Introduction the question about what the effect of


            The sharing economy is stated as an economy in which the resources, human or physical, are shared among companies or individuals (Matofska, 2016). Among these resources are the human resources or human capital, which mainly consist of knowledge and experiences (Becker, 1994). The distribution of these individual resources among other people can be though. Upwork, a US-based digital platform, serves as a connecting element between individuals looking to disperse their resources and the companies and organizations looking for such resources (Upwork, 2018). This raises the question about what the effect of connecting elements such as Upwork has on the sharing economy. This is why this paper is going to discuss if the core activities of Upwork have any effects on the sharing economy. By first assessing Upwork as a platform and its main occupation to determine its position within the sharing economy. After Upwork’s position is revealed, some of their activities will be discussed and linked to a positive or negative effect on the sharing economy.



Upwork as a part of the sharing economy

            Upwork was formerly known as Elance-oDesk but re-branded in 2015. It is based in Mountain View, California. The platform is the result of a merger between two companies: Elance and oDesk, only Stratis Karamanlakis, one of the four founders of these companies is still named as a founder of Upwork on their website. The current CEO of the platform is Stephane Kasriel, who formerly held a position as Global Head of Consumer Products, Global Head of Mobile Business Development at PayPal and Managing Director of PayPal France (Upwork, 2018).

            Upwork is active in the freelancing industry, connecting freelancers from all over the world to companies or organizations in search of people with certain qualifications and skills fit their projects (Upwork, 2018). Platforms like Upwork are seen by some economists as a market in which main focus lies with connecting multiple parties whom otherwise wouldn’t be able to interact with one another (Gawer, 2014). There are many types of these markets, yet the one Upwork can relate to the most is the two-sided market. In this sort of market, there are two main groups, the benefit of one group joining the platform depends mostly on the size of the other group on the platform (Gawer, 2014). This reaction between the two sides can be compared with an indirect network effect (Hagiu and Wright, 2011, in (Gawer, 2014)). Yet it could be stated that Upwork is a multi-sided platform in which there are third-party connections, companies who wish to work together with the platform and expand it. For example, GeniusLink partnered up with Upwork, this created an addition of twenty million experts and five thousand skills to the platform (Geniuslink, 2018).


One of Upwork’s main actors are the individuals all across the world looking for a job or a project to contribute to. These individuals will benefit when there is more activity on the other side of the platform since there will be more jobs and projects available. The other main actor of Upwork would be the companies, organizations and other instances searching for employees, workers or temporary team members with particular skills. This group will benefit when there is a wide variety of individuals with diverse talents. Through this platform, these individuals can offer their services and thereby experience to companies and organizations. The way of working with individuals all over the world was noticed as before as the e-lance economy by Malone and Laubacher in 1998, with the development of Linux. To join Upwork, the interested parties have to go through the following process. First, both freelancers and employers have to sign up at Upwork. By signing up the freelancers let companies and organizations know they are searching for work and let them set their own price. On the demand side, the organizations and companies need to sign up to deliver the projects the hired freelancers have to work on. Upwork makes use of a system that sorts each freelancer that signed up on their skills and previous working experiences. When an organization or company wants to hire a freelancer for one of their projects Upwork shows them a selection of the freelancers who are most fitting to the project. The organization or company then can select the optimal freelancer out of the list presented by Upwork. As the project advances chats can be started and files can be shared through the Upwork platform. If the organization or company is satisfied with the work of the freelancer, the payments will go through the Upwork platform as well (Upwork, 2018).


