The Just and Democratic Platform?Possibilities of Platform Cooperativism

JULIET B. SCHOR AND SAMANTHA EDDY

Introduction

The Great Recession shone a bright light on structural problems that had been accumulating in the global economy for years: the acceleration of ex­treme inequality in the household distributions of income and wealth, weak demand, hidden unemployment, unsustainable consumer debt, and growing imbalances between rural and urban areas.

The core idea is that small-scale, personal economic activity becomes via­ble as a result of digital tools, matching algorithms, and crowdsourced reputa­tional data. These features overcome the long-standing drawbacks of peer-to- peer or person-to-person markets, such as costly search and risky exchanges.

Consumers reap benefits and individual providers can control their work lives in new and empowering ways (Castillo, Knoepfle, and Weyl 2018; Einav, Farro- nato, and Levin 2016; Horton and Zeckhauser 2016; Schor 2020; Sundararajan 2016). In particular, the “sharing economy” offered the possibility of giving workers control over their schedules, total hours of work, and the labor pro­cess itself. The promise is that individuals can do it themselves by participat­ing in this emergent, humane market (Fitzmaurice et al 2020).

Not everyone believed in the promise of the “sharing economy.” There has been widespread skepticism about some platform companies, particularly Uber, which has the largest labor force by a big margin. Some argued that the sharing sector represented the emergence of a hyper-predatory regime of labor control (Hill 2015; Rosenblat 2018; Scholz 2016b). Others foresaw a new frontier in the commodification and corporatization of everyday life and the destruction of urban quality of life (Morozov 2013; Slee 2015; see also the chapter by Stears in this book). A decade after its founding, many in the US have written off the sharing economy as a malignant force degrading work­ers and neighborhoods. Others still see potential in the technologies and peer-to-peer structure. The experiences of some European countries, which have subjected platforms to more stringent regulation, suggest that policies and impacts are not predetermined by economics or technology (Rahman and Thelen 2019; Soderqvist 2017; Thelen 2018). Since 2018, regulatory activ­ity protecting residents and workers has increased in the US, particularly in ride-hailing and accommodation. And after years of unsuccessful legal ef­forts to reclassify platform workers from independent contractors to em­ployees (Collier, Dubal, and Carter 2017), pioneering legislation to convert providers to employees has been enacted, although this fight is ongoing. It is possible that after a decade of regulatory arbitrage and nullification by the firms (Acevedo 2016; Calo and Rosenblat 2017; Collier, Dubal, and Carter 2018; Rahman 2016), the power of platforms is being reined in.

But this familiar turn to regulation, welcome as it will be, may not exploit the more transformative possibilities of the new technologies used by plat­forms in the sharing economy (Benkler 2004, 2006, 2013; Schor 2010). That may require a less traditional approach. In particular, the peer-to-peer (P2P) structure enabled by technology may not only make transactions more effi­cient, it may also do the same for democratic governance. This is the conten­tion of a small but growing movement for platform cooperativism (Scholz 2014, 2016a; Scholz and Schneider 2016). Platform cooperatives borrow some of the features of worker cooperatives, in particular worker ownership and governance. But because platforms typically operate differently than conven­tional firms, they also offer new opportunities and challenges. Platform co­ops raise the possibility that P2P marketplaces can support a new enterprise form that is capable of achieving greater economic justice and democracy than conventional firms.

Platform cooperatives are best understood as one type of firm within a larger, more pluralist economy. This vision counters the conceit of twentieth­century economic theory that the capitalist firm is optimal and that econo­mies should evolve toward a singular business form. Rather, it sees platform cooperatives as one type in a diverse ecosystem of ownership and governance arrangements that include small and large-scale commons, trusts, varied fi­nancial arrangements (public banks, crowdsourcing, credit cooperatives), small and owner-run businesses, nonprofits, networked enterprises, and oth­ers (Alperovitz 2011; Benkler 2006; Ostrom 1990; Piore and Sabel 2000).

This chapter draws on findings from our research on the sharing economy conducted in the sociology department of Boston College from 2011 to 2018. The research covered 12 cases of for-profit and nonprofit entities, including the first academic study of a platform cooperative.

"Sharing Economy” Practices: Goods, Space, and Labor Services

There are three main subsegments within the sharing economy: goods, space, and gig labor services, although this division is somewhat arbitrary, given that all exchanges take place in space and require both labor and capital.² The precursors of today's sharing economy are eBay and Craigslist, two peer- to-peer markets that were established in 1995 and familiarized users with the P2P structure (Schor and Fitzmaurice 2015). In addition, eBay pioneered the use of a crowdsourced ratings and reputation system, a feature integral to nearly all the commercial platforms and that many of its former employees went on to employ as founders of sharing economy sites (Stein 2015). The pairing of the for-profit eBay with the not-for-profit Craigslist is also notable, as it mirrors the mixed composition of the sector in its original incarnation. Both also began as marketplaces for used goods, responding to the surfeit of imported consumer items available at historically low prices (Schor 2010). By creating online markets for used mass-market goods, these platforms trans­formed used-goods exchanges, which had previously operated as informal, low-value markets.

