FAHP-TOPSIS model in ranking critical success factors of e-learning: A comparative analysis of normalization methods

Abstract

The teaching and learning process has become effective and explicit due to the progressive development of e-learning. This has significantly transformed the education framework. As a result, evaluating the usefulness of e-learning requires a detailed understanding of the critical success factors that impact the success of e-learning environments. This study ranked these factors using Multi-Criteria Decision-Making techniques. Specifically, the Fuzzy Analytical Hierarchy Process was used to determine the weight of each factor, while the Technique for Order of Preference by Similarity to Ideal Solution was used to rank the factors of e-learning. The study also examined and compared four normalization methods commonly applicable in the Technique for Order of Preference by Similarity to Ideal Solution. The results showed Vector, Max and Sum normalization methods produced highly consistent rankings which differ from the ranking produced by the Max-Min method. This finding is significant as it indicates the choice of normalization technique can influence the final ranking of factors.