Skip to main content
SpringerLink
Log in

Understanding individual adoption of mobile instant messaging: a multiple perspectives approach

  • Published:
Information Technology and Management Aims and scope Submit manuscript

Abstract

Use of mobile instant messaging has grown tremendously in the last few years, and is positioned as a platform for mobile business. This study aims to explore how an individual’s intention to use mobile instant messaging is influenced by technical and individual characteristics as well as social influence factors. A research model based on perceived usefulness and perceived enjoyment, including technical characteristics (ease of use and convenience), individual characteristics (computer playfulness and personal innovativeness), and social influence factors (perceived critical mass and identification) was developed. The model was empirically analyzed using structural equation modeling with data from mobile instant messaging service users in Korea. The results indicate that most of the proposed technical characteristics, individual characteristics, and social influence factors have impacts on perceived usefulness and/or perceived enjoyment, which form the intention to use mobile instant messaging. Our findings provide strategic guidelines for service providers with respect to the development and operations of mobile instant messaging.

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

Similar content being viewed by others

References

  1. Agarwal R, Prasad J (1998) A conceptual and operational definition of personal innovativeness in the domain of information technology. Inf Syst Res 9(2):204–215

    Article  Google Scholar 

  2. Agarwal R, Karahanna E (2000) Time flies when you’re having fun: cognitive absorption and beliefs about information technology usage. MIS Q 24(4):665–694

    Article  Google Scholar 

  3. Associated Press (2014) WhatsApp: a $19 billion bet for Facebook. Retrieved on May 1, 2014 fromhttp://news.yahoo.com/whatsapp-19-billion-bet-facebook-053029423--finance.html

  4. Bagozzi RP, Yi Y (1988) On the evaluation of structural equation models. J Acad Mark Sci 16(1):74–94

    Article  Google Scholar 

  5. Baron RM, Kenny DA (1986) The moderator–mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol 51(6):1173–1182

    Article  Google Scholar 

  6. Brown SA, Dennis AR, Venkatesh V (2010) Predicting collaboration technology use: integrating technology adoption and collaboration research. J MIS 27(2):9–54

    Google Scholar 

  7. Chin WW (1998) Issues and opinion on structural equation modeling. MIS Q 22(1):vii–xvi

    Google Scholar 

  8. Chiu CM, Hsu M, Wang ETG (2006) Understanding knowledge sharing in virtual communities: an integration of social capital and social cognitive theories. Decis Support Syst 42(3):1872–1888

    Article  Google Scholar 

  9. Csikszentmihalyi M (1975) Beyond boredom and anxiety. Jossey-Bass, San Francisco

    Google Scholar 

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

    Article  Google Scholar 

  11. Davis FD, Bagozzi RP, Warshaw PR (1992) Extrinsic and intrinsic motivation to use computers in the workplace. J Appl Soc Psychol 22(4):1111–1132

    Article  Google Scholar 

  12. DeLone WH, McLean ER (1992) Information system success: the quest for the dependent variable. Inf Syst Res 3(1):60–95

    Article  Google Scholar 

  13. Deng Z, Lu Y, Wei KK, Zhang J (2010) Understanding customer satisfaction and loyalty: an empirical study of mobile instant messages in China. Int J Inf Manag 30(4):289–300

    Article  Google Scholar 

  14. Doll WJ, Torkzadeh G (1988) The measurement of end-user computing satisfaction. MIS Q 12(2):259–274

    Article  Google Scholar 

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

    Google Scholar 

  16. Finneran CM, Zhang P (2005) Flow in computer-mediated environments: promises and challenges. Commun AIS 15(4):82–101

    Google Scholar 

  17. 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 

  18. Gefen D, Straub DW (2005) A practical guide to factorial validity using PLS graph: tutorial and annotated example. Commun AIS 16(5):91–109

    Google Scholar 

  19. Glass R, Li S (2010) Social influence and instant messaging adoption. J Comput Inf Syst 51(2):24–30

    Google Scholar 

  20. Ha I, Yoon Y, Choi M (2007) Determinants of adoption of mobile games under mobile broadband wireless access environment. Inf Manag 44(3):276–286

    Article  Google Scholar 

  21. Kelman HC (1958) Compliance, identification and internalization: three processes of attitude change. J Confl Resolut 2(1):51–60

    Article  Google Scholar 

  22. Korea Internet and Security Agency (KISA) (2012) 2012 Survey on the Internet usage. Retrieved on September 22, 2013 from http://isis.kisa.or.kr/eng/board/?pageId=040100&bbsId=10&itemId=323

  23. Lewis W, Agarwal R, Sambamurthy V (2003) Sources of influence on beliefs about information technology use: an empirical study of knowledge workers. MIS Q 27(4):657–678

