Skip to main content
SpringerLink
Log in

The contributing factors of continuance usage of social media: An empirical analysis

  • Published:
Information Systems Frontiers Aims and scope Submit manuscript

Abstract

The problem of leveraging social media for establishing and sustaining consistent policies, procedures and methods of online communication can be challenging for busy professionals. To address this issue and to contribute to the literature we develop our research model to gain a deeper upstanding of the factors that influence social media continuance usage. The theoretical background for our research model are technology acceptance model and diffusion of innovation. We collected our data from college students that are enrolled in a large public university located in North America. We analyze our data using confirmatory factor analysis and structural equation modeling. The results of our data analysis show that ease of use, usefulness, and satisfaction of social media have a positive and significant influence on social media continuance usage. Also, our results show that relative advantage, compatibility, information quality, and risk of social media have a positive influence on the usefulness of social media. We discussed the results implications for theory development and practice.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Action control (pp. 11–39). Springer Berlin Heidelberg.

    Chapter  Google Scholar 

  • Anderson, J. C., & Gerbing, D. W. (1998). Structural equation modeling in practice: a review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.

    Article  Google Scholar 

  • Bagozzi, R. P., & Phillip, L. W. (1982). Representing and testing organizational theories: a holistic construal. Administrative Science Quarterly, 27, 459–489.

    Article  Google Scholar 

  • Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94.

    Article  Google Scholar 

  • Bagozzi, R. P., Davis, F. D., & Warshaw, P. R. (1992). Development and test of a theory of technological learning and usage. Human relations, 45(7), 659–686.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Brown, S. A., & Venkatesh, V. A. (2005). A comparison of competing models and an extension of the model of adoption of technology in the household: an investigation of household adoption of personal computers. MIS Quarterly, 29(3), 399–426.

    Article  Google Scholar 

  • Chang, M. K., & Cheung, W. (2001). Determinants of the intention to use internet/WWW at work: a confirmatory study. Information Management, 39, 1–14.

    Article  Google Scholar 

  • Chau, P. Y. K., & Hu, P. J. (2001). Information technology acceptance by individual professionals: a model comparison approach. Decision Sciences, 32(4), 699–719.

    Article  Google Scholar 

  • Cheng, K. M. (2013). An evaluation of RFID door security system at Taipei arena ice land based on technology acceptance model. International Journal of Management & Information Systems (IJMIS), 17(2), 117–130.

    Article  Google Scholar 

  • Chin, W. W. (1998). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), vii–xvi.

    Google Scholar 

  • Dang, Y., Zhang, Y., Chen, H., Brown, S. A., Hu, P. J.-H., & Nunamaker, J. F. (2012). Theory-informed design and evaluation of an advanced search and knowledge mapping system in nanotechnology. Journal of Management Information Systems, 28(4), 99–128.

    Article  Google Scholar 

  • Davis Jr, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results (Doctoral dissertation, Massachusetts Institute of Technology) http://hdl.handle.net/1721.1/15192

  • Davis, F. D. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International journal of man-machine studies, 38(3), 475–487.

    Article  Google Scholar 

  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.

    Google Scholar 

  • Davis, J. F. (1999). Effectiveness of internet advertising by leading national advertisers. In D. W. Schumann and Ethorson (Eds.), Advertising and the World Wide Web (pp. 81–98). Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982–1003.

    Article  Google Scholar 

  • DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of Management Information Systems, 19(4), 9–30.

    Article  Google Scholar 

  • Fogg, B. I. (2003). Persuasive technology: Using computers to change what We think and do. Morgan Kaufmann Publishers.

  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equations with unobservable variables and measurement error. Journal of Marketing Research, 18, 39–50.

    Article  Google Scholar 

  • Gangi, D. P. M., & Wasko, M. (2016). Social media engagement theory: Exploring the influence of user engagement on social media usage. Journal of organizational and end user computing, (28:2), 53–73.

    Article  Google Scholar 

  • Garvin, D. A., Edmondson, A. C., & Gino, F. (2008). Is yours a learning organization? Harvard Business Review, (86:3), 109.

  • Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: an integrated model. MIS quarterly, 27(1), 51–90.

    Article  Google Scholar 

  • Guesalaga, R. (2016). The use of social media in sales: individual and organizational antecedents, and the role of customer engagement in social media. Industrial Marketing Management, 54, 71–79.

    Article  Google Scholar 

  • Hanafizadeh, P., & Khedmatgozar, H. R. (2012). The mediating role of the dimensions of the perceived risk in the effect of customers’ awareness on the adoption of internet banking in Iran. Electronic Commerce Research, 12(2), 151–175.

    Article  Google Scholar 

  • He, Q., Duan, Y., Fu, Z., & Li, D. (2006). An innovation adoption study of online e-payment in Chinese companies. Journal of Electronic Commerce in Organizations, 4(1), 48–69.

    Article  Google Scholar 

  • Hu, H. F., Al-Gahtani, S. S., & Hu, P. J. H. (2013). Examining the moderating role of gender in Arabian workers’ acceptance of computer technology. Communications of the Association for Information Systems, 33(1), 47–66.

  • Idemudia, E. C. (2014). The visual-cognitive model for internet advertising in online market places. International Journal of Online Marketing, 4(3), 1–20.

    Article  Google Scholar 

  • Idemudia, E. C., & Raisinghani, M. S. (2014). The influence of cognitive trust and familiarity on adoption and continued use of smartphones: an empirical analysis. Journal of International Technology and Information Management, 23(2), 69–94.

