The impact of organizational foresight competency on airport security performance

• Main Author: Al Hebsi, Mira Abdulla Essa
• Format: Thesis
• Language: English; English
• Published: 2024
• Online Access: http://eprints.utem.edu.my/id/eprint/27432/1/The%20impact%20of%20organizational%20foresight%20competency%20on%20airport%20security%20performance.pdf; http://eprints.utem.edu.my/id/eprint/27432/2/The%20impact%20of%20organizational%20foresight%20competency%20on%20airport%20security%20performance.pdf; http://eprints.utem.edu.my/id/eprint/27432/; https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=123476

As global air traffic continues to expand, the management of airports has evolved into a complex system, with the integration of security measures posing ongoing challenges. Addressing security concerns through predictive strategies has become imperative, and the convergence of future foresight, big data, and Artificial Intelligence (AI) technology is at the forefront of this endeavor. This research aims to critically examine the impact of utilizing future foresight powered by big data and AI technology, along with fostering a learning orientation, on the development of an innovation culture within airport management, ultimately influencing airport security performance. To achieve these objectives, a quantitative research methodology was employed, utilizing a survey research strategy. The survey questionnaire was distributed among 540 security personnel at Dubai Airport (DXB) Terminal One, with a sample size of 225 determined through simple random sampling, based on Slovin's formula. Data analysis was conducted using structural equation modeling (SEM) in IBM SPSS Statistics and SPSS AMOS. The findings of the study reveal that organizational foresight (B=.477, p < 0.05) and learning orientation (B = .175, p < 0.05) have a significant positive impact on innovation culture. Furthermore, innovation culture was also found to have a significant positive relationship with airport security performance (B = .328, p < 0.05). Specifically, the analysis revealed that 0.908% of security performance can be explained by the variables considered in the study. Additionally, deleting certain items from the list had minimal impact, with only 0.122% of squared multiple correlations and 9.58% of scale variance affected. However, the study did not find statistically significant moderating effects of big data and AI technology on the relationship between organizational foresight competence and innovation culture, nor did it find a direct impact of these technologies on innovation culture. These findings suggest that while technology plays a role, there are remaining gaps that need to be addressed to fully realize innovation in airport security management. In conclusion, this research highlights the potential for airport security performance management from a strategic perspective, emphasizing the importance of innovation culture. It emphasizes the significance of big data and AI technology in enhancing security measures but also reveals that their full potential has not been realized. As an implication of this study, it is recommended that airport security authorities work to establish mechanisms that facilitate the effective integration of big data and AI systems, optimizing their contribution to airport security. This research emphasizes the need for ongoing technological advancements and the cultivation of an innovation-driven culture in the aviation security sector.