social attachment, life satisfaction and sns continuance
TRANSCRIPT
Int. J. Mobile Communications, Vol. X, No. Y, xxxx 1
Copyright © 20XX Inderscience Enterprises Ltd.
Social attachment, life satisfaction and SNS continuance: a dual-role perspective
Nan Wang, Yongqiang Sun* and Liuhan Zhan School of Information Management, Wuhan University, Wuhan, Hubei 430072, China Email: [email protected] Email: [email protected] Email: [email protected] *Corresponding author
Xiao-Liang Shen Economics and Management School, Wuhan University, Wuhan, Hubei 430072, China Email: [email protected]
Abstract: As the sustainability of social networking sites (SNS for short) heavily relies on the content generated by users, it is important to understand the factors driving users’ continuous participation. Considering that SNS has permeated almost every facet of people’s lives, this study proposes to understand SNS continuance from the life-oriented perspective beyond the technology-oriented perspective. Further, due to the social nature of SNS, we propose to understand the antecedents of life satisfaction by considering the dual role of social attachment. It is posited to directly enhance individuals’ life satisfaction and negatively influence life satisfaction through the mediating effect of envy. An online survey among WeChat Moments users in China was conducted to validate the proposed research model and hypotheses. The data analysis results based on partial least squares approach confirm all the hypotheses.
Keywords: social networking sites; SNS; life satisfaction; social attachment; envy; continuance intention.
Reference to this paper should be made as follows: Wang, N., Sun, Y., Zhan, L. and Shen, X-L. (xxxx) ‘Social attachment, life satisfaction and SNS continuance: a dual-role perspective’, Int. J. Mobile Communications, Vol. X, No. Y, pp.xxx–xxx.
Biographical notes: Nan Wang is an Associate Professor of the School of Information Management, Wuhan University. Her research interests include e-commerce, knowledge management and virtual community. Her work has appeared in several international journals including Decision Support Systems, International Journal of Information Management, among others.
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Yongqiang Sun is a Professor of the School of Information Management, Wuhan University. He obtained his PhD from the City University of Hong Kong and University of Science and Technology of China. His research interests include e-commerce, knowledge management, virtual community and human-computer interactions. His work has appeared in several international journals including Information Systems Research, Journal of AIS, Decision Support Systems, Information & Management, among others.
Liuhan Zhan is a Master graduate student of the School of Information Management, Wuhan University. His research interests include knowledge management and virtual community. His work has appeared in Aslib Journal of Information Management, PACIS and several Chinese journals.
Xiao-Liang Shen is a Professor at the Economics and Management School of Wuhan University. His research interests include IT innovation adoption and diffusion, knowledge management, social media and e-commerce. He has published in several academic journals and conferences including Journal of Information Technology, Decision Support Systems, Journal of the Association for Information Science and Technology, etc.
1 Introduction
In recent years, the development of information and communication technology, especially social networking sites (e.g., SNS), has deeply changed the way how individuals communicate and live (Nitzburg and Farber, 2013; Yin et al., 2018; Sun et al., 2017b; Chen et al., 2017). SNS has become a platform for users to follow others’ lives by browsing status updates (Tandoc et al., 2015) and to express their feelings and share their information (Lim and Yang, 2015). The prevalence of SNS makes it easier and more convenient for users to get familiar and communicate with others, leading to an enriched and colourful social life.
Despite the popularity of SNS, its eventual success depends on users’ continued usage (Lai and Shi, 2015; Wang and Chou, 2016; Zhou et al., 2015). Previous studies have identified that users’ continued usage is an intentional behaviour, which is determined by their satisfaction with technology, as embodied in the expectation-confirmation model (ECM) (e.g., Bhattacherjee and Lin, 2015; Bhattacherjee, 2001). However, these studies have relied heavily on the technology-oriented factors to predict users’ continuance (Zhou et al., 2014), while life-oriented factors are scarcely discussed. In nowadays, since SNS has become an integral part of people’s lives, it may influence people’s attitude and perception relevant to life quality, e.g., life satisfaction which reflects the global and subjective assessments of an individual’s quality of life (Diener et al., 1985). Although life satisfaction has been found to be an important predictor of organisational commitment and loyalty in organisational behaviour literature (e.g., Chiu et al., 2013), whether life satisfaction could motivate users’ continuance intention of SNS remains rarely examined. Thus, this paper will extend the research of SNS continuance from the perspective of life satisfaction theoretically and examine the relationship between life satisfaction and SNS continuance empirically. Therefore, the first research question of this study is:
RQ1 Will life satisfaction influence users’ SNS continuance intention?
Social attachment, life satisfaction and SNS continuance 3
Further, regarding the important role of life satisfaction in driving SNS continuance, another research question is to understand the factors associated with the formulation of life satisfaction. Based on the contextualisation principle of theory building, it is necessary to explore the antecedents of life satisfaction by addressing the unique features of SNS context. Unlike the adoption of utilitarian technology (e.g., office and e-mail) which stresses on the instrumental or utilitarian value of technology, SNS adoption is heavily determined by the social interactions among different SNS users (Ang et al., 2015) because SNS is mainly used for social purposes including making new friends and connecting with old friends (Griffiths, 2013; Lee et al., 2014; Shin and Biocca, 2018). To well capture the social nature of SNS adoption, this study argues that the extent to which SNS users are attached with other users will determine the level of life satisfaction by drawing upon the social attachment theory (Ellison et al., 2007; Elphinston and Noller, 2011; Brehm et al., 2004; Cross, 2003). The impacts of social attachment in shaping life satisfaction have not been adequately investigated in prior studies and should be well explored.
