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Exploring the continuance intention of social networking websites: an empirical research

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Abstract

Despite the increasing popularity of social networking websites, very little is known about users’ extrinsic and intrinsic motivations that influence their continued use of these websites. The long-term development of social networking websites depends on their users’ continuance of use. To examine the extrinsic and intrinsic motivations, this study integrates the technology acceptance model, the theory of planned behavior, the expectation disconfirmation model, and flow theory to construct a research model which investigates the factors that motivate users to continue to use social networking websites. The research model was tested empirically within the context of Facebook and 482 samples of data were analyzed using a structural equation modeling approach. The analysis showed that the proposed theoretical model provided a deep understanding of user continuance behavior towards social networking websites. The theoretical and practical implications of this study are discussed.

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References

  • Adams DA, Nelson RR, Todd PA (1992) Perceived usefulness, ease-of-use, and usage of information technology: a replication. MIS Q 16(2):227–247

    Article  Google Scholar 

  • Ajzen I (1991) The theory of planned behavior. Organ Behav Hum Decis Process 50(2):179–211

    Article  Google Scholar 

  • Ajzen I (2002) Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. J Appl Soc Psychol 32(4):665–683

    Article  Google Scholar 

  • Ajzen I, Fishbein M (1980) Understanding attitudes and predicting social behavior. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Aldas-Manzano J, Ruiz-Mafe C, Sanz-Blas S (2009) Exploring individual personality factors as drivers of M-shopping acceptance. Ind Manag Data Syst 109(6):739–757

    Article  Google Scholar 

  • Amoako-Gyampah K, Salam AF (2004) An extension of the technology acceptance model in an ERP implementation environment. Inf Manag 41(6):731–745

    Article  Google Scholar 

  • Bakker AB (2005) Flow among music teachers and their students: the crossover of peak experiences. J Vocat Behav 66(1):26–44

    Article  Google Scholar 

  • Bhattacherjee A (2000) Acceptance of Internet applications services: the case of electronic brokerages. IEEE Trans Syst, Man and Cybern—Part A: Syst Humans 30(4):411–420

    Article  Google Scholar 

  • Bhattacherjee A (2001) Understanding information systems continuance: an expectation-confirmation model. MIS Q 25(3):351–370

    Article  Google Scholar 

  • Cadotte ER, Woodruff RB, Jenkins RL (1987) Expectations and norms in models of consumer satisfaction. J Mark Res 24(3):305–314

    Article  Google Scholar 

  • Chai S, Kim M (2012) A socio-technical approach to knowledge contribution behavior: an empirical investigation of social networking sites users. Int J Inf Manag 32(2):118–126

    Article  Google Scholar 

  • Chang YP, Zhu DH (2012) The role of perceived social capital and flow experience in building users’ continuance intention to social networking sites in China. Comput Hum Behav 28(3):995–1001

    Article  Google Scholar 

  • CheckFacebook.com (2012) Facebook Marketing Statistics, Demographics, Reports, and News, available at: http://www.checkfacebook.com/. Accessed 23 June 2012

  • Choi D, Kim J (2004) Why people continue to play online games: in search of critical design factors to increase customer’s loyalty to online contents. Cyber Psychol Behav 7(1):11–24

    Article  Google Scholar 

  • Chow M, Herold DK, Choo TM, Chan K (2012) Extending the technology acceptance model to explore the intention to use second life for enhancing healthcare education. Comput Educ 59(4):1136–1144

    Article  Google Scholar 

  • Churchill GA, Surprenant C (1982) An investigation into the determinants of consumer satisfaction. J Mark Res 19(4):491–504

    Article  Google Scholar 

  • Csikszentmihalyi M (1993) The evolving self. Harper & Row, New York

    Google Scholar 

  • Cyr D, Bonanni C, Bowes J, Ilsever J (2005) Beyond trust: web site design preferences across cultures. J Glob Inf Manag 13(4):25–54

    Article  Google Scholar 

  • Davis FD (1989) Perceived usefulness, perceived ease-of-use, and user acceptance of information technology. MIS Q 13(3):319–340

