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https://doi.org/10.36719/2663-4619/110/67-70

Ali Aliyev

IMC University of Applied Sciences Krems

bachelors

https://orcid.org/0009-0005-1243-8637

ali.researcher@outlook.com

 

AI-Driven Optimization in Project Management and Marketing: A Case

Study of Airbnb Using Generative Adversarial Networks

 

Abstract

With an emphasis on AI-driven optimization to improve business performance, this study explores the use of Generative Adversarial Networks (GANs) in project management. This study shows how artificial intelligence (AI) can significantly improve project outcomes by using GANs to create synthetic data, model intricate project scenarios, and optimize important performance metrics like booking rates, revenue per available room (RevPAR), and average daily rates (ADR). Using Airbnb as an example, the analysis shows that a 4 % increase in occupancy would improve RevPAR by $4.22 per room, while a 5% increase in booking rates might result in an extra $3.41 billion in income.

This study highlights the importance of GANs in improving project management decision-making, resource allocation, and risk management. It also emphasizes how scalable GAN-powered solutions are for improving marketing tactics. In the end, GANs give businesses a strong tool to boost consumer engagement, increase operational efficiency, and boost competitiveness in ever-changing markets.

Keywords: generative adversarial networks (GANs), project management, AI-driven optimization, business performance, revenue per available room (RevPAR), marketing strategies

 


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