    Google Scholar 

  24. Li D, Chau PYK, Lou H (2005) Understanding individual adoption of instant messaging: an empirical investigation. J AIS 6(4):102–129

    Google Scholar 

  25. Li D, Chau PYK, Van Slyke C (2010) A comparative study of individual acceptance of instant messaging in the US and China: a structural equation modeling approach. Commun AIS 26(5):85–106

    Google Scholar 

  26. Liao Z, Cheung MT (2002) Internet-based E-Banking and consumer attitudes: an empirical study. Inf Manag 39(4):283–295

    Article  Google Scholar 

  27. Lin KY, Lu HP (2011) Why people use social networking sites: an empirical study integrating network externalities and motivation theory. Comput Hum Behav 27(3):1152–1161

    Article  Google Scholar 

  28. Lou H, Luo W, Strong D (2000) Perceived critical mass effect on groupware acceptance. Eur J Inf Syst 9(2):91–103

    Article  Google Scholar 

  29. Lu J, Yao JE, Yu C (2005) Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. J Strateg Inf Syst 14(3):245–268

    Article  Google Scholar 

  30. Lu Y, Zhou T, Wang B (2008) Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Comput Hum Behav 6(2):29–39

    Google Scholar 

  31. Markus ML (1987) Toward a ‘critical mass’ theory of interactive media: universal access, interdependence and diffusion. Commun Res 14(5):491–511

    Article  Google Scholar 

  32. McGlaun S (2014) WhatsApp handles 50 billion messages daily, more than SMS delivery. SlashGear. [Online]. http://www.slashgear.com/whatsapp-handles-50-billion-messages-daily-more-than-sms-delivery-21313892/. Accessed 07 June 2014

  33. Moon JW, Kim YG (2001) Extending the TAM for a World-Wide-Web context. Inf Manag 38(4):217–230

    Article  Google Scholar 

  34. Nahapiet J, Ghoshal S (1998) Social capital, intellectual capital, and the organizational advantage. Acad Manag Rev 23(2):242–266

    Google Scholar 

  35. Olanoff D (2012) WhatsApp hits new daily record. The next Web. [Online]. http://thenextweb.com/apps/2012/08/23/whatsapp-hits-new-record-10-billion-total-messages-one-day/. Accessed 07 June 2014

  36. Olanoff D (2011) WhatsApp users now send over one billion messages a day. The next Web. [Online]. http://thenextweb.com/apps/2011/10/31/whatsapp-users-now-send-over-one-billion-messages-a-day/. Accessed 07 June 2014

  37. Palen L (1999) Social, individual and technological issues for groupware calendar systems. In: Proceedings of the 1999 CHI conference on human factors in computing systems. ACM Press, Pittsburgh, pp 17–24

  38. Pavlou PA, Liang H, Xue Y (2007) Understanding and mitigating uncertainty in online exchange relationships: a principal–agent perspective. MIS Q 31(1):105–136

    Google Scholar 

  39. Podsakoff PM, MacKenzie SB, Lee J-Y, Podsakoff NP (2003) Common method bias in behavioral research: a critical review of the literature and recommended remedies. J Appl Psychol 88(5):879–903

    Article  Google Scholar 

  40. Premkumar G, Rammurthy K, Liu H (2008) Internet messaging: an examination of the impact of attitudinal, normative and control belief systems. Inf Manag 45(7):451–457

    Article  Google Scholar 

  41. Rowlands S (2014) Instant messaging to account for 75% of mobile messaging traffic by 2018, but only generate 2% of revenues. Juniper Res

  42. Sun H, Zhang P (2006) Causal relationships between perceived enjoyment and perceived ease of use: an alternative approach. J AIS 7(9):618–645

    Google Scholar 

  43. Sun H, Zhang P (2008) An exploration of affect factors and their role in user technology acceptance: mediation and causality. J Am Soc Inf Sci Technol 59(8):1252–1263

    Article  Google Scholar 

  44. Van der Heijden H (2004) User acceptance of hedonic information systems. MIS Q 28(4):695–704

    Google Scholar 

  45. Van Slyke C, Ilie V, Stafford T (2007) Perceived critical mass and the adoption of a communication technology. Eur J Inf Syst 16(3):270–283

    Article  Google Scholar 

  46. 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 

  47. Webster J, Martocchio JJ (1992) Microcomputer playfulness: development of a measure with workplace implications. MIS Q 16(2):201–226

    Article  Google Scholar 

  48. Yi MY, Jackson JD, Park JS, Probst JC (2006) Understanding information technology acceptance by individual professionals? Toward an integrative view. Inf Manag 43(3):350–363

    Article  Google Scholar 

  49. Yoon C (2010) Antecedents of customer satisfaction with online banking in China: the effects of experience. Comput Hum Behav 26(6):1296–1304

