Uber Eats has become a key platform for online food delivery, leveraging the interconnectedness of the Internet to enable consumers to order food online and enjoy it at home. A critical analysis of Uber Eats and its transformative impact on society, economy and politics, with a focus on web-based technologies, will be presented in this essay.
The first section introduces what Uber Eats is, the second section describes the history of Uber Eats, the third section talks about Uber Eats’ business model, the fourth and fifth sections describe Uber Eats’ Internet ecology and discuss Uber Eats’ transformative innovation.
What is Uber Eats?
Uber Eats is a food delivery service launched by Uber in 2014 (Raina et al., 2019). Consumers use the platform to buy food online, and the platform provides food delivery service to deliver food from restaurants to customers (Bates et al., 2020). In other words, Uber Eats is a third party that connects consumers and restaurants. Uber Eats is a typical product of the development of the sharing economy, using the Internet as a medium to gain economic benefits together in their way (John, 2018).
‘How Uber Eats Works’ on YouTube. Uber Eats, All Rights Reserved.
What is the history of Uber Eats development?
- As we know, Uber Eats’ parent company is Uber. Uber was founded by Garrett Camp and Travis Kalanick in 2009. Uber brought the ‘sharing economy’ into the mainstream, and surveys have shown a significant increase in user interest in the sharing economy (John, 2018).
- Technology has been the driving force behind the development of food delivery services (Raina et al., 2019). The company began to launch its UberFRESH service in August 2014, and in 2015 officially changed its name to Uber Eats. Uber Eats officially launched its app, which only provides online food delivery.
- Today, Uber Eats is available in 45 countries and over 6,000 cities.
Behind Uber Eats’ business model
Ertz and Proulx (2018) claim that the cooperative economy is sustainable. Uber Eats is an online platform that connects consumers and restaurants. Consumers can purchase their favourite food online through Uber Eats, and restaurants accept orders through the platform, which are then delivered by Uber Eats’ team. This online consumption has revolutionized people’s traditional eating behaviour. Also, this business model brings benefits to both parties (Christina et al., 2020), as consumers’ needs are satisfied through Uber Eats, and food delivery riders are paid through the consumption process, leading to benefits for everyone involved in the entire consumption process.
Online marketplaces can also communicate with each other while facilitating the coordination of resources (Hawlitschek et al., 2018). The direct dialogue between consumers and restaurants is also a significant advantage of Uber Eats. The restaurant first publishes information on Uber Eats, including restaurant profiles, food categories, restaurant addresses, and pictures of their dishes. When the consumer reads the information published by the restaurant, communication is constructed. Thus, the consumer has a general understanding of the restaurant, and if it meets the needs of the consumer, This will lead to consumption. At the same time, the consumer can check the status of the order at any time; after the order is completed, the consumer provides feedback of the restaurant and the rider on Uber Eats. Both the restaurants and the riders are rated by the platform through the feedback, so that makes improvements.
Another core advantage is the preference setting. When consumers order food, they can choose according to their preferences, such as delivery fees, the length of delivery time, the discounts, and the choice of food preferences. Many aspects of personalized Service Setting to meet the different needs of consumers. This kind of consumption will continue to happen when consumers have a positive experience.
Technology is the driving force behind the sharing economy (Li et al., 2020). As more and more online markets turn to the sharing economy as the theoretical basis of the model, Uber Eats is becoming more and more accepted as a model of consumption. At the same time, it is undeniable that Uber Eats has brought some degree of convenience to people’s eating habits.
Uber Eats’ internet ecology
Internet ecology refers to the web as a system that provides communication in which interacting entities exchange values that influence and support each other (Illarionova et al., 2019). In the Uber Eats’ ecology, it consists of partners, competitors, restaurants, riders, users, owners, and regulators.
There are three major online food delivery services in Australia, Deliveroo, Uber Eats, and Menulog (Bates et al., 2020). In other words, these three platforms almost dominate the Australian food delivery service. Competitors of Uber Eats are providing food delivery services.
The core entity of Uber Eats are restaurants, who cooperate with Uber Eats to provide food online to consumers. At the same time, online payment help is provided by Uber Eats’ partners, such as VISA, MASTERCARD, and PayPal. Google maps are the technical support. From this perspective, restaurants, riders, and consumers are all users of Uber Eats.
In Australia, Uber Eats are regulated by the local government and related agencies such as the Australian Competition and Consumer Commission (ACCC). These organizations ensure fairness and impartiality in the consumption of Uber Eats.
Below is a diagram of Uber Eats’ internet ecology:
Uber Eats – A transformative disruptive innovation hatched from the internet?
