Managerial Economics

 

 

 

 

 

 

 

Managerial Economics

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Introduction

1. Research Questions
2. What impact has test-based discrimination had on the availability of Airbnb services to specific individuals?
3. How does price discrimination foster the habit of avoiding to accommodate certain rival groups in society?
4. What impact do financial constraints have on mitigating discrimination?
5. What impact do sports emotions have on Airbnb pricing, rivalry, and test-based discrimination?
6. What is the difference between housing services offered around football colleges and other Airbnb services in different areas?
7. Case Study Method

Online markets are an established common method of accessing goods and services. Furthermore, specific individuals are often in charge of setting up prizes for their goods or products. The same aspects apply to Airbnb services since the hosts establish a certain price range. Hence, the pricing on households is directly affected by the hosts. Airbnb studies have shed light on household preferences and financial decisions regarding real estate or hospitality services. Discrimination in the Airbnb market varies depending on either the sellers’ or buyers’ profile descriptions (Edelman and Luca, 2014). Equally important, Airbnb service exhibits aspects of discrimination in regards to sellers and buyers. Therefore, this study and method aim to highlight the discrimination and rival features that define the Airbnb market.

Similarly, this paper applies a qualitative analysis method that sheds some light on household finances and discrimination. First, the study analyzes test-based, statistical, and digital discrimination generated in Airbnb platforms. The main aim is to find empirical support for test-based discrimination and rivalry trends in the Airbnb market. Secondly, this study analyzes price discrimination channels. Price discrimination enables an Airbnb provider to impose higher prices on specific people in the market.  A qualitative analysis of the available data helps shed light on price based discrimination. Thirdly, the study also analyzes the ability of financial constraints to boost competition. Besides, financial constraints can make one Airbnb provider lower prizes, a factor that increases competition. Thus, the method used in this case study is the qualitative analysis of the available data regarding test-based discrimination, financial constraints, and price based discrimination.

Literature Review

The current economy has introduced new novel alternate businesses in hospitality. Airbnb’s are one of the revolutionary methods used by real estate owners to increase sales and improve profitability.  Furthermore, Airbnb is a revolutionary method used to monetize properties. The listing is set up online by a host providing the property access to a range of clients seeking accommodation. Studies show that Airbnb is a business that can exhibit some aspects of financial constraints, rivalry, and price discrimination, depending on the market (Bliss and Warachka, 2017). For instance, price based discrimination influence the Airbnb pricing offered to rival football teams. In this case, Airbnb setups offer higher pricing to rival teams to avoid offering accommodation services to rival teams. Consequently, a similar concept is used to foster discrimination and segregation in the housing market.   Although Airbnb is expected to be unbiased business establishments, some price discrimination and rivalry elements are evident.

Similarly, in the utility framework, business decisions are dependent on probabilities and preferences. The same probabilities are used to create taste-based discrimination. Test-based discrimination is whereby a seller or buyer intentionally ignores purchasing a specific service because of their preferences’ (Bliss and Warachka, 2017). Moreover, taste-based discrimination is highly dependent on the willingness to offer or pay the price to avoid interactions with specific groups or individuals. The online market offers users an opportunity to share their profile and preferences. However, the same preferences can be used to foster discrimination against a specific group. The same factor is expected from sellers marketing their houses on Airbnb sites. Racial and gender discrimination is a common aspect that affects online rental sellers in Airbnb platforms (Edelman and Luca, 2014). Perhaps, discrimination affects both the sellers and buyers.

Markedly, discrimination is a common practice within the Airbnb market. The housing market has various forms of discrimination that often lead to segregation and economic inefficiencies’. Airbnb is an online platform that offers every seller to enter their market without any form of vetting. The sad part is the existing legislation is not efficient enough to solve the problem of discrimination. Further, a study carried out by Edelman showed that individuals with names that sound white have an easier time accessing housing services when compared to clients with African American names (Farrahi, 2019). Consequently, the individuals with African American-based names are either denied the service or offered higher prices on the US’s housing packages. Publishing of the information led to the introduction of new policies in the Airbnb market. Perhaps, the creation of better policies helps reduces any form of discrimination in the Airbnb business.