More importantly, prior studies based on social attachment theory tend to emphasise the positive effects of social attachment but pay less attention to its potential negative effects. However, some recent studies have pointed out that social attachment may lead to certain negative consequences. Specifically, when following others’ information disclosed in SNS (Krasnova et al., 2015), SNS users may evaluate their own lives through the comparison between themselves and others (Haferkamp and Krämer, 2011) and feel sad when they think that they are not so good as their peers (Smith and Kim, 2007). As social attachment increases the degree of identity and familiarity with others (Lim et al., 2014; Ren et al., 2012), envy is more likely to be induced according to envy theory (Chou and Edge, 2012; Krasnova et al., 2015). Regarding the detrimental effects of envy on life satisfaction (Smith and Kim, 2007), there will be a negative effect of social attachment on life satisfaction through envy.
The above arguments suggest that there are two opposite mechanisms to explain the relationship between social attachment and life satisfaction. However, the dual role of social attachment has not been well recognised in prior studies which focus on the positive side only. Therefore, the second research question of this study is:
RQ2 What about the dual role of social attachment in shaping life satisfaction?
The subsequent parts of this article are structured as follows. The second section presents the theoretical background by reviewing related studies on life satisfaction, social attachment and envy. Then, we propose our research model and hypotheses. The next section describes the research methodology and then presents the results of data analysis. Finally, we discuss the findings and implications for theory and practice.
2 Theoretical background
2.1 SNS continuance
During the last decades, technology continuance has gained a lot of attention in IS research. Whether a technology succeeds depends on its continued usage rather than its first-time use (i.e., initial adoption) (Bhattacherjee and Lin, 2015; Bhattacherjee, 2001). Different from the theories explaining initial adoption such as technology acceptance
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model (TAM) (Davis et al., 1989), theory of planned behaviour (TPB) (Ajzen, 1991) and the unified theory of technology adoption and use (UTAUT) (Venkatesh et al., 2003), technology continuance can be interpreted by the ECM (Bhattacherjee, 2001), which captures user satisfaction as the prominent influencing factor of continuance (Sun et al., 2017a; Shin, 2017; Shin and Hwang, 2017). Specifically, based on ECM and TPB, Kim (2010) developed an integrated model to predict continuance intentions toward mobile data service. Through integrating ECM and cognitive dissonance theory, Bock et al. (2010) examined the effects of contribution overload and information overload on continuance intention.
Although these extant studies have examined the role of satisfaction in technology continuance, they focus on the satisfaction with the utilitarian value brought by technology usage. The underlying assumption for this logic is that technology is mainly used for utilitarian purposes (e.g., productivity, efficiency and effectiveness). However, this theory may be not adequate to explain SNS continuance because the major purpose for using SNS relies on social value rather than utilitarian value (Sun et al., 2015). As SNS has been deeply embedded in users’ lives and changed the way how they live, exploring the life-oriented factors of continuance intention should be paid more attention (Zhan et al., 2016). To the best of our knowledge, very few studies have examined the SNS continuance intention from users’ perception of life quality (i.e., life satisfaction). Therefore, this study will extend technology continuance research by examining the effect of life satisfaction.
2.2 SNS usage and life satisfaction
Life satisfaction is a person’s subjective and global evaluation on his/her quality of life (Diener et al., 1985). Although life satisfaction has been widely investigated in psychology and sociology (Lim and Putnam, 2010), the role of life satisfaction in IS field has begun to receive attention only in recent years. Among these studies, the relationship between SNS usage and life satisfaction has been interpreted in different ways (Best et al., 2014; Krasnova et al., 2015).
The controversy relies on two aspects: causal direction and effect valence. As to causal direction, some studies argue that SNS usage is associated with psychological need satisfaction which influences life satisfaction, i.e., from SNS usage to life satisfaction (e.g., Ang et al., 2015; Liu and Yu, 2013; Brooks, 2015; Chen and Lee, 2013). In contrast, life satisfaction gained from past SNS usage can drive users’ continuance usage of SNS too, i.e., from life satisfaction to SNS usage. From a longitudinal view, SNS usage and life satisfaction dyadically affect each other at different time points: past SNS usage (i.e., t – 1) affects the present evaluation on life satisfaction (i.e., t) which further influences future SNS usage (i.e., t + 1). This is consistent with the logic to describe the relationship between self efficacy and performance in social cognitive theory (e.g., Wood and Bandura, 1989). In this study, as we pay attention to the SNS continuance which is about future SNS usage, the second theorisation approach from life satisfaction to continuance intention will be used.
As to effect valence, some researchers advocate the positive effects of SNS usage on life satisfaction by arguing that SNS usage can facilitate psychological need satisfaction with social relationships (Ang et al., 2015) and social support (Liu and Yu, 2013). On the contrary, some researchers postulate that SNS usage may induce technostress, low performance (Brooks, 2015), communication overload and psychological distress (Chen
Social attachment, life satisfaction and SNS continuance 5
and Lee, 2013), finally exert negative effects on life satisfaction. The mixed findings about the relationship between SNS usage and life satisfaction are based on the logic which treats SNS usage as the cause while life satisfaction as the result. In this study, as we focus on SNS continuance where life satisfaction is the taken as the antecedent of continuance intention, we propose this relationship should be positive. Further, consistent with prior studies, we propose that past SNS usage may have two opposite effects on life satisfaction. Specifically, considering social attachment as a construct to reflect past SNS usage (Ellison et al., 2007; Elphinston and Noller, 2011), we argue that social attachment may have both positive and negative effects on life satisfaction.
