Determinants of rental strategy: short-term vs long-term rental strategy

Abstract

Purpose Short-term rental option enabled via accommodation sharing platforms is an attractive alternative to conventional long-term rental. The purpose of this study is to compare rental strategies (short-term vs long-term) and explore the main determinants for strategy selection. Design/methodology/approach Using logistic regression, this study predicts the rental strategy with the highest rate of return for a given property in the City of Philadelphia. The modeling result is then compared with the applied machine learning methods, including random forest, k-nearest neighbor, support vector machine, naïve Bayes and neural networks. The best model is finally selected based on different performance metrics that determine the prediction strength of underlying models. Findings By analyzing 2,163 properties, the results show that properties with more bedrooms, closer to the historic attractions, in neighborhoods with lower minority rates and higher nightlife vibe are more likely to have a higher return if they are rented out through short-term rental contract. Additionally, the property location is found out to have a significant impact on the selection of the rental strategy, which emphasizes the widely known term of “location, location, location” in the real estate market. Originality/value The findings of this study contribute to the literature by determining the neighborhood and property characteristics that make a property more suitable for the short-term rental vs the long-term one. This contribution is extremely important as it facilitates differentiating the short-term rentals from the long-term rentals and would help better understanding the supply-side in the sharing economy-based accommodation market.

Beauty premium or beauty penalty in sharing accommodation situations based on lay theories

“…Confirming hosts’ trustworthiness and genuineness of their service/product information is necessary for consumers. To enhance the credibility, hosts are supposed to provide more information about the living space in detail, like security and privacy, information technology quality and house traits (Shokoohyar et al , 2020; Yang et al , 2019). Updating host profiles as well as room/facilities availability regularly to generate positive impressions of the hosts to improve consumers’ perceived trustworthiness (Park and Tussyadiah, 2020).…”

Factors affecting short-term rental first price: A revenue management model

“…Adding to the previous paragraph, Shokoohyar et al (2020) state that “properties with more bedrooms, closer to the historic attractions, in neighborhoods with lower minority rates and higher nightlife vibe are more likely to have a higher return if they are rented out through Short-Term Rental contract.” Cui et al (2018) assume that “higher-priced homeowners and higher-priced renters are more likely to live in properties with a greater number of bedrooms, near a major employment center, park, or school, as well as in a suburban location[…] school attendance with higher school quality.”…”

“…Different authors, such as Shokoohyar et al (2020) , have found that property location has a significant impact on the rental strategy chosen, underscoring the importance of that well-known refrain “location, location, location” in the property market. Authors such as Benítez-Aurioles (2018) and Gunter and Önder (2018) have focussed previously on geolocation, showing that listing prices are related to distance from the city center, and the response time of the host is negatively correlated with such bookings.…”

Understanding patterns and competitions of short‐ and long‐term rental markets: Evidence from London

“…As a topic of contemporary interest, various research has focused on examining the implications of Airbnb. This includes the impact on traditional accommodation sectors where Airbnb are argued to have a profound impact on hotel revenues (Zervas et al, 2017) as well as the long‐term housing market (Ayouba et al, 2020; Barron et al, 2017; Shabrina et al, 2022; Shokoohyar et al, 2020). Shokoohyar et al (2020) found that certain neighborhood characteristics contribute to a higher rate of return when properties are being rented as STR.…”

“…This includes the impact on traditional accommodation sectors where Airbnb are argued to have a profound impact on hotel revenues (Zervas et al, 2017) as well as the long‐term housing market (Ayouba et al, 2020; Barron et al, 2017; Shabrina et al, 2022; Shokoohyar et al, 2020). Shokoohyar et al (2020) found that certain neighborhood characteristics contribute to a higher rate of return when properties are being rented as STR. Ayouba et al (2020) pointed out that Airbnb rentals put outward pressure on rents in several French cities and Shabrina et al (2022) presented an analysis concluding that Airbnb misuse in London (in which entire home property listings do not follow the local regulations) can be associated with disruptions toward the traditional long‐term housing market.…”