Digital transformation in the defense industry: A maturity model combining SF-AHP and SF-TODIM approaches

Autor: Emine Elif Nebati, Berk Ayvaz, Ali Osman Kusakci
Přispěvatelé: Kuşakcı, Ali Osman
Rok vydání: 2023
Předmět:
Zdroj: Applied Soft Computing. 132:109896
ISSN: 1568-4946
DOI: 10.1016/j.asoc.2022.109896
Popis: As an inevitable process, digitalization has become a priority for many companies. The measurement of digital maturity is the first step toward adequately executing this. Although digital maturity models (DMM) have been developed for different sectors in the literature, such studies in the defense industry are lacking due to sector-specific dynamics. This study aims to close this gap and proposes a digital maturity model specific to the defense industry. In this study, a novel model was developed that combines the SF-AHP and SF-TODIM methods due to the uncertainty and hesitancy contained in the evaluation. The validity of the presented novel model has been demonstrated in a prominent defense company in Turkey. According to the results, the most notable digital maturity dimensions are the evaluation of opportunities and alignment with stakeholders. In addition, the model indicates that the company owns the required soft skills, such as leadership, organizational culture, and strategic determination for digital transformation (DT). On the other hand, essential hard skills such as technology and operational competencies are yet to be improved. Lastly, sensitivity and comparison analyses are conducted to validate and verify the obtained results’ stability and robustness.
Databáze: OpenAIRE