Abstract

Abstract In this study, the dynamic pricing optimization problem faced by the maritime transportation service provider company is considered. The aim is to find optimal prices for each journey for each level of unsold seats by using probabilistic dynamic programming. Conjoint analysis is used to identify the consumer behavior in case of price changes to the current product, namely journey. The optimal policies show the necessity of applying dynamic pricing policy instead of fixed pricing and the diversification of optimal policies under different conditions.

Highlights

  • Revenue management is a business principle that balances supply and demand to control price and/or inventory availability in order to maximize revenue and profit growth[1]

  • The realized demands in the past years show that the demand varies based on the season, weekdays/weekends and purpose of the trip

  • We consider a class of multistage problems called the dynamic pricing optimization problem faced by the maritime transportation service provider company in Istanbul

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Summary

Introduction

Revenue management is a business principle that balances supply and demand to control price and/or inventory availability in order to maximize revenue and profit growth[1]. Nowadays it has become important to develop operational models that incorporate customer choice[3]. At this point, revenue management with dynamic pricing models come into the scene. There has been no study conducted for maritime intercity passenger transportation industry to the best of our knowledge. This market shows some similarities to the airlines market, but it has some differences as well due to the level of competition in the market, prices and conventions of the consumers. This study tries to fill the gap in the literature by developing a dynamic pricing model for maritime intercity passenger transportation industry.

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