Correspondingly, financial constraints are also used to reduce discrimination. An analysis of the Airbnb market shows that the lowering of accommodation or housing prices increases competition. Equally important, a rivalry affects the listing prices and revenue generated through financial constraints. Price discrimination rarely affects the financially constrained establishments since the host is focused on overcoming competition. Furthermore, price discrimination and rivalry is a habit fostered by well-established Airbnb’s (Bliss and Warachka, 2017). The well-established Airbnb’s have unlimited resources necessary to encourage rivalry and discrimination in the market. The financially constrained Airbnb’s focus on overcoming competition while the well-established hosts focus on encouraging rivalry. Therefore, financial constraints are used to mitigate rivalry and discrimination in Airbnb businesses.

Data

The generated data is obtained from several studies regarding price discrimination, test-based discrimination, ethnic discrimination, and financial constraints in the market. In this case, my main focus was on two basic studies carried out in the Airbnb market. The first research paper carried out a study on rental properties close to college football stadiums (Bliss and Warachka, 2017). Consequently, football rivals are vital in this study since they depict high rivalry levels created by the strong emotions and love towards their teams.  The hosts of the Airbnb’s that are neighboring the college football stadiums have the ability to alter listing prices, making it easy to observe the variation in pricing for non-rival and rival teams. Thus, the data collected can be sued to analyze the amount of dislike towards the opposing team.

Similarly, the data is made up of 1321 Airbnb units based around college towns. The units provided accommodation for around 232 games from 2014 to 2015. Consequently, the units are in the form of hotel rooms and offer self-contained accommodation services for fans during college games (Bliss and Warachka, 2017). The same setup is used to physically separate guests based on their teams. In this case, the observations are generated from unit-games pairs, which correspond with a football game in the town. A rival indicator that analyzes each college team football rivals is also vital in the study. Besides, an updated list of rivals was generated from sports media houses such as Sports Illustrated and ESPN. Hence, to improve precision, well-known teams such as Notre Dame-USC, Alabama-LSU, and Florida-Florida State are used.

The second data was generated from information regarding Airbnb hosts and their listing. Moreover, the information is collected from existing literature regarding ethnic discrimination in Airbnb services. In this study, a field experiment was done in 1006 Swedish hosts.  The analysis of guests’ listings showed that the Airbnb’s could host Swedish sounding, Arabic sounding, low, and high-class clients. Notably, the experiment was carried on the first 12 days of April 2019.  In this case, every host’s profile page provided a summary and basic information regarding the listed properties that belong to the host. Equally,  the same information was used to generate information regarding a housing service and its listing properties. One host can own several properties and sign them up for Airbnb services. Therefore, the collected information provided basic information, such as the host’s gender and preferences.

Markedly, the data was generated from Superhost since it can measure a host’s efficiency. For a real-estate to register in the Super host site, some factors are considered. One has to maintain an overall rating of 4.8/5 with a response rate of 80% and a review of 50%. Superhost is run by the Airbnb business making it an effective study group (Farrahi, 2019). Moreover, an analysis of the hosts’ pages provided data regarding the year of membership, reviews, frequency of answers, and listings. The data provided information about the number of times hosts use the pages, making it easy to study hosts activating and its relationship to discrimination. Besides, the same data provide information regarding pricing and interactions between the hosts and guests. In this case, Airbnb’s are characterized by a private room, shared room, or entire place. The rooms and their allocated prices are made available to clients after the host’s approval. Thus, the rate of payment and accessibility to clients is highly dependent on host preferences.

Analysis and Discussion

Several facts are established from the first article. First, the games played against rivals’ record the highest pricing of Airbnb services. An average listing price that sums up to $277 when it comes to rival associated prices. However, the home team fans listing prices sums up to an average of $247.  Although the games against rivals have higher listing prices, the revenue generate is average. Moreover, games against rivals record a high occupancy rate of up to 655, which is low compared to friendly games against top-ranked teams (Bliss and Warachka, 2017). Homecoming games are also generating more returns when compared to games against rivals. Perhaps, it is because homecoming and top-listed games generate more interest when compared to rival games.

