Impact of Gender Profiling and Racial Profiling on the Crisis Escalation between Customers and Front-Line Security at Dubai International Airport

Ibrahim Ahmad Ali Mohammad  Falamarzi; Mashitah binti Mohd  Udin; Mohammed R. A.  Siam

doi:10.48165/sajssh.2021.2302

Authors

Ibrahim Ahmad Ali Mohammad Falamarzi School of Government , Universiti Utara Malaysia, Malaysia.
Mashitah binti Mohd Udin School of International Studies, Universiti Utara Malaysia, Malaysia.
Mohammed R. A. Siam School of Business Management, Universiti Utara Malaysia, Malaysia.

DOI:

https://doi.org/10.48165/sajssh.2021.2302

Keywords:

Gender Profiling, Racial Profiling, Crises Escalation, Dubai International Airport

Abstract

The aim of the study is to examine the impact of racial profiling and gender profiling on the crisis escalation between front-line security and passengers in Dubai Airport. The study belongs to positivism philosophy, deduction approach, quantitative methodology, empirical survey passed study, used cross-sectional data, and data is original. The target or study population chosen for this research is the total number of employees, both senior and junior staff working at the Dubai international airport. The reason for this is that if crises stuck, all will be affected, and they have a big role to play in managing crises. The actual sample size is 360 employees, and the distributed survey is 446, which is distributed by using face-to-face data collection methods in a convenient technique of sample selection. Overall, the model is successful because it can predict 33.4% of the crisis escalation, and the direct relationships for the two predictors of crisis management are significant. The precedence for the relations based on the path coefficient value is gender profiling (0.424) and racial profiling (0.397). This study is limited to the empirical examination of UAE airports; however, replicating the same design with the same research design but in different countries will provide extra knowledge to generalize the proposed relations. In addition, the model can explain up to 33.4% of the crisis management variance; scholars are welcome to investigate more crisis escalation causes to increase the model power and propose a more comprehensive model.

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