Skip to main content

Advertisement

SpringerLink
Log in

Individual adoption of convergent mobile phone in Italy

  • Original Paper
  • Published:
Review of Managerial Science Aims and scope Submit manuscript

Abstract

The present study integrates the technology acceptance and convergence streams of research to develop and test a model of individual adoption of convergent mobile technologies. Adopting structural equation modelling, we hypothesize that relative advantage, effort expectancy, social influence and facilitating conditions affect directly individual attitude and, indirectly the intention to use convergent mobile technologies. The model explains a highly significant 53.2% of the variance for individual attitude, while individual attitude accounts for 33.9% of the variance in behavioral intention.

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

  • Agarwal R (2000) Individual acceptance of information technologies. In: Zmud RW (ed) Framing the domains of it management: projecting the future from the past. Pinnaflex Educational Resources, Cincinnati, pp 85–104

    Google Scholar 

  • 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 

  • Ahuja MK, Thatcher JB (2005) Moving beyond intentions and toward the theory of trying: effects of work environment and gender on post-adoption information technology use. MIS Q 29(3):427–459

    Google Scholar 

  • Ajzen I (2001) Nature and operation of attitudes. Annu Rev Psychol 52:27–58

    Article  Google Scholar 

  • Benbasat I, Zmud R (2003) The identity crisis within the is discipline: defining and communicating the discipline’s core properties. MIS Q 27(2):183–194

    Google Scholar 

  • Briggs A, Burke P (2000) A social history of the media. From Gutemberg to the internet. Blackwell Publishers, Oxford

    Google Scholar 

  • Brown SA, Venkatesh V (2005) Model of adoption of technology in households: a baseline model test and extension incorporating household life cycle. MIS Q 29(3):399–426

    Google Scholar 

  • Burkhardt ME, Brass DJ (1990) Changing patterns or patterns of change: the effects of a change in technology on social network structure and power. Adm Sci Q 35(1):104–128

    Article  Google Scholar 

  • Castells M (1996) The rise of the network society. Blackwell Publishers, Oxford

    Google Scholar 

  • Chin W (1998) Issues and opinions on structural equation modeling. MIS Q 22(1):7–10

    Google Scholar 

  • Chon BS, Choi JH, Barnett GA, Danowski JA, Joo S (2003) A structural analysis of media convergence: cross-industry mergers and acquisitions in the information industries. J Media Econ 16(3):141–157

    Article  Google Scholar 

  • Constantiou ID, Damsgaard J, Knutsen L (2007) The four incremental steps toward advanced mobile service adoption. Commun ACM 50(6):51–55

    Article  Google Scholar 

  • Creusen MEH, Schoormans JPL (2005) The different roles of product appearance in consumer choice. J Prod Innova Manage 22(1):63–81

    Article  Google Scholar 

  • Danowski JA, Choi JH (1998) Convergence in the information industries. Telecommunications, broadcasting and data processing 1981–1996. In: Sawhney H, Barnett GA (eds) Progress in communication sciences, vol 15. Ablex, Stamford, CT, pp 125–150

    Google Scholar 

  • Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 13(3):318–340

    Article  Google Scholar 

  • Fang X, Chan S, Brzezinski J, Xu S (2005) Moderating effects of task type on wireless technology acceptance. J Manage Inf Syst 22(3):123–157

    Google Scholar 

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

    Google Scholar 

  • Fornell C, Bookstein F (1982) Two structural equation models: Lisrel and pls applied to consumer exit-voice theory. J Market Res 19(3):440–452

    Article  Google Scholar 

  • Fortunati L (2002) Italy: stereotypes, true and false. In: Katz James E, Aakhus Mark A (eds) Perpetual contact. Mobile communication, private talk, public performance. Cambridge University Press, Cambridge, pp 42–62

    Google Scholar 

  • Fulk J (1993) Social construction of communication technology. Acad Manage J 36(5):921–951

    Article  Google Scholar 

  • Gallivan M, Srite M (2005) Information technology and culture: identifying fragmentary and holistic perspectives of culture. Inf Organ 15(4):295–338

    Article  Google Scholar 

  • Gallivan MJ, Spitler VK, Koufaris M (2005) Does information technology training really matter? A social information processing analysis of coworkers’ influence on IT usage in the workplace. J Manage Inf Syst 22(1):153–192

    Google Scholar 

  • Ghorpade J, Hattrup K, Lackritz JR (1999) The use of personality measures in cross-cultural research: a test of three personality scales across two countries. J Appl Psychol 84(5):670–679

    Article  Google Scholar 

  • Greenstein S, Khanna T (1997) What does industry convergence mean? In: Yoffie DB (ed) Competing in the age of digital convergence. Harvard Business School Press, Boston, MA

    Google Scholar 

  • Hennington AH, Janz BD (2007) Information systems and healthcare: physician adoption of electronic medical records: applying the Utaut model in a healthcare context. Commun AIS Issue 19:60–80

    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 Q 23(2):183–213

    Article  Google Scholar 

  • Karahanna E, Ahuja M, Srite M, Galvin J (2002) Individual differences and relative advantage: the case of GSS. Decisi Support Syst 32(4):327–341

