A TETRAD-based approach for theory development in information systems research

Abstract

Theory development and theory testing are two primary processes in social science research. Statistical methods and tools are used in various stages of these processes. Information systems researchers have employed many statistical methods and tools for theory testing. However, very few statistical approaches are known to help researchers with theory development. In this paper, we introduce TETRAD as a powerful approach to aid researchers in developing and discovering new theoretical relationships. We illustrate the TETRAD approach by re-analyzing data from two articles published in premier information systems journals. The results from the previous examples demonstrate that TETRAD is a useful tool for uncovering potential theoretical relationships, especially when prior knowledge of underlying theory bases is lacking. We demonstrate that TETRAD is an effective and powerful statistical tool that can assist researchers in the iterative process of theory development.