The Impact of the platform economy on the employment relationship, Uber case study
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Contents
Chapter 1: Introduction 3
1.1 The study background 3
1.2 Research questions and objectives 7
Chapter 2: Literature Review 8
2.1 The Sharing economy and digital platforms 8
2.2 Networks and big data 10
2.3 platform capitalism 12
2.3 Uber platform economy workers 15
2.4 The Socio-demography of Under Drivers 16
2.5 Motivation for Uber workers in joining the platform 17
2.6 The working hours and pay for Uber service platform drivers 19
2.6.1 The view of payouts and the working hours 19
2.7 Uber service economy worker’s challenges 20
Chapter 3: Methodology 23
3.1 Introduction 23
3.2 The research philosophy 23
3.3 Research Strategy 24
3.4 The research Method and data Sources 24
3.5 Reasons for selecting the research method 25
3.6 Data Analysis 26
3.7 Benefits of Secondary data 27
3.8 Weakness for Secondary data use 27
Chapter 4: Findings and Discussion 29
4.1 The exploitations by the Uber platform on its workers 29
4.2 The benefits and challenges of Uber Surveillance for its drivers 33
4.3 How Uber sharing economy platform affect the local economy of taxi drivers 34
Chapter 5: Conclusion 40
Chapter 1: Introduction
1.1 The study background
Looking at current labour market dynamics necessitates a study on the impact of technologically driven change on labour organizations, especially in light of the growth of the internet’s involvement in job matching (Rogers, 2016, pp. 479). While the significance of the internet in labour matching was first investigated 15 years ago Bates et al., (2019), it is noted that the internet’s value is significantly rising since then. Therefore, the internet was first utilized as a bulletin for efficiently advertising job openings among job seekers Wang et al., (2017 pp. 130-150), but its current importance goes well beyond that (Schor, 2016). The introduction of online outsourcing platforms, which have elevated the internet from its role as a mere bulletin board and incorporated it into the organization of labour itself, is one of the most exciting new developments. Simply said, an Uber driver or an Upwork web designer is unlikely to be aware of the geographical location of the company for which they work. The virtual platform, which allocates labour and organizes earnings payment, is crucial for them. People’s knowledge of these platforms, however, is still at its start. The European Commission (EC) released the long-awaited Communication on the European Agenda for the Collaborative Economy (European Commission 2016) and that is in the year 2016 the month of June, which is a term that refers to the role of online platforms in enabling temporary access to goods and services, such as labour outsourcing.
The sharing economy was defined as ‘business models where activities are supported by digital sites that create an open marketplace for the temporary usage of commodities or services generally provided by private individuals in the supporting document. In terms of analyzing the influence of this modern economy on society, such a broad definition leaves us with very little to work with. Furthermore, the Communication states that there is still no agreement on terminology. The collaborative economy is also known as the ‘sharing economy,’ the ‘peer to peer economy,’ or the ‘on-demand economy,’ among other terms. They are highly charged terms with a variety of connotations.
Partnership or peer engagement is distinct from ‘sharing,’ and both concepts are distinct from the meaning associated with the concept of ‘on-demand.’ At the same time, the term “collaboration” isn’t usually associated with a marketplace where people can trade goods and services. Most outsourcing platforms, on the other hand, are regular market transactions that should be classified as “renting” rather than “sharing.” Wang et al., (2017 pp. 130-150), as a result, we suggest the name “platform economy,” because the underlying phenomenon is the use of internet platforms to lower labour outsourcing transaction fees and provide temporary access to goods and services (Bates et al., 2019). Outsourcing platforms provide a matching service, connecting labour demand with supply. They thus enable the market to organize labour access even in situations where using a matching service is too expensive or if market flaws necessitate reliance on institutions such as the employment relationship. This phenomenon has three significant elements. Platforms, for starters, give an algorithm that enables the successful matching of labour providers and users. Second, technological advancements have reduced transaction costs to the point that platforms can now handle micro-transactions (Rogers, 2016, pp. 479). Third, platforms provide services to mitigate or manage risks associated with market transactions, addressing market failures such as incomplete information on labour providers or the possibility of cheating. Reputation and monitoring systems, as well as basic insurance mechanisms and legal services against fraud, are among these services.
This diversity of the service economy platforms has an equally diverse range of impacts on the labour market. The distinctions between the types of service economy platforms discussed above help comprehend the various types of impact. For starters, platforms can enable the reorganization of operations that formerly relied on an employment relationship into self-employment activities. This is likely the most profoundly altering effect, and policymakers should pay attention to it. Successful platforms, on the other hand, have reformed industries that had previously relied on some forms of self-employment (Rogers, 2016, pp. 479). Uber is a good example, but another is CoContest, an Italian forum for interior designers. Other platforms may make it easier to provide services remotely, potentially leading to employment being offshored from local labour markets. MTurk, which pairs workers from all over the world, and also Contest, which matches (among others) Serbian designers with clients in Italy, are two examples of such impacts Schor, (2016), for example, lists local services like transport, dining out, hospitality, and art/entertainment as categories in which the sharing economy is anticipated to flourish, implying that the impact of offshore may not be as significant, at least in the medium term.
Platforms, even if they just restructure self-employment, promote competitiveness by lowering entry barriers, putting more pressure on salary and working conditions. Such is the situation with Uber, which pits experienced drivers against students or people on parental leave looking for a way to supplement their income regularly. Reduced entry barriers also lead to the blurring of physical boundaries between work and home environments, endangering workers’ health & wellbeing (Rogers, 2016, pp. 479). Fourth, platform reputational mechanisms lead to the increased marketization of the labour market. Working on these online job platforms includes the ‘begging and bragging’ rituals associated with modern academia, freelance journalism, and art creation.
According to Bates et al., (2019), the gig economy platforms like that of Uber frequently gets to talk about their role in the empowerment of entrepreneurship and also the creation of jobs. However, it has been identified that these platforms do not empower workers whereby has been widely witnessed from the Uber drivers strikes (Jarrett, 2016). It is noted that the Uber digital platform does not ensure empowerment of its workers who are the drivers as the entrepreneurs is at its odds and that is with the creation of the well-functioning market and this is more so at the odds with the ability of the platform to monetize this market and also in capturing value. As mentioned by Muller, (2019, pp. 167), the platform prioritizes the creation of a very efficient market and also its monetization, and hence often exploiting the workers as it gets to do so. The Uber platform economy exploits the workers since it has removed the free agency, the reduced bargaining power and also their rights, the platform had made the workers subservient to it and also increased dependency of workers on the platform. Therefore, this gets to affect the workers negatively as a result of this digital media which has denied the Uber workers their freedom as it is solely based on this platform. Notably, the drivers are greatly shortchanged by the Uber sharing platform and that is to the tune of about 40-50% (Rogers, 2016, pp. 479). This is through the entitlements that are accrued to these sharing platforms for every trip that the drivers make whereby this has been estimated to be much more. This is also because in the process whereby the drivers are on their working time (on the trip with the client) the accepted amount by the driver during the trip sometimes gets to drop off as the platform sometimes gives offers to the clients and this is not compensated down to the driver. Therefore, some of them end up making huge losses as they get to work by using the Uber sharing platform.
1.2 Research questions and objectives
To formulate the study, there must be research aims and objectives. The research aims and objectives help to guide the research in getting to know the area of focus to come up with the study findings. The fore the research questions and objectives are as follows;
Research Objective
To find out the inefficiencies for Uber and how its sharing economic platform affect its drivers and the local taxi drivers by focusing on Europe and America.
