Quite simply, to the skilled, the prepared, the connected, in the well-resourced, go the spoils. Those with capital and skills are better positioned to prosper, differentially and over time, relative to those who start with less, if they can start at all. In platform livelihoods, reputation ratings serve as powerful signals to each individual new buyer about whether to choose a more or less experienced freelancer, driver, innkeeper, musician, etc. these ratings quickly amplify differences between the newbies and the superstars an application effect where good ratings and good work are self-fulfilling and compounding.
Finally, it’s worth comparing livelihood experiences, but not simply between individuals, or between livelihoods, or even between countries, but instead between pathways of progression and advancement. If patterns of adoption, impact, and use of these technologies (marketplace platforms and social commerce) follow those of other technologies, we should be attuned to ways in which the benefits and harms of such technologies do not accrue to all individuals equally. Several studies in this corpus of 75 show patterns of diversions and amplification, as outlined elsewhere in the technology literature (Toyama 2011; Tichenor, Donohue, and Olien 1970). Quite simply, to the skilled, the prepared, the connected, and the well-resourced, go the spoils.
Skills and capital are well-understood from observations of earlier technologies. Those educated and skilled do better in retail (Zollmann and Wanjala 2020; Kabanda and Matsinhe 2019); and perhaps do better in microtasking and freelancing as well (Anwar and Graham 2020). Those with resources to buy more cars, or open more properties for home sharing, may do better than those who are struggling to amass the capital to get involved (Ruiz-Correa et al. 2019). To be clear, this is not simply a case of barriers to access, but in changes to the velocity with which one can advance via platform labor or platform sales. Those with capital and skills are better positioned to prosper, differentially and over time, relative to those who start with less, if they can start at all.
But the new effect here is ratings. Reputation ratings, and even the counts on amount of work acquired in the past (D’Cruz and Noronha 2016), serve as powerful signals (Partnership for Finance in a Digital Africa 2019; Rani and Furrer 2019; Nastiti 2017; Selabe 2017; Garcia et al. 2020; Wood et al. 2019a; 2019b; Jack, Chen, and Jackson 2017; Anwar and Graham 2019) to each individual new buyer about whether to choose a more or less experienced freelancer, driver, innkeeper, musician, etc. These ratings quickly amplify differences between the newbies and the superstars, between those designated as trusted brands, and those that are portrayed as a greater risk. This is an application effect where good ratings and good work are self-fulfilling and compounding. Granted, professional reputations and track records have been a part of doing business for as long as there’s been business. Platform models foreground these reputations, requiring hypervigilance of all (Gray and Suri 2019), and codifying precarity for more users than not. To those with the scores go the new work, and new entrants must struggle and scratch to even get in the game (Malik, Nicholson, and Heeks 2018).
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D’Cruz, Premilla, and Ernesto Noronha. 2016. “Positives Outweighing Negatives: The Experiences of Indian Crowdsourced Workers.” Work Organisation, Labour & Globalisation 10 (1): 44–63. https://doi.org/10.13169/workorgalaboglob.10.1.0044.
Garcia, Liza, Teresita Barrameda, Jessamine Pacis, and Arlen Sandino Barrameda. 2020. “Digitization and Domestic Work: The Policy Environment in the Philippines.” Bengaluru, India: IT for Change. https://itforchange.net/platformpolitics/wp-content/uploads/2020/04/Philippines-Research-Report.pdf.
Gray, Mary L, and Siddharth Suri. 2019. Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass. Houghton Mifflin Harcourt.
Jack, Margaret, Jay Chen, and Steven J. Jackson. 2017. “Infrastructure as Creative Action: Online Buying, Selling, and Delivery in Phnom Penh.” In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 6511–6522. CHI ’17. Denver, Colorado, USA: Association for Computing Machinery. https://doi.org/10.1145/3025453.3025889.
Kabanda, Salah, and Fernanda Matsinhe. 2019. “Contextualist Inquiry into E-Commerce Institutionalization in Developing Countries: The Case of Mozambican Women-Led SMMEs.” Interdisciplinary Journal of Information, Knowledge and Management 14 (January): 325–42. https://go.gale.com/ps/i.do?p=AONE&sw=w&issn=15551229&v=2.1&it=r&id=GALE%7CA616904581&sid=googleScholar&linkaccess=abs.
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Nastiti, Aulia D. 2017. “Worker Unrest and Contentious Labor Practice of Ride-Hailing Services in Indonesia 1.” In Arryman Symposium. Jakarta: Buffett Institute, Northwestern University. https://www.edgs.northwestern.edu/documents/2017-nastiti—arryman-paper,-evanston-symposium,-may-13.pdf.
Partnership for Finance in a Digital Africa. 2019. “Micro-Entrepeneurs in a Platform Era.” Farnham, Surrey, UK. https://www.financedigitalafrica.org/wp-content/uploads/2019/04/FiDA-Micro-entrepreneurs-in-a-platform-era.pdf.
Rani, Uma, and Marianne Furrer. 2019. “On-Demand Digital Economy: Can Experience Ensure Work and Income Security for Microtask Workers?” Journal of Economics and Statistics (Jahrbuecher Fuer Nationaloekonomie Und Statistik) 239 (3): 565–97. https://ideas.repec.org/a/jns/jbstat/v239y2019i3p565-597n6.html.
Ruiz-Correa, Salvador, Itzia Ruiz-Correa, Carlo Olmos-Carrillo, Fatima Alba Rendón-Huerta, Beatriz Ramirez-Salazar, Laurent Son Nguyen, and Daniel Gatica-Perez. 2019. “Mi Casa Es Su Casa? Examining Airbnb Hospitality Exchange Practices in a Developing Economy.” ACM Transactions on Social Computing 2 (1): 2:1–2:24. https://doi.org/10.1145/3299817.
Selabe, William Kute. 2017. “The Sharing Economy in the Global South: Uber’s Precarious Labour Force in Johannesburg.” Johannesburg: University of the Witwatersrand. http://wiredspace.wits.ac.za/handle/10539/24466.
Tichenor, P. J., G. A. Donohue, and C. N. Olien. 1970. “Mass Media Flow and Differential Growth in Knowledge.” Public Opinion Quarterly 34 (2): 159–70. https://doi.org/10.1086/267786.
Toyama, Kentaro. 2011. “Technology as Amplifier in International Development.” In Proceedings of the 2011 IConference, 75–82. IConference ’11. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/1940761.1940772.
Wood, Alex J, Mark Graham, Vili Lehdonvirta, and Isis Hjorth. 2019a. “Good Gig, Bad Gig: Autonomy and Algorithmic Control in the Global Gig Economy.” Work, Employment and Society 33 (1): 56–75. https://doi.org/10.1177/0950017018785616.
———. 2019b. “Networked but Commodified: The (Dis)Embeddedness of Digital Labour in the Gig Economy.” Sociology 53 (5): 931–50. https://doi.org/10.1177/0038038519828906.
Zollmann, Julie, and Catherine Wanjala. 2020. “What Is Good Work? Perspectives of Young Workers in Nairobi.” Text report and accompanying slides. Nairobi, Kenya: The Mastercard Foundation. https://www.juliezollmann.com/are-new-jobs-good.