    Article  Google Scholar 

  • Karahanna E, Agarwal R, Angst C (2006) Reconceptualizing compatibility beliefs in technology acceptance research. MIS Q 30(4):781–804

    Google Scholar 

  • Ko D-G, Kirsch LJ, King WR (2005) Antecedents of knowledge transfer from consultants to clients in enterprise system implementations. MIS Q 29(1):59–85

    Google Scholar 

  • Kraut R, Mukhopadhyay T, Szczypula J, Kiesler S, Scherlis B (1999) Information and communication: alternative uses of the internet in households. Inf Syst Res 10(4):287–303

    Article  Google Scholar 

  • Lee A, Baskerville RL (2003) Generalizing generalizability in information systems research. Inf Syst Res 14(3):221–243

    Article  Google Scholar 

  • Levitt B, March JG (1988) Organizational learning. Ann Rev Soc 14:319–338

    Article  Google Scholar 

  • 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 

  • Magni M, Pennarola F (2008) Intra-organizational relationships and technology acceptance. Int J Inf Man 28(6):517–523

    Google Scholar 

  • Moore GC, Benbasat I (1991) Development of an instrument to measure the perceptions of adopting an information technology innovation. Inf Syst Res 2(3):192

    Article  Google Scholar 

  • Morris MG, Venkatesh V (2000) Age differences in technology adoption decisions: implications for a changing work force. Pers Psychol 53(2):375–403

    Article  Google Scholar 

  • Nambisan S, Agarwal R, Tanniru M (1999) Organizational mechanisms for enhancing user innovation in information technology. MIS Q 23(3):365–395

    Article  Google Scholar 

  • Orlikowski W (1992) The duality of technology: rethinking the concept of technology in organizations. Organ Sci 3(3):398–427

    Article  Google Scholar 

  • Orlikowski W, Iacono CS (2000) The truth is not out there: an enacted view of the “digital economy”. In: Brynjolfsson E, Kahin B (eds) Understanding the digital economy: data, tools, and research. The MIT Press, Cambridge, MA

    Google Scholar 

  • Orlikowski WJ, Iacono CS (2001) Research commentary: desperately seeking the “it” in it research-a call to theorizing the IT artifact. Inf Syst Res 12(2):121–134

    Article  Google Scholar 

  • Rogers EM (2003) Diffusion of innovations, fifth edn. The Free Press, New York

    Google Scholar 

  • Salancik GR, Pfeffer J (1978) A social information approach to job attitudes and task design. Adm Sci Q 23:224–252

    Article  Google Scholar 

  • Stone A (1989) Wrong number: the breakup of AT&T. Basic Books, New York

    Google Scholar 

  • Suprateek S, Wells JD (2003) Understanding mobile handheld device use and adoption. Commun ACM 46(12):35–40

    Article  Google Scholar 

  • Taylor S, Todd PA (1995) Assessing IT usage: the role of prior experience. MIS Q 19(4):561–570

    Article  Google Scholar 

  • Tornatzky LG, Klein KJ (1982) Innovation characteristics and innovation adoption implementation: a meta-analysis of findings. IEEE Trans Eng Manage 29(1):28–44

    Google Scholar 

  • van de Vijver F, Leung K (1997) Methods and data analysis for cross-cultural research. Sage Publications, Thousand Oaks, CA

    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, Morris MG (2000) Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Q 24(1):115–139

    Article  Google Scholar 

  • Venkatesh V, Ramesh V (2006) Web and wireless site usability: understanding differences and modeling use. MIS Q 30(1):181–206

    Google Scholar 

  • Venkatesh V, Morris MG, Davis GB, Davis FD (2003) User acceptance of information technology: toward a unified view. MIS Q 27(3):425–478

    Google Scholar 

  • Wejnert B (2002) Integrating models of diffusion of innovations: a conceptual framework. Ann Rev Soc 28:297–326

    Article  Google Scholar 

  • Yoffie DB (1996) Competing in the age of digital convergence. Calif Manag Rev 38(4):31–54

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Management, Institute of Organization and Information Systems, Bocconi University, Via Rontgen, 1, 20136, Milan, Italy

    Stefano Basaglia, Leonardo Caporarello, Massimo Magni & Ferdinando Pennarola

  2. Department of Business Administration, Faculty of Economics and Business Administration, University of Bergamo, Via dei Caniana 2, 24127, Bergamo, Italy

    Stefano Basaglia

Authors
  1. Stefano Basaglia
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Leonardo Caporarello
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Massimo Magni
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ferdinando Pennarola
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Leonardo Caporarello.

Additional information

Authors are listed alphabetically.

Appendix

Appendix

Table 4 Constructs and items
Full size table

Rights and permissions

Reprints and permissions

About this article

Cite this article

Basaglia, S., Caporarello, L., Magni, M. et al. Individual adoption of convergent mobile phone in Italy. Rev Manag Sci 3, 1–18 (2009). https://doi.org/10.1007/s11846-009-0025-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11846-009-0025-6

Keywords

JEL Classification

Search

Navigation