Research Questions
What are the exploitations for the Uber platform on its workers?
What are the benefits and challenges of Uber Surveillance of its drivers?
How does the Uber sharing economy platform affect the local economy of taxi drivers?
Chapter 2: Literature Review
2.1 The Sharing economy and digital platforms
As explained by Sutherland and Jarrahi, (2018, pp. 328-341), the sharing economy is the social and economic activity that is facilitated by platforms. This kind of platform is typically online sales or technology frameworks whereby Uber is the best example. Uber is a service economy that offers the services in travels through an online platform and hence ensuring much flexibility to its customers (Constantiou et al., 2017). Therefore, the digital economy is greatly emerging and that is why the companies like Uber are creating online structures which get to ensure that they can give quality services to their customers.
Therefore, the sharing platform economy is greatly being propelled with the development of IT and also the powerful information technology whereby there is a greater transformation of service. Therefore, in the service economy, it is noted that the internet is part of the strategy that the existing companies make use of to be more competitive as compared to other companies. As by Schor, (2016), for example, this can be noted in the transport industry whereby Uber is greatly utilizing the internet to be more competitive as compared to the local taxis. This is due to the flexibility that it ensures to the customers in terms of booking and accessing for example the Uber cars in various locations.
Malik and Wahaj, (2019 pp. 248-251), argues that in the current days, the “sharing economy “basically stems from several demand-side trends and that is the set of supply-side kind of technological changes. As explained by Arcidiacono, Gandini, and Pais, (2018), concerning the demand side it is noted that the advancing ecological consciousness leads some of the consumers into choosing borrowing o getting to reuse the goods over the purchase of new ones. Notably, there is a constant increase in urbanization and the people basically in the metropolitan regions can be able to find the sharing and renting chances more easily.
According to Wessel, Thies, and Benlian, (2017), also supports that the most important change which has resulted in the emergence and development of the sharing economy is technology. As by Cohen and Sundararajan, (2015, pp. 116), the improvement of data and also the analytics gets to make the cost of matching the buyers and also the sellers to be much lower as compared to the past decades. Also with the greater spread of smartphones, it is noted that people can have access to the sharing economy and get the services that they need at any time anywhere (Yaraghi and Ravi, 2017). Likewise, the common tracking GPS gets to allow basically for both better customer service (it is noted that Uber knows whereby to meet the customers). Notably, the scholars like the Uber digital reputation “ratings” can get to make a functional substitute and that is for the personal trust, getting to make more and the transactions possible (Arcidiacono et al., 2018). For instance, if the Uber drivers have five hundred reviews which are equivalent to the “five-star” review, it is noted that the rider may be willing to board the car for that driver despite even the point whereby he or she lacks the classic documents of trustworthiness and example the business license.
Taking all this together, it is noted that the changes resulted in the rise of the sharing economy as indicated by Geissinger et al., (2019, pp. 419-429), it is noted that the sharing economy services have been able to explode in popularity and that in the past few years with the expectation of this kind of trends to continue with the total value of the global sharing economy which is mainly predicted to increase to about 335 billion US dollars by the year 2025. This is due to the significant rise as it was only fifteen US dollars back in the year 2014.
As explained by Schor, and Fitzmaurice, (2015), argues that ride-sharing services like Uber gets to turn vehicles that would otherwise sit and remain unused in the on-demand taxis and helping the drivers to make a living. It is also noted that the inputs basically have some real costs and they are also being subjected to wear. Codagnone et al., (2016), also explains that the drivers get to face several opportunities cost basically for their time, however, the analysis of Uber indicates that the drivers tend to work for Uber more so during the periods when they would not have the work to do. Therefore, this indicates that the opportunity cost for time may be much relatively low. Therefore, the research studies indicate that Uber, Lyft and Sidecar are the most prominent ride-sharing services, and that is with Uber being the largest of the three by far. As to Henten and Windekilde, (2016), the Uber company was launched back in the year 2009 and in getting to the mid of the year 2014 it was having about 8 million users and about one hundred and sixty thousand drivers in total. The company by this year was operating in two hundred and fifty countries and hence one of the largest companies in the sharing service economy since its venture capital was valued at $40 billion in the year 2014.
2.2 Networks and big data
Networks and big data have been some of the most recent developments in the field of information technology. Dillahunt and Malone, (2015 pp. 2285-2292), this has made it much easier to communicate and also in keeping and handling various data properly. During the 1990s, most firms’ key IT problem was facilitating and recording more and faster transactions to increase business efficiency. Nowadays, in the age of the Internet, most of the emphasis is on delivering more information (e.g., documents, medical images, videos, gene sequences, sensor data streams) to systems, PCs, mobile devices, and living rooms more quickly and conveniently. As by Kim et al., (2019, pp. 1565), in the next decade, the challenge for businesses will be to better assess, exploit, and profit on all of these information sources while also integrating them into their operations. The Big Data era will arrive.
In today’s IT market, the term “Big Data” refers to a new generation of technologies and architectures that enable high-velocity data capture, discovery, and/or analysis to cheaply extract value from very huge quantities of a wide range of data. IDC believes that companies that can use Big Data to make real-time business choices will have a significant competitive advantage over those that can’t (Chiroma et al., 2018). This will be especially true in industries that are undergoing rapid transition and consolidation.
Big Data is about more than just adopting a new application or software technology like Hadoop for IT firms. It’s a major new IT domain that’ll necessitate new system architectures, administrative skill sets, and data management/access/use regulations over time. Dillahunt and Malone, (2015, pp. 2285-2292), the majority of companies, on the other hand, begin with smaller installations based on current resources. The network (both within the data centre and across the WAN) will play a crucial role in enabling speedy, sustainable expansion while also ensuring these systems are linked to the existing mission-critical transaction and content environments as Big Data efforts expand in scope and significance.
This is for example in the sharing economy which is a relatively new phenomenon of the digital era that has enabled millions of people to earn money by sharing their assets. Approximately 10,000 businesses are currently involved in the sharing economy. Even if you’ve never heard of the term “sharing economy,” you’ve almost certainly heard of some of the companies that are part of it. Companies like Airbnb and Uber are allowing ordinary people to profit from their common assets, such as their vehicles or homes. Big data helps the growth of these businesses in a variety of ways, and we’ll look at some of them today. Continue reading to learn about five ways that big data is boosting the sharing economy.
Therefore, the existence of big data ensures that the activities in the service economy are carried out effectively and this is with the processing of information at a very high sped and proper keeping of records. According to Schmidt, (2017, pp. 2016), this is for example in terms of GPRs information keeping, mapping and other special aspects with the help of networks which help to ensure the development of the service economy. Notably, the service economy benefits from Big Data by gaining important insights. Big Data is used by the service economy businesses to improve their marketing efforts methods and advanced business analytics.
2.3 platform capitalism
As explained by Dillahunt and Malone, (2015, pp. 2285-2292), Facebook, Google, Microsoft, Apple, Uber and Airbnb these firms are greatly getting to transform themselves into platforms; whereby they are the businesses that ensure the provision of a wide range of sectors have greatly transformed themselves into platforms. This is basically by getting to provide businesses with the hardware and software foundation for other people to be able to operate on. Therefore, this is one of the transformation signals concerning the main shift in the manner in which the capitalist firms get to operate and how they interact with the rest of the economy. Therefore, there is a greater emergence of platform capitalism.
