The Covid-19 pandemic has negatively affected life worldwide and caused catastrophic loss of life. It has also been harming the economic activities of businesses, and airline companies are among the sectors most affected by this situation. One of the goals for survival in such a situation is to make the best in airline revenue management (ARM). The most helpful model for ARM is Expected Marginal Seat Revenue (EMSR), widely used in the literature and industry. In this study, the simple and effective models that simulated EMSRa, EMSRb, and EMSRc were developed, called EMSR Total Revenue Control (EMSRtrc). The proposed three models aim to keep the simplicity of the original EMSR models while creating a new perspective and methodology. The developed EMSRtrc models were tested with numerical examples and compared with EMSRa, EMSRb, and EMSRc models proposed previously in the literature. Numerical examples show that the developed EMSRtrc models perform better than the EMSRa, b, and c. For the minimum revenue category, the developed EMSRtrc models exhibit outstanding performance. The results show that the proposed models guarantee a higher minimum revenue of 9.900, 11.619, and 2.537%, respectively. The EMSRtrc models have generated higher revenue and achieved a higher load factor rate of up to 98% simultaneously. Considering the third numerical example, the approximate number of empty seats is 1.3 for the EMSRtrc-(a), 2.65 for the EMSRtrc-(b), and 7.85 for the EMSRtrc-(c). The overall results demonstrate that the proposed model is an effective tool for ARM.
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