The second category is space-sharing. Here the originator is Couchsurfing, which was started in 1999 and uses a gift exchange model for hosting trav­elers. Like successor sites such as Airbnb, Couchsurfing uses crowdsourced reputational data to build trust among potential hosts and guests. It has a mission to build connection among people across the world, and research shows that has been successful building friendships, although the strength of induced social ties declines with frequency of use (Parigi and State 2014; Parigi et al.

The third subsegment is labor services, also known as the gig or on- demand economy. This is a diverse segment, including ride-hailing and de­livery, caring labor, housecleaning, and errands or “handyperson” odd jobs.³ Uber reports an estimated 3.9 drivers globally, with perhaps one million in the United States. Care. com, the largest platform for caring labor, reports 13.9 million caregivers as of March 2019.⁴ There are also not-for-profits in this segment. Timebanks organize multilateral barter exchange on the principle that each provider's time is equally valued. Other examples include repair cafes and food exchanges (swaps, surplus redistribution, food preparation).

The diversity of business organization, exchange model, user type and structure, and mix of capital and labor has contributed to terminological and analytic ambiguity and controversy (Frenken and Schor 2017; Schor and Attwood-Charles 2017). Figures 10.1 and 10.2 categorize entities according to their profit-status, user structure (P2P versus B2C), skill level, and mix of capital and labor. Other relevant dimensions include the form of exchange (monetary, barter, gift, loan), medium of exchange (some sites create their own currencies), whether the work is done offline or online, and whether the customers are individuals or businesses.

The earliest term for the sector was “collaborative consumption” (Botsman and Rogers 2010), which focused on arrangements that increased the utiliza­tion of existing assets and included sharing space (e.g., accommodations and

Structure

Peer-to-Peer Business-to-Consumer

For-profit

Not-for-

Profit

Figure 10.1. Capital platforms.

Figure 10.2. Labor platforms.

offices) and goods (e.g., car rentals, household items). Some analysts reserve the term “sharing economy” for this type of exchange, whether monetized or not, because it involves shared use of the asset across time (Frenken and Schor 2017). However, others argue that if a rental fee is charged, the practice is not sharing because it is done for monetary gain (Belk 2007). In practice, the term has been used indiscriminately and incoherently to encompass nearly all platforms that use matching algorithms (Schor and Attwood- Charles 2017). As some platforms became increasingly predatory toward their workers, the use of the word “sharing” became less defensible and declined in favor of terms such as the gig and on-demand economy, for labor platforms, and the platform economy (Kenney and Zysman 2016) for the entire sector. However, those terms are both broader (including B2B and digital labor, as well as social media and retail sites) and narrower (excluding nonprofits). The term “sharing economy” has traditionally been used to refer to both for- profit and not-for-profit consumer-oriented P2P entities of the three types discussed above (goods, space, and labor). Because that is the segment that we have focused on in our research, that is the term employed here. However, it is important to note that describing commercial entities such as Airbnb or Uber as “sharing” companies can serve to obscure their antisocial practices.

A Disruptive Innovation

Platform technology has been hailed as a disruptive innovation that will yield welfare for producers and consumers in these multisided markets (Ro­chet and Tirole 2003), as well as additional common good claims.⁵ There is widespread agreement that these firms have been disruptive, but observers differ in their analysis of why. Some argue that political economy factors ac­count for the success of the major platforms, in particular the ability to ig­nore regulations and to misclassify workers as independent contractors and other factors related to market and political power (Calo and Rosenblat 2017; Collier, Dubal, and Carter 2017; Dubal 2017; Rahman and Thelen 2019; Vallas 2019; van Doorn 2017). However, the viability of platforms in countries where they have conformed to regulations suggests that this is not the whole story (Rahman and Thelen 2019; Soderqvist 2017; Thelen 2018).

The alternate approach focuses on the novel technological features of platforms. Most important is that these technologies render peer-to-peer markets more efficient and therefore more feasible. Three aspects of the technology are salient. First, platforms reduce the transaction costs asso­ciated with exchanges by organizing electronic payments and insurance, mobilizing GPS technology, and facilitating easy entry and exit of suppli­ers. This reduces setup and financial outlays for sellers to engage in income­generating activity. Second, algorithms make efficient matches between buy­ers and sellers and reduce search, a previously costly activity in P2P markets on account of the heterogeneity of sellers. And third, the platforms gather crowdsourced reputational information to create trust among strangers, which enables a key feature of multisided markets—namely, that they en­able “stranger sharing” (Schor 2014). (The classic contribution on new forms of sharing is Benkler [2004], who uses the term social sharing.) Historically, stranger sharing has been limited on account of the risks of transacting with unknown others. The presence of both brokers and other intermediaries and trusted brands can be understood partly as ways to mitigate the risks as­sociated with exchanges among unknowns. Crowdsourced reputational data has the potential to perform a similar function and increases willingness to transact with strangers.⁶ The combination of these three factors results in lower barriers to entry and enhanced viability for single-person producers, as simple economic analysis can show (Einav, Farronato, and Levin 2016). Some economists have even gone as far as to predict that it heralds the “end of employment” (Sundararajan 2016) although that seems unlikely given that the efficiencies of the technology are less relevant for complex production processes that require extensive coordination. However, platform technology is well suited to services, which currently employ a majority of the US labor force. Thus, the question arises: Can these digital innovations be an enabling factor for a substantial sector of the economy to be organized as independent entities with substantive control over their conditions of production?