As by Surie and Koduganti, (2016), the very first question is about the overall size of the on-demand economy, and estimates on this vary greatly. Lawrence Katz and Alan Krueger’s estimate, which concluded that platform employees made up only half of the labour force, is at the low end of the range of estimates. At the top end of the scale is the Pew Research Center’s estimate of 8% of the working-age population, based on a 2015 survey. Only workers who made the majority of their income through platforms were counted in a recent European survey, and they accounted for 4.3 per cent of the U.K. labour force. A plausible estimate of the platform civilian labour force, which includes both part-time and full-time workers, would be less than 5%. Even though these figures appear to be modest, the platform labour force has grown significantly. For example, policy analysts Diana Farrell and Fiona Greig discovered in a study for JP Morgan Chase that employment platform membership climbed tenfold between 2012 and 2015, a trend that continued through the last month of their research in 2015. Some industries have seen unusually rapid growth, such as the ride-hailing sector.
Other studies also have indicated that the platform economy greatly utilizes the existence of data and that is with the easily available applications, to monitor and also exploit the workers and this is for example in terms of what they paid when related to the services that they offer. Most of the platforms for example the Uber platform have the data regarding their drivers and with the applications that they have, they can monitor the drivers and the trips which they make at any time (Dillahunt and Malone, 2015, pp. 2285-2292). This also gets to ensure that they can control the amount that the workers get and hence forming platform capitalism. This has made also many companies rise and empress platform capitalism whereby this can be noted through the increase of companies that are getting into the service economy for example Lyft which is also operating like Uber.
Several threats have emerged as a result of platform capitalism in the service sector industry across the world. According to Surie and Koduganti, (2016), threats to worker well-being have already been discussed to a certain extent in most international research studies. Crowd working services like Mechanical Turk and Upwork are anticipated to increase outsourcing and exacerbate the long-term trend that leads “from the career, to the job, to the task” since they lower the cost of the transactions required to outsource even sophisticated labour. 22 The worry here is that prospective employees will increasingly be unable to access the job stability and internal labour markets that corporations historically supplied.
The worker’s exposure to entrepreneurial discourse that personalized recommendation workers also leads them to perceive the economic activity as a competitive game with little room for mutual assistance or labour solidarity is also a significant concern. Uber drivers (who frequently compete for customers) and Upwork (where workers bid against one another in winner-take-all situations) also exhibit this entrepreneurial individuality (Kenney and Zysman, 2016, pp. 61). Workers engage in what Brooke Duffy, author of (Not) Getting Paid to Do What You Love: Gender, Social Media, and Aspirational Labor, calls “aspirational labour”—unpaid work conducted in the hopes of achieving monetary success or even “micro-celebrity.” 23 In many sectors of the platform economy, the fact that some workers appreciate flexibility and control over their work schedules is likely to be a barrier to organizing.
Platform capitalism has also resulted to meant political threats which are greatly developing internationally. This is due to the retail revolution which was rested in part basically in a wave of shifts and deregulation in the antitrust regulations which started under the Reagan Administration of the platform firms which gest to presuppose the existence of a favourable regulatory and legal environment (Kenney and Zysman, 2016, pp. 61). This is the reason why Uber and other existing platform forms have been able to mount huge lobbying campaigns which mainly seek to configure the employment law and the regulatory policy and that is amongst the state governments. Following the National Employment Law Project for the year 2016, it is noted that Uber had about here hundred and seventy active lobbyists and that is in forty-four states, and hence dwarfing some of the largest business and also technology corporations. Most of the firms have also pressured the state legislatures in getting to adopt the “pre-emption” laws which get to deny the cities the legal arena for the establishment of the right of the workers.
Therefore, the struggles get to resemble in a very close manner to the campaigns and that is by the temporary help industry in the year 1960s, which also aimed at constructing a legal infrastructure which is friendly in the industry. However, it is noted that in some cases, lobbying through the platform films has been able to suffer the defeats which are much notable (Dillahunt and Malone, 2015, pp. 2285-2292). Therefore, the kind of capitalism that is being experienced in the service platform economy is because the internet has facilitated the ability for the existing companies to make much more profits and due to the existence of cheap labour which helps to facilitate the same.
2.3 Uber platform economy workers
Just like any other platform of economy, there must be the workers who get to facilitate the daily operations which are involved in the given platform economy. Therefore, in this case, the main workers are the drivers for Uber who drive the cars and ensure that the customers reach their destinations safely (Jaradat et al., 2015, pp. 592-597). Since the platform was launched in the United Kingdom back in the year 2013, it is noted that Uber’s pool of drivers has been able to grow exponentially. However, getting to identify the number of Uber drivers is very much complicated and this s basically with the fact that the drivers have a full description concerning their working hours; the labour which is being supplied with the drivers may greatly vary in weekly, daily or monthly basis. To be able to circumvent this kind of an issue, Schor, and Attwood‐Charles, (2017, pp. 12), gest to define the ‘active’ Uber driver basically as someone who gets to complete at least four trips in a particular month. Therefore, the driver is the main worker for this kind of platform economy and they are employed by Uber company to provide transport services to the platform customers.
Therefore, the Uber workers who are the drivers are being regulated by the rules that Uber has made and subjected them to. However, some of these workers are constantly claiming that the platform does not treat them well with several challenges that it poses on them. As by Wang et al., (2017 pp. 130-150), it has even resulted in strikes for example in the year 2016 in the UK whereby these workers demonstrated due to the harsh rules like surveillance that Uber makes on them.
However, in the industry that Uber operates, there are also other workers which have been affected. This includes the local economy taxi drivers who work to also earn a living from this kind of business (Cichocki, 2014). Therefore, the development of sharing platform economy for Uber has created many challenges for them and this is for example the high competition and lack of customers since most of them have moved to the Uber sharing platform.
2.4 The Socio-demography of Under Drivers
As explained by Wang et al., (2017, pp. 1-19), the Uber drivers rea basically among those people who are self-employed in their job including the taxi drivers who operate in the local economy for transportation. Most of the Uber drivers are basically between the age of 20 to 40 years and hence the overwhelmingly prime-aged relative to the general workforce for example in London. Concerning the broader taxi population gets to suggest that the partners with Uber mainly tend to be somehow younger as compared to the typical black cab PHV driver and that is London (Kenney and Zysman, 2016, pp. 61). As the drivers are average older as compared to the workers in London, it is however unsurprising that the rates for marriage are high amongst both the Uber drivers and also the broader taxi workforce, and also that both of the two groups are much more likely to have children. However, most of the drivers in Uber are men and this is due to the extreme underrepresentation of women. As indicated by Surie, and Koduganti, (2016), it is noted that the immigrants are over presented amongst the Uber drivers. According to Schmidt, (2017, pp. 2016), even though the immigrants are overrepresented mainly in the broader black cab and also the PHV driver population, whereby the share between the drivers for Uber is much higher.
2.5 Motivation for Uber workers in joining the platform
According to Schmidt, (2017, pp. 2016), concerning the employment history of the Uber drivers is that this is a permanent job for them since most of the drivers who join the platform are those who are jobless. Therefore, they can have a permanent job until the time that they decide to leave, be laid off or get fired. Therefore, because Uber drivers are having a permanent job working with Uber is one of the greatest factors that get to motivate them in joining the Uber platform and hence work with the company.
The workers for the Uber platform which is a sharing economy are also motivated by unemployment. According to the study carried out by Lenaerts et al., (2018, pp. 60-78), found pout that most of the workers get to join the Uber platform due to unemployment and hence they decide to join Uber and get a job. Therefore, this suggests that most of the divers in Uber did not partner with Uber as a result of failure to find a permanent job in the conventional labour market. Instead, it is noted that a number of them got to transition out of employment in the transport sector as a number of them were working in the services sector whereby this includes the distribution in the restaurants and the hotels.