2.3 Social attachment
Social attachment is generally defined as the emotional attachment to a community and a sense of belonging and identification (Brehm et al., 2004; Cross, 2003; Shin, 2018). In the SNS context, it refers to the emotional attachment to certain persons or groups within SNS (Ren et al., 2012). Individuals develop attachment to their community through different ways. Ren et al. (2012) supposed that attachment comes up through two ways: group identity and interpersonal bonds. Besides, Lim et al. (2014) extended the classification by arguing that there are three distinct forms of attachment namely identity-based attachment, bond-based attachment and comparison-based attachment.
Specifically, identity-based attachment means that a person identifies with specific groups within a SNS (Lim et al., 2014; Ren et al., 2012), believing that group members belong to the same category (Sassenberg, 2002). In other words, because of shared visions or purposes, members would like to be classified into certain groups. For bond-based attachment, what is important is the connections between a person and other specific individuals in the community (Sassenberg, 2002; Lim et al., 2014). If a person is familiar with other individuals and they have frequent interactions, he/she is more likely to develop bond-based attachment (Sassenberg, 2002; Ren et al., 2007). As for comparison-based attachment, it is based on social comparison theory which states that individuals seek to compare themselves with others for self-evaluation and self-improvement, particular with someone who is similar to them (Bessenoff, 2006). That is to say, individuals with comparison-based attachment are attracted by the position within an SNS (Lim et al., 2014).
In previous studies, social attachment is generally considered as the essential factor for the success of online communities. For instance, Ren et al. (2012) stated that attachment to online communities will increase members’ willingness to build communities and stay in communities. Lim et al. (2014) examined the effects of social attachment on members’ mental states and found that social attachment can influence individuals’ continuous usage intention. However, the role of social attachment may be not one-sided. Higher social attachment may lead to more social comparison and higher possibility for envy to occur, while envy is negatively associated with life satisfaction. That is to say, beyond the positive effect of social attachment on life satisfaction, social attachment may exert negative impact on life satisfaction through the mediating effect of envy.
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2.4 Envy on SNS
Envy is defined as “an unpleasant and often painful blend of feelings characterised by inferiority, hostility and resentment caused by a comparison with a person or group of persons who possess something we desire” [Smith and Kim, (2007), p.49]. Envy exists not only in individuals’ offline lives, but also among SNS users (Krasnova et al., 2015; Vogel et al., 2015). In recent years, with the popularity of SNS, apart from the positive effects of SNS on people’s lives, scholars have begun to be concerned with the dark side of SNS. For example, based on cognitive emotion theory, Lim and Yang (2015) argued that SNS usage can increase social comparison and result in more negative emotions related to social comparison (e.g., envy) and these negative emotions will lead to various detrimental effects such as burnout and switching intention. Drawing upon social comparison theory, Krasnova et al. (2015) demonstrated that information consumption on SNS is positively associated with envy, which would negatively influence users’ cognitive and affective well-being. Besides, Tandoc et al. (2015) also found that individuals who use Facebook more frequently and have a bigger network of friends tend to experience more feelings of envy.
These studies on envy have two key theoretical implications. On the one hand, envy as a negative emotion will have a negative impact on life satisfaction. On the other hand, social attachment is positively associated with envy. These two implications together suggest an indirect negative effect of social attachment on life satisfaction through envy, beyond the direct positive effect of social attachment on life satisfaction.
3 Research model and hypotheses
Based on the life-oriented perspective of SNS continuance and the dual role of social attachment in shaping life satisfaction, we develop a research model as shown in Figure 1. The detailed explanations for hypotheses will be provided in the following sections.
3.1 Life satisfaction and continuance intention
Prior studies on technology continuance have validated satisfaction with technology as an important predictor of continuance intention based on ECM (Bhattacherjee, 2001; Bock et al., 2010). The underlying mechanism for ECM postulates that technology usage can generate certain values to users and consequently they will continue using the technology if these values meet their expectations through the expectation-confirmation process. This mechanism is applicable for both utilitarian technologies (e.g., office) and social technologies (e.g., SNS) while the values involved in the technology usage process may be different (Hsiao et al., 2016). Specifically, for utilitarian technology, users may focus on the utilitarian or instrumental values such as productivity, efficiency and effectiveness. In contrast, for social technology, the focus shifts from the utilitarian values to the social values. Further, regarding that SNS has penetrated into users’ ordinary lives and facilitated the fusion of technology and life, satisfaction with technology is not adequate to capture the whole impacts of SNS. Therefore, we propose to employ life satisfaction to reflect the overall evaluation on the consequences induced by SNS usage. According to the logic of ECM, we propose that when users believe that SNS usage can enhance their
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life satisfaction, they will be more likely to continue using SNS (Chiu et al., 2013). Therefore, we hypothesise:
H1 Life satisfaction is positively associated with continuance intention.