  Upwork is currently connecting freelancers to twenty percent of the Fortune 500 companies (Corporaal & Lehdonvirta, 2017). Furthermore, Upwork has partnered up with Geniuslink, a company that focusses on improving customer experience on websites. This partnership offers Uplink direct access to more than twenty million experts with over 5000 skills (Upwork, 2017). The success of a platform as Upwork mainly depends on the number of users, so both the freelancers and the companies and organizations looking for work. This is relatable to network effects, where success is dependent on the number of users of a product or service (Birke, 2009). To increase the number of users, platforms use scaling strategies. According to Bonchek and Choudary (2013), the success of a platform’s strategy is determined by three factors. These factors are connection, attraction, and flow. Connection stands for the ease in which people can create content and interact with other content. When the connection process is smooth, the attraction will increase and draw more users to the platform. By this, the platform creates a network market for their users. Lastly, the attraction will cause a flow among the users. This means that there will be enough interaction between users and lead to co-creation of content. Upwork is getting their profits from the commission, they charge a percentage of the money the freelancers receive. There are two sorts of commission. At first, there is the straight pricing, which collects a service fee of ten percent per hourly wage. The second kind of commission is the tiered pricing. This commission is valid for as long as the freelancer is working for a client, this can be over a longer period of time with multiple agreements between the freelancer and client. The commission starts at twenty percent of the total wage received up to five hundred dollars. If the wage is more, for example, one thousand dollars, the commission will be twenty percent of five hundred dollars and ten percent on every dollar above five hundred and below the ten thousand dollars. If the total amount of money earned by a freelancer working for one client goes over ten thousand dollars, Upwork will charge five percent commission on every dollar above the ten thousand (Upwork, 2018).


            To recite the definition of the sharing economy, as stated by Matofska in 2016, an economy in which the resources, human or physical, are shared among companies or individuals. It is true that Upwork doesn’t share any physical objects. Yet, Upwork fits in this interpretation of the sharing economy mostly because the core activity of Upwork is linking freelancers with major companies or organizations. In other words, the platform is spreading human resources among companies or individuals. There currently is no claim from Upwork that it sees its platform as a part of the sharing economy. Although, some economists see the Upwork platform as a part of the sharing economy based on the fact that the platform stimulates the digital sharing of resources (Codagnone & Martens, 2016). The platform hasn’t violated any regulations yet. During the signing up process, there are multiple safeguards which make sure that any abuse of the platform can be prevented. For example, they use an identity verification before you can join the platform as a freelancer.  On top of that, the possibility of violations is being removed by the terms of service and policies handled by the platform. Furthermore, there is an active online forum in which any complaints or misbehaviors can be reported (Upwork, 2018).





The effects of Upwork on the sharing economy

            The connection between Upwork’s core activities and the sharing economy have been presented, what now remains is explaining how some of these activities will affect the sharing economy. That is why the hypothesis will be: Upwork will affect the sharing economy to some extent. Upwork’s activities will be assessed by creating four questions which later will be used to formulate an answer to the hypothesis. The first question will be about negative recommendations having an effect on the sharing economy. The next question will be about the effect of increasing amount of web-based alternatives on the sharing economy. The third will be about the rising competition between platforms within the sharing economy. Lastly, the matter of direct network effects within Upwork influencing the sharing economy will be treated.


Can fake negative ratings cause a decrease of the sharing economy?

            Uber, another company active within the sharing economy, makes use of the availability of cars in cities to serve as an alternative to the taxi (Cramer & Krueger, 2016). The concept is that everyone with a vehicle can be an Uber driver, this will create a close match between supply and demand. Yet to fully match supply and demand, Uber makes use of a driver-passenger matching technology. This system is based on the ratings of yourself as a customer and the potential drivers according to previous rides with an Uber driver. What if these same ratings would be applied to Upwork’s platform, instead of only matching through capabilities and experiences. Using this way of rating is also known as the reputation economy, in which reputations are seen as a kind of capital (Langley & Leyshon, 2017). This could improve the platform, but also harm the platform. For example, a study on the ratings on Yelp revealed that sixteen percent were fakes (Malhotra & Van Alstyne, 2014). Fabricated negative ratings can diminish the chances that companies will pick a certain freelancer. This could cause people to stop sharing their resources and result in a shrinkage of the sharing economy.




