Advertisement

User Adoption and Loyalty of Location Based Social Network Service in China

  • Yubo Zhang
  • Pei-Luen Patrick Rau
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8528)

Abstract

This study made an investigation of user adoption and loyalty of location based social network service. Regression analysis was conducted to identify the predictors of user adoption measured by intention and frequency according to Innovation Diffusion Theory and the theory of Uses and Gratifications. Personal innovativeness was found to effectively predict future intention. Perceived popularity was found to effectively predict future frequency. Not all five dimensions of perceived innovativeness had equal predicting power to user adoption. Perceived needs proved to effectively predict user adoption measured by both future intention and future frequency. Path analysis showed a structure integrating predictors of e-loyalty together, including trust, satisfaction, flow experience and switching cost. Comparison of continuers, quitters and refusers of LBSNS showed that continuers had higher level of willingness to pursue fashion and behaved more innovative than others. Comparison of three typical LBSNS applications showed a more advantageous position of dedicated LBSNS than SNS and microblog in terms of loyalty.

Keywords

Adoption loyalty location-based social network service 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Ostlund, L.E.: Perceived innovation attributes as predictors of innovativeness. Journal of Consumer Research 1, 23–29 (1974)CrossRefGoogle Scholar
  2. 2.
    Chang, B.H., Lee, S.E., Kim, B.S.: Exploring factors affecting the adoption and continuance of online games among college students in South Korea: Integrating uses and gratification and diffusion of innovation approaches. New Media & Society 8, 295–319 (2006)CrossRefGoogle Scholar
  3. 3.
    Peslak, A., Ceccucci, W., Sendall, P.: An empirical study of social networking behavior using diffusion of innovation theory. In: Conference on Information Systems Applied Research, Nashville Tennessee, USA (2010)Google Scholar
  4. 4.
    Folorunso, O., Vincent, R.O., Adekoya, A.F., Ogunde, O.: Diffusion of innovation in social networking sites among university students. International Journal of Computer Science and Security 4, 361 (2009)Google Scholar
  5. 5.
    Coursaris, C.K., Yun, Y., Sung, J.: Twitter Users vs. Quitters: A Uses and Gratifications and Diffusion of Innovations approach in understanding the role of mobility in microblogging. In: 2010 Ninth International Conference on Mobile Business and 2010 Ninth Global Mobility Roundtable, pp. 481–486. IEEE (2010)Google Scholar
  6. 6.
    Rogers, E.M.: Diffusion of innovations. Simon and Schuster, New York (1995)Google Scholar
  7. 7.
    Yi, M.Y., Jackson, J.D., Park, J.S., Probst, J.C.: Understanding information technology acceptance by individual professionals: Toward an integrative view. Information & Management 43, 350–363 (2006)CrossRefGoogle Scholar
  8. 8.
    Rogers, E.M., Shoemaker, F.F.: Communication of Innovations: A Cross-Cultural Approach. The Free Press, New York (1971)Google Scholar
  9. 9.
    Quan-Haase, A., Young, A.L.: Uses and gratifications of social media: A comparison of Facebook and Instant Messaging. Bulletin of Science, Technology & Society 30, 350–361 (2010)CrossRefGoogle Scholar
  10. 10.
    Feng, C.: Research on the Motivation and Behavior Patterns of Social Media Users and Brand Message Content Strategy. Industrial Engineering, vol. Master, p. 224. Tsinghua University, Beijing (2012)Google Scholar
  11. 11.
    Lindqvist, J., Cranshaw, J., Wiese, J., Hong, J., Zimmerman, J.: I’m the mayor of my house: examining why people use foursquare - a social-driven location sharing application. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 2409–2418. ACM, Vancouver (2011)Google Scholar
  12. 12.
    Anderson, R.E., Srinivasan, S.S.: E‐satisfaction and e‐loyalty: A contingency framework. Psychology & Marketing 20, 123–138 (2003)CrossRefGoogle Scholar
  13. 13.
    Gronholdt, L., Martensen, A., Kristensen, K.: The relationship between customer satisfaction and loyalty: cross-industry differences. Total Quality Management 11, 509–514 (2000)CrossRefGoogle Scholar
  14. 14.
    Chiou, J.S.: The antecedents of consumers’ loyalty toward Internet service providers. Information & Management 41, 685–695 (2004)CrossRefGoogle Scholar