Figure 1 Research model
Social attachment
Life satisfaction
Envy
Continuance intention
H3 H4
H2 H1
Control variables:gender, age,
number of friends, duration
3.2 Social attachment and life satisfaction
Social attachment describes individuals’ emotional connections with community and it is recognised as a sense of belonging and identification (Cross, 2003). Attachment to a community such as SNS can satisfy their social needs because they feel they become more intimate with their friends. Those who have high-quality relationships are more likely to experience high levels of life satisfaction (Best et al., 2014). Besides, the sense of belonging can make individuals feel safe and comfortable (Cross, 2003), thus spending more time and effort to support community members (Ren et al., 2012). These supports from others can enhance individuals’ physical and psychological satisfaction by reducing the perception of stress (Liu and Yu, 2013; Nabi et al., 2013). As social attachment makes individuals feel emotionally involved and supported and these pleasant feelings make them become more positive about their life quality, we hypothesise:
H2 Social attachment is positively associated with life satisfaction.
3.3 Social attachment and envy
Envy is a kind of hostile emotion that individuals experience inherently (Tandoc et al., 2015). SNS is a convenient platform where more information about others’ lives can be consumed, thus providing more opportunities for individuals to compare with others. In other words, heavy SNS users are more likely to experience envy. Chou and Edge (2012) argued that using SNS can impact users’ perceptions of others’ lives and more usage means more comparisons with others. Likewise, Tandoc et al. (2015) supposed that individuals who use SNS more frequently tend to have higher levels of SNS envy. When individuals build attachment to SNS, it will increase users’ participation and retention (Ren et al., 2012). Given that, we expect that social attachment increases the likelihood to compare with others and envy would arise more probably.
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Meanwhile, individuals tend to envy others who are similar to themselves (Smith and Kim, 2007), because these similarities are more representative and can provide a better benchmark for self-evaluation (Krasnova et al., 2015). Individuals who establish identity-based and bond-based attachment are usually familiar with certain groups and persons on SNS and believed that they have much in common (Lim et al., 2014; Ren et al., 2012). These similarities may cause individuals to experience envy. Besides, individuals with comparison-based attachment are more prone to care about their standings in communities (Lim et al., 2014). Social comparison orientation can induce a variety of negative outcomes including envy (Lim and Yang, 2015; Vogel et al., 2015). Above all, social attachment to SNS can be regarded as a driver of envy. Hence, we hypothesise:
H3 Social attachment is positively associated with envy.
3.4 Envy and life satisfaction
Envy is an unpleasant and painful feeling with a range of negative outcomes, which can do harm to individuals’ mental and physical health (Smith and Kim, 2007). Psychologically, it is related to a variety of undesirable feelings such as frustration, inferiority, hostility and resentment (Krasnova et al., 2015; Smith and Kim, 2007). Physically, envious users tend to experience more stress because of their urgent desires (Krasnova et al., 2015; Smith and Kim, 2007) and too much stress would make them burnout (Lim and Yang, 2015). In addition, users who envy others believe that others are happier than them and life is unfair (Chou and Edge, 2012), leading to negative attitude towards life. Regarding the detrimental effects of envy on mental and physical health, we expect that these negative outcomes would reduce their life satisfaction. Hence, we hypothesise:
H4 Envy is negatively associated with life satisfaction.
4 Methodology
4.1 Research settings
WeChat Moments, a popular SNS in China, was selected as the research setting for the study. WeChat Moments is a social APP embedded in WeChat. It provides a virtual community where users can develop social networks with their peers and communicate with others through updating status, uploading photos and sharing articles, music or videos. Users can post comments and press ‘liking’ to interact with their friends too. Due to the multiple functions and convenience, WeChat has become one of the most popular social networking services in China. Therefore, WeChat Moments can be an appropriate context for this study.
4.2 Measurements
All measurement items of this study were adapted from previous studies and these items were adjusted to match the research context. To ensure the accuracy of item expression, we invited two graduate students to check the content validity and face validity of the
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questionnaire before the formal survey. As the survey was conducted in China, the questionnaire was translated into Chinese through a translation committee approach (Van de Vijver and Leung, 1997). There were four constructs in this study and each construct was measured using multiple items (see Table A1 for details). All the items were measured using a seven-point Likert scale, ranging from ‘strongly disagree’ to ‘strongly agree’. Besides, demographic variables such as gender, age, duration of everyday use and number of friends were included as control variables.
4.3 Data collections
An online survey was conducted to collect data. Online rather than offline survey was used for the following two reasons. First, SNS usage behaviour is a kind of online behaviour and SNS users usually prefer to obtain information through the online channel rather than offline channel, so using online survey is fit with the research context. Second, the URL to the online questionnaire can be easily diffused through the social network in SNS, so it is more convenient to contact with the potential respondents than offline survey. Table 1 Respondent demographics
Demographic variables Category Frequency Percentage (%) Male 138 43.40 Gender
Female 180 56.60 Under 18 1 0.31
18–25 127 39.94 26–30 106 33.33 31–40 61 19.18
Age
Above 40 23 7.23 Under one hour 56 17.61
1–2 hours 139 43.71 2–4 hours 89 27.99
Duration of everyday use
Above four hours 34 10.69 Under 50 58 18.24 50–100 120 37.74
100–200 99 31.13
Number of friends
Above 200 41 12.89
The survey was conducted using sojump.com, which is a professional online survey agency in China. This website provides a lot of functions for questionnaire design and has been widely used by academic research in recent years (e.g., Fang et al., 2014; Zhou et al., 2012; Lien and Cao, 2014). After finishing the questionnaire design, a URL leading to the questionnaire can be obtained. The snowball sampling technique was used to recruit respondents. Specifically, students of a course about research methodology were firstly invited to participate in the survey voluntarily and these students were asked to share the questionnaire URL to their WeChat friends too. Respondents were eligible only when they had certain experience in using WeChat Moments. The snowball sampling
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technique was used because it is more appropriate for the study relevant to social network and it has been frequently used in prior SNS studies (e.g., Baltar and Brunet, 2012; Sheldon, 2012; Rau et al., 2008).