- Uber Eats’ transformative innovation is reflected in the creation of more Internet-dependent economic income and jobs. Uber Eats provides food delivery services for small restaurants (Correa et al., 2018). Large chains such as McDonald’s has their own food delivery application- McDelivery, which to some extent generate more revenue for large restaurants, this is why small restaurants that do not offer delivery have their interests compromised to some extent, and platforms like Uber Eats provides a choice of food delivery option for small restaurants. However, as a for-profit company, Uber Eats generates contracts with restaurants. The platform receives 15-30% of the revenue from each order (Feldman et al., 2019), which means that the restaurants get 85%-70% of the original profit. However, for small restaurants, whose margins are already slim, their efforts and income are not matched by a commensurate return. The online food service is a symbol of the exploitative market labour force. At the same time, online food services provide many jobs, such as riders, programmers for Uber Eats. With the increase in food delivery services, as well as the growth of the bicycle industry, including food packaging companies, there will be a significant increase in related jobs. It is worthing to consider whether everyone who works is paid in proportion to their efforts. Uber Eats’ delivery workers are paid based on the number of meals they deliver (Li et al., 2020). It means that riders do not receive a stable income, the market is unpredictable in terms of the number of meals delivered, and this unpredictability is a significant factor in the success of their work. Factors directly affect the jobs involved, not just the salaries of the delivery workers, but also the bicycle industry, the food packaging industry and so on. At the same time, uncontrollable factors, such as bad weather, traffic jams, affect the speed of delivery. If the delivery time is exceeded, it affects their tips, as well as consumer comments, which affect their ratings. Thus, under the theory of the sharing economy, Uber Eats, as a platform with control and therefore, more benefits represent a more exploitative behaviour phenomenon for restaurants and riders. However, more work will be provided as the popularity of the platform increases.
- On the other hand, Uber Eats makes intelligent recommendations for users based on data analysis to improve user satisfaction. In the course of using Uber Eats, it always recommends the best restaurants for users, which are intelligent recommendations based on the user’s location, the ordering history, and set preferences. According to Karppinen (2017) Committee, the right to use data includes the right to fair use and ownership of personal data. Users are concerned about how their data is being used, especially if they are not sure what it is being used for. Research studies have shown that to the extent that commercial organizations have access to data and analysis of data can be conducted to advance potential benefits (Groggin et al., 2017). When Uber Eats analyzes the data, it will recommend restaurants that meet the consumer’s needs for the most part. In this case, it is more likely that the benefits will be shared, the consumer’s needs will be met, the restaurants will get more orders, and the rider will not deliver orders that are out of delivery range and thus affect the delivery time. As a result, Uber Eats data analysis is gradually being accepted, as it has dramatically improved user satisfaction and made many parties more profitable. As more and more people accept Uber Eats data analysis, more and more people are using Uber Eats, which has changed people’s lifestyles to a great extent. This way of eating saves time for people, avoiding the cooking time, cleaning time, or time on the road when eating out, and time waiting for meals; compared to the time consumers spend waiting for delivery, people can do what they want to do.
- The development of Uber Eats has also led to a new regulatory process. Consumers can provide feedback about their experience on the platform (Correa et al., 2018), which directly affects how restaurants and riders are rated on Uber Eats. The rating criteria can also be specific to various aspects, such as satisfaction with the food, food packaging, or whether they got the food on time. In other words, consumer comments directly influence the choices of other consumers, and a rating solely based on the experience of the consumer is bound to be biased to some extent. For example, satisfaction with the food, which is evaluated differently depending on individual; or simplicity of the packaging in order to conserve resources, which is evaluated differently when comparing with the beautifully packaged food. However, Research found that the amount of plastic waste generated due to food delivery is also on the rise (Li et al., 2020). The problem of plastic waste continues to increase if it receives a lower rating due to packaging issues. This is a social problem that can arise from Uber Eats’ consumer experience-focused approach to regulation. In cases of unfair contracts between Uber Eats and restaurants, ACCC supervises Uber Eats to change its unfair contracts; however, many of the problems caused by the consumer’s subjective experience still exist, and the relevant departments need to establish monitoring systems.
In conclusion, Uber Eats is a key entity in the internet transformation, a new business model developed under the sharing economy system. It provides more work and more potential revenue for small restaurants on the economic side, but issues of unfairness in labour contracts with restaurants and riders seem to persist. There is also widespread acceptance of Uber Eats’ collection and analysis of personal data. Nevertheless, a system based on subjective consumer ratings raises questions about whether it is unreasonable to restaurants or environmental pollution; these require regulatory policies from the relevant agencies and state governments.
Bates, S., Reeve, B., & Trevena, H. (2020). A narrative review of online food delivery in Australia: challenges and opportunities for public health nutrition policy. Public health nutrition, 1–11. Advance online publication. https://doi.org/10.1017/S1368980020000701
Christina, L., Eilya, T., Milad, M., & Eugene, I. (2020). Economic Impact of Uber Eats: Assessing the impact of Uber Eats on the restaurant sector and the wider New Zealand economy, New Zealand Institute of Economic Research. http://hdl.handle.net/11540/12522.
Correa, J., Garzón, W., Brooker, P., Sakarkar, G., Carranza, S., Yunado, L., & Rincón, A. (2018) Evaluation of collaborative consumption of food delivery services through web mining techniques, Journal of Retailing and Consumer Services, 46, 45-50. DOI: https://doi.org/10.1016/j.jretconser.2018.05.002
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