AirForecast: A Predictive Analytics for Airbnb Pricing TrendsÂ
AirForecast: A Predictive Analytics for Airbnb Pricing TrendsÂ
Accurate pricing forecasts are crucial for market participants in the ever-changing tourism sector, such as property owners, tourists, and policy-makers. The emergence of platforms such as Airbnb has brought about increased intricacy in the pricing of accommodations, which is influenced by a multitude of factors spanning from local events to worldwide economic patterns. Although Airbnb's comprehensive data collection includes intricate information regarding guest preferences and booking trends, effectively utilizing this data to accurately forecast future pricing poses a substantial hurdle. The COVID-19 pandemic has made this situation more complex, causing disruptions to previous patterns and requiring the use of flexible and resilient forecasting techniques.
Accurate pricing forecasts are crucial for market participants in the ever-changing tourism sector, such as property owners, tourists, and policy-makers. The emergence of platforms such as Airbnb has brought about increased intricacy in the pricing of accommodations, which is influenced by a multitude of factors spanning from local events to worldwide economic patterns. Although Airbnb's comprehensive data collection includes intricate information regarding guest preferences and booking trends, effectively utilizing this data to accurately forecast future pricing poses a substantial hurdle. The COVID-19 pandemic has made this situation more complex, causing disruptions to previous patterns and requiring the use of flexible and resilient forecasting techniques.
The primary objective of this research is to create a prognostic model that can forecast Airbnb lodging prices for the year 2024, utilizing data from 2020 and 2023. This model seeks to incorporate several influential aspects, such as listing attributes, seasonal fluctuations, and external occurrences, and to adjust to sudden changes in the market. The primary objective is to provide a resilient instrument for making decisions based on data, which can assist stakeholders in strategic planning and operational modifications to synchronize with forthcoming market circumstances.
The primary objective of this research is to create a prognostic model that can forecast Airbnb lodging prices for the year 2024, utilizing data from 2020 and 2023. This model seeks to incorporate several influential aspects, such as listing attributes, seasonal fluctuations, and external occurrences, and to adjust to sudden changes in the market. The primary objective is to provide a resilient instrument for making decisions based on data, which can assist stakeholders in strategic planning and operational modifications to synchronize with forthcoming market circumstances.