A total of 394 WeChat Moments users engaged in the investigation. After removing inappropriate responses (e.g., reduplicative responses from the same IP address, responses with missing values and responses within a short time), 318 valid samples were obtained. The sample size was comparable to prior studies on SNS (e.g., Chen et al., 2017; Lai and Shi, 2015; Seol et al., 2016) and was adequate for the data analysis of the current research model. According to the principle of partial least squares (PLS), the minimum sample size for data analysis should be ten times the largest number of independent variables or formative indicators (Chin and Newsted, 1999), which is 60 for the current study as there are six predictors for life satisfaction including the four control variables. Thus, the sample size of 318 was adequate for the data analysis. The demographic information is shown in Table 1.
5 Data analysis
The PLS method was used to analyse the research model. As a second-generation structural equation modelling (SEM) technique, PLS can estimate indicators’ loadings of constructs and the relationships among constructs at the same time (Fornell and Bookstein, 1982; Fornell and Larcker, 1981). Besides, it is more suitable for the study with small sample size and formative constructs (Hair et al., 2011). As the sample size for the current study was relatively small and social attachment was treated as a formative second-order construct, PLS was chosen as the analytic tool. Specifically, SmartPLS 2.0 was used to conduct data analysis (Ringle et al., 2005). Following a two-step analysis principle (Fornell and Bookstein, 1982), we will report the results for measurement model and structural model accordingly.
5.1 Measurement model
The measurement model was evaluated by examining the reliability, convergent validity and discriminant validity. Reliability can be evaluated through Cronbach’s alpha, composite reliability (CR) and average variance extracted (AVE) and the threshold values for them are 0.7, 0.7 and 0.5, respectively (Fornell and Larcker, 1981; Nunnally et al., 1967). As shown in Table 2, the values of Cronbach’s alpha, CR and AVE for all the constructs were higher than the recommended threshold values, indicating that these constructs were with good reliabilities.
Convergent and discriminant validity were assessed using confirmatory factor analysis (i.e., CFA). Convergent validity can be assessed by examining the item loadings to see whether items within the same construct are highly correlated and discriminant validity can be assessed by checking whether item loadings on the intended constructs were higher than on other constructs (Fornell and Bookstein, 1982). As shown in Table 3, all item loadings satisfied the requirements of convergent and discriminant validity. In addition, discriminant validity can also be assessed by checking if the square root of AVE of a given construct is higher than the correlations between this construct and other constructs (Fornell and Bookstein, 1982). According to Table 4, all the square roots of
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AVEs are higher than the correlations, demonstrating good discriminant validities for all the constructs. Table 2 Psychometric properties of measures
Construct Item Mean Std. dev Cronbach’s alpha CR AVE IA1 5.55 1.166 IA2 5.70 1.211 IA3 5.02 1.386 IA4 4.83 1.490
Identity-based attachment (IA)
IA5 4.78 1.553
0.887 0.918 0.692
BA1 5.57 1.324 BA2 5.45 1.422 BA3 5.00 1.493 BA4 5.20 1.450
Bond-based attachment (BA)
BA5 4.88 1.609
0.902 0.927 0.718
CA1 4.19 1.696 CA2 4.14 1.729 CA3 4.93 1.548
Comparison-based attachment (CA)
CA4 4.90 1.552
0.911 0.938 0.790
EN1 3.02 1.715 EN2 3.06 1.765 EN3 3.07 1.760 EN5 3.90 1.653 EN6 3.80 1.665 EN7 3.37 1.751
Envy (EN)
EN8 3.36 1.862
0.925 0.939 0.688
LS1 4.86 1.359 LS2 4.81 1.357 LS3 4.91 1.402
Life satisfaction (LS)
LS4 4.81 1.419
0.922 0.945 0.811
CI1 5.91 1.177 CI2 5.89 1.292 CI3 5.82 1.273
Continuance intention (CI)
CI4 5.92 1.167
0.952 0.965 0.874
The second-order construct, social attachment in this model, was assessed by checking the weights of sub-constructs. As shown in Figure 2, the weights were significant for all the three sub-constructs: identity-based attachment (w = 0.392, t = 33.983), bond-based attachment (w = 0.394, t = 28.071) and comparison-based attachment (w = 0.335, t = 23.171). Thus, all the three dimensions of social attachment were included in the data analysis.