    Google Scholar 

  • Idemudia, E. C., Raisinghani, M. S. & Samuel-Ojo, O. (2013) "The Influence of IT-Related Beliefs on Emotional Trust for a Smartphone and Smartphone Continuance Usage: An Empirical Study." International Journal of Technology Diffusion (IJTD) 4, 2: 31–48.

  • Islam, A. K. M. N. (2012). The Role of Perceived System Quality as Educators’ Motivation to Continue E-learning System Use. AIS Transactions on Human-Computer Interaction, 4(1), 25–43.

    Article  Google Scholar 

  • Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 61. doi:10.1016/j.bushor.2009.09.003.

    Article  Google Scholar 

  • Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2), 183–213.

    Article  Google Scholar 

  • Kietzmann, J. H., & Hermkens, K. (2011). Social media? Get serious! Understanding the functional building blocks of social media. Business Horizons, 54, 241–251. doi:10.1016/j.bushor.2011.01.005.

    Article  Google Scholar 

  • Klopping, I. M., & McKinney, E. I. (2004). Extending the technology acceptance model and the task-technology fit model to consumer E-commerce. Information Technology, Learning, and Performance Journal, 22, 1.

    Google Scholar 

  • Komiak, S., & Benbasat, I. (2006). The effects of personalization and familiarity on trust and adoption of recommendation agents. MIS Quarterly, 30(4), 941–960.

    Article  Google Scholar 

  • Lin, J. C., & Lu, H. (2000). Toward an understanding of the behavioral intention to use a web site. International Journal of Information Management, 20, 197–208.

    Article  Google Scholar 

  • McDonald, J. J., Bisset, C., Coleman, M. G., Speake, D., and Brady, R. R. W. 2015. “contemporary use of social media by consultant colorectal surgeons,” colorectal disease (17:2), pp 165–171.

    Google Scholar 

  • Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a word-wide-web content. Information Management, 38(4), 217–230.

    Article  Google Scholar 

  • Perrigot, R., Kacker, M., Basset, G., & Cliquet, G. (2012). Antecedents of early adoption and use of social media networks for stakeholder communications: Evidence from franchising. Journal of Small Business Management, (50:4), 539–565.

    Article  Google Scholar 

  • Podsakoff, M., Mackenzie, S. B., Lee, J., & Podsakoff, N. P. (2003). Common method biases in behavior research: a critical review of the literature and recommendation remedies. Journal of Applied Psychology, 88(5), 879–903.

    Article  Google Scholar 

  • Seth, S. (2016). Why Snapchat is better than Facebook, eb. 5, Retrieved from http://www.cnbc.com/2016/02/05/why-snapchat-is-better-than-facebook-commentary.html.

  • Shannon, C. E. (1951). Prediction and entropy of printed English. Bell system technical journal, 30(1),50–64.

    Article  Google Scholar 

  • Sigala, M., Benckendorff, P., Koo, C., & Tussyadiah, I. (2016). Call for papers by guest Co-editors, Journal of Business Research Special issue on Value co-destruction and online deviant behavior in tourism.

  • Speier, C., & Morris, M. G. (2003). The influence of query interface design on decision-making performance. MIS Quarterly, 27(3), 397–423.

    Article  Google Scholar 

  • Turban, E., Sharda, R., Aronson, J. E., & King, D. (2008). Business intelligence: A managerial approach. Upper Saddle River, NJ: Pearson Prentice Hall.

  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46(2), 186–204.

    Article  Google Scholar 

  • Venkatesh, V., Thong, J.Y.L. and Xu, X. (2012) ‘Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology’, MIS Quarterly, 36, 1:157–178.

    Article  Google Scholar 

  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425–478.

    Article  Google Scholar 

  • Vessey, I. (1991). Cognitive fit: a theory-based analysis of the graphs versus tables literature. Decision Sciences, 22(2), 219–240.

    Article  Google Scholar 

  • Wang, A. T., Sandhu, N. P., Wittich, C. M., Mandrekar, J. N., & Beckman, T. J. (2012). Using social media to improve continuing medical education: A survey of course participants. Mayo Clinic Proceedings, (87:12), 1162–1170.

    Article  Google Scholar 

  • Wu, J., & Wang, S. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information Management, 42, 719–729.

    Article  Google Scholar 

  • Xu, J. D., Benbasat, I., & Cenfetelli, R. T. (2013). Integrating service quality with system and information quality: an empirical test in the e-service context. MIS Quarterly, 37(3), 777–794.

    Article  Google Scholar 

  • Zhang, L., Zhu, J., & Liu, Q. (2012). A meta-analysis of mobile commerce adoption and the moderating effect of culture. Computers in Human Behavior, 28(5), 1902–1911.

    Article  Google Scholar 

  • Zheng, L., Favier, M., Huang, P., & Coat, F. (2012). Chinese consumer perceived risk and risk relievers in e-shopping for clothing. Journal of Electronic Commerce Research, 13(3), 255–274.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Business, Arkansas Tech University, Rothwell Hall, Room 448, 106 West O Street, Russellville, AR, 72801, USA

    Efosa Carroll Idemudia

  2. TWU School of Management, Denton, TX, 76204, USA

    Mahesh S. Raisinghani

  3. Department of Computer Science, Pima Community College, East Campus, Tucson, AZ, USA

    Olusola Samuel-Ojo

Authors
  1. Efosa Carroll Idemudia
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mahesh S. Raisinghani
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Olusola Samuel-Ojo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Efosa Carroll Idemudia.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Idemudia, .C., Raisinghani, M.S. & Samuel-Ojo, O. The contributing factors of continuance usage of social media: An empirical analysis. Inf Syst Front 20, 1267–1280 (2018). https://doi.org/10.1007/s10796-016-9721-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10796-016-9721-3

Keywords

Search

Navigation