Principal Component Analysis on Morphological Variability of Critical Success Factors for Enterprise Resource Planning

The concept of critical success factors (CSFs) has been widely used as a measure to tackle the hurdles associated with numerous implementations of enterprise resource planning (ERP) systems. This study evaluates the morphological variability of CSFs using the analytical principal component analysis technique to identify principal components (PCs) that can be adopted for a successful ERP system implementation. The dataset of 205 CSFs from 127 different studies was evaluated for the morphological variability in those studies. According to the results, 66 PCs were identified and ranked accordingly. The first 49 PCs with eigenvalues greater than 1 accounted for 89.67 % of the variability recorded. The first 6 PCs respectively accounted for 13.67%, 19.37%, 24.67%, 29.41%, 33.52% and 36.94% cumulative variations. In general, the graphical illustration of the study results show the palpable division between the taxonomic groups for 3 PCs.

@article{Epizitone2020,
  title     = {Principal Component Analysis on Morphological Variability of Critical Success Factors for Enterprise Resource Planning},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {11},
  number    = {5},
  year      = {2020},
  publisher = {The Science and Information Organization},
  author    = {Ayogeboh Epizitone and Oludayo. O. Olugbara},
  doi       = {10.14569/IJACSA.2020.0110529},
  url       = {https://doi.org/10.14569/IJACSA.2020.0110529}
}