  15. 15.
    Cyr, D., Head, M., Ivanov, A.: Perceived interactivity leading to e-loyalty: Development of a model for cognitive–affective user responses. International Journal of Human-Computer Studies 67, 850–869 (2009)CrossRefGoogle Scholar
  16. 16.
    Ribbink, D., Van Riel, A.C.R., Liljander, V., Streukens, S.: Comfort your online customer: quality, trust and loyalty on the internet. Managing Service Quality 14, 446–456 (2004)CrossRefGoogle Scholar
  17. 17.
    Flavián, C., Guinalíu, M., Gurrea, R.: The role played by perceived usability, satisfaction and consumer trust on website loyalty. Information & Management 43, 1–14 (2006)CrossRefGoogle Scholar
  18. 18.
    Lin, H.-H., Wang, Y.-S.: An examination of the determinants of customer loyalty in mobile commerce contexts. Information & Management 43, 271–282 (2006)CrossRefGoogle Scholar
  19. 19.
    Ee Hong, N., Kee-Young, K.: Examining the determinants of Mobile Internet service continuance: a customer relationship development perspective. International Journal of Mobile Communications 8, 210–229229 (2010)CrossRefGoogle Scholar
  20. 20.
    Zhou, T., Li, H., Liu, Y.: The effect of flow experience on mobile SNS users’ loyalty. Industrial Management & Data Systems 110, 930–946 (2010)CrossRefGoogle Scholar
  21. 21.
    Csikszentmihalyi, M.E., Csikszentmihalyi, I.S.E.: Optimal experience: Psychological studies of flow in consciousness. Cambridge University Press, Cambridge (1988)CrossRefGoogle Scholar
  22. 22.
    Qi, Y., Fu, C.: The Effects of Flow and Attachment on the e-Loyalty of SNS Websites. In: 2011 International Conference on Management and Service Science (MASS), pp. 1–6. IEEE (Year)Google Scholar
  23. 23.
    Hsu, C.-L., Chang, K.-C., Chen, M.-C.: The impact of website quality on customer satisfaction and purchase intention: perceived playfulness and perceived flow as mediators. Information Systems and E-Business Management 10, 549–570 (2012)CrossRefGoogle Scholar
  24. 24.
    Hsu, C.-L., Wu, C.-C., Chen, M.-C.: An empirical analysis of the antecedents of e-satisfaction and e-loyalty: focusing on the role of flow and its antecedents. Information Systems and E-Business Management, 1–25 (2012)Google Scholar
  25. 25.
    Fuentes-Blasco, M., Saura, I.G., Berenguer-Contrí, G., Moliner-Velázquez, B.: Measuring the antecedents of e-loyalty and the effect of switching costs on website. The Service Industries Journal 30, 1837–1852 (2010)CrossRefGoogle Scholar
  26. 26.
    Yang, Z., Peterson, R.T.: Customer perceived value, satisfaction, and loyalty: The role of switching costs. Psychology & Marketing 21, 799–822 (2004)CrossRefGoogle Scholar
  27. 27.
    Aydin, S., Özer, G., Arasil, Ö.: Customer loyalty and the effect of switching costs as a moderator variable: A case in the Turkish mobile phone market. Marketing Intelligence & Planning 23, 89–103 (2005)CrossRefGoogle Scholar
  28. 28.
    Deng, Z., Lu, Y., Wei, K.K., Zhang, J.: Understanding customer satisfaction and loyalty: An empirical study of mobile instant messages in China. International Journal of Information Management 30, 289–300 (2010)CrossRefGoogle Scholar
  29. 29.
    Min, D., Wan, L.: Switching factors of mobile customers in Korea. Journal of Service Science 1, 105–120 (2009)CrossRefGoogle Scholar
  30. 30.
    Raacke, J., Bonds-Raacke, J.: MySpace and Facebook: Applying the uses and gratifications theory to exploring friend-networking sites. CyberPsychology & Behavior 11, 169–174 (2008)CrossRefGoogle Scholar
  31. 31.
    Ostlund, L.E.: The role of product perceptions in innovative behavior. In: Fall Conference of American Marketing Association, pp. 259–266 (Year)Google Scholar
  32. 32.
    Schmitz, J., Fulk, J.: Organizational Colleagues, Media Richness, and Electronic Mail A Test of the Social Influence Model of Technology Use. Communication Research 18, 487–523 (1991)CrossRefGoogle Scholar
  33. 33.
    Wang, Z., Tchernev, J.M., Solloway, T.: A dynamic longitudinal examination of social media use, needs, and gratifications among college students. Computers in Human Behavior 28, 1829–1839 (2012)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Yubo Zhang
    • 1
  • Pei-Luen Patrick Rau
    • 1
  1. 1.Institute of Human Factors and ErgonomicsTsinghua UniversityBeijingChina

Personalised recommendations