Revenue Optimization for SAUDIA Transit Operation

Abstract

People have been migrating to various locations in search of better living. This is why they began to adopt and innovate multiple modes of transportation since the dawn of civilization. In the modern era, airline sector has transformed into a convenient mode of transportation due to time limitations of passengers. Given the dynamics of the airline sector and drastically changing global environment, SAUDIA airline realized the need of the time to revamp its operational capacities and strategies to deal with fierce competition. SAUDIA serves both domestic and international markets with huge customer facilitation; however, recently it has gone through severe competition and a subsequent loss of market share due to its slow response to the dynamics of the market. Therefore, understanding the constituent elements to revamp its network is crucial for SAUDIA to regain its market share so that it may attain its desired revenues. Keeping in view, this study is an endeavor to propose a new schedule based on a synergy of SWOT analysis, waves for the SAUDIA schedule, premium market analysis and nested logit model to overcome these problems. The proposed framework utilizes the shape of the waves under specific constraints to generate improved schedule by calculating market share and to decide based on nested logit regression model. The implication of this new schedule requires meeting several constraints such as the availability of aircraft within allocated time-windows, minimum connection time and minimum usage rate per aircraft per day. Findings of the study suggest that the proposed schedule is expected to increase total transit traffic by 48 percent with a 30 percent increase in the number of sources and destinations by SAUDIA, whereas it will enhance the overall fleet utilization by 12.5 percent. Additionally, it is anticipated that the proposed schedule would surge the revenues by 17 percent as compared to SAUDIA's regular weekly plan. 

Country : Saudi Arabia

1 Mohammed Enaytullah Ahmed2 Atif Shahzad3 Waqar Ahmed

  1. Department of Industrial Engineering, King Abdulaziz University, Jeddah, KSA
  2. Department of Industrial Engineering, King Abdulaziz University, Jeddah, KSA
  3. Department of Industrial Engineering, King Abdulaziz University, Jeddah, KSA

IRJIET, Volume 6, Issue 6, June 2022 pp. 85-93

doi.org/10.47001/IRJIET/2022.606011

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