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Winner-Takes-All Dynamics in the Online Gig Economy A Qualitative and Quantitative Analysis

Winner-Takes-All Dynamics in the Online Gig Economy A Qualitative and Quantitative Analysis

 
Susanne Klausing, University of Oxford
 
This paper investigates market dynamics in the online gig economy by combining a qualitative and quantitative approach. It develops a theoretical framework to identify monopolistic tendencies in the online gig economy and subsequently uses the Google Trends Application Programming Interface (API) to quantify and track market shares. Thereby, the paper addresses the shortage of available data on platform usage and suggests specific areas of action for policy makers.
The online gig economy consists of online gig platforms which connect online workers and clients and make a direct working relation between them possible. These platforms have been rising as an alternative form of work arrangement with approximately 44.7 million online gig workers worldwide in 2015 and an annual growth of 25% (Codagnone, Abadie, & Biagi, 2016; Kässi & Lehdonvirta, 2018). Online gig platforms can be theorised as two-sided markets as they connect distinct customer groups and facilitate value-adding interactions between them (Evans, 2003a). Studies investigating competition dynamics on two-sided markets point out that they are prone to become winner-takes-all markets (Barwise, 2018). In this case, the top-ranking economic agents receive a comparably large market share (Shupp, 2000). The high market concentration is claimed to be especially strong in the internet economy with eBay dominating the auction market and Facebook ruling the social networking market (Wu, 2010).
So far, no study has investigated market dynamics in the online gig economy. This lack of research can be explained by the limited data availability as online gig platforms are reluctant to disclose usage and user data. The nascency of the business further complicates market estimates (De Stefano, 2016; Kuek et al., 2015). However, getting an understanding of market domination in the online gig economy is particularly relevant due to the potential power platforms can wield over workers who are not protected by legal labour rights (Graham et al., 2017). Despite the political relevance, the current lack of data “hampers the provision of policy advice” (OECD, 2019). Thus, the present study asks:
Is the online gig economy a winner-takes-all market?
To investigate the research question, the paper elaborates on the biggest global English-language online gig platforms Upwork, Freelancer.com, Peopleperhour, Fiverr, Guru and MTurk (Kuek et al., 2015). To draw a more comprehensive picture of the online gig economy, the study identifies topical (e.g. platforms specialized on programming) and regional (e.g. platforms specialised on the American market) submarkets. As these have their own dynamics, monopolistic tendencies in submarkets are further investigated (Klepper & Thompson, 2006).
To this end, the determinants of two-sided markets being winner-takes-all markets are synthesized into a theoretical framework. The determining factors include network effects (i.e. an individual’s adoption of a good or service benefits other individuals using it or raises the other individuals’ incentives for adoption); single homing (i.e. the tendency to rely on one platform); market segmentation and product differentiation (i.e. the existence of different customer segments and products); congestion (i.e. crowding-out effects on the platform); as well as economies of scale and feedback effects (i.e. decreasing costs with increasing platform activity due to learning and feedback) as factors affecting market concentration (Chen & Tse, 2008; Duch-Brown, 2017; Eisenmann, Parker, & Van Alstyne, 2006; Evans, 2003b; Evans & Schmalensee, 2007; Farrell & Klemperer, 2007; Mayer-Schönberger & Ramge, 2018; Sun & Tse, 2007). After elaborating on these factors, the theoretical framework is applied to the online gig economy and it is examined to what extent the market features of the online gig economy match the determining factors for a winner-takes-all market. Subsequently, a quantitative analysis using Google Trends data attempts to examine market shares in the online gig economy. Google Trends is a service providing information on Google search query volumes and has been used as a proxy for economic activity in the platform economy (Choi & Varian, 2012; Wallsten, 2015). The service offers a broad coverage with 92% of internet users worldwide using the Google search engine (statcounter, 2019). The raw data is accessed using a Google trends API which allows access to the monthly, region-specific search interests. By using the API any volume of search interest can be compared in real-time.
The study provides important insights as it identifies determinants of winner-takes-all markets and analyses to what extent these are met in the online gig economy. By identifying factors fostering market concentration, the analysis points out concrete areas for countermeasures. It further quantifies the distribution of market shares in the online gig economy by introducing Google Trends data as a new measure to quantify and track monopolistic tendencies.
By shedding light on the market dynamics in the online gig economy and counteracting the shortage of public data on platform usage, the study adds to the literature on the gig economy and provides important insights for competition policy makers.

References

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