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Table 3 Loadings and cross-loadings
IA BA CA EN LS CI IA1 0.827 0.606 0.551 0.105 0.352 0.490 IA2 0.703 0.577 0.363 –0.083 0.328 0.543 IA3 0.892 0.698 0.553 0.168 0.438 0.485 IA4 0.882 0.683 0.594 0.218 0.439 0.383 IA5 0.842 0.683 0.611 0.266 0.411 0.317 BA1 0.630 0.808 0.421 0.050 0.304 0.511 BA2 0.675 0.870 0.492 0.063 0.391 0.555 BA3 0.616 0.852 0.548 0.139 0.377 0.455 BA4 0.648 0.865 0.550 0.138 0.357 0.474 BA5 0.737 0.841 0.636 0.268 0.362 0.369 CA1 0.558 0.568 0.899 0.441 0.286 0.218 CA2 0.595 0.568 0.892 0.425 0.319 0.221 CA3 0.576 0.547 0.877 0.329 0.250 0.439 CA4 0.580 0.554 0.887 0.332 0.255 0.412 EN1 0.148 0.076 0.312 0.828 –0.047 –0.089 EN2 0.060 0.036 0.325 0.815 –0.073 –0.081 EN3 0.167 0.096 0.398 0.839 –0.026 –0.124 EN5 0.212 0.230 0.414 0.838 –0.070 0.083 EN6 0.202 0.216 0.414 0.856 –0.045 0.058 EN7 0.032 0.012 0.250 0.826 –0.191 –0.082 EN8 0.127 0.162 0.326 0.804 –0.110 –0.012 LS1 0.456 0.412 0.303 –0.046 0.899 0.332 LS2 0.405 0.362 0.226 –0.135 0.919 0.332 LS3 0.450 0.391 0.287 –0.113 0.921 0.314 LS4 0.401 0.358 0.313 –0.029 0.862 0.263 CI1 0.467 0.516 0.335 –0.012 0.339 0.916 CI2 0.508 0.544 0.343 –0.043 0.333 0.948 CI3 0.495 0.506 0.341 –0.033 0.321 0.934 CI4 0.487 0.509 0.333 –0.024 0.299 0.941
Notes: The loadings of EN4 and LS5 were lower than 0.7, thus they were not included in the analysis process. IA = identity-based attachment; BA = bond-based attachment; CA = comparison-based attachment; EN = envy; LS = life satisfaction; CI = continuance intention.
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Table 4 Correlation matrix and square roots of AVEs
IA BA CA EN LS CI IA 0.832 BA 0.782 0.847 CA 0.649 0.629 0.889 EN 0.175 0.160 0.430 0.829 LS 0.476 0.423 0.313 –0.091 0.901 CI 0.524 0.555 0.362 –0.030 0.346 0.935
Notes: IA = identity-based attachment; BA = bond-based attachment; CA = comparison-based attachment; EN = envy; LS = life satisfaction; CI = continuance intention. The italic diagonal values are the square roots of AVEs.
Figure 2 The relationships between first-order and second-order constructs
Social attachment
Bond-based attachment
Identity-based attachment
Comparison-based attachment
.394**
.335**
.392**
Note: **p < 0.01.
5.2 Structural model
The results for structural model are shown in Figure 3. According to the results, the structural model explains 11.2% of the variance of envy, 28.3% of the variance of life satisfaction and 17.9% of the variance of continuance intention. As hypothesised, life satisfaction has a significant positive effect on continuance intention (β = 0.291, t = 4.195), supporting H1. Social attachment has a significant positive effect on life satisfaction (β = 0.519, t = 10.040), supporting H2. Social attachment has a significant positive effect on envy (β = 0.294, t = 5.084), supporting H3. Envy has a significant negative effect on life satisfaction (β = –0.228, t = 4.049), supporting H4. Besides, some control variables are found to have significant effects. Specifically, gender is found to negatively affect envy (β = –0.170, t = 3.033) and age (β = 0.191, t = 3.990) and duration of everyday use (β = 0.161, t = 2.918) are found to significantly affect continuance intention.
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Figure 3 Results of research model
Social attachment
Life satisfaction
Envy
Continuance intention
.294* –.228**
.519**
Gender (–.170**) Age (n.s)
Number of friends (n.s) Duration (n.s)
R2=.179
R2=.112
R2=.283
Gender (n.s) Age (n.s)
Number of friends (n.s) Duration (n.s)
Gender (n.s) Age (.191**)
Number of friends (n.s) Duration (.161**)
.291**
Note: **p < 0.01, n.sp > 0.05.
6 Discussions and implications
6.1 Discussions
The main objective of this study is to extend the understanding of SNS continuance from the perspective of life satisfaction and examine the dual role of social attachment on life satisfaction. Several interesting findings can be derived from the data analysis results. First, the results demonstrate a positive relationship between life satisfaction and individuals’ SNS continuance intention, indicating that when SNS users believe that SNS usage can enhance life satisfaction they will be more likely to continue using SNS. Unlike prior studies on technology continuance focusing on the role of satisfaction with the utilitarian values of technology (e.g., Bhattacherjee and Lin, 2015; Bhattacherjee, 2001), this study recognises the fusion of technology and life and proposes using life satisfaction to reflect the whole impacts of SNS on users (Zhan et al., 2016). Further, this finding is also consistent with prior studies on life satisfaction in psychology and sociology (e.g., Lim and Putnam, 2010; Diener et al., 1985), extending the applicable scope of life satisfaction theory to the research context of SNS.
