Time is an important factor in the use of information technology. However, traditional information systems research methods cannot adequately account for the dynamic nature of time-based relationships often found in longitudinal data. This shortcoming is problematic when investigating volatile relationships that evolve over time (e.g., information technology use across users, departments, and organizations). Educational, sociological, and management researchers study the influence of time using a rigorous multilevel method called growth modeling. We demonstrate the use of growth modeling in this tutorial, which is based on a semester-long study of an actual web-based university-level course content delivery system. The tutorial provides guidance on preliminary data tests, the construction and analysis of growth models using hierarchical linear modeling, and the interpretation of final results. The tutorial also describes other unique advantages of using growth modeling for IS research.
Otondo, Robert F.; Barnett, Tim; Kellermanns, Franz W.; Pearson, Allison W.; and Pearson, Rodney A.
"Assessing Information Technology Use over Time with Growth Modeling and Hierarchical Linear Modeling: A Tutorial,"
Communications of the Association for Information Systems:
Vol. 25, Article 45.
Available at: http://aisel.aisnet.org/cais/vol25/iss1/45