    Article  Google Scholar 

  • Davis FD, Bagozzi RP, Warshaw PR (1989) User acceptance of computer technology: a comparison of two theoretical models. Manag Sci 35(8):982–1003

    Article  Google Scholar 

  • Deci EL, Ryan RM (1987) The support of autonomy and the control of behavior. J Pers Soc Psychol 53(6):1024–1037

    Article  Google Scholar 

  • Fishbein M, Ajzen I (1975) Belief, attitude, intention, and behavior: an introduction to theory and research. Addison-Wesley, MA

    Google Scholar 

  • Fornell C, Larcker DF (1981) Evaluating structural equation models with unobservable variables and measurement error. J Mark Res 18(1):39–50

    Article  Google Scholar 

  • Gefen D, Straub DW (1997) Gender differences in the perception and use of e-mail: an extension to the technology acceptance model. MIS Q 21(4):389–400

    Article  Google Scholar 

  • Gefen D, Karahanna E, Straub DW (2003) Inexperience and experience with online stores: the importance of TAM and trust. IEEE Trans Eng Manag 50(3):307–321

    Article  Google Scholar 

  • Hair JF, Anderson RE, Tatham RL, Black WC (1995) Multivariate data analysis with readings. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Hair JF, Anderson RE, Tatham RL, Black WC (1998) Multivariate data analysis. Prentice Hall, Upper Saddle

    Google Scholar 

  • Hair JF, Black WC, Babin BJ, Anderson RE, Tatham RL (2006) Multivariate data analysis. Prentice Hall, Upper Saddle

    Google Scholar 

  • Hendrickson AR, Collins MR (1996) An assessment of structure and causation of IS usage. ACM SIGMIS Database 27(2):61–67

    Article  Google Scholar 

  • Hsu CL, Lu HP (2004) Why do people play on-line games? An extended TAM with social influences and flow experience. Inf Manag 41(7):853–868

    Article  Google Scholar 

  • Hsu CL, Wu CC, Chen MC (2012) An empirical analysis of the antecedents of e-satisfaction and e-loyalty: focusing on the role of flow and its antecedents. Inf Syst E-Bus Manag. doi:10.1007/s10257-012-0194-8

    Google Scholar 

  • Hu L, Bentler PM (1999) Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model: a Multidiscip J 6(1):1–55

    Article  Google Scholar 

  • Igbaria M, Schiffman SJ, Wieckowshi TJ (1994) The respective roles of perceived usefulness and perceived fun in the acceptance of microcomputer technology. Behav Inf Technol 13(6):349–361

    Article  Google Scholar 

  • iResearch (2011) Reports on Social Networking Sites Users’ Behavior in China from 2010–2011, Available at: http://www.iresearch.com.cn/Report/1607.html. Accessed 28 Oct 2012

  • Jackson SA, Marsh HW (1996) Development and validation of a scale to measure optimal experience: the flow state scale. J Sport Exerc Psychol 18(1):17–35

    Google Scholar 

  • Jarvenpaa SL, Todd PA (1996/1997) Consumer reactions to electronic shopping on the world wide web. Int J Electron Commer 1(2):59–88

    Google Scholar 

  • Kabadayi S, Gupta R (2005) Web site loyalty: an empirical investigation of its antecedents. Int J Internet Mark Advert 2(4):321–345

    Article  Google Scholar 

  • Karahanna E, Straub DW, Chervany NL (1999) Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quart 23(2):183–213

    Article  Google Scholar 

  • Keen C, Wetzels M, De Ruyter K, Feinberg R (2004) E-tailers versus retailers: which factors determine consumer preferences. J Bus Res 57(7):685–695

    Article  Google Scholar 

  • Kim B (2011) Understanding antecedents of continuance intention in social networking services. Cyberpsychol Behav Soc Netw 14(4):199–205

    Article  Google Scholar 

  • Kim B, Han I (2009) The role of trust belief in community-driven knowledge and its antecedents. J Am Soc Inf Sci Technol 60(5):1012–1026