Second, the results point out that social attachment affects life satisfaction through two opposite mechanisms. On the one hand, social attachment is positively associated with life satisfaction, which reveals that social attachment can induce individuals’ positive attitude towards their lives and enhance life satisfaction. This mechanism is consistent with previous studies that mainly consider the positive effects of social attachment (Bateman et al., 2011; Ren et al., 2012). On the other hand, social attachment can also decrease life satisfaction through the mediating effect of envy. Specifically, social attachment can increase the possibility of social comparison during the information consumption process and lead to an unpleasant emotion (e.g., envy) (Lim and Yang, 2015; Tandoc et al., 2015; Krasnova et al., 2015) and this negative emotion will in turn result in a variety of negative outcomes and reduce individuals’ global evaluation of their life satisfaction. Although the positive effect of social attachment has been well examined, the negative effect of social attachment has rarely been identified. The dual role of social attachment in shaping life satisfaction provides a mechanism to explain the
Social attachment, life satisfaction and SNS continuance 15
mixed results of social attachment and reminds practitioners to recognise both the positive and negative effects of social attachment during website design.
6.2 Theoretical implications
This study provides several theoretical implications. First, this study extends the technology continuance theory by considering the important role of life satisfaction in SNS continuance. Prior studies on technology continuance focus on the utilitarian outcomes associated with technology usage and tend to use satisfaction with technology as the construct to capture the whole impact of technology usage. However, SNS has connected the technology and life together and formed an integral world of online and offline life. In this case, satisfaction with technology is not adequate to cover the impact of SNS usage, while life satisfaction which reflects the influence of SNS on individuals’ lives is more appropriate. This study empirically confirms that life satisfaction does have a significant impact on SNS continuance. This study enriches technology continuance literature (SNS literature in particular) by shifting the research focus from the technology-centred perspective to a broader perspective (i.e., life-centred perspective) to understand the post-adoption behaviour.
Second, this study explores the antecedents of life satisfaction from the perspective of social attachment. Prior studies on technology continuance have stressed on the role of technological factors based the assumption that users would like to continue using a technology because the technology is good. However, for SNS that is a social technology, when users make decisions on whether or not to continue using SNS, they may pay more attention to other users or social networks rather than technology per se. Considering the social nature of SNS, this study proposes that social attachment which captures the attachment to social relationships rather than technology attachment that reflects the attachment to the technology would play a more important role. This study enriches SNS literatures by shifting the research focus from technology per se to users who collaboratively use the technology.
Third, this study identifies the dual role of social attachment in shaping life satisfaction. Prior studies tend to stress on the positive effect of social attachment assuming that a close social relationship would generate positive outcomes. However, it may be not the whole story in SNS context. This study, to the best of our knowledge, is the first study revealing the two opposite effects of social attachment. Specifically, this study argues that social attachment can increase the possibility of social comparison with other SNS users during information consumption process and hence induce a negative emotion namely envy. As envy is negatively associated with life satisfaction, social attachment will exert a negative impact on life satisfaction through envy. The dual role of social attachment provides a novel theoretical perspective to understand the mixed results about the relationship between social attachment and life satisfaction and calls for future research to offer a more comprehensive understanding on the different mechanisms of social attachment.
6.3 Practical implications
This study can offer practical implications for SNS providers and users. First, this study finds that life satisfaction is an important predictor of SNS continuance. When
16 N. Wang et al.
designing SNS functions, SNS providers should shift the design principle from the technology-oriented principle to the life-oriented principle. Specifically, SNS providers should not focus on the superiority of technology, but on whether the design can enhance users’ life satisfaction. With the guidance of this principle, SNS providers should understand users’ requirements and develop a world tightly combining users’ online and offline activities. Further, when evaluating whether a SNS design is good or not, life satisfaction rather than technology satisfaction should be regarded as an important criterion.
Second, the results suggest that social attachment has both positive and negative effects on life satisfaction. For SNS providers, they should leverage the positive effects of social attachment while avoid the negative effects of social attachment during SNS design process. Specifically, SNS should highlight the social supports that users obtain from social interactions while allow users to reduce their exposure to particularly envy-inducing content such as travelling, eating or playing through information screening functions. For SNS users, to get rid of envy, individuals need to use SNS moderately and spend more time and effort on offline activities. Further, SNS users should form right attitudes towards SNS by peacefully treating others’ achievements and improve their abilities to screen envy-inducing information.
6.4 Limitations and future research
In spite of some interesting findings, this study still has several limitations. First, as only Chinese WeChat Moments users were included in this investigation, whether or not the findings can be applicable in other types of SNS or in other countries needs to be further explored in future research. Specifically, WeChat and Sina Weibo are two popular but different types of SNS such that WeChat is with higher sociability than Sina Weibo (e.g., Wang and Sun, 2016), so the impacts of social attachment may vary across SNSs with different sociability. Further, unlike China which is widely regarded as a country with a collective culture stressing on social relationships, the role of social attachment may be not so significant for the countries with an individualistic culture (Hofstede, 2003). Therefore, future research can either confirm our research findings in other research contexts or advance the theoretical understanding by considering the moderating effects of sociability and culture.
Second, a cross-section rather than a longitudinal design of survey was used in the research design, so the causal direction of the relationship between life satisfaction and continuance intention cannot be verified. As summarised in the literature review section, prior studies have shed light on two different mechanisms to explain the relationship between life satisfaction and SNS usage: from SNS usage to life satisfaction and from life satisfaction to SNS usage. In the current study, as we focus on SNS continuance, the second mechanism should be applicable. However, to better capture the whole logic chain and the evaluation of SNS usage behaviour, future research can investigate the dyadic relationship between life satisfaction and SNS usage through a longitudinal design.