According to Surie and Koduganti, (2016), his study found out also that some of the drivers also in Uber were basically in partnership with the platform mainly intending to make extra income. Basically in the aim of shedding light on where in the London income distribution Uber drivers were drawn from in the study, there was the focus in knowing their potential income. The researcher found out that the Uber divers have some other businesses that they carry out more so those that do not need much pressure or the other seasonal jobs (Graham and Woodcock, 2018). Some of them operate their businesses and hence they decide to get more income hence something that motivates them to get into the Uber platform for work and earn an extra income.
As Muller, (2019, pp. 167), his research carried out in the United States indicates that one of the main motivations basically for the Uber drivers joining the platform is mainly the perceived flexibility which the platform gets to offer them. It is true indeed since the drivers for Uber are not committed I got to drive a given number of hours, and they have the chance to go offline anytime that they need to. Notably, the drivers are in a position to take on trips basically through the traditional minicab operators or other given rider sharing applications at any time they like to do so. As by Bodie, (2017 pp. 17), the workers for Uber are also under any obligation in terms of accepting the trips while they are online in the Uber application. Therefore, this indicates how greatly the workers for the Uber platform have the flexibility with this job and also much freedom which is a motivating factor for most of the divers who are working with Uber.
The other motivating factor is that when as a driver in the Uber platform, there is a high guarantee that one can get the customers than when working for the local taxis. This is because Uber carried out its marketing and has made a great influence on the customers and hence is highly preferred (Thelen, 2018 pp. 973). Therefore, this is a motivation to the drivers in getting to partner with Uber as there is a high guarantee of customers and also with the reviews which they get it helps the drivers to grow and hence of the greatest thing that motivates the drivers in getting to work for the Uber platform.
Therefore, these imply that the typical Uber driver in London is not a marginalized worker compelled to cooperate with Uber owing to a lack of other options. According to Schmidt, (2017, pp. 2016), the majority of Uber drivers quit their regular jobs to start driving for the company, and the platform’s flexibility seemed to be what drew them in. According to Schmidt, (2017, pp. 2016), furthermore, while the majority of Uber drivers report low salaries in comparison to other London employees, nearly half claim their incomes grew after partnering with Uber, probably because many drivers switched out of low-paying blue-collar and service employees. Even though the majority of drivers appear to be satisfied with their work arrangements, a minority of drivers would prefer set hours and typical employment arrangements.
2.6 The working hours and pay for Uber service platform drivers
According to the information given by Bates et al., (2019), indicates that Uber drivers are paid for every trip that they get to drive concerning the predetermined formula; for example, in London, the drivers on the UberX gets to receive the base fare of 2.50 Euros, plus the 1.25 Euros per mile and also 0.15 Euros per minute while on the trip and that is with the minimum fare for any kind of trip that is for 5 Euros (Drahokoupil and Piasna, 2017 pp. 335-340). The system basically for dynamic pricing which is referred to as “surge pricing” makes the use of a multiplier (for example x 1.5) basically to the areas of high demand, which in turn gets to induce the significant spatial and also temporal variation in the fares. The payouts are being made in a direct way to the drivers and that is after the Uber platform gets to deduct its “service fee” which mainly stands at either twenty or twenty-five per cent and that depends on the time when the driver got to join the platform.
Surie, and Koduganti, (2016), in terms of variation for the driver’s payouts, it is noted that the payouts in the Uber platform are relatively stable and that is across the working time distribution, whereby this gets to suggest that the variation in the payouts does not get to reflect on the distinction in productivity between the full-time and the part-time drivers. Therefore, this means that the Uber drivers are basically utilizing extensively their choice over the working period and also in the adjustment of the number of hours that they work.
In comparison with the local taxi drivers, a research carried out by Kenney, and Zysman, (2019), UK indicated that the Uber drivers are paid better as compared to the local taxi drivers. This is because they can get many requests since Uber is a platform that is easier to use and preferred with many people and hence many requests from the customers than the local taxis who have to wait for clients in a given area or basically who depend on some specific customers.
Chapter 3: Methodology
3.1 Introduction
This part describes the research methods which were employed by the researcher to get the information required in the study. Therefore, this methodology part explains every aspect of the research methods, research strategy, data sources and data analysis for this study to help in the study formulation. This part will also get to explain the strengths and limitations of the research methods used in the study. This research method is therefore explained as follows.
3.2 The research philosophy
This part of the study is concerned with the nature of knowledge and how the research is developed. Its importance lies in the assumptions it contains, which are relevant to people’s perceptions of the world and are responsible for the study methodology and strategy choices and influences. Two alternative approaches to research philosophy are ontology and epistemology. In terms of how people think, the two terms have different meanings, especially when it comes to the researcher and the study’s period. The interpretivism philosophy will be applied in this study, which emphasizes that the researcher must acknowledge and consider the disparities that exist between social actors and people (Ørngreen, and Levinsen, 2017, pp. 70-81). This is the basis for identifying the need for this research, which is intended for a specific group of people who are workers in the service economy. Actors are people and their particular presentation of attributes, exactly as the actors in plays and movies, because of the differences in their experiences, needs, histories, and lifestyles that shape their way of living and personalities. Interpretivism’s most important components are symbolic interactionism and phenomenology. People’s perceptions of the world are addressed in the latter, whilst people’s ongoing observation and knowledge of the reality in which they live are addressed in the former. Individuals observe and interpret the actions of individuals with whom they contact.
The qualities are determined by the acceptance of interpretivism, a relativistic approach to ontology. When dealing with the way the world works, scholars assume ontology. The relationship between relativism and ontology leads to a wide range of reality interpretations, which is neither inaccurate nor correct (Ørngreen, and Levinsen, 2017, pp. 70-81). Because everyone has a different experience, behaviour, and choice, it’s important to look at things from many angles. Epistemology is the acknowledged knowledge in a certain field of study; epistemology is shared and defined in this study using a subjectivist approach. Because observations are influenced by individuals, there is no widespread, unaffected knowledge on the subject.
3.3 Research Strategy
The research will make use of qualitative research studies by focusing on the collection of secondary data. Therefore, the qualitative research approach involves the collection and the analysis of data which is informed of text, video or pictures and that is to help n the creation of an understanding through the facts, opinions and experiences given through the data collected (Kothari, 2004). Therefore, the research strategy will be used in gathering in-depth insights regarding the Impact of the platform economy on the employment relationship by focusing on Uber as the case study.
3.4 The research Method and data Sources
As early indicated, the research will be carried out by the use of qualitative research methods whereby there will be a focus on the collection of secondary data. This is by focusing on the use of secondary data from the existing literature materials which are the materials given by other researchers who have carried out their studies in this area earlier before. Therefore, the literature materials which will be used in this case will be obtained from the existing online libraries which include; Google Scholar, IEEE and Science Direct (Graham and Anwar, 2019). There will be the use of the research keywords to search for these materials and hence in the formulation of the study findings. Some of the keywords which will be used include; platform economy, relationship, Uber service economy, digital media platforms and many more. Therefore, through the use of these research keywords, the researcher can get the correct information that is required for this study since the literature material will be obtained. The search in the databases will also be customized with the age range. This is helping to search the latest materials written within the last twenty years as this will help in getting the latest materials for use with the latest information for the study to ensure its validity (Pandey and Pandey, 2015). In addition, the inclusion criteria, in this case, will be, the materials that are written within the last twenty years and have the information regarding the service economy. While the exclusion criteria will be the exclusion of the materials which have been written more than twenty years ago and do not have the information related to the service economy after the search is made by the use of the selected keywords.