    Article  Google Scholar 

  50. Yoon C, Kim S (2007) Convenience and TAM in a ubiquitous computing environment: the case of wireless LAN. Electron Commer Res Appl 6(1):102–112

    Article  Google Scholar 

  51. Yoon C, Wang Z (2011) The role of citizenship behaviors and social capital in virtual communities. J Comput Inf Syst 52(1):106–115

  52. Zaman M, Ananda Rajan MA, Dai Q (2010) Experiencing flow with instant messaging and its facilitating role on creative behaviors. Comput Hum Behav 26(5):1009–1018

    Article  Google Scholar 

  53. Zhou T, Lu Y (2011) Examining mobile instant messaging user loyalty from the perspectives of network externalities and flow experience. Comput Hum Behav 27(2):883–889

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Business Administration, Mokpo National University, 61 Dorim-ri, Chungkye-myun, Muan-gun, Chonnam, 534-729, Korea

    Cheolho Yoon & Changyun Jeong

  2. School of Engineering, University of California, Merced, Merced, CA, USA

    Erik Rolland

Authors
  1. Cheolho Yoon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Changyun Jeong
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Erik Rolland
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Cheolho Yoon.

Appendix

Appendix

1.1 Perceived usefulness: Likert scale ranging from strongly disagree to strongly agree

PU1:

Using KakaoTalk enables me to communicate with others more effectively.

PU2:

Using KakaoTalk improves my efficiency in sharing information and connecting with others.

PU3:

KakaoTalk is a useful service for interaction with others.

PU4:

Overall, KakaoTalk is useful to me.

1.2 Perceived enjoyment: Likert scale ranging from strongly disagree to strongly agree

PE1:

Using KakaoTalk is enjoyable.

PE2:

Using KakaoTalk is pleasurable.

PE3:

I have fun using KakaoTalk.

1.3 Behavioral intention: Likert scale ranging from strongly disagree to strongly agree

BI1:

I plan to use KakaoTalk in the future.

BI2:

I intend to continue using KakaoTalk in the future.

BI3:

I expect my use of KakaoTalk to continue in the future.

1.4 Ease of use: Likert scale ranging from strongly disagree to strongly agree

EOU1:

Learning to operate KakaoTalk is easy.

EOU2:

It is easy for me to become skillful at using KakaoTalk.

EOU3:

It is easy to use KakaoTalk to communicate with others.

EOU4:

Overall, KakaoTalk is easy to use.

1.5 Convenience: Likert scale ranging from strongly disagree to strongly agree

CV1:

Using KakaoTalk enables me to communicate with others at a time that is convenient for me.

CV2:

Using KakaoTalk enables me to communicate with others anyplace.

CV3:

Using KakaoTalk gives me convenience in communicating with others.

CV4:

I find KakaoTalk convenient for interacting with others.

1.6 Computer playfulness: Likert scale ranging from strongly disagree to strongly agree

CF1 :

When using KakaoTalk I am spontaneous. (dropped).

CF2 :

When using KakaoTalk I am unimaginative.* (dropped).

CF3:

When using KakaoTalk I am flexible.

CF4:

When using KakaoTalk I am creative.

CF5:

When using KakaoTalk I am playful.

CF6 :

When using KakaoTalk I am unoriginal.* (dropped).

CF7 :

When using KakaoTalk I am uninventive.* (dropped).

1.7 Personal innovativeness: Likert scale ranging from strongly disagree to strongly agree

PI1:

If I heard about a new information technology, I would look for ways to experiment with it.

PI2 :

In general, I am hesitant to try out new information technologies.* (dropped).

PI3:

Among my peers, I am usually the first to try out new information technologies.

PI4:

I like to experiment with new information technologies.

1.8 Perceived critical mass: Likert scale ranging from strongly disagree to strongly agree

PCM1:

Many friends use KakaoTalk.

PCM2:

Of the people I communicate with regularly, many use KakaoTalk.

PCM3:

A large percentage of the people I communicate with use KakaoTalk.

PCM4:

In my community, I see many people using KakaoTalk.

1.9 Identification: Likert scale ranging from strongly disagree to strongly agree

ID1:

I feel a sense of kinship with people with whom I frequently communicate using KakaoTalk.

ID2:

I have a feeling of togetherness or closeness with people with whom I frequently communicate using KakaoTalk.

ID3:

There is a close identity between me and the people with whom I interact using KakaoTalk.

ID4:

When I use KakaoTalk, I sometimes identify with people.

Note: * Reversed scale.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yoon, C., Jeong, C. & Rolland, E. Understanding individual adoption of mobile instant messaging: a multiple perspectives approach. Inf Technol Manag 16, 139–151 (2015). https://doi.org/10.1007/s10799-014-0202-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10799-014-0202-4

Keywords

Search

Navigation