A Multi-Period Optimization Model for Service Providers Using Online Reservation Systems: An Application to Hotels

Area of Science:

• Operations Research
• Supply Chain Management
• E-commerce Optimization

Background:

• Online distribution channels face challenges in managing inventory for high-margin products with zero salvage value.
• Customer segmentation based on purchasing behavior, such as duration of need, is crucial for effective demand forecasting and resource allocation.

Purpose of the Study:

• To develop a multi-period optimization model for online sales of high-margin, zero-salvage products.
• To analyze the impact of customer segmentation (regular vs. long-term stay) on optimal inventory and pricing decisions.
• To provide actionable insights for service providers to enhance profitability and mitigate risks associated with overselling.

Main Methods:

• Development of a multi-period optimization model incorporating customer classification.
• Analysis of operational parameters influencing optimal decision-making.
• Conducting numerical experiments to validate the model's findings.

Main Results:

• Optimal decisions vary significantly based on customer type (regular vs. LTS), quantity required, and the multi-period duration.
• Long-term stay customers present both opportunities for guaranteed demand and risks of overselling penalties.
• Early purchasing by multi-period customers is recommended to maximize benefits.

Conclusions:

• Service providers should adopt dynamic strategies that consider customer segmentation and purchase duration to optimize profit and maintain reputation.
• Effective inventory management in online channels requires a nuanced approach to demand forecasting and risk assessment.
• The proposed model offers a robust framework for optimizing sales in complex distribution environments.