3.5 Reasons for selecting the research method
In carrying out research, a given method is selected due to some reasons. Therefore, in this case, the researchers decided to make the use of qualitative research method by the use of secondary data due to some reasons and they include; the research method was preferred due to the nature of the study whereby the information can be easily accessed online and that is on the databases which have been described above. This is also the easiest research method and hence saving the research time and costs (Ørngreen, and Levinsen, 2017, pp. 70-81). The research scope is also wide and hence cannot be carried out by the use of primary research methods. This is because the research focuses on the Uber case study and there is no commonplace that the Uber drivers who are the main target can be accessed and most of them are in their busy schedules with the customers who want to travel to various destinations. Additionally, this is the period of the Covid-19 pandemic and the government rules require that people should avoid social interaction and hence maintain social distance (Pandey and Pandey, 2015). Therefore, it will be hard to access the respondents and at the same time is risky as people are greatly avoiding social interaction to avoid the spread of the pandemic. Therefore, this makes the researcher prefer carrying out the study by the use of secondary sources as the main source of data in the study formulation.
3.6 Data Analysis
After the information has been collected from the literature materials selected for use in the study formulation. The information has to be analyzed to make meaning. In this research study, the data will be analyzed and that is by the use of the content analysis method which is used to analyze the information which is the text from the materials used (Johnston, 2017, pp. 619-626). According to Scandura, and Williams, (2000, pp. 1248-1264), content analysis is a data analysis method that is used as the research tool for getting to determine the presence of some given themes, words or concepts within some given qualitative data in research. Therefore, through the application of content analysis, it is noted that the researcher can analyze and quantify the presence, relationships and meanings of such themes, certain words and concepts. Through this analysis method, the fact and arguments of the author will be analyzed and used in the formulation of the study findings and making the right conclusions.
3.7 Benefits of Secondary data
In the application of secondary data in research, some benefits are associated with the use of this kind of data collection method. The first advantage regarding the use of secondary data is that it enables the researcher to have an access to a wide range of information sources which helps greatly in the study formulation. As indicated by Brislin, (1976, pp. 215-229), secondary data sources are made of a wide range since there are many articles online and that is indifferent databases. Most of them have been carried out by different scholars and hence when they are compared they lead to the best information and with a very strong validity for the results as the data is compared from a number of the literature materials.
The other advantage in the use of secondary data is that the researcher can get more valid data and also is focused on the aspects that the researcher needs. This is because the researcher can customize the search for materials in the databases and hence something that allows him to be able to obtain only the kind and number of materials required (Noor, 2008 pp. 1602-1604). The collection of secondary data is also easier as compared to other research methods since there are no many costs that are incurred. The only costs incurred are the internet costs and this is cheaper as compared to primary data collection whereby the researcher has to travel from one place to another and hence taking much costs and time.
3.8 Weakness for Secondary data use
Even though secondary data has some advantages in research studies it also has some weaknesses. The first disadvantage is that the use of secondary data may lead to the lack of full research validity. This is because the data is obtained from secondary sources of data that have been researched by other research scholars who have carried out their studies in that area (Rogers, 2016, pp. 479). Therefore, the information may be outdated or invalid because the facts which existed in the previous years may not be the ones which are existing in the current time. In addition, the researcher is not able to apply his or her research variables (Kothari, 2004). Therefore, the secondary data research study variables used may not be the same as the one which the researcher could wish to use and hence the lack of data validity is something that may mislead the study. The other limitation is that the researcher obtains the information from the secondary sources of data and hence not the primary sources. This limits the validity of the data obtained as the researcher does not obtain the information directly from the people involved.
Chapter 4: Findings and Discussion
4.1 The exploitations by the Uber platform on its workers
According to research carried out, it is noted that even though the Uber platform economy gets to benefit its workers who are the drivers, it also gets to exploit them to a far much extent. This is not only in Uber but also for most of the app-based or the “gig” economy companies which are frequently dressed up in the talk concerning the “modern innovation” and also the 21st Century work”. Therefore, the precarious, contingent work in Uber is mainly nothing new. We have always had jobs which are low paying, insecure and dismissed basically as the “unskilled”. This is due to the systematic racism which is being witnessed amongst the Uber workers and this is more so in the UK and the exploitative economy. The Uber platform does not get to ensure equality regarding how it treats its workers in these platform economies. There is a lot of cases of racism amongst the drivers when it comes to partnership with Uber and during the working relationship with Uber whereby there have been complaints from the black drivers as a result of unprecedented treatment for these drivers from the Uber platform management (Rogers, 2016, pp. 479). Therefore, this gets to create many challenges for this kind of driver and also affecting their operations in this service economy. Therefore, it can be noted that in the service economy platforms like Uber, there is also the existence of racism despite that most of the activities are carried out in the applications and this has been one of the greatest challenges amongst the Uber drivers in this case who are the workers for this kind of service economy platform.
The Uber platform economy exploits the workers since it has removed the free agency, the reduced bargaining power and also their rights, the platform had made the workers subservient to it and also increased dependency of workers on the platform. Therefore, this gets to affect the workers negatively as a result of this digital media which has denied the Uber workers their freedom as it is solely based on this platform. Notably, the drivers are greatly shortchanged by the Uber sharing platform and that is to the tune of about 40-50% (Rogers, 2016, pp. 479). This is through the entitlements that are accrued to these sharing platforms for every trip that the drivers make whereby this has been estimated to be much more. This is also because in the process whereby the drivers are on their working time (on the trip with the client) the accepted amount by the driver during the trip sometimes gets to drop off as the platform sometimes gives offers to the clients and this is not compensated down to the driver. Therefore, some of them end up making huge losses as they get to work by using the Uber sharing platform.
As Wang et al., (2017 pp. 130-150), also argues that the only difference that exists between today’s platform economy companies like Uber is the claim that they do not get to play by the rules since they get to make use of digital applications to manage their workers, However, even though as many of these tech giants gets to remain unprofitable, it is noted that they have been allowed for the far long to shock responsibility and that is for the provision of the just and safe working conditions in which the workers can be able to thrive both on and off the job. According to Wang et al., (2017 pp. 130-150), in Uber, it is noted that there is a challenge in ensuring the workers’ rights and this has been positioned to be the modern challenge. However, in the event when we get to think about the challenges which are faced by the gig and also the application based workers like the Uber workers, who are people of colour, there must be some kind of learning made from the past to be able to ensure that this kind of economy can move forward. Most of the governments have also failed to solve the worker exploitation which is being witnessed in the Uber service economy platform and there are not much better significant rules which have been put in place to ensure that the workers are not exploited by these services economy platforms.
The Platform economy workers like in the ae of Uber are exploited in terms of what they receive as their payment. This is because these gig economy companies get to urge the rivers, independent contractors, the delivery people and other workers who get to build their business, take the direction from them and whose pay they get to set millions of small businesses which do not require the baseline advantages and also protections. They get to do this for example in Uber to shield themselves and that is from getting to take responsibility for their frontline workforce. Schor, (2016), the corporations then get to avoid paying the basic costs and this is for example the minimum wage, the paid sick leave, healthcare, the compensation coverage and also the litany of other major benefits for the employees. For most of the workers, it is noted that this kind of condition gets to serve to proliferate the inequality nationwide and also ultimately in getting to uphold the deeply flawed economy building upon the worker exploitation and also suffering. These claims are also justified by Dudley, Banister and Schwanen, (2017, pp.492-499), whereby he indicates that the Uber platform economy gets to exploit greatly their drivers and that is basically in terms of what they get as their payments. In most cases, this platform takes much more from the drivers and that is the commissions for each trip whereby the drivers get a less amount compared to the fact that they have to pay themselves, fuel the cars and also get to ensure that they are maintained always. Therefore, the Uber platform economy greatly exploits its workers in terms of pay as they get a little payment than what Uber tales sometimes do because of the application service that it offers to them in the service economy. Additionally, the Uber workers do not have the bargaining power as all the rules and matters concerning the rates which the drivers get are made by the company management. Even to some major issues concerning their pay, the workers cannot be able to negotiate with the platform and hence a good ground that the platform is using to exploit the workers in terms of pay and also their rights. This is also with the lack of proper policies which gets to govern the platform in most of the economies like the UK.
