A sound follower base is a prerequisite for the survival of a brand micro-blog. Thus, determining how to enhance followers’ continuance intentions to follow is critical. We integrated the value-based adoption mode and social identity theory to test a conceptual model. The proposed model identified three sets of blog utilities (information, social, and service) affecting followers’ continuance intention through perceived value and brand micro-blog identification. Using a Chinese sample drawn from the Sina micro-blog, we sought to clarify why followers continue to follow a brand micro-blog. The concluding section discusses our findings in terms of implications for theory and practice.
AdamsDANelsonRRToddPA (1992) Perceived usefulness, ease of use, and usage of information technology: a replication. MIS Quarterly16(2): 227–247.
2.
AladwaniAMPalviaPC (2002) Developing and validating an instrument for measuring user-perceived web quality. Information & Management39(6): 467–476.
3.
AlgesheimerRDholakiaUMHerrmannA (2005) The social influence of brand community: Evidence from European car clubs. Journal of Marketing69(3): 19–34.
4.
AndrewsJCNetemeyerRGBurtonS. (2004) Understanding adolescent intentions to smoke: An examination of relationships among social influence, prior trial behavior, and antitobacco campaign advertising. Journal of Marketing68(3): 110–123.
5.
AshforthBEMaelF (1989) Social identity theory and the organization. Academy of Management Review14(1): 20–39.
6.
BagozziRPDholakiaUM (2006) Open source software user communities: A study of participation in Linux user groups. Management Science52(7): 1099–1115.
7.
BerryLLZeithamlVAParasuramanA (1990) Five imperatives for improving service quality. MIT Sloan Management Review22: 29–37.
8.
BhattacherjeeA (2001) Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly25(3): 351–370.
9.
BhattacherjeeAPremkumarG (2004) Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. MIS Quarterly28(2): 229–254.
10.
BlauPM (1964) Exchange and Power in Social Life. Transaction Publishers.
11.
BradyMKRobertsonCJCroninJJ (2001) Managing behavioral intentions in diverse cultural environments: An investigation of service quality, service value, and satisfaction for American and Ecuadorian fast-food customers. Journal of International Management7(2): 129–149.
12.
CarlsonBDSuterTABrownTJ (2008) Social versus psychological brand community: The role of psychological sense of brand community. Journal of Business Research61(4): 284–291.
13.
ChiuC-MWangET (2008) Understanding Web-based learning continuance intention: The role of subjective task value. Information & Management45(3): 194–201.
14.
CohenJCohenPWestSG. (2013) Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. Routledge.
15.
CooilBKeininghamTLAksoyL. (2007) A longitudinal analysis of customer satisfaction and share of wallet: Investigating the moderating effect of customer characteristics. Journal of Marketing71(1): 67–83.
16.
CoyleJRSmithTPlattG (2012) “I’m here to help.” How companies’ microblog responses to consumer problems influence brand perceptions. Journal of Research in Interactive Marketing6(1): 27–41.
17.
DavisFDBagozziRPWarshawPR (1992) Extrinsic and intrinsic motivation to use computers in the workplace 1. Journal of Applied Social Psychology22(14): 1111–1132.
18.
De VriesLGenslerSLeeflangPS (2012) Popularity of brand posts on brand fan pages: an investigation of the effects of social media marketing. Journal of Interactive Marketing26(2): 83–91.
19.
DeLoneWHMcLeanER (1992) Information systems success: The quest for the dependent variable. Information Systems Research3(1): 60–95.
20.
DholakiaUMBagozziRPPearoLK (2004) A social influence model of consumer participation in network-and small-group-based virtual communities. International Journal of Research in Marketing21(3): 241–263.
21.
FinnS (1985) Information-theoretic measures of reader enjoyment. Written Communication2(4): 358–376.
22.
FisherRJWakefieldK (1998) Factors leading to group identification: A field study of winners and losers. Psychology & Marketing15(1): 23–40.
23.
FlintDJWoodruffRBGardialSF (2002) Exploring the phenomenon of customers’ desired value change in a business-to-business context. Journal of Marketing66(4): 102–117.
24.
FornellCLarckerDF (1981) Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research18(1): 39–50.
25.
FrickRW (1992) Interestingness. British Journal of Psychology83(1): 113–128.
26.
HassanSLiF (2007) Evaluating the usability and content usefulness of web sites: a benchmarking approach. Electronic Commerce: Concepts, Methodologies, Tools, and Applications: Concepts, Methodologies, Tools, and Applications1: 402.
27.
HoggMAAbramsD (1988) Social Identification. Routledge.
28.
HsiaoC-CChiouJ-S (2012) The impact of online community position on online game continuance intention: Do game knowledge and community size matter?Information & Management49(6): 292–300.
29.
HsuCLLiuCCLeeYD (2010) Effect of commitment and trust towards micro-blogs on consumer behavioral intention: a relationship marketing perspective. International Journal of Electronic Business8(4): 292–303.
30.
IgbariaMZinatelliNCraggP. (1997) Personal computing acceptance factors in small firms: a structural equation model. MIS Quarterly: 279–305.
31.
KahnemanDTverskyA (1979) Prospect theory: An analysis of decision under risk. Econometrica: Journal of the Econometric Society: 263–291.
32.
KaplanAMHaenleinM (2010) Users of the world, unite! The challenges and opportunities of social media. Business Horizons53(1): 59–68.
33.
KimAJKoE (2012) Do social media marketing activities enhance customer equity? An empirical study of luxury fashion brand. Journal of Business Research65(10): 1480–1486.
34.
KimH-WKankanhalliA (2009) Investigating user resistance to information systems implementation: A status quo bias perspective. MIS Quarterly33(3): 567–582.
