Introduction
Uber is a company that, for many people, has become synonymous with a taxi. Uber’s business model was one of the first on the market to provide competitive advantages such as lower prices, better service, and faster pick-up times than traditional taxis. In fact, this company has changed the approach to the provision of transportation services in many countries using technological capabilities. In this case study, the features of Uber’s work will be examined through the perspective of various economic theories and concepts to analyze and determine the reasons for its success and future opportunities.
The Market Before Uber’s Entry
The taxi market before the Uber entrance was largely disorganized and based on limited supply. For example, in the United States, cities sell a limited number of medallions to limit the number of taxis (Gabel, 2016). Passengers had to catch a cab on the street or make a phone call and hope they could get a car at the right time. In addition, the prices were relatively high as the taxi license required training, vehicle checks, and high fees (Gabel, 2016). There was also no way to learn about driver skills or customer behavior and provide feedback. Consequently, clients often face inconvenience in obtaining services and high prices.
Uber took into account all these shortcomings and made them the basis of its work. The main feature was the technology that made it possible to connect passengers and drivers and simplified access to the service. In addition, as freelancers, drivers do not need such thorough checks, preparation, and purchase of medallion, which reduces costs and, therefore, the price of the service. In addition, lower barriers to entry have increased the popularity of taxi jobs among drivers and increased supply (Gabel, 2016). Thus, Uber has improved the speed, convenience, price, and quality of taxi customer service through technology, thereby gaining popularity among the public.
Uber’s Surge Pricing
Uber uses different approaches to price surging to ensure its income, as well as to balance supply and demand. The first approach is based on the fact that during periods of high demand, the application raises the prices of services to balance it with the supply. For example, during the morning rush, after the end of mass events, or on rainy days, many people prefer to use a taxi to get to their destination. The program monitors the number of application openings during high-demand periods and raises the price of services in particular zones (Guda & Subramanian, 2019).
Drivers who are free to work at a convenient time for them, according to their working conditions, see price growth that is beneficial to their own profit, which increases the supply of services, that is, the number of available cars. At the same time, some users who see high taxi prices refuse the service. Consequently, supply and demand are balanced, and the company receives a higher income.
Moreover, Uber also uses a price discrimination approach, which is widely applied in different service companies. This approach is based on assessing how much a client is willing to pay to receive services and setting different prices according to this assessment. For example, Uber offers different types of cars, such as business class, which have a higher service cost. However, a practice that is more in line with the surge pricing concept is that a trip to a more expensive area of the city has a higher price than a similar trip to an area with an average real estate value (McKenzie, 2017).
Thus, this approach is generally aimed at generating more profit for the company, but it also increases demand because, at the expense of customers who pay a higher price, Uber can offer a lower cost of a ride to people who are not willing to pay more. Therefore, this approach is appropriate, logical, and profitable if Uber can accurately access customers’ willingness to pay. In this way, customers who can pay more will not give up services because of a slight increase for them, but customers with a lower price threshold will be more interested in using Uber services. Consequently, while both approaches to price surging may irritate some customers, they have a positive effect on the balance of supply and demand and generate profits for the company.
Uber’s Business Model From Perspective of Economies of Scale and Economies of Scope
Uber provides many services in various countries of the world. The goals of business expansion and diversification are not only long-term objectives for a company to become a global leader but also operations that bring benefits from an economic point of view. For this reason, Uber’s diversification and scaling can be considered by applying the concepts of economies of scale and economies of scope.
The concept of economies of scale is, in fact, fundamental to Uber. The idea of economies of scale is based on the fact that the production of a higher quantity of products increases its cost advantage (Colombini, 2018). While Uber is more perceived by users as a transport company because it provides taxi services, the organization is actually a technology company. Uber does not own a single car but employs drivers with their vehicles, receiving a portion of their profits from each trip.
Consequently, the cost of its production remains the same, but the profit depends on how many drivers use the system and bring profit to the company. With each new driver and each new trip, the profit more and more exceeds the cost of production, or in the case of Uber, the creation of new system options and their support. For this reason, Uber is expanding its services to an ever-larger area and overcoming local transport companies.
The concept of economies of scope has also become applicable to Uber in the current time and is associated with the diversification of its services. This concept is based on the fact that the total cost of production of a company decreases with the increasing variability of services (Colombini, 2018). Uber offers its customers not only a taxi but also food delivery or a driver who can deliver the car and its owner to the desired location.
Thus, the leaders and developers have added several functions to the original system, which brings them significant income from a single resource. For example, a driver can deliver food to Uber Eats customers if there is currently low demand for taxi services. Consequently, the total cost of production of the system is reduced since they are used for several profitable purposes at once. Thus, both concepts apply to the Uber business model and bring economic benefits to it.
Uber’s Use of Game Theory
Uber drivers are not employees of the company; thus, they cannot be forced to work a certain number of hours and in a particular place. For this reason, Uber uses game theory to develop incentives and motivate drivers to work harder and longer and provide sufficient supply. For example, Uber uses the practice of “binge-driving,” offering a new ride to the driver before they finish the current one (Pendergrass, 2019). At the same time, the “accept” button in the application is more visible and convenient, which makes it much easier for the driver to agree to the next ride than to reject it (Pendergrass, 2019). According to game theory or gamification, this approach forces the driver to agree not to miss out on achievements, and the difference between the “agree” and “reject” buttons influences this choice subconsciously.
