IT innovation adoption in the government sector: identifying the critical success factors

This paper aims to acquire underlying knowledge of how IT is adopted in private sector organisations and further explore what factors impact its adoption (optimistically and pessimistically).

An interpretive and qualitative multiple case study approach was selected to test and validate the conceptual model empirically. The selection of the interpretivism viewpoint in the context of this research is to understand how government organisations adopt new technologies and support their decisions and actions. The interpretive research methodology is related to data gathering and generating solid descriptions and interpretations and further allows theory building. Through a multiple case study strategy, factors influencing EAI adoption in the government sector are investigated. In doing so, various data collection methods such as interviews, documentation, and observation are adopted.

The author identified 42 critical success factors (CSF) for IT innovation adoption. These factors provide sufficient understanding of their importance when adopting an innovation (technology). The author exploits these factors further when developing a conceptual EAI adoption model and also presents a taxonomy of the IT innovation adoption process. This taxonomy is an eight‐stage adoption process based on studying 11 IT adoption models. Simply acquiring or adopting a technology is not sufficient – in order to obtain the anticipated benefits, IT must be deployed and used appropriately by the organisation and its intended users. However, this taxonomy would further assist in identifying factors affecting IT innovation adoption at each stage of the adoption process.

The proposed conceptual IT innovation adoption model is a contribution to theory. This model presents a detailed list of factors that impact IT adoption in government sector organisations. The author conjectures that each factor within this model signifies its importance and must be considered by organisations while adopting innovation (technology). The taxonomy of the IT innovation adoption process is another contribution. This taxonomy is developed by studying 11 IT adoption models as presented in this paper. This taxonomy identifies the pre‐adoption and post‐adoption stages of an adoption process. Further in this taxonomy, the author identifies stages where the organisation is impacted, i.e. the pre‐adoption stage and post‐adoption, where individual adopters are impacted.