Therefore, according to Kenney and Zysman, (2016, pp 61), the gig economy platforms like that of Uber frequently gets to talk about their role in the empowerment of entrepreneurship and also the creation of jobs. However, it has been identified that these platforms do not empower workers whereby has been widely witnessed from the Uber drivers strikes. It is noted that the Uber digital platform does not ensure empowerment of its workers who are the drivers as the entrepreneurs is at its odds and that is with the creation of the well-functioning market and this is more so at the odds with the ability of the platform to monetize this market and also in capturing value. As mentioned by Muller, (2019, pp. 167), the platform prioritizes the creation of a very efficient market and also its monetization, and hence often exploiting the workers as it gets to do so. The Uber platform economy exploits the workers since it has removed the free agency, the reduced bargaining power and also their rights, the platform had made the workers subservient to it and also increased dependency of workers on the platform. Therefore, this gets to affect the workers negatively as a result of this digital media which has denied the Uber workers their freedom as it is solely based on this platform. Notably, the drivers are greatly shortchanged by the Uber sharing platform and that is to the tune of about 40-50% (Rogers, 2016, pp. 479). This is through the entitlements that are accrued to these sharing platforms for every trip that the drivers make whereby this has been estimated to be much more. This is also because in the process whereby the drivers are on their working time (on the trip with the client) the accepted amount by the driver during the trip sometimes gets to drop off as the platform sometimes gives offers to the clients and this is not compensated down to the driver. Therefore, some of them end up making huge losses as they get to work by using the Uber sharing platform
4.2 The benefits and challenges of Uber Surveillance for its drivers
As indicated by Surie, and Koduganti, (2016), the Uber sharing economy is good to the drivers but also something that ends negatively affecting them. This is for example the facial recognition technology that is used for the identification of Uber drivers. This has been greatly challenged in the United Kingdom whereby the App Drivers have mainly called for Microsoft to suspend the company’s use of the B2B facial recognition. As by Drahokoupil and Fabo, (2016), this was after several cases whereby the derivers complained about the misidentified drivers and proceeded to have their license for the operation which were revoked by the Transport for London. Therefore, this kind of case concerning failed facial recognition has made many divers lose their jobs and hence a challenge that is noted from the Uber platform. Notably, the electronic surveillance system for Uber does also not have the regulatory standard which has been set out basically around the workplace surveillance technology which the Transport for London encouraged Uber to implement. This surveillance also affects the divers through inequalities which have been reported in a great manner more so based on race and gender.
Even though the Uber surveillance of its customers has some challenges, it also has some positive impacts on the drivers. As indicated by Kenney and Zysman, (2016, pp 61), safety is much more important for the Uber platform delivers and even in other platforms. Therefore, the surveillance that is ensured by the Uber platform online for its drivers is very much necessary since it helps to ensure that the drivers are always monitored through the surveillance technology in the Uber platform. This helps to ensure that the drivers are always protected and even when someone gets an accident, the Uber team can be able to realize as the platform is enabled with this technology. Sometimes the driver gets attacked along the way and this is for example by the car hijackers. Therefore, through the Uber surveillance technology, this kind of risk can be prevented as the diver can raise a notification and the Uber team gets to stop the car through the tracking system that Uber providers for the Uber cars. Therefore, this greatly helps to ensure the safety of the drivers and the Uber car through the Uber surveillance technology on its drivers.
The Uber customers are also registered with their credit cards and they make use of the credit cards to pay their fares. Therefore, this animates the risk of the customers failing to pay or the risks of handling cash for the drivers. According to Wang et al., (2017 pp. 130-150), therefore, there is the safety of the drivers’ money is being ensured by the Uber surveillance for the drivers and the customers more so through the customer data and the cash transactions. Because Uber ensures that the customers pay through their credit cards, there is the safety of their money and also easy tracking of the customers in case anything happens to the drivers.
4.3 How Uber sharing economy platform affect the local economy of taxi drivers
The Uber digital platform development is also a greater challenge to the local taxi drivers. This is due to the devaluation of the local economy taxi drivers in terms of jobs loss and also loss of their customers. As indicated by Drahokoupil and Piasna, (2017, pp. 335-340), Uber is a digital platform that greatly ensures that all the activities involved in getting a taxi service are carried out online. This has negatively affected the local economy taxi drivers since they are not able to afford this kind of platform and hence getting to lose much of the customers to the Uber platform economy. Most of the local taxi drivers have even gone ahead to demonstrate has the Uber platform has destroyed their business and some of them going for a day without any customer. Graham and Woodcock, (2018), argues that, despite the efficiency which has been created by the Uber platform, it also affects the local economy taxi system as it is not able to ensure this kind of efficiency and maintain the competitive level which Uber has ensured. Therefore, this has made the local economy taxi drivers lose their jobs.
According to Dudley, Banister and Schwanen, (2017, pp.492-499), the Uber sharing economy gets to impact the local economy taxi system through the lower prices and the more quality services that it ensures. It also gets to ensure a high level of transparency and that is basically in terms of choosing drivers and the determination of fares. According to Kilhoffer et al., (2017), this has greatly made most of the customers abandon the use of the local economy taxi services and hence making the drivers suffer as most of them have lost their jobs in the taxi service system. Therefore, there is the unroyal price competition which has been created by Uber in the process and this is as it gets to provide lower prices as compared to the local economy taxi drivers.
There have been many studies on the effect of the Uber sharing economy on the drivers and it has been found that there are some similarities in the studies about the effects of the economy on Uber drivers. In many cases, the cases of the economy have been showing the positive effects only but the address of the negative effects has been received (Agarwal, Mani and Telang, 2019). Thus few findings have put focus on the negative side of the driver where they can be treated as victims of the Uber sharing economy and not be treated like suspects through surveillance and tight regulations. The Uber sharing economy has been helpful to the drivers in many ways. For instance, the number of drivers in the economy is huge in itself which means that there is a livelihood being made out of that economy (Harding, Kandlikar and Gulati, 2016, pp.15-25). The economy has been growing due to the rising need by the people to get to their destinations faster, the increased traffic and the slow public transport has also informed the need to have such surge in the number of drivers in the Uber sharing economy which has improved how the drivers finance their lives through Uber as a job service (Avital et al., pp. 1-7). The fact that Uber has been employing many drivers with an average pay rate as compared to other taxi companies is a sign that the Uber drivers would have a higher economic bargaining power than the others. This is because they can finance better lifestyles as compared to their colleagues working in the same industry but with different companies (Origo and Pagani, 2009, pp.547-555). Therefore, the lives of the drivers have been impacted positively by the Uber sharing economy as they can get employment and get good salaries in this matter as compared to the pay from other companies. The fact that the Uber drivers are many compared to other taxi companies is proof that the economic impacts on their lives are more positive in comparison with the lives of the other drivers (Zha, Yin and Yang, 2016, pp.249-266). The simplest fact of working is earning and any company which pays quite well as compared to others in the same industry, this is an indication of an upward progression in the matters of the drivers’ sensitive issues which help in building confidence and driving motivation for the drivers to work for the company (Wells, Attoh and Cullen, 2018). Therefore, to sum up, the significance of the Uber sharing economy to the economy of the drivers is that there is a definite earning of livelihood which makes the drivers able to facilitate and provide to their families and thus they can live a normal life because they have a source of income and therefore they can also participate in the nation-building instead of leaving many people sited and waiting for the government aid (Bansal, Sinha and Daziano, 2020, pp.225-236).
