Identifying and Prioritizing Digital Transformation Elements Using Fuzzy Analytic Hierarchy Process

Digital transformation addresses multiple aspects of the organization. These aspects are the elements to be addressed for the digital transformation in any organization and are categorized as dimensions and sub-dimensions. In this work, these elements are collected from a wide range of related literature (56 publications). The most relevant elements were then identified through expert survey; involving 12 experts. The weights for these elements were identified using multi-criteria decision-making (MCDM) techniques. The Analytical Hierarchy Process (AHP) is one of the most often used MCDM techniques to incorporate individual and subjective preferences when conducting analysis and convert complex issues into a clear hierarchical structure. This work applies fuzzy AHP to take into consideration the treatment of uncertainty issues (in AHP), using the geometric mean method, and through an iterative process, calculate the weights of various dimensions and sub-dimensions, and prioritize them within the proposed roadmap for digital transformation implementation. Sensitivity analysis and comparison with AHP were used to validate our findings and the robustness of our approach. The proposed approach identified 9 main dimensions and 42 sub-dimensions which align with the majority of the literature. However, the advantage of this approach is the prioritization of these nine dimensions and their sub-dimensions as per the weights assigned to each one of them, allowing the project manager to allocate the available resources to the dimensions with the highest priority. The results show that the strategy and business process dimensions are the most crucial ones in the implementation of digital transformation.

@article{H2023,
  title     = {Identifying and Prioritizing Digital Transformation Elements Using Fuzzy Analytic Hierarchy Process},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {14},
  number    = {9},
  year      = {2023},
  publisher = {The Science and Information Organization},
  author    = {Mohammed Hitham M. H and Hatem Elkadi and Neamat El Tazi},
  doi       = {10.14569/IJACSA.2023.0140986},
  url       = {https://doi.org/10.14569/IJACSA.2023.0140986}
}