    Article  Google Scholar 

  • Kim B, Choi M, Han I (2009) User behaviors toward mobile data services: the role of perceived fee and prior experience. Expert Syst Appl 36(4):8528–8536

    Article  Google Scholar 

  • Kucukarslan SN, Nadkarni A (2008) Evaluating medication-related services in a hospital setting using the disconfirmation of expectations model of satisfaction. Res Soc Adm Pharm 4(1):12–22

    Article  Google Scholar 

  • Lee MC (2009) Factors influencing the adoption of internet banking: an integration of TAM and TPB with perceived risk and perceived benefit. Electron Commer Res Appl 8(3):130–141

    Article  Google Scholar 

  • Liao C, Chen JL, Yen DC (2007) Theory of planning behavior (TPB) and customer satisfaction in the continued use of e-service: an integrated model. Comput Hum Behav 23(6):2804–2822

    Article  Google Scholar 

  • Liao C, Palvia P, Chen JL (2009) Information technology adoption behavior life cycle: toward a technology continuance theory (TCT). Int J Inf Manag 29(4):309–320

    Article  Google Scholar 

  • Lin HF (2008) Antecedents of virtual community satisfaction and loyalty: an empirical test of competing theories. Cyber Psychol Behav 11(2):138–144

    Article  Google Scholar 

  • Lu Y, Zhou T, Wang B (2009) Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Comput Hum Behav 25(1):29–39

    Article  Google Scholar 

  • Mathwick C, Rigdon E (2004) Play, flow, and the online search experience. J Consum Res 31(2):324–332

    Article  Google Scholar 

  • McKinney V, Yoon K, Zahedi FM (2002) The measurement of web-customer satisfaction: an expectation and disconfirmation approach. Inf Syst Res 13(3):296–315

    Article  Google Scholar 

  • Moon JW, Kim YG (2001) Extending the TAM for a world-wide-web context. Inf Manag 38(4):217–230

    Article  Google Scholar 

  • Novak TP, Hoffman DL, Yung YF (2000) Measuring the customer experience in online environments: a structural modeling approach. Mark Sci 19(1):22–42

    Article  Google Scholar 

  • Novak TP, Hoffman DL, Duhachek A (2003) The influence of goal-directed and experiential activities in online flow experiences. J Consumer Psychol 13(1/2):3–16

    Article  Google Scholar 

  • Nunnally JC (1978) Psychometric theory. McGraw-Hill, New York

    Google Scholar 

  • Oinas-Kukkonen H (2000) Balancing the vendor and consumer requirements for electronic shopping systems. Inf Technol Manag 1(1–2):73–84

    Article  Google Scholar 

  • Oliver RL (1976) Effect of expectation and disconfirmation on postexposure product evaluation: an alternative interpretation. J Appl Psychol 62(4):480–486

    Article  Google Scholar 

  • Oliver RL (1980) A cognitive model of the antecedents and consequences of satisfaction decisions. J Mark Res 17(4):460–469

    Article  Google Scholar 

  • Oliver RL (1981) Measurement and evaluation of satisfaction process in retail settings. J Retail 57(3):25–48

    Google Scholar 

  • Oliver RL, Burke RR (1999) Expectation process in satisfaction formation: a field study. J Serv Res 1(3):196–214

    Article  Google Scholar 

  • Page TJ, Spreng RA (2002) Difference scores versus direct effects in service quality measurement. J Serv Res 4(3):184–192

    Article  Google Scholar 

  • Park BW, Lee KC (2010) Effects of knowledge sharing and social presence on the intention to continuously use social networking sites: the case of twitter in Korea. In: The International Conference on U- and E-Service, Science and Technology. South Korea

  • Pelling E, White KM (2009) The theory of planned behaviour applied to young people’s use of social networking websites. Cyberpsychol Behav 12(6):755–759

    Article  Google Scholar 

  • Posthuma RA, Dworkin JB (2000) A behavioral theory of arbitrator acceptability. Int J Confl Manag 11(3):249–266

