| Timely availability of high quality and reliable software is critical to successful use of information systems (IS). Unfortunately, software produced is typically late, over budget, and of poor quality. Computer-aided software engineering (CASE) has potential to improve productivity, cut cost, and eliminate quality problems of software development. However, contrary to the predictions of the existing theory of innovation diffusion, organizations are slow to adopt and implement it.; An inadequate conceptual and theoretical foundation of organizational innovation diffusion theory is a major cause for its inability to explain slow diffusion of CASE. Diffusion of innovations has been studied primarily using communications perspective, which has not been successful in explaining the organizational diffusion of complex information technology (IT) innovations, including CASE, CAD, CAM, and others. These technologies are characterized by high user interdependencies and knowledge barriers. Knowledge burden aspect suggests that complex IT innovations cannot be adopted as "black box" solutions but rather impose a substantial knowledge burden on potential adopters. Know-how to use such innovations has to be developed in situ and de novo, which requires both individual learning, and organizational learning.; This study identifies the gaps in the IS literature on the organizational diffusion of IT innovations and models IT diffusion in organizations by integrating communications and organizational learning perspectives. It develops measures for many new constructs, refines measures for some old constructs, and using a survey methodology empirically identifies factors that significantly relate to the diffusion of CASE technology.; The results of this study show that size of IS department (ISD), organizational size, proportion of development project in ISDI and perceived capability of CASE are important variables in differentiating "adopters" and "non-adopters." The results also show that the level of adoption of CASE is significantly related to ISD size, organizational size, perceived technological characteristics of CASE (capability, efficiency, and stability), and organizational learning variables (turnover of technical IS personnel, environmental scanning, job/role rotation, and media richness of communication channels). The level of infusion is primarily related to organizational learning variables (turnover of technical IS personnel, job/role rotation, and media richness of communication channels). |
