Paper Summary
Title: Price dispersion across online platforms: Evidence from hotel room prices in London (UK)
Source: arXiv
Authors: Debashrita Mohapatra et al.
Published Date: 2023-10-20
Podcast Transcript
Hello, and welcome to paper-to-podcast. Today, we're diving into a topic that's as puzzling as a Rubik's cube, and just as colorful - the mysterious world of online hotel prices.
Our episode today is inspired by a paper titled "Price dispersion across online platforms: Evidence from hotel room prices in London (United Kingdom)", by Debashrita Mohapatra and colleagues. Imagine you're booking a hotel room in London. You'd think that the same room would cost the same amount on all websites, right? Well, just like a magician pulling a rabbit out of a hat, this research reveals something quite unexpected.
The researchers checked out prices for the 200 most popular hotels in London across different booking websites and found that prices varied up to 9% around the mean hotel room prices. That's like finding out that your friend paid £90 for the same £100 room you just booked! It's a bit like discovering your identical twin has been secretly wearing mismatched socks all these years.
But here's a plot twist worthy of a Hollywood movie: as the booking date got closer to the day of the stay, these prices started to behave a bit like school friends at a reunion - they began to converge. However, even though they got closer, they didn't become identical twins. The price differences persisted until the day of the stay, meaning that the "one price fits all" law was on vacation. So, next time you book a hotel room, remember you could be paying more (or less) than the next person for the exact same room!
In terms of how they did their magic trick, our researchers collected data from the top 200 most popular hotels, comparing prices across various booking sites. To make sure the hotels were playing fair, they only looked at prices for a one-night stay for two guests in the same type of room. They gathered this data for seven different dates, scraping prices from 15 different booking dates for each. Then, they calculated the coefficient of variation of prices, which is a fancy way of saying they measured how much prices varied from the average.
One of the strengths of this research is how it delves into a real-world issue: the variance in hotel room prices across different online platforms. The researchers used a thorough, systematic approach, collecting data from the 200 most popular hotels in London through web scraping, and ensuring the homogeneity of the products they were comparing.
However, no study is perfect, and this one has its limitations. For instance, the study only focuses on hotel prices in London, which might limit the generalizability of the findings to other cities or countries. The research also relies on data from a single price comparison website, which might not fully represent all online platforms.
Despite these limitations, this study has immense potential applications for online business strategists, consumers, and policymakers. Understanding the patterns of price dispersion could help businesses optimize their pricing strategies, potentially leading to increased profitability. For consumers, this research could encourage more informed purchasing decisions. Policymakers and regulators in the digital economy might find these insights useful in establishing fairer rules and regulations.
So, next time you're booking a hotel room, remember that the price tag might be as changeable as a chameleon. You might just have to wave a magic wand (or do a little more research) to find the best deal.
You can find this paper and more on the paper2podcast.com website.
Supporting Analysis
So, imagine you're booking a hotel room in London. You'd think that the same room would cost the same amount on all websites, right? Well, according to this research, that's not the case! The researchers checked out prices for the 200 most popular hotels in London across different booking websites and found that prices varied up to 9% around the mean hotel room prices. That's like finding out that your friend paid £90 for the same £100 room you just booked! But here's a plot twist: as the booking date got closer to the day of the stay, these prices started to behave a bit like school friends at a reunion - they began to converge. However, even though they got closer, they didn't become identical twins. The price differences persisted until the day of the stay, meaning that the "one price fits all" law was on vacation. So, next time you book a hotel room, remember you could be paying more (or less) than the next person for the exact same room!
This study dives into the curious world of online hotel booking in London. The researchers collected data from the top 200 most popular hotels, comparing prices across various booking sites. To make sure the hotels were playing fair, they only looked at prices for a one-night stay for two guests in the same type of room. They gathered this data for seven different dates, scraping prices from 15 different booking dates for each. Then, they calculated the coefficient of variation of prices, which is a fancy way of saying they measured how much prices varied from the average. To make sure the results were legit, they used regression analysis that considered different factors like the reputation and user-friendliness of the booking site. They also looked at how the average price and price dispersion (a.k.a. price scatterbrain-ness) changed as the booking date got closer to the stay date.
One of the most compelling aspects of this research is how it delves into a real-world issue: the variance in hotel room prices across different online platforms. The researchers used a thorough, systematic approach, collecting data from the 200 most popular hotels in London through web scraping, and ensuring the homogeneity of the products they were comparing. This attention to detail significantly enhances the reliability of their findings. Furthermore, their use of a simple theoretical model to explain their findings showcases their ability to translate complex economic phenomena into understandable terms. The researchers also effectively addressed potential areas of criticism, such as the influence of website reputation and user-friendliness, by incorporating these elements into their regression analysis. They demonstrated best practices by not only gathering and analyzing data, but also by verifying the accuracy of the prices listed on comparison websites. The study's robust empirical evidence, combined with a clear theoretical intuition, make it a strong contribution to the field.
The paper does not explicitly state its limitations. However, based on the provided information, one can infer that the research might have some potential limitations. For instance, the study only focuses on hotel prices in London, which might limit the generalizability of the findings to other cities or countries. The research also relies on data from a single price comparison website (Skyscanner.com), which might not fully represent all online platforms. Additionally, the study's theoretical model, which assumes zero search costs for consumers, might oversimplify real-world conditions where consumers might incur costs in terms of time and effort. Finally, the study uses data collected for a specific period (November 2017); thus, it might not account for seasonal variations or changes over time in hotel pricing strategies.
This research could have several practical applications, especially for online business strategists and consumers. For online retailers and price comparison platforms, understanding the patterns of price dispersion could help them optimize their pricing strategies, potentially leading to increased profitability. It could also aid in forecasting price trends, helping businesses better manage inventory and capacity. For consumers, this research could encourage more informed purchasing decisions. Recognizing that prices tend to converge as the booking date approaches might encourage consumers to wait until closer to their stay to book a hotel room. Additionally, policymakers and regulators in the digital economy might find these insights useful. If they understand the causes and effects of price dispersion, they could establish fairer rules and regulations. This research could also be beneficial for future academic studies relating to price dispersion and the law of one price, particularly in online markets.