p < 0.01), and trust in SNS providers (β = 0.16, p < 0.001) significantly and positively influenced users’ intention to disclose location information on “Moments.” Therefore, H1, 2, 4, 5, and 6 were supported. Furthermore, fear of losing face related positively to social norms (β = 0.23, p < 0.001), in line with H3. Trust in SNS members (β = 0.60, p < 0.001) was found to have a significant and positive effect on trust in SNS providers, supporting H7. Figure 2 shows the outcomes of path analysis.

4.3. Post-hoc Analysis

As shown in Table 1, 41.3% of respondents reported that they did not disclose locations on WeChat during past half year. In this post-hoc analysis, we tended to conduct a multi-group analysis between users without past location-disclosure and with disclosure. Among the 545 participants, 225 participants were the users without past location-disclosure (Group 1) and 320 participants were the users with past location-disclosure (Group 2). The results show that absolute fit indices (χ²/df = 2.304; RMSEA = 0.049) and incremental fit indices (CFI = 0.906; TLI = 0.909; IFI = 0.906) demonstrate a good model fit. Interestingly, we found same results in these two groups (see Figure 3). These results are consistent with the main research model, except for the non-significant effect of fear of losing face on location disclosure intention. It implies that whether users have disclosed locations or not, only when others think that they should disclose locations on WeChat, individuals who are afraid of losing face may disclose their locations on WeChat because they are worried about whether their behavior is in line with social expectations. The same results of these two groups show that whether participants have the experiences of location disclosure on WeChat in the past, our results would not be different, demonstrating a good reliability of our results. In addition, even though these two groups had the same results, the reason why some users disclosed locations in the past and the others did not need more investigation in the future.

5. Discussion

First, the results showed that the desire to gain face, the fear of losing face, and social norms significantly predicted people’s intention to engage in location disclosure behavior on “Moments.” When users’ location disclosure behavior is examined under the lens of Chinese culture, Chinese cultural factors should be considered. Face consciousness is a universal concept but is particularly salient in China [53]. This study demonstrated that both the desire to gain face and the fear of losing face have positive effects on an individual’s check-in behavior on WeChat. That is, individuals who have a greater desire to gain face or a greater fear of losing face are more likely to disclose their locations on WeChat. Moreover, due to the Chinese culture of collectivism, the extent to which people are influenced by the group is strong. The results confirmed that social norms have a direct and positive effect on WeChat users’ location disclosure. Chinese people disclose their locations on WeChat because other important people do it. In addition, this study also showed that fear of losing face has a positive effect on social norms. It implies that individuals who are more afraid of losing face will be more worried that their behavior is not in line with social norms.

Furthermore, this study demonstrated that trust in SNS members and trust in SNS providers also significantly predicts WeChat users’ check-in behavior. Trust was not only strongly related to an individual’s information disclosure in an e-commerce context or on social networks [40] but also positively related to an individual’s location information disclosure. This paper considered the effect of trust in two forms: trust in SNS members and trust in SNS providers. Both of these kinds of trust predicted WeChat users’ check in behavior. Moreover, trust in SNS providers had a stronger effect, which is in line with previous findings [15]. When SNS providers are perceived to be reliable, users were likely to feel less risk in disclosing location information on SNS. Moreover, we also confirmed the trust transfer theory in the context of SNSs. Trust in WeChat “friends” could be transferred to trust in an SNS provider, which was consistent with previous studies [46,54]. That is, the more strongly individuals trusted in social network members, the more likely they were to trust in an SNS provider. Thus, it is very important for providers to enhance features that allow for more user interactivity in order to promote interpersonal trust and, in turn, trust in platforms.

6. Conclusions

The purpose of this study was to explore factors (face consciousness, social norms, and trust) that predicted Chinese users’ location information disclosure behavior on WeChat. We collected data through an online survey. The research model and the proposed hypotheses were tested using the structural equation modeling method. The findings suggested that a desire to gain face, fear of losing face, and social norms were significantly related to WeChat users’ check in behavior. Moreover, fear of losing face also positively impacted social norms. Trust in SNS members and trust in SNS providers significantly predicted people’s location disclosure on WeChat. We also confirmed the presence of trust transfer in the context of SNS. These findings have strong implications that may be applied to help marketing practitioners and SNS providers develop strategies and improve service quality.

This study offers the following theoretical implications. First, this study developed a comprehensive framework of Chinese characteristics to understand Chinese users’ check-in behavior, including individual (desire to gain face and fear of losing face), social (social norms), and platform-related factors (trust in SNS members and trust in SNS providers). More research is required to explore the influence of other unique Chinese factors on SNS users’ information disclosure behavior. Second, based on the trust transfer theory, this article further demonstrated that trust in an SNS provider can benefit from trust in SNS friends. This suggests that platforms that have more users with strong ties are more likely to gain their users’ trust. Third, we also explored the relationship between individual and environmental factors. Individuals who have more fear of losing face pay more attention to social norms.

The results provide the following important practical implications. First, since trust in SNS members and trust in SNS providers have significant positive effects on users’ intentions to disclose location-related information, SNS providers should pay more attention to dealing with user’s problems and feedback. Providers also need to make efforts to address most member concerns and keep their commitments to members in order to increase users’ trust in social networks. Second, people’s check-in behavior on social networks is influenced by other important users. Businesses could develop a reminder function of friends’ check ins by focusing on users who interact frequently to encourage users to disclose their locations.

This study has several limitations. First, we adopted a snowball-sampling method and ensured that the participants were WeChat users. However, some participants reported that they had no experience in disclosing locations on SNSs. Further studies should consider recruiting respondents who had disclosed location-related information at least one time in order to better examine the factors influencing location disclosure. Second, our results may be limited to Chinese samples. Care should be taken when generalizing our findings to other social networks or other cultures. Third, there are some different types of disclosing location information and different locations may carry different meanings. For example, scenic areas would be perceived as more socially desirable, but home and work locations would be perceived as more sensitive. Future research could investigate the difference of diversified location types in location disclosure behavior and compare their effectiveness of different location disclosure service. Fourth, our study tried to explore whether social norms play an effective role in SNS users’ location disclosure behavior. Since social norms have different dimensions, such as descriptive norms and injunctive norms, future studies may investigate if different dimensions of social norms have different effects on location disclosure on SNSs.