How will the increase in online services, like Upwork, have a favorable outcome for the sharing economy?

            The digitalization of society, the urge for everyone and anything to go online, has been characteristic for our time period. Especially the service sector is moving to web-based platforms or software (Arthur, 1994). This means that every service, performed by people, are replaced by online software or platforms which do exactly the same thing as their human predecessor. As a result of this people are laid off, just because they have become replaced by cheaper alternatives. Yet, the increase of these service platforms and software may be stimulating the sharing economy. When all these superfluous people are in need of work, some might sign themselves up as a freelancer at platforms like Upwork. By doing this there will be more skills and resources available and that could mean a growth for the sharing economy.



How does Upwork’s network effects increase the competition between human resource platforms and how does this affect the sharing economy?

 Indirect network effects are sated as when different sides of a network can benefit from the capacity and distinction of the other side (Birke, 2009). For Upwork the indirect network effects are different from a platform or network selling products or goods. Upwork is providing a service to companies and organizations connecting them to skilled individuals. Therefore, the result of their indirect network effects will be mainly about increasing the number of freelancers and skills. For example, the simplification of accessing the platform will cause or increase the network effects of a platform (Van Alstyne, Parker & Choudary, 2016). The increase in users will attract potential partners who wish to be a part of the platforms (McIntyre & Srinivasan, 2017). Upwork partnered up with Geniuslink for example, to increase the amount of skill they housed and gain access to five thousand skills in order to triple its talent network (Geniuslink, 2018). A direct result, to the examples given above, will be the increased value for all participants of the platform (Van Alstyne, Parker & Choudary, 2016). This will raise the competition between Upwork and other online markets for freelancers, primarily because gaining a competitive advantage would cause an ongoing process of increasing the number of users for the biggest platform (McIntyre & Srinivasan, 2017). The sharing economy will grow as a result of this. Mostly because a large user base attracts more people and skills, for example, Geniuslink partnering up with Uplink. Eventually, the amount of human resources will grow too.



How could direct network effects within Upwork improve the sharing economy?.

            Direct network effects as stated by McIntyre & Srinivasan (2017), are when the benefit of participating is dependent on the number of users with whom they can interact. The users of Upwork are the freelancers and companies, but for this part let’s focus on the freelancers. Millions of freelancers are signed up to Upwork, searching for work. This is the interaction between companies or organizations and the freelancers. Still, the definition of direct network effects states that the benefit is dependent on the amount of users freelancers can interact with. At Upwork the only way the individuals who signed up could contact each other is through an online forum. This online forum creates an opportunity for the freelancers to discuss all sorts of things such as projects, employers and even explain or teach some skills. If the skills from one freelancer could be taught to another, the number of people who possess the skill increases. This means there are more resources available to share on the platform and in the sharing economy.



            Upwork is an active part of the sharing economy by sharing human resources between freelancers and companies and organizations. Freelancers have to sign up to the platform to let companies know they are looking for work. The platform will find the best individuals for a project. Furthermore, Upwork is using their platform for every action between companies and the freelancers, from discussing terms to paying wages. By being viewed as a two or multi-sided market direct and indirect network effects can be spotted (Gawer, 2014). Upwork has removed any insecurities to the platform by making use of identity verification, this will prevent fake reviews or fake freelancers. Otherwise, it may cause people to withdraw themselves out of the sharing economy. Upwork’s network effects are making sure that the it remains the leading platform by increasing the number of users (McIntyre & Srinivasan, 2017). This will attract a variety of partners and therefore all sorts of skills, for example Geniuslink. Eventually, this will make the sharing economy grow. The direct network effects within Upwork could increase the number of individuals with a certain skill and in this way broaden the sharing economy. To conclude and answer the research question, Upwork is mostly causing growth for the sharing economy, up to a certain extent, by broadening the variety of skills made available as human resources in the platform.


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