1. ¹Management Information Systems, College of Business Administration, University of Central Florida, Orlando, FL, U.S.A.
2. ²Department of Accounting and Information Systems, School of Business, University of Kansas, Lawrence, KS, U.S.A.
3. ³Management Information Systems, College of Business, Ohio University, Athens, OH, U.S.A.
4. ⁴Fogelman College of Business and Economics, The University of Memphis, Memphis, TN, U.S.A.

Correspondence: Craig Van Slyke, Management Information Systems, College of Business Administration, University of Central Florida, PO Box 161400, BA1-325F, Orlando, FL 32816-1400, U.S.A. Tel: +1 407-823-4149; Fax: +1 407-823-2389; E-mail: cvanslyke@bus.ucf.edu

Received 21 January 2005; Revised 23 September 2005; Re-revised 27 June 2006; Re-revised 13 February 2007; Accepted 30 March 2007.

Abstract

Computer-based communication technologies are increasingly important to personal and organizational communication. One important factor related to the adoption and diffusion of communication innovations is critical mass. Critical mass influences the adoption and diffusion of interactive communication innovations, both through network externalities and through sustainability of the innovation. Unfortunately, critical mass is difficult to measure and is typically only demonstrable after the critical mass point has been reached. Potential adopters' perceptions of critical mass also may be important to adoption decisions. In this paper, we extend this thinking using a synthesis of the Theory of Reasoned Action and Diffusion of Innovation theory by developing a research model. The model is empirically tested using survey data that are analyzed using partial least squares. The focal innovation is instant messaging. Results indicate that perceived critical mass influences use intentions directly and through perceptions of the characteristics of the innovation. The perceived innovation characteristics impact attitude toward use, which in turn impacts use intentions. The model predicts a sizable and significant portion of both attitudes and use intentions. Further, perceived critical mass is able to explain a significant portion of the variance in each perceived innovation characteristic. Implications for research and practice are discussed.