Looking at the data collected it is evident that Uber employs many people under the age of thirty and the percentage for this is 19% which is higher than the other companies who stand at only 9% (Hall and Krueger, 2018, pp.705-732). This means the young people have been given a chance in life by Uber as compared to the other companies who only employ a small number. Thus, the consideration of the different ages in the employment of the drivers by the Uber company means that they try to strike a balance where the young people are encouraged to take on jobs instead of waiting for the ones which might take time to come. In the labour market studies the reports have shown that almost 48% of the Uber drivers are college degree holders and this is not the case in the other taxi companies who only have a little percentage of 18% (Beer, Brakewood, Rahman and Viscardi, 2017, pp.84-91). This shows that college graduates have a primary source of income and that Uber has given them a chance to get a secondary source of income and this is one of the reasons. The other reason why Uber has a large number of college graduates as their drivers are because many of them might still be looking for their dreams or other jobs which concern what they studied in school. There is evidence of the Uber industry giving the local economies of where they exist a chance to promote innovativeness by having college graduates as drivers. The fact that Uber has been viewed by many studies as one revolutionary of the transportation service industry means that the lives of the drivers will also be taken care of and be improved in the same process (Rogers, 2015, p.85). Thus despite the criticism that the company currently receives it is a fact that the development of technologies and innovations that are going on more than any time in the history of the lives of humans is an indication that professional drivers will find a place in Uber where they can work with the better working conditions which will be put in place as a result of the changes (Berger, Chen and Frey, 2018, pp.197-210). Thus the change in technology and revolution means that the skill set of the drivers will be improved in the same way, this is because from them to work for the company they must have complacency with the innovations and the latest technology. This will mean that there will be more training and more education and this is the development of the persons for instance the drivers. Through Human Resource Development, the training and development of the pieces of training are one of the retention strategies of the employees and the retention comes with its benefits to the company and subsequent benefits to the employees (Calo and Rosenblat, 2017, p.1623). Thus the local economy will enjoy having more qualified drivers who will be more learned and can successively deliver better services as per the policies and the likeness of the people.
However, the Uber drivers in any place have been considered as independent contractors this means that there is no entitlement to a minimum wage, they can’t get paid vacations by the company, no training and development, no health insurance and many other benefits that the fully employed individuals get (Glöss, McGregor and Brown, 2016, pp. 1632-1643). This means that the drivers who use Uber as their primary source of income have to use their resources for example to get better training or even to go on vacation which of course will not be paid at the time when they are off work. This means that the Uber driver’s economy will surround a particularly defined pattern that may have negative effects on their lives (Harding, Kandlikar and Gulati, 2016, pp.15-25). Everyone dreams of a vacation, break off work and many other benefits this helps in refreshing the mind and thus increase productivity. However, because Uber is reluctant and rigid to change its working policies it has become even more difficult for the drivers to enjoy working with the company as it is not encouraging at all. The fact that some studies like one done in NerdWallet showed that the drivers would get benefits of healthcare which are worth almost 5,500 dollars in a single year plus other thousands in form of reimbursements in the mileage if the company would be providing them with the same benefits as the full-time employees (Chung and Wu, 2013, pp.97-107).
Furthermore, there have been reports of violence of passengers against the Uber drivers and this affected the drivers because as a result of the status f their employment they are not entitled to work protection. This means that the drivers with such experiences of violence will not be satisfied at the job place and thus their productivity will be lower (Dudley, Banister and Schwanen, 2017, pp.492-499). The physical harm, emotional and psychological torture affects the divers and they cannot be compensated for as most of the passengers get away with it, thus they have to see treatment and even counselling with their resources which in turn affects their economic performance as they spend on things which should not have been on their expense list and thus it hurts in all ways (Tang and Wei, 2020, pp.554-568). The motivation of the Uber drivers would be below not only because of the low income which they get while working for the company but also such the bad experiences that they get from working for the company. With such one can quit the job and thus can cause even more economic downfall of the persons especially when one quits and they do not have another work now they have to stay at home (Cramer and Krueger, 2016, pp.177-82).
Chapter 5: Discussion
In conclusion, it is noted that there has been much growth in the platform economy and this is due to the existence and development of the internet which gets to support the same. The platform economy makes use of online applications and these are being facilitated by the internet. Therefore, the sharing platform economy is greatly being propelled with the development of IT and also the powerful information technology whereby there is a greater transformation of service. As by Drahokoupil and Fabo, (2016), indicating that the service economy is noted that the internet is part of the strategy that the existing companies make use of to be more competitive as compared to other companies. As by Kenney and Zysman, (2016, pp 61), this can be noted that in the transport industry whereby Uber is greatly utilizing the internet to be more competitive as compared to the local taxis. This is due to the flexibility that it ensures to the customers in terms of booking and accessing for example the Uber cars in various locations. It was also noted in the study that the “sharing economy” basically stems from several demand-side trends and that is the set of supply-side kind of technological changes. Additionally, the advancing ecological consciousness leads some of the consumers into choosing borrowing o getting to reuse the goods over the purchase of new ones. Notably, there is a constant increase in urbanization and the people basically in the metropolitan regions can be able to find the sharing and renting chances more easily. The information which was also obtained from the literature review of the study indicated that with the greater spread of smartphones, it is noted that people can have access to the sharing economy and get the services that they need at any time anywhere (Arcidiacono et al., 2018). Likewise, the common tracking GPS gets to allow basically for both better customer service (it is noted that Uber knows whereby to meet the customers). Notably, the scholars like the Uber digital reputation “ratings” can get to make a functional substitute and that is for the personal trust, getting to make more and the transactions possible. For instance, if the Uber drivers have five hundred reviews which are equivalent to the “five-star” review, it is noted that the rider may be willing to board the car for that driver despite even the point whereby he or she lacks the classic documents of trustworthiness and example the business license (Yaraghi and Ravi, 2017). Big data has also facilitated the development of the service economy. According to Wang et al., (2017 pp. 130-150), Big Data is about more than just adopting a new application or software technology like Hadoop for IT firms. It’s a major new IT domain that’ll necessitate new system architectures, administrative skill sets, and data management, access, use regulations over time. Most of the companies, on the other hand, begin with smaller installations based on current resources. The network (both within the data centre and across the WAN) will play a crucial role in enabling speedy, sustainable expansion while also ensuring these systems are linked to the existing mission-critical transaction and content environments as Big Data efforts expand in scope and significance. For instance, the sharing economy is a relatively new phenomenon of the digital era that has enabled millions of people to earn money by sharing their assets. Approximately 10,000 businesses are currently involved in the sharing economy (Dillahunt and Malone, 2015, pp. 2285-2292), Even if you’ve never heard of the term “sharing economy,” you’ve almost certainly heard of some of the companies that are part of it. Companies like Airbnb and Uber are allowing ordinary people to profit from their common assets, such as their vehicles or homes. Big data helps the growth of these businesses in a variety of ways, and we’ll look at some of them today. Continue reading to learn about five ways that big data is boosting the sharing economy.
