Using Confirmatory Factor Analysis (CFA) As a Tool to Improve the Assessment of Digital Government: The Case of the Mexican State Portals Ranking

There are different measurements and rankings in the literature that evaluate critical factors for a successful adoption of digital government. Each of these frameworks applies diverse variables and approaches to assessing digital government success. However, the nature of digital government success is complex and implies multiple dimensions that make it difficult to evaluate in practice. There is the need to build more robust approaches to improve these assessments to explore the multiple dimensions of digital government success. Some authors have proposed factor analysis techniques as a useful tool for this task. Using a well-known ranking of state government portals in Mexico during the period 2009-2015, this study conducted a confirmatory factor analysis to evaluate the dimensions of this instrument, which includes 132 items. This ranking could be considered a typical tool for measuring and assessing digital government, similar to the ones used in many countries and by some international organizations. The purpose of this study is to extend our understanding of the multiple dimensions of digital government success and to provide guidance for improving and refining existing techniques for measuring and assessing digital government. The results ratify most of the original dimensions, but allows reducing the number of questions and obtain more robust estimations. Based on the analysis, we provide a set of practical recommendations for improving measurement methodologies and for the assessment of digital government.

Puron-Cid, G., Gil-Garcia, J. R., Luna-Reyes, D. E., Luna-Reyes, L. F., Picazo-Vela, S., & Sandoval-Almazan, R. (2017). Using Confirmatory Factor Analysis (CFA) As a Tool to Improve the Assessment of Digital Government: The Case of the Mexican State Portals Ranking. In Proceedings of the 18th Annual International Conference on Digital Government Research (pp. 289–299). New York, NY, USA: ACM. https://doi.org/10.1145/3085228.3085290