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Dynamic pricing in performance theater industry: An empirical study

Naragain Phumchusri

Open publisher page 2 citations

Abstract

In recent years, revenue management (RM) have played an important role in driving more profitability for industries selling perishable products with fixed amount of resources and different customers are willing to pay a different price for each of them. While dynamic price has been widely used in airline and hotel industry, a smaller number of researches explore the existence of dynamic pricing behaviors in non-travel industry. This paper investigates effects of relevant factors such as timing and realized demand on the performance ticket prices. While previous empirical studies related to performance ticket prices rely on the aggregate data and have not focused on exploring how the price changes during the selling season, this study uses detailed transaction sales obtained from 117 classical concert tickets, enabling the study of dynamic pricing structures. Three different models are compared: Ordinary Least Square, Random Effect and Fixed Effect models. The results indicate that Fixed Effect is the most appropriate model as compared to others. We found that day of shows, i.e., Saturday shows are significantly priced higher than others. The tickets of shows during the end of the season (during February to April) have lower prices compared to the beginning. We found timing in the selling period has significant impact on ticket prices. In particular, ticket price is lower when it is closer to the show date and a large amount of discount occurs right before the show starts.

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What this paper is about

In recent years, revenue management (RM) have played an important role in driving more profitability for industries selling perishable products with fixed amount of resources and different customers are willing to pay a different price for each of them. While dynamic price has been widely used in airline and hotel industry, a smaller number of researches explore the existence of dynamic pricing behaviors in non-travel industry. This paper investigates effects of relevant factors such as timing and realized demand on the performance ticket prices. While previous empirical studies related to performance ticket prices rely on the aggregate data and have not focused on exploring how the price changes during the selling season, this study uses detailed transaction sales obtained from 117 classical concert tickets, enabling the study of dynamic pricing structures. Three different models are compared: Ordinary Least Square, Random Effect and Fixed Effect models. The results indicate that Fixed Effect is the most appropriate model as compared to others. We found that day of shows, i.e., Saturday shows are significantly priced higher than others. The tickets of shows during the end of the season (during February to April) have lower prices compared to the beginning. We found timing in the selling period has significant impact on ticket prices. In particular, ticket price is lower when it is closer to the show date and a large amount of discount occurs right before the show starts.

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Available abstract

In recent years, revenue management (RM) have played an important role in driving more profitability for industries selling perishable products with fixed amount of resources and different customers are willing to pay a different price for each of them. While dynamic price has been widely used in airline and hotel industry, a smaller number of researches explore the existence of dynamic pricing behaviors in non-travel industry. This paper investigates effects of relevant factors such as timing and realized demand on the performance ticket prices. While previous empirical studies related to performance ticket prices rely on the aggregate data and have not focused on exploring how the price changes during the selling season, this study uses detailed transaction sales obtained from 117 classical concert tickets, enabling the study of dynamic pricing structures. Three different models are compared: Ordinary Least Square, Random Effect and Fixed Effect models. The results indicate that Fixed Effect is the most appropriate model as compared to others. We found that day of shows, i.e., Saturday shows are significantly priced higher than others. The tickets of shows during the end of the season (during February to April) have lower prices compared to the beginning. We found timing in the selling period has significant impact on ticket prices. In particular, ticket price is lower when it is closer to the show date and a large amount of discount occurs right before the show starts.

Key concepts: Ticket, Revenue management, Profitability index, Dynamic pricing, Revenue, Pricing strategies, Business, Database transaction

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