| A problem of growing importance for firms and organizations is the increasing complexity of the information systems and technology (IS&T) landscape. There is a lack of tools, models, and methodologies for analyzing relationships among information technologies and trends in technological change. This dissertation presents three essays which address this gap in research. The first essay presents a theory-based conceptual framework and a methodology for modeling the IS&T landscape as an ecosystem and identifying path-dependent relationships among technologies. The second essay presents time-series analyses of IS&T innovations. This essay provides a test of the theoretical constructs proposed in Essay 1 and a predictive model of the interactions among innovations in IS&T components, products, and infrastructure. The third essay presents a new clustering-based methodology, and an overview of the corresponding software tool, for identifying and visualizing patterns and trends of technological change within an IS&T ecosystem. The methodology proposed in Essay 3 can also be applied for identifying and visualizing trends in general multidimensional temporal data. Together, these essays comprise a new set of tools designed to help practitioners and researchers analyze relationships among information technologies, reduce the complexity of the IS&T landscape, and help firms make better IS&T investment decisions. |