The service economy platforms like Uber, the research identified that workers who are the drivers are being regulated by the rules that Uber has made and subjected them to. However, some of these workers are constantly claiming that the platform does not treat them well with several challenges that it poses on them. This has even resulted in strikes for example in the year 2016 in the UK whereby these workers demonstrated due to the harsh rules like surveillance that Uber makes on them. Regarding the study carried out by Wang et al., (2017 pp. 130-150), it was identified that in the industry that Uber operates, there are also other workers which have been affected. This includes the local economy taxi drivers who work to also earn a living from this kind of business (Cichocki, 2014). Therefore, the development of sharing platform economy for Uber has created many challenges for them and this is for example the high competition and lack of customers since most of them have moved to the Uber sharing platform.
The study also focused on the benefits and challenges that Uber surveillance creates on its workers. It was found that even though the Uber surveillance of its customers has some challenges, it also has some positive impacts on the drivers. As indicated by Wang et al., (2017 pp. 130-150), safety is much more important for the Uber platform delivers and even in other platforms. Therefore, the surveillance that is ensured by the Uber platform online for its drivers is very much necessary since it helps to ensure that the drivers are always monitored through the surveillance technology in the Uber platform. This helps to ensure that the drivers are always protected and even when someone gets an accident, the Uber team can be able to realize as the platform is enabled with this technology. Sometimes the driver gets attacked along the way and this is for example by the car hijackers. Therefore, through the Uber surveillance technology, this kind of risk can be prevented as the diver can raise a notification and the Uber team gets to stop the car through the tracking system that Uber providers for the Uber cars. Kenney and Zysman, (2016, pp 61), therefore, this greatly helps to ensure the safety of the drivers and the Uber car through the Uber surveillance technology on its drivers. However, the technologies in the Uber application like facial recognition technology that is used for the identification of Uber drivers. This has been greatly challenged in the United Kingdom whereby the App Drivers have mainly called for Microsoft to suspend the company’s use of the B2B facial recognition. As by Drahokoupil and Fabo, (2016), this was after several cases whereby the derivers complained about the misidentified drivers and proceeded to have their license for an operation which were revoked by the Transport for London. Therefore, this kind of case regarding failed facial recognition has made many divers lose their jobs and hence a challenge that is noted from the Uber platform. Notably, the electronic surveillance system for Uber does also not have the regulatory standard which has been set out basically around the workplace surveillance technology which the Transport for London encouraged Uber to implement.
The other aspect which the study focused was on the study on how the service economy platforms exploit the workers. Therefore, in the case of Uber, it was identified that the Uber platform economy exploits the workers since it has removed the free agency, the reduced bargaining power and also their rights, the platform had made the workers subservient to it and also increased dependency on workers in the platform. Therefore, this gets to affect the workers negatively as a result of this digital media which has denied the Uber workers their freedom as it is solely based on this platform. Notably, the drivers are greatly shortchanged by the Uber sharing platform and that is to the tune of about 40-50% (Rogers, 2016, pp. 479). This is through the entitlements that are accrued to these sharing platforms for every trip that the drivers make whereby this has been estimated to be much more. This is also because in the process whereby the drivers are on their working time the accepted amount by the driver during the trip sometimes gets to drop off as the platform sometimes gives offers to the clients and this is not compensated down to the driver. As by Jarrett, (2016), there is evidence of the Uber industry giving the local economies of where they exist a chance to promote innovativeness by having college graduates as drivers. The fact that Uber has been viewed by many studies as one revolutionary of the transportation service industry means that the lives of the drivers will also be taken care of and be improved in the same process (Rogers, 2015, p.85). Thus despite the criticism that the company currently receives it is for a fact that the development of technologies and innovations that are going on more than any time in the history of the lives of humans is an indication that professional drivers will find a place in Uber where they can work with the better working conditions which will be put in place as a result of the changes (Berger, Chen and Frey, 2018, pp.197-210). Thus the change in technology and revolution means that the skill set of the drivers will be improved in the same way, this is because from them to work for the company they must have complacency with the innovations and the latest technology. This will mean that there will be more training and more education and this is the development of the persons, for instance, the drivers. Notably, there is a lot of cases of racism amongst the drivers when it comes to partnership with Uber and during the working relationship with Uber whereby there have been complaints from the black drivers as a result of unprecedented treatment for these drivers from the Uber platform management. Therefore, this gets to create many challenges for this kind of driver and also affecting their operations in this service economy (Jarrett, 2016). Therefore, it can be noted that in the service economy platforms like Uber, there is also the existence of racism despite that most of the activities are carried out in the applications and this has been one of the greatest challenges amongst the Uber drivers in this case who are the workers for this kind of service economy platform. Other research studies also justified that Uber sharing economy gets to impact the local economy taxi system through the lower prices and the more quality services that it ensures. It also gets to ensure a high level of transparency and that is basically in terms of choosing drivers and the determination of fares. According to Kilhoffer et al., (2017), this has greatly made most of the customers abandon the use of the local economy taxi services and hence making the drivers suffer as most of them have lost their jobs in the taxi service system. Therefore, there is the unroyal price competition which has been created by Uber in the process and this is as it gets to provide lower prices as compared to the local economy taxi drivers.
Therefore, even though the existence of the digital economy sharing platforms like Uber helping the workers in various ways, there is still much exploitation on them and this is due to the lack of proper methods to regulate this kind of activity. Therefore, concerning the information that was obtained, there is a research gap that was identified. There are much fewer research studies that have focused on how policies can be formulated to ensure that there is no worker exploitation in the sharing economy platforms like the Uber workers. Therefore, it is suggested that future research studies should get to focus on this area which has been given such little attention from the researchers.
Chapter 6 : Conclusion
The digital platform allows the interaction of different stakeholders, and for the attainment of platform efficiency, the needs of each stakeholder must be met. The inclusion of the multifaceted platform in labour regulation is the only way to achieve an optimal employment relationship within the platform. The issues on labour relations have to be balanced with platform owners being willing to compromise and consider and develop a system that manages its diverse workers. The different stakeholders are responsible for taking charge and placing the digital platforms responsible for their businesses to ensure positive integration between public and private services in the community. The digital platform managers should also recognise that the emergence of digital media threats such as deep fakes and digital disruptions are likely to compromise employment relationships. Greater security and authentication measures have to be put in place to control the degree to which anonymity within the platform will lead to quality and delivery compromises. The state and municipalities must also regulate the monopoly power of the digital platform. The degree of control these platforms have over the end-users is higher, and if not well managed, it leads to end-user exploitation. As such, provisions within the state should be made to ensure the firms correctly disclose their earning and workers are granted collective bargaining rights so that the platform benefits become transferable to them.
Chapter 7: Recommendation
The employment relationship in the digital platforms can need to be solved to improve these platforms’ efficiency. This is achievable through the labour regulation of the digital platform. Issues such as permanent deactivation of one’s account could be addressed by introducing a system in which a deactivation does not affect one’s rating until fair judgment is carried out. As such, employee’s grievances on unfair retrenchment or deactivation will be addressed. Another important measure that could be adopted is the extension of collective agreements that provide a wider employee category to include platform workers. The platforms could use their monitoring techniques to assess who should be termed as self-employed and part-time employees. Workers in the digital platform should be given collaborative rights, which will allow the platform employees to voice their grievances. High tech data security measures should be adopted to ensure that the private data of the platform users are safe from unauthorised access.
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