Social attachment, life satisfaction and SNS continuance 17
Acknowledgements
The work described in this paper was partially supported by the grants from the grants from Humanities and Social Sciences Foundation of the Ministry of Education, China (Project No. 16YJC870011, 17YJC630157), the Major Project of the Ministry of Education of China (Grant No. 17JZD034), the National Natural Science Foundation of China (Project No. 71671132) and the Research Fund for Academic Team of Young Scholars at Wuhan University (Project No. Whu2016013).
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Social attachment, life satisfaction and SNS continuance 21
Appendix
Table A1 Measures of constructs
Vari
able
Ite
m
Mea
sure
men
t
IA1
I ide
ntify
ver
y m
uch
with
cer
tain
gro
ups w
ithin
WeC
hat M
omen
ts.
IA2
I fit
wel
l int
o ce
rtain
gro
ups w
ithin
WeC
hat M
omen
ts.
IA3
The
grou
ps I
belo
ng to
with
in W
eCha
t Mom
ents
are
an
impo
rtant
refle
ctio
n of
who
I am
. IA
4 Th
e gr
oups
I be
long
to w
ithin
WeC
hat M
omen
ts a
re im
porta
nt to
my
sens
e of
wha
t kin
d of
per
son
I am
.
Iden
tity-
base
d at
tach
men
t (IA
) (Li
m e
t al.,
201
4)
IA5
The
grou
ps I
belo
ng to
with
in W
eCha
t Mom
ents
hav
e a
lot t
o do
with
how
I fe
el a
bout
mys
elf.
BA1
I fee
l clo
se to
cer
tain
indi
vidu
als w
ithin
WeC
hat M
omen
ts.
BA2
I fin
d ce
rtain
indi
vidu
als w
ithin
WeC
hat M
omen
ts to
be
impo
rtant
to m
e.
BA3
I lik
e to
spen
d tim
e w
ith c
erta
in in
divi
dual
s with
in W
eCha
t Mom
ents
. BA
4 I f
avou
r cer
tain
indi
vidu
als w
ithin
WeC
hat M
omen
ts.
Bond
-bas
ed a
ttach
men
t (B
A) (
Lim
et a
l., 2
014)
BA5
I pre
fer c
erta
in in
divi
dual
s with
in W
eCha
t Mom
ents
. C
A1
I ofte
n co
mpa
re m
ysel
f with
oth
ers w
ithin
WeC
hat M
omen
ts.
CA
2 I l
ike
com
parin
g m
ysel
f with
oth
ers w
ithin
WeC
hat M
omen
ts.
CA
3 I l
ike
to k
now
my
stan
ding
am
ong
othe
rs w
ithin
WeC
hat M
omen
ts.
Com
paris
on-b
ased
at
tach
men
t (C
A)
(Lim
et a
l., 2
014)
CA
4 I l
ike
to k
now
how
I ra
nk re
lativ
e to
oth
ers w
ithin
WeC
hat M
omen
ts.
U
sing
WeC
hat M
omen
ts m
akes
me
feel
that
…
EN1
I gen
eral
ly fe
el in
ferio
r to
othe
rs.
EN2
It is
so fr
ustra
ting
to se
e so
me
peop
le a
lway
s hav
ing
a go
od ti
me.
EN
3 It
som
ehow
doe
s not
seem
fair
that
som
e pe
ople
seem
to h
ave
all t
he fu
n.
EN4
I wish
I ca
n tra
vel a
s muc
h as
som
e of
my
frien
ds d
o.
EN5
Man
y of
my
frien
ds h
ave
a be
tter l
ife th
an m
e.
EN6
Man
y of
my
frien
ds a
re h
appi
er th
an m
e.
EN7
My
life
is le
ss fu
n th
an th
ose
of m
y fri
ends
.
Envy
(EN
) (T
ando
c et
al.,
201
5)
EN8
Life
is u
nfai
r.
Usi
ng W
eCha
t Mom
ents
mak
es m
e fe
el th
at …
LS
1 In
mos
t way
s my
life
is cl
ose
to m
y id
eal.
LS2
The
cond
ition
s of m
y lif
e ar
e ex
celle
nt.
LS3
I am
satis
fied
with
my
life.
LS
4 So
far,
I hav
e go
tten
the
impo
rtant
thin
gs I
wan
t in
life.
Life
satis
fact
ion
(LS)
(D
iene
r et a
l., 1
985)
LS5
If I c
ould
live
my
life
over
, I w
ould
cha
nge
alm
ost n
othi
ng.
CI1
I i
nten
d to
con
tinue
usin
g W
eCha
t Mom
ents
rath
er th
an d
iscon
tinue
its u
se.
CI2
If
I cou
ld, I
wou
ld li
ke to
con
tinue
my
use
of W
eCha
t Mom
ents
.C
I3
I will
con
tinue
to u
se W
eCha
t Mom
ents
in th
e fu
ture
.
Con
tinua
nce
inte
ntio
n (C
I) (B
ock
et a
l., 2
010)
CI4
A
ll th
ings
con
sider
ed, i
t is
likel
y th
at I
will
con
tinue
to u
se W
eCha
t Mom
ents
in th
e fu
ture
.