    Article  Google Scholar 

  • Qi J, Li L, Li Y, Shu H (2009) An extension of technology acceptance model: analysis of the adoption of mobile data services in China. Syst Res Behav Sci 26(3):391–407

    Article  Google Scholar 

  • Rettie R (2001) An exploration of flow during Internet use. Internet Res 11(2):103–113

    Article  Google Scholar 

  • Sheng ML, Hsu CL, Wu CC (2011) The asymmetric effect of online social networking attribute-level performance. Ind Manag Data Syst 111(7):1065–1086

    Article  Google Scholar 

  • Shih H (2004) An empirical study on predicting user acceptance of e-shopping on the Web. Inf Manag 41(3):351–368

    Article  Google Scholar 

  • Shim S, Eastlick MA, Lotz SL, Warrington P (2001) An online prepurchase intentions model: the role of intention to search. J Retail 77(3):397–416

    Article  Google Scholar 

  • Shin N (2006) Online learner’s ‘flow’ experience: an empirical study. British J Educ Technol 37(5):705–720

    Article  Google Scholar 

  • Siekpe JS (2005) An examination of the multidimensionality of the flow construct in a computer-mediated environment. J Electron Commer Res 6(1):31–43

    Google Scholar 

  • Skadberg YX, Kimmel JR (2004) Visitors’ flow experience while browsing a Web site: its measurement, contributing factors and consequences. Comput Hum Behav 20(3):403–422

    Article  Google Scholar 

  • Spreng RA, Mackenzie SB, Olshavsky RW (1996) A reexamination of the determinants of consumer satisfaction. J Market 60(3):15–32

    Article  Google Scholar 

  • Su S (2010) Inside Facebook, Available at: http://www.insidefacebook.com/2010/04/12/does-taiwans-explosive-facebook-growth-mean-more-to-come-in-east-asia/. Accessed Nov 2011

  • Subramanian GH (1994) A replication of perceived usefulness and perceived ease-of-use measurement. Decis Sci 25(5/6):863–874

    Article  Google Scholar 

  • Taylor S, Todd PA (1995) Understanding information technology usage: a test of competing models. Inf Syst Res 6(2):144–176

    Article  Google Scholar 

  • Teo T, Lee B (2010) Explaining the intention to use technology among student teachers: an application of the Theory of Planned Behavior (TPB). Campus-Wide Inf Syst 27(2):60–67

    Article  Google Scholar 

  • Teo TSH, Lim VKG, Lai RYC (1999) Intrinsic and extrinsic motivation in internet usage. Omega- Int J Manag Sci 27(1):25–37

    Article  Google Scholar 

  • Tong DYK (2009) A study of e-recruitment technology adoption in Malaysia. Ind Manag Data Syst 109(2):281–300

    Article  Google Scholar 

  • Trevino LK, Webster J (1992) Flow in computer-mediated communication: electronic mail and voice mail evaluation and impacts. Commun Res 19(5):539–573

    Article  Google Scholar 

  • Vallerand RJ (1997) Toward a hierarchical model of intrinsic and extrinsic motivation. Adv Exp Soc Psychol 29:271–360

    Article  Google Scholar 

  • Venkatesh V (2000) Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance model. Inf Syst Res 11(4):342–365

    Article  Google Scholar 

  • Venkatesh V, Davis FD (2000) A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag Sci 46(2):186–204

    Article  Google Scholar 

  • Venkatesh V, Speier C (2000) Creating an effective training environment for enhancing telework. Int J Hum Comput Stud 52(6):991–1005

    Article  Google Scholar 

  • Webster J, Trevino LK, Ryan L (1993) The dimensionality and correlates of flow in human-computer interactions. Comput Hum Behav 9(4):411–426

    Article  Google Scholar 

  • Wirtz JJ, Bateson JEG (1999) Introducing uncertain performance expectations in satisfaction models for services. Int J Serv Indus Manag 10(1):82–99

    Google Scholar 

  • Wolfinbarger M, Gilly MC (2001) Shopping online for freedom, control, and fun. Calif Manag Rev 43(2):34–55

