Do price positioning and dynamic pricing work on Airbnb too?
An analysis of multi-unit vs. single-unit hosts
By Linchi Kwok, Associate Professor at The Collins College of Hospitality Management
Room-sharing websites not only want more travelers to use their service to book a stay as travelers but also want more people to list the underutilized space on their platforms as hosts. They want to help hosts gain more profits over time, allowing them to attract additional hosts and keep their existing hosts happy.
To gain a better understanding of how pricing strategies work the listings on room sharing websites --- a new and interruptive lodging product, it is essential to find out whether such pricing strategies as price positioning and dynamic pricing are helpful in increasing a listing's revenue performance. Additionally, will such pricing strategies' effects on listing performance vary between multi-unit and single-unit hosts (i.e., hosts managing more than one listing vs. those managing one only)?
The research study
I worked with another researcher, Karen Xie at the University of Denver on an empirical study - "Pricing Strategies on Airbnb: Are Multi-unit Hosts Revenue Pros?" which was published in International Journal of Hospitality Management. In this study, we aimed to test the following hypotheses:
H1a: Price positioning positively affects an Airbnb listing's revenue performance.
H1b: Dynamic pricing positively affects an Airbnb listing's revenue performance.
H2: An Airbnb listing managed by a multi-unit host has a higher revenue performance than the one managed by a single-unit host.
H3a: The positive effect of price positioning on an Airbnb listing's revenue performance is more salience for a multi-unit host than for a single-unit host.
H3b: The positive effect of dynamic pricing on an Airbnb listing's revenue performance is more salient for a multi-unit host than for a single-unit host.
The data and the analysis
We collected the data from a research company that provides trusted data and analytics services about Airbnb. Our data represent the 10 major Airbnb markets in the U.S., which are also the top 10 metropolitan areas with largest populations and gross domestic products (GDPs) in the nation, consisting 320,243 listings operated by 216,058 hosts over 34 months from October 2014 to July 2017. The unit in our econometric analysis is A Listing's Monthly Revenue Performance. Other variables in our analysis include: host type (multi-unit vs. single unit hosts), price difference (a listing's average rate - the average rate of other listings in a neighborhood), price variation (standard deviation of the listing price in a given month), supply control (number of other listings in a neighborhood in a given month), listing control (e.g., number reviews of a listing, average rating, number of bedrooms, etc.), and host control (e.g., availability in days of a month, response time in minutes, etc.).
- Positioning a listing at a higher price point than the average price of neighborhood listings can significantly increase the listing's revenue performance, supporting H1a.
- Dynamic pricing is also effective in driving up a listing's revenue performance, supporting H1b.
- A listing managed by a multi-unit host out-performs the one managed by a single-unit host, supporting H2.
- A multi-unit host will magnify the positive effect of price positioning on a listing's revenue performance, supporting H3a.
- Contradicting to H3b, the positive effect of dynamic pricing is weakened for a multi-unit host.
The practical implications
Drawing from the results from our analysis, we make the following recommendations:
For multi-unit host
- To maintain a relatively high price positioning
- To be careful when using the dynamic pricing strategy to avoid its negative effects.
For single-unit host
- To maintain a relatively high price positioning
- To consistently monitor the market demand and fluctuate the listing price accordingly
For room-sharing platforms
- To conduct more analysis in other markets for more insights, using ours as an example
- To provide training on the topic of price positioning to help hosts set up the initial price
- To provide market insights for hosts, making suggestions or reminders to hosts in adjusting the listing price.
- To offer different training sessions on dynamic pricing for multi-unit and single-unit hosts
- To pay close attention to those listings with a relatively high price positioning in the market and see how their price points are compared to the hotel's average daily rate.
- To pay close attention to the dynamic pricing strategy adopted by multi-unit hosts
The theoretical implications
- We establish the relationships between Airbnb hosts' pricing strategies, including price positioning and dynamic pricing, and an Airbnb listing's revenue performance, responding to the need for more in-depth analysis of the pricing strategies adopted by Airbnb hosts as entrepreneurs.
- Our findings reveal the important role that multi-unit hosts play in the P2P room-sharing context. The moderation effect of host type should also be considered in relevant studies.
We believe our study addressed a few important research questions. The results provide some insightful business intelligence to several key stakeholders in room-sharing businesses, assisting them in making informed business decisions regarding the effective pricing strategies in the room-sharing sector.
Through your observations or experience, what other pricing strategies can be useful in helping hosts increase listing revenues? What other research questions that need to be addressed in future studies?
Note: A relevant (but somewhat different) discussion about this research is also available on MultiBriefs.com.