Due to the social networking relationship, users’ continuance of social networking sites (SNS) may receive social influence from their peers and referents. This research identified the effect of social support on social influence in mobile SNS. Social support consists of both informational support and emotional support. Social influence is reflected by three factors: subjective norm, social identity and group norm. The results suggested that social support has a significant effect on social influence. The results imply that service providers need to build a supportive climate in order to facilitate social influence and users’ continuance usage.
BaiYYaoZDouYF (2015) Effect of social commerce factors on user purchase behavior: An empirical investigation from renren.com. International Journal of Information Management35(5): 538–550.
2.
BaronRMKennyDA (1986) The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology51(6): 1173–1182.
3.
BhattacherjeeA (2001) Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly25(3): 351–370.
4.
ChaoualiW (2016) Once a user, always a user: Enablers and inhibitors of continuance intention of mobile social networking sites. Telematics and Informatics33(4): 1022–1033.
5.
ChenJShenX-L (2015) Consumers’ decisions in social commerce context: An empirical investigation. Decision Support Systems79: 55–64.
6.
China Internet Network Information Center (2017) The 40th China Statistical Report on Internet Development. China Internet Network Information Center.
7.
ChoiGChungH (2013) Applying the Technology Acceptance Model to social networking sites (SNS): Impact of subjective norm and social capital on the acceptance of SNS. International Journal of Human-Computer Interaction29(10): 619–628.
8.
ChouCHWangYSTangTI (2015) Exploring the determinants of knowledge adoption in virtual communities: A social influence perspective. International Journal of Information Management35(3): 364–376.
9.
DholakiaUMBagozziRPPearoLK (2004) A social influence model of consumer participation in network- and small-group-based virtual communities. International Journal of Research in Marketing21: 241–263.
10.
FishbeinMAjzenI (1975) Belief, Attitude, Intention and Behavior: An introduction to theory and research. Reading, MA, Addison-Wesley.
11.
GefenDStraubDWBoudreauMC (2000) Structural equation modeling and regression: guidelines for research practice. Communications of the Association for Information Systems4(7): 1–70.
12.
HaYWParkMCLeeE (2014) A framework for mobile SNS advertising effectiveness: user perceptions and behaviour perspective. Behaviour & Information Technology33(12): 1333–1346.
13.
HajliMN (2014) The role of social support on relationship quality and social commerce. Technological Forecasting and Social Change87: 17–27.
14.
KabaBToureB (2014) Understanding information and communication technology behavioral intention to use: Applying the UTAUT model to social networking site adoption by young people in a least developed country. Journal of the Association for Information Science and Technology65(8): 1662–1674.
15.
KelmanHC (1958) Compliance identification, and internalization: Three processes of attitude change. The Journal of Conflict Resolution2(1): 51–60.
16.
KimH-WGuptaSKohJ (2011) Investigating the intention to purchase digital items in social networking communities: A customer value perspective. Information & Management48(6): 228–234.
17.
KuY-CChenRZhangH (2013) Why do users continue using social networking sites?An exploratory study of members in the United States and Taiwan. Information & Management50(7): 571–581.
18.
LiangT-PHoY-TLiY-WTurbanE (2011) What drives social commerce: The role of social support and relationship quality. International Journal of Electronic Commerce16(2): 69–90.
19.
LinC-P (2011) Assessing the mediating role of online social capital between social support and instant messaging usage. Electronic Commerce Research and Applications10(1): 105–114.
20.
LinHFanWChauPYK (2014) Determinants of users’ continuance of social networking sites: A self-regulation perspective. Information & Management51(5): 595–603.
21.
LinKYLuHP (2015) Predicting mobile social network acceptance based on mobile value and social influence. Internet Research25(1): 107–130.
22.
LinT-CHsuJS-CChengH-LChiuC-M (2015) Exploring the relationship between receiving and offering online social support: A dual social support model. Information & Management52(3): 371–383.
23.
LuarnPYangJCChiuYP (2015) Why people check In to social network sites. International Journal of Electronic Commerce19(4): 21–46.
24.
MalhotraYGallettaD (2003) A multidimensional commitment model of volitional systems adoption and usage behavior. Journal of Management Information Systems22(1): 117–151.
25.
NunnallyJC (1978) Psychometric Theory. New York, McGraw-Hill.
26.
OhHJOzkayaELaRoseR (2014) How does online social networking enhance life satisfaction? The relationships among online supportive interaction, affect, perceived social support, sense of community, and life satisfaction. Computers in Human Behavior30: 69–78.
27.
ParkEBaekSOhmJChangHJ (2014) Determinants of player acceptance of mobile social network games: An application of extended technology acceptance model. Telematics and Informatics31(1): 3–15.
RozzellBPiercyCWCarrCTKingSLaneBLTornesMJohnsonAJWrightKB (2014) Notification pending: Online social support from close and nonclose relational ties via Facebook. Computers in Human Behavior38: 272–280.
30.
ShenAXLCheungCMKLeeMKOChenH (2011) How social influence affects we-intention to use instant messaging: The moderating effect of usage experience. Information Systems Frontier13(2): 157–169.
31.
TsaiH-TBagozziRP (2014) Contribution behavior in virtual communities: Cognitive, emotional, and social influences. MIS Quarterly38(1): 143–163.
32.
VenkateshVDavisFD (2000) A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science46(2): 186–204.
33.
WangESTChouNPY (2016) Examining social influence factors affecting consumer continuous usage intention for mobile social networking applications. International Journal of Mobile Communications14(1): 43–55.
34.
WangYHsiaoS-HYangZHajliN (2016) The impact of sellers’ social influence on the co-creation of innovation with customers and brand awareness in online communities. Industrial Marketing Management54: 56–70.
35.
WangYLMeisterDBGrayPH (2013) Social influence and knowledge management systems use: Evidence from panel data. MIS Quarterly37(1): 299–313.
36.
WongCHTanGWHLokeSPOoiKB (2015) Adoption of mobile social networking sites for learning?Online Information Review39(6): 762–778.
37.
XuBLiD (2015) An empirical study of the motivations for content contribution and community participation in Wikipedia. Information & Management52(3): 275–286.
38.
XuYYangYChengZLimJ (2014) Retaining and attracting users in social networking services: An empirical investigation of cyber migration. Journal of Strategic Information Systems23(3): 239–253.
39.
YanLTanY (2014) Feeling blue?Go online: An empirical study of social support among patients. Information Systems Research25(4): 690–709.
40.
YoonCRollandE (2015) Understanding continuance use in social networking services. Journal of Computer Information Systems55(2): 1–8.
41.
ZhangHLuYGuptaSZhaoL (2014) What motivates customers to participate in social commerce?The impact of technological environments and virtual customer experiences. Information & Management51(8): 1017–1030.
42.
ZhangKZKBenyoucefMZhaoSJ (2016) Building brand loyalty in social commerce: The case of brand microblogs. Electronic Commerce Research and Applications15: 14–25.
43.
ZhangZ (2010) Feeling the sense of community in social networking usage. IEEE Transactions on Engineering Management57(2): 225–239.
44.
ZhaoLLuYWangBChauPYKZhangL (2012) Cultivating the sense of belonging and motivating user participation in virtual communities: A social capital perspective. International Journal of Information Management32(6): 574–588.
45.
ZhouTLiHXLiuY (2010) The effect of flow experience on mobile SNS users’ loyalty. Industrial Management & Data Systems110(5-6): 930–946.
46.
ZhuDHChangYPLuoJJLiX (2014) Understanding the adoption of location-based recommendation agents among active users of social networking sites. Information Processing & Management50(5): 675–682.