Another example is a driver motivation system based on monetary rewards for various achievements. For example, Uber offers drivers different badges, bonuses, and promotions for specific achievements that can increase their earnings (Pendergrass, 2019). For example, such an achievement can be a high rating from customers, a high number of trips, or a long distance. According to game theory, the feeling of euphoria for each achievement forces the player to delve deeper into the game and strive for the next accomplishment to experience this feeling again (Pendergrass, 2019). Thus, while earning badges, drivers can work longer than planned or go to places they do not want to go. Such approaches are just one of the few that Uber uses to attract drivers and customers, and they are primarily based not on material motivation but on a psychological and sociological game.
Uber’s Incentive Pay Model
In addition to incentives based on the theory of gamification, Uber also uses the usual material bonuses to attract drivers to work, especially during quarantine. As Chapman (2021) noted, the demand for taxis has skyrocketed after the vaccinations and the removal of some of the restrictions, but drivers still do not have a significant desire to work in a pandemic, which forced Uber to invest 250 million in bonuses. This approach, as well as rewards and badges for achievements in pre-pandemic times, solve the “principal-agent problem.”
This problem is to motivate employees to do their job efficiently without increasing the cost of their control (Adams, n.d.). Consequently, bonuses solve the problem of employee motivation. However, these monetary incentives are pretty costly for the company. Gamification of driver’s application reduces these costs somewhat by incentivizing drivers to achieve the next achievement rather than providing significant financial incentives, but these costs are still high.
Asymmetric Information Issues With Uber’s Business Model
Despite its advantages, Uber has the disadvantage of asymmetric information issues. This flaw is expressed in the fact that drivers and customers do not know and cannot get information about how prices, ratings, and other details that are displayed in the application are formed. Application creators have information about the activities and location of drivers and customers, but drivers and customers only see directions, orders, and prices, which gives them the advantage and the ability to manipulate data.
Asymmetric information issues have two scenarios that can be applied to Uber. The first option is an adverse selection when one side does not know about the type and quality of the other side’s product (Dermawan et al., 2019). The second option is moral harm, which means deliberately hiding information from one side of the other (Dermawan et al., 2019). The fact that drivers and customers see only the final result, for example, prices or ratings, but can only guess about the processes of their formation, refers to the first option. However, if Uber deliberately overprices rides to boost supply or downrate drivers to reduce their earnings, this may apply to the second scenario. Although no such evidence has been provided, information asymmetries exist and may undermine the confidence of drivers and customers.
Assess Uber’s Potential for International Expansion
Uber has many benefits for customers and drivers, suggesting significant international expansion potential. People in most countries have access to the application and want to get a taxi in a short time and at a low price. However, each country has its own rules for international trade and employment, which can bring challenges and hinder Uber’s expansion. Firstly, this issue is antimonopoly legislation; secondly, the rules for ensuring data privacy; and thirdly, the regulation of labor rules and safety.
The antimonopoly issue is related to the fact that it is profitable for Uber to outperform competitors and cover a large part of the market by reducing costs and increasing profits. Uber needs to remove competitors from the market to ensure profitability, but if a company with a similar business model operates in the country, for example, Lift, Uber is difficult to accuse of monopolization. However, in countries where Uber-like services are not developed, this approach can mean a monopoly because, most likely, customers will choose the cheaper and more convenient Uber, and it will gain a larger market share.
Consequently, the company will violate antitrust laws that apply in most countries and international trade. In addition, the governments of some states require access to all application data for various reasons, which violates their privacy (“The technology,” 2019). Consequently, the refusal of Uber to provide this access may impede work in the country. Moreover, many states oppose the classification of drivers as freelancers instead of employees, which is key to the Uber business model, and require specific measures to ensure the safety of customers and passengers (“The technology,” 2019). However, Uber cannot change their business model, which means that it cannot expand to some countries.
Conclusion
Therefore, the analysis demonstrates that Uber’s success is based on its business model, although it also has disadvantages for international expansion. Uber has some features that ensure its success, such as the use of technology, which makes the use of services convenient for both drivers and customers. The second feature is the classification of drivers as freelancers, which, on the one hand, gives them the freedom to choose a convenient time for work and, on the other hand, reduces the company’s expenses for providing benefits.
In addition, the use of game theory and price surging allows the company to motivate drivers and balance supply and demand. However, this model also discourages Uber from expanding to states that view drivers as employees and cause controversy and conflict in countries where it works. However, Uber has the potential to expand to other cities and countries that value the company’s convenience but are not yet in its coverage area.
References
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Chapman, L. (2021). Uber and Lyft are spending millions on driver bonuses to end shortage. Bloomberg. Web.
Colombini, F. (Ed.) (2018). Raising capital or improving risk management and efficiency? Springer.
Dermawan, D., Ashar, K., Noor, I., & Manzilati, A. (2020). Asymmetric information of sharing economy. Advances in Economics, Business and Management Research, 144, 29-33. Web.
Gabel, D. (2016). Uber and the persistence of market power. Journal of Economic Issues 50(2), 527-534.
Guda, H., & Subramanian, U. (2019) Your Uber is arriving: Managing on-demand workers through surge pricing, forecast communication, and worker incentives. Management Science, 65(5), 1996-2014. Web.
McKenzie, J. (2017). The economics behind Uber’s new pricing model. The Conversation. Web.
Pendergrass, W.S. (2019). Game theory through smartphone app use in support of for-hire transportation network companies. Proceedings of the Conference on Information Systems Applied Research, Cleveland, Ohio.
The technology 202: This is why Uber’s global expansion poses risks as it goes public. (2019). Web.