35.
KimHWChanHCGuptaS (2007) Value-based adoption of mobile Internet: an empirical investigation. Decision Support Systems43(1): 111–126.
36.
KimSSMalhotraNK (2005) A longitudinal model of continued IS use: An integrative view of four mechanisms underlying postadoption phenomena. Management Science51(5): 741–755.
37.
KwakHChunHMoonS (2011) Fragile online relationship: A first look at unfollow dynamics in Twitter. CHI ‘11: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ACM, New York, 2011: 1091–1100.
38.
KwonESSungY (2011) Follow me! Global marketers’ Twitter use. Journal of Interactive Advertising12(1): 4–16.
39.
LabrecqueLI (2014) Fostering consumer–brand relationships in social media environments: The role of parasocial interaction. Journal of Interactive Marketing28(2): 134–148.
40.
LimayemMHirtSGCheungCMK (2007) How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly31(4): 705–737.
41.
LinC-P (2010) Learning virtual community loyalty behavior from a perspective of social cognitive theory. International Journal of Human-Computer Interaction26(4): 345–360.
42.
LinHFanWChauPY (2014) Determinants of users’ continuance of social networking sites: A self-regulation perspective. Information & Management51(5): 595–603.
43.
LinTCWuSHsuJSC. (2012) The integration of value-based adoption and expectation-confirmation models: An example of IPTV continuance intention. Decision Support Systems54(1): 63–75.
44.
LiuYL (2003) Parent-child interaction and children’s depression: the relationships between parent-child interaction and children’s depressive symptoms in Taiwan. Journal of Adolescence26(4): 447–457.
45.
MalthouseECHaenleinMSkieraB. (2013) Managing customer relationships in the social media era: Introducing the social CRM house. Journal of Interactive Marketing27(4): 270–280.
46.
MolinerMA (2009) Loyalty, perceived value and relationship quality in healthcare services. Journal of Service Management20(1): 76–97.
47.
MoonS (2011) Analysis of Twitter unfollow: How often do people unfollow in Twitter and why?Social Informatics: Third International Conference, SocInfo 2011, Singapore, October 6–8 2011 Proceedings. 7–7.
48.
MunizAMJrO’GuinnTC (2001) Brand community. Journal of Consumer Research27(4): 412–432.
49.
NicolaouAIMcKnightDH (2006) Perceived information quality in data exchanges: Effects on risk, trust, and intention to use. Information Systems Research17(4): 332.
50.
ParasuramanAZeithamlVABerryLL (2004) SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing64(1): 12–40.
51.
PaulinMPerrien (1996) Measurement of service quality the effect of contextuality. Managing Service QualityIII(III): 257–273.
52.
PetterSMcLeanER (2009) A meta-analytic assessment of the DeLone and McLean IS success model: An examination of IS success at the individual level. Information & Management46(3): 159–166.
53.
PittLFWatsonRTKavanCB (1995) Service quality: a measure of information systems effectiveness. MIS Quarterly19(2): 173–187.
54.
PodsakoffPMOrganDW (1986) Self-reports in organizational research: Problems and prospects. Journal of Management12(4): 531–544.
55.
RokeachM (1973) The Nature of Human Values. Free Press.
56.
ShenY-CHuangC-YChuC-H. (2010) Virtual community loyalty: An interpersonal-interaction perspective. International Journal of Electronic Commerce15(1): 49–74.
57.
SirdeshmukhDSinghJSabolB (2002) Consumer trust, value, and loyalty in relational exchanges. Journal of Marketing66(1): 15–37.
58.
SungYKimYKwonO. (2010) An explorative study of Korean consumer participation in virtual brand communities in social network sites. Journal of Global Marketing23(5): 430–445.
59.
TeoH-HWeiKKBenbasatI (2003) Predicting intention to adopt interorganizational linkages: an institutional perspective. MIS Quarterly27(1): 19–49.
60.
UlagaWEggertA (2006) Value-based differentiation in business relationships: Gaining and sustaining key supplier status. Journal of Marketing70(1): 119–136.
61.
VenkateshVThongJYChanFK. (2011) Extending the two-stage information systems continuance model: Incorporating UTAUT predictors and the role of context. Information Systems Journal21(6): 527–555.
62.
WadeSEBuxtonWMKellyM (1999) Using think-alouds to examine reader-text interest. Reading Research Quarterly34(2): 194–216.
63.
WangJ-CChiangM-J (2009) Social interaction and continuance intention in online auctions: A social capital perspective. Decision Support Systems47(4): 466–476.
64.
WoisetschlägerDMHartlebVBlutM (2008) How to make brand communities work: Antecedents and consequences of consumer participation. Journal of Relationship Marketing7(3): 237–256.
65.
WoodruffRB (1997) Customer value: The next source for competitive advantage. Journal of the Academy of Marketing Science25(2): 139–153.
66.
XuWSchneiderC (2011) Micro-blogging: The effects of information quality, system quality, and community quality on satisfaction and continuance intention. SIGHCI 2011 Proceedings. Paper 16.
67.
YangZCaiSZhouZ. (2005) Development and validation of an instrument to measure user perceived service quality of information presenting Web portals. Information & Management42(4): 575–589.
68.
YangZPetersonRT (2004) Customer perceived value, satisfaction, and loyalty: The role of switching costs. Psychology & Marketing21(10): 799–822.
69.
ZeithamlVA (1988) Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. Journal of Marketing52(3): 2–22.
70.
ZhaoLLuY (2012) Enhancing perceived interactivity through network externalities: An empirical study on micro-blogging service satisfaction and continuance intention. Decision Support Systems53(4): 825–834.
