With the debut of two new brands this month — Airbnb Plus and Beyond by Airbnb, Airbnb is expected to appeal to even more travelers in the market. Airbnb, as well as other room-sharing websites, are making huge disruptions to the lodging industry.
On one hand, room-sharing websites add a tremendous amount of inventory to the market by enabling any consumers with extra living space to run a business as a lodging operator. On the other hand, room-sharing websites introduced innovative changes to the traditional online reservation process as what is commonly used by hotels and OTAs (online travel agents).
As business entities, hotels and OTAs will usually accept or decline a consumer’s reservation request strictly based on vacancy and price, without any assessment on the consumer’s demographic or social-economic backgrounds. Room-sharing websites provide the cyber marketplace for travelers and hosts where they can be connected. The reservation process on room-sharing websites will not be initiated until a traveler send a request to a host after the traveler browses the available listings as well as the host profiles attached to the listings. When a host receives a request, s/he will then evaluate the traveler’s information, which may include the traveler’s nickname, a profile picture, previous stays, length of membership on the website, as well as such demographics as age, birthplace, and education, until the host reaches a final decision of accepting or declining the request.
The publicity of user profiles, however, can also increase the chances for hosts to discriminate certain renters because they are now able to make decisions upon renters’ demographic information. Two years ago, for example, an African-American man filed a lawsuit against Airbnb for the company’s ignorance of the hosts’ race discrimination as he had found it very difficult to get his reservation requests accepted by a host.
The reciprocal reservation process on room-sharing websites, however, also made me wonder if a traveler’s “attractiveness” to the host may play a role in closing the sales. With that in mind, I worked with Karen Xie, an assistant professor at University of Denver on a research project entitled “Buyer-Seller Similarity: Does It Lead to a Successful Peer-to-Peer (P2P) Transaction of Room-Sharing Services?” The paper will soon become available on International Journal of Contemporary Hospitality Management, including the following highlights:
The theoretical framework: similarity-attraction among buyers and sellers
In general, the similarity-attraction theory posits that people are more likely to feel attracted to those similar to themselves. In a dyadic buyer-seller relationship, for example, sellers who share certain personality traits or similar attributes with the buyers, such as height, age, and product preferences, possibly find it easier to make sales. Meanwhile, consumers are also found to be more inclined to interact with those sellers who share a birthday, the same birthplace, and other incidental factors.
The research questions
Building on the similarity-attraction paradigm, we aimed to address two research questions in our investigation:
- How do host-renter similarities affect the likelihood of a P2P room-sharing transaction?
- Would such similarity-attraction effects vary as renter experience or host capacity increases?
The data and the analysis
We collected the data from XiaoZhu.com, a leading room-sharing platform in China because the website provided us the opportunity to match the similar attributes between a host and a renter for each of the successful transaction, such as similarity in age, birthplace, and education. Other information, including renter experience (as measured in number of days since s/he signed up on the website), host capacities (as measured in number of units that a host operates on a room-sharing website), as well as some other listing attributes, were also collected. After building a large-scale, granular online observational dataset, we then employed a logistical regression model in our analysis.
- A similarity in age between a host and a renter will lead to a higher likelihood of a P2P transaction.
- A similarity in education will also lead to a higher likelihood of a P2P transaction.
- As the length of a renter’s membership increases, the positive effect of age similarity on the likelihood of a P2P transaction will be mitigated, but the positive effect of education similarity will be strengthened.
- As the number of properties managed by a host increases, the positive effect of age similarity is weakened.
- To promote successful P2P transactions, room-sharing websites may consider matching the hosts and renters with similar attributes that were identified in the study.
- Hosts who want to make more incomes on room-sharing websites, may also put their preferences on the travelers of a similar age and have a similar educational background, leading to more successful P2P transactions in the future.
- Hotels may also explore the effectiveness of such “matching” tactics, e.g., having service staff to serve a hotel guest of a similar age or with a similar educational background.
- In the long term, hotels may also consider better defining or branding their hotels with the distinguishable “persona” that match with the ones of their target customers.
- This study acknowledged the reciprocal reservation process between a host and a traveler (renter) on room-sharing websites. By integrating the data from both renters and sellers in one analysis, we were able to identify several buyer-seller similarity effects on the likelihood of a P2P room-sharing transaction.
- This is probably the first empirical study in sharing economy that applied the similarity-attraction theory to the investigation, providing new explanations of what leads to the likelihood of a P2P transaction.
- Even though this study was not designed to address whether hosts discriminate renters on room-sharing websites, the findings indicate that other factors, such as the “attractions” between a host and a renter, may also influence the host’s decision of accepting or rejecting a reservation request.
Do you also observe similarity-attraction effects in hospitality businesses? How can businesses increase sales through buyer-seller similarity effects?
This post is also published on Hospitality.Net, and the picture was also downloaded from the same source.