    Article  Google Scholar 

  • Wu JJ, Chang YS (2005) Towards understanding members’ interactivity, trust, and flow in online travel community. Ind Manag Data Syst 105(7):937–954

    Article  Google Scholar 

  • Wu L, Chen JL (2005) An extension of trust and TAM model with TPB in the initial adoption of on-line tax: an empirical study. Int J Human–Comput Stud 62(6):784–808

    Article  Google Scholar 

  • Ximen LS, Ma GL, Liu QH (2009) The outbreak of the Internet revolution at present. China Machine Press, Beijing

    Google Scholar 

  • Yi Y (1990) A critical review of consumer satisfaction. In: Zeithaml VA (ed) Review of Marketing. American Marketing Association, Chicago, pp 68–123

    Google Scholar 

  • Yi Y, La S (2003) The moderating role of confidence in expectations and the asymmetric influence of disconfirmation on customer satisfaction. Serv Ind J 23(5):20–47

    Article  Google Scholar 

  • Zwick R, Pieters R, Baumgartner H (1995) On the practical significance of hindsight bias: the case of the expectancy-disconfirmation model of consumer satisfaction. Organ Behav Hum Decis Process 64(1):103–117

    Article  Google Scholar 

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Appendix: Scale items

Appendix: Scale items

Perceived ease-of-use (PEOU) [the first three items were adapted from Davis (1989)]

PEOU1: I find Facebook easy to use.

PEOU2: Learning to operate Facebook is easy for me.

PEOU3: It is easy for me to become skillful at using Facebook.

PEOU4: I find it easy to use Facebook to connect and share with the people in my life.

Perceived usefulness (PU) [adapted from Davis (1989)]

PU1: I find Facebook useful in my life.

PU2: Using Facebook enables me to more easily/quickly communicate with others.

PU3: Using Facebook increases the efficiency of communication between myself and others.

PU4: If I use Facebook, my ability to communicate conveniently with others will be increased.

Disconfirmation (DIS) [adapted from Bhattacherjee (2001)]

DIS1: My experience with using Facebook was better than I expected.

DIS2: The service level provided by Facebook was better than I expected.

DIS3: Overall, most of my expectations from using Facebook were confirmed.

Satisfaction (SAT) [adapted from Bhattacherjee (2001)]

SAT1: My overall experience of Facebook use was that I was very satisfied.

SAT2: My overall experience of Facebook use was that I was very pleased.

SAT3: My overall experience of Facebook use was that I was very contented.

SAT4: My overall experience of Facebook use was that I was absolutely delighted.

Subjective norm (SN) [adapted from Taylor and Todd (1995)]

SN1: People who are important to me think that I should use Facebook.

SN2: People who influence me think that I should use Facebook.

Perceived behavioral control (PBC) [adapted from Taylor and Todd (1995)]

PBC1: Using Facebook is entirely within my control.

PBC2: I have the knowledge and ability to use Facebook.

PBC3: I am able to skillfully use Facebook.

Flow (FL) [adapted from Novak et al. (2003)]

FL1: When I was browsing this website (Facebook), I felt very captivated.

FL2: When I was navigating this website (Facebook), time seemed to pass very quickly.

FL3: When I was visiting this website (Facebook), nothing seemed to matter to me.

Attitude (ATT) [adapted from Taylor and Todd (1995)]

ATT1: Using Facebook is a good idea.

ATT2: I like using Facebook.

ATT3: Using Facebook is a wise idea.

Continuance intention (INT) [adapted from Bhattacherjee (2001)]

INT1: I intend to continue to use Facebook rather than discontinue its use.

INT2: My intentions are to continue to use Facebook than other online social networks.

INT3: If I could, I would like to continue to use Facebook as much as possible.

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Hsu, CL., Yu, CC. & Wu, CC. Exploring the continuance intention of social networking websites: an empirical research. Inf Syst E-Bus Manage 12, 139–163 (2014). https://doi.org/10.1007/s10257-013-0214-3

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  • DOI: https://doi.org/10.1007/s10257-013-0214-3

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