Document Type : Research Paper


1 Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran.

2 Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.

3 ICT Research Institute (Iran Telecommunication Research Center), Tehran, Iran.


This paper presents an optimization model for hotel pricing in the competitive environment following the Covid-19 epidemic, in which the government intervenes by offering appropriate tariffs and hotels use incentive policies such as discounts to attract customers. we consider the government as the leader and the hotels as the followers of the Stalkberg model, then apply the Nash equilibrium to determine the optimal price and demand of hotels in competitive conditions, taking into account the discount. By considering a government utility function, the optimal level of government tariffs is determined. The results indicate that government intervention in the tourism industry includes measures that benefit tourism. Because the government can increase the hotel revenue and expand tourism in favor of hoteliers by reducing its profits. Extensive analysis has been performed on five-star, four-star, and three-star hotels in a tourist area in Iran, and some of the most important managerial insights have been explained.


Main Subjects

[1]     Song, M., & Li, H. (2019). Estimating the efficiency of a sustainable Chinese tourism industry using bootstrap technology rectification. Technological forecasting and social change, 143, 45–54.
[2]     Balli, F., Curry, J., & Balli, H. O. (2015). Inter-regional spillover effects in New Zealand international tourism demand. Tourism geographies, 17(2), 262–278.
[3]     Tugcu, C. T. (2014). Tourism and economic growth nexus revisited: A panel causality analysis for the case of the Mediterranean Region. Tourism management, 42, 207–212.
[4]     Hosseini, S. M., Paydar, M. M., Alizadeh, M., & Triki, C. (2021). Ecotourism supply chain during the Covid-19 pandemic: A real case study. Applied soft computing, 113, 107919.
[5]     Motevalli-Taher, F., & Paydar, M. M. (2021). Supply chain design to tackle coronavirus pandemic crisis by tourism management. Applied soft computing, 104, 107217.
[6]     Jahangiri, S., Abolghasemian, M., Ghasemi, P., & Chobar, A. P. (2023). Simulation-based optimisation: analysis of the emergency department resources under Covid-19 conditions. International journal of industrial and systems engineering, 43(1), 1–19.
[7]     Bank, W. (2020). Global economic prospects. World Bank Group.
[8]     Pan, Y., Hussain, J., Liang, X., & Ma, J. (2021). A duopoly game model for pricing and green technology selection under cap-and-trade scheme. Computers & industrial engineering, 153, 107030.
[9]     Zhang, Y. (2010). Supply-side structural effect on carbon emissions in China. Energy economics, 32(1), 186–193.
[10]   Godinho, P., Phillips, P., & Moutinho, L. (2018). Hotel location when competitors may react: A game-theoretic gravitational model. Tourism management, 69, 384–396.
[11]   Sánchez Pérez, M., Illescas-Manzano, M. D., & Martinez-Puertas, S. (2020). You’re the only one, or simply the best. hotels differentiation, competition, agglomeration, and pricing. International journal of hospitality management, 85, 102362.
[12]   Köseoglu, M. A., Parnell, J. A., & Doyle, J. D. (2015). Market orientation, strategy and revenue growth in the Turkish hotel industry. Journal of travel & tourism marketing, 32(8), 1099–1116.
[13]    Hao, F., Xiao, Q., & Chon, K. (2020). Covid-19 and China’s hotel industry: Impacts, a disaster management framework, and post-pandemic agenda. International journal of hospitality management, 90, 102636.
[14]    Jiang, Y., & Wen, J. (2020). Effects of Covid-19 on hotel marketing and management: a perspective article. International journal of contemporary hospitality management, 32(8), 2563–2573.
[15]    Gössling, S., Scott, D., & Hall, C. M. (2020). Pandemics, tourism and global change: a rapid assessment of Covid-19. Journal of sustainable tourism, 29(1), 1–20.
[16]    Chopra, L., Verma, R. S., & Mandal, P. C. (2021). Pricing strategies for companies during the Covid-19 pandemic. International journal of business strategy and automation (IJBSA), 2(4), 1–19.
[17]    Ivanov, S. (2014). Hotel revenue management: from theory to practice. Zangador.
[18]    Vives, A., Jacob, M., & Payeras, M. (2018). Revenue management and price optimization techniques in the hotel sector: A critical literature review. Tourism economics, 24(6), 720–752.
[19]    Aydin, N., & Birbil, S. I. (2018). Decomposition methods for dynamic room allocation in hotel revenue management. European journal of operational research, 271(1), 179–192.
[20]    Baker, T., Eziz, A., & Harrington, R. J. (2020). Hotel revenue management for the transient segment: taxonomy-based research. International journal of contemporary hospitality management, 32(1), 108–125.
[21]    Klein, R., Koch, S., Steinhardt, C., & Strauss, A. K. (2020). A review of revenue management: Recent generalizations and advances in industry applications. European journal of operational research, 284(2), 397–412.
[22]   Liat, C. B., Mansori, S., & Huei, C. T. (2014). The associations between service quality, corporate image, customer satisfaction, and loyalty: Evidence from the Malaysian hotel industry. Journal of hospitality marketing & management, 23(3), 314–326.
[23]   Calheiros, A. C., Moro, S., & Rita, P. (2017). Sentiment classification of consumer-generated online reviews using topic modeling. Journal of hospitality marketing & management, 26(7), 675–693.
[24]    Vives, A., & Jacob, M. (2020). Dynamic pricing for online hotel demand: The case of resort hotels in Majorca. Journal of vacation marketing, 26(2), 268–283.
[25]    Mariello, A., Dalcastagné, M., & Brunato, M. (2020). Hotelsimu: simulation-based optimization for hotel dynamic pricing. International conference on learning and intelligent optimization (pp. 341–355). Springer, Cham.
[26]    Mousavi, E. S., Hafezalkotob, A., Makui, A., & Sayadi, M. K. (2021). Hotel pricing decision in a competitive market under government intervention: A game theory approach. International journal of management science and engineering management, 16(2), 83–93.
[27]    Kim, M., Roehl, W., & Lee, S. K. (2019). Effect of hotels’ price discounts on performance recovery after a crisis. International journal of hospitality management, 83, 74–82.
[28]    Lotfi, R., Sheikhi, Z., Amra, M., AliBakhshi, M., & Weber, G. W. (2021). Robust optimization of risk-aware, resilient and sustainable closed-loop supply chain network design with Lagrange relaxation and fix-and-optimize. International journal of logistics research and applications, 1–41.
[29]    Lotfi, R., Kargar, B., Gharehbaghi, A., & Weber, G. W. (2021). Viable medical waste chain network design by considering risk and robustness. Environmental science and pollution research, 1–16.
[30]    Lotfi, R., Kheiri, K., Sadeghi, A., & Babaee Tirkolaee, E. (2022). An extended robust mathematical model to project the course of Covid-19 epidemic in Iran. Annals of operations research, 1–25.