Organizations are increasingly adopting social communication technologies (SCT) such as private social-networking sites and social software to enable their members to interact, share information and collaborate. The problem addressed in this study is the limited understanding of reasons of slow SCT adoption for internal communication in comparison to the external diffusion of these technologies. The purpose of this study is to discover social software adoption factors and analyze whether some of them have a significant impact on the SCT adoption rates in organizations. The theoretical foundation for this research is based on a few theories, including the diffusion of innovations (Rogers, 1962, 1983, 2003) and technology-organization-environment framework (Tornatzky, Fleischer & Chakrabarti, 1990). The study uses the concurrent mixed methods design, applies a set of qualitative (digital ethnography) and quantitative (structured survey) instruments, statistical methods (correlation, regression, and content and interpretive analysis). Data was collected from representatives of various types of organizations that employ social software or social intranet.

As a result of the content analysis and interpretive phenomenological examination of data, the author offers the classification of factors encountered by practitioners during the process of social software adoption in organizations. The suggested classification is not a social software adoption model or a comprehensive hierarchy of all factors, but just a necessary step in creating of such model.

As a result of quantitative analysis of data, which included correlation and regression analyses, the researcher has established that some of the factors have little impact on adoption rates (industry with rho = 0.132, p. = . 451 ) or low level of correlation with adoption rates (symmetrical communication structure with rho = - 0.309, p. = 0.071). Other factors should be added to the SCT adoption model to serve as predictors of how fast employees will adopt social software inside the organization. Among them are: organizational structure (rho =0.584), asymmetrical communication structure (rho = 0.517, p. = .001) and organizational size (rho = 0.412, p. = .001). In addition, the author made meta-inferences that utilized two techniques for triangulation, by bringing together data from qualitative and quantitative components of the study.