Enterprise Architecture Framework Selection for Collaborative Freight Transportation Digitalization: A Hybrid FAHP-FTOPSIS Approach

Collaborative freight transportation plays a crucial role for Logistic Service Providers (LSPs) seeking to enhance profitability and service quality, yet it faces challenges at strategic, operational, and technical levels. Digital transformation creates opportunities to overcome these hurdles by extending collaboration beyond physical logistics to encompass information management and digital transformation. Enterprise Architecture Frameworks (EAFs) offer promising solutions by providing a holistic view of various levels within such ecosystems and ensuring alignment between information systems and strategic objectives. However, selecting the right EAF is a complex and critical step. This study introduces an innovative approach for selecting an enterprise Architecture (EA) framework to support the development of a collaborative freight transportation platform. It emphasizes the importance of adopting a systematic EA methodology in the digitalization of the freight transportation sector. The decision-making process integrates established techniques such as the Analytic Hierarchy Process (AHP) and the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (F-TOPSIS). Applied to a case study involving a Moroccan logistics company, the approach demonstrates effectiveness in framework selection. The study’s findings underscore the method’s significance as a valuable tool for organizations embarking on digital transformation through EA, offering adaptability across diverse industries and contexts.

@article{Saoud2024,
  title     = {Enterprise Architecture Framework Selection for Collaborative Freight Transportation Digitalization: A Hybrid FAHP-FTOPSIS Approach},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {11},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Abdelghani Saoud and Adil Bellabdaoui and Mohamed Lachgar and Mohamed Hanine and Imran Ashraf},
  doi       = {10.14569/IJACSA.2024.01511115},
  url       = {https://doi.org/10.14569/IJACSA.2024.01511115}
}