On the other hand, pricing and financial constraints are not dependent on the demand for accommodation. An analysis of the generated data shows that the increase in accommodation pricing does not mean that the demand is high.  Furthermore, the exaggerated prices are meant to create discrimination against the team. Thus, instead of generating more revenue, the Airbnb services offer services to the same team members while scaring away rival team fans with exaggerated prices. Markedly, financially constrained housing services offer their services to fans regardless of their teams. The financially constrained Airbnb’s accommodate every client regardless of their preferences’. An analysis of the financial constraints shows that it can overcome any form of discrimination in the Airbnb market. Thus, financial constraints can mitigate test-based and price based discrimination.

The second report also helps to establish facts regarding ethnic discrimination. From the analysis, guests with Swedish sounding names account for up to 66% of the listings. In contracts, the guests with Arabic sounding names make up to 49% of the listing. There is a percentage difference of 17% regarding the likelihood of Superhost listing to offer booking invitations between Swedish sounding and Arabic sounding names (Farrahi, 2019). Thus, there is no significant difference in ethnic discrimination since the coefficient is less than 1%. However, there is no significant gap in bookings for rural and urban areas in Sweden.  Clients are offered the same services and pricing regardless of whether the area is rural or urban.  Besides, the online platform offers a random selection of users for the hosts. Perhaps, randomization of Airbnb and other housing services helps mitigate discrimination.

From the analysis of the two research studies, it is evident that there is a variation in international Airbnb’s and housing services offered around college football stadiums. The stadiums’ housing services exhibit some form of test-based discrimination and price-based discrimination against clients.  During sports season, Airbnb’s near college stadiums intentionally hike their rival team members’ prices. The main price discrimination is to limit the ability of rival teams to access accommodation. However, the common form of discrimination experienced in the Swedish Airbnb’s is ethnic and class discrimination. Ethnic discrimination is experienced when a host prefers housing Swedish client’s while ignoring the Arabic clients’. The same challenges is experienced in the US since certain hosts prefer housing Americans while ignoring African American clients’. In this case, financial constraint is the only factor that makes hosts avoid any form of discrimination.

Conclusion

Generally, Airbnb is a revolutionary method used to monetize properties. The listing is set up online by a host providing the property access to a range of clients seeking accommodation. However, Airbnb services can exhibit certain aspects of financial constraints, rivalry, and price discrimination, depending on the market. For instance, price based discrimination influence the Airbnb pricing offered to rival football teams. In this case, Airbnb setups offer higher pricing to rival teams to avoid offering accommodation services to rival teams. The same form of discrimination is experienced in the Swedish and American markets. There is discrimination against individuals with Arab ancestry in Sweden, while in America, there is discrimination against African Americans. However, discrimination is more prevalent in the US market rather than in other international markets like Sweden. Perhaps, discrimination can take varied forms depending on the market.

On the other hand, financial constraint is the only factor that can be used to overcome any form of discrimination. Financial constraints not only provide unbiased accommodation to clients’ but also boost competition in the market. Besides, financial constraints can make one Airbnb provider lower prizes, a factor that increases competition. Correspondingly, financial constraints are also used to reduce discrimination. An analysis of the Airbnb market shows that the lowering of accommodation or housing prices increases competition. Equally important, a rivalry has a varied effect on the listing prices and revenue generated through financial constraints. Price discrimination rarely affects the financially constrained establishments since the host is focused on overcoming competition. However, price discrimination is common in financially stable housing services. Therefore, financial constraints are used to mitigate rivalry and discrimination in Airbnb businesses.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

References’

Edelman, B. G., & Luca, M. (2014). Digital discrimination: The case of Airbnb. com. Harvard Business School NOM Unit Working Paper, (14-054).

Bliss, B., & Warachka, M. (2017). Rivalries, Price Discrimination, and Financial Constraints: Evidence from Airbnb.

Farrahi, N. (2019). The Sharing Economy and Discrimination: Evidence from a Field Experiment in Sweden.