The hope that platform technology will result in viable, nonpredatory peer-to-peer markets runs counter to the view that technology markets have a tendency toward monopoly (Dube et al. 2018; Kahn 2017). Dominant firms such as Google, Facebook, and Amazon are considered to be beneficiaries of network effects (i.e., a cost structure that declines with additional users). In a monopolistic market, the platform can engage in predation and manipu­lation of users, thereby undermining the possibility for viable independent production (Calo and Rosenblat 2017; Rahman 2016). This is less of an issue in the sharing sector than in online tech markets. There are some genuine net­work effects—for example, on lodging sites. However, many of the services on offer (ride-hail, delivery, caring labor) are local (Horan 2016), which cur­tails network effects. Furthermore, these markets differ from Facebook and Google because those firms are selling their own products. Sharing platforms are intermediaries among independent producers and consumers. (Amazon is a hybrid in this respect.) Even if the platform is large, if it can facilitate an ecosystem of small or independent producers and if it is democratically owned and/or governed, it can serve their needs.

Labor Outcomes on For-Profit Platforms

One decade in, have platforms met the promises of the sharing economy dis­course? For consumers, there has been clear benefit, especially in ride-hail, lodging, and delivery, through lower prices and increased supply. For work­ers, the picture is mixed, although it is difficult to quantify outcomes because of a lack of data from the platforms and the casualness of this type of em­ployment. The literature is plagued by Uber-centricity, and while ride-hail does comprise a large segment, it is unique in a number of ways (Schor et al. 2020; Ticona and Mateescu 2018). The research is especially limited on higher-skilled providers and caring labor, despite the latter being the larg­est category of earners in the sector (Ticona, Mateescu, and Rosenblat 2018). Furthermore, conditions in this sector change rapidly, as platforms can easily alter compensation, incentives, rules, and terms of service, and many do so frequently. However, some conclusions are possible. We address three main areas: wages and compensation, autonomy and labor process, and gover- nance/voice in the firm.

With respect to wages and compensation, the picture is mixed, with marked differences across skill level and between capital and labor platforms. In general, the relatively high wages of the early years have been reduced as more providers join platforms. However, on a number of platforms, earnings are comparatively good. For example, on TaskRabbit, the platform we have studied, hourly wages remain high and workers are generally satisfied (Schor et al. 2020). Similarly, we have found that earners on “capital” platforms such as Airbnb are earning substantial sums and express high levels of satisfac­tion; see also Farrell, Greig, and Hamoudi (2018). By contrast, in ride-hail there is accumulating evidence of a race to the bottom, as the dominant plat­forms squeeze drivers' earnings (Horan 2016) and exert more control (Rosen- blat 2018). Studies of some of the nation's largest cities reveal that full-time ride-hail work is common, and earnings after expenses are often below the hourly minimum wage (Parrott and Reich 2018; UCLA Institute for Research on Labor and Employment 2018). Bank account data reveals a 53 percent col­lapse in monthly driver earnings between 2014 and 2018 (Farrell, Greig, and Hamoudi 2018). Journalistic accounts and qualitative research have docu­mented deteriorating conditions, with drivers sleeping in their cars, going deeper into debt, and expressing tremendous frustration with the growing share of revenue being extracted by the platforms (Robinson 2017; Streit- feld 2019). Delivery work appears to be on a similar trajectory, with declin­ing income for workers and growing evidence of discontent. We have found that platform outcomes are much better for supplemental earners than for those attempting to make full-time livelihoods (Schor et al. 2020). Across platforms, supplemental earners have safer conditions, greater job satisfac­tion, and often higher hourly wages than those who are dependent on their platform earnings to pay their basic expenses.

On questions of autonomy, control over schedules, and conditions of work, there is also mixed evidence. The opportunity to work without a boss and with control over one's own schedule and conditions of work has been a major attraction for many platform earners. For supplemental earners, those aspects of the experience are mostly realized and highly appreciated. On the other hand, dependent workers lose flexibility, and while they continue to appreciate the lack of a “boss,” in the most predatory sectors (e.g., ride-hail and delivery), they are more subject to “algorithmic control” (Rosenblat and Stark 2016) and the discipline of the market (Schor et al. 2020). Dependent workers are more compelled to conform to demand-based schedules that maximize their earnings, and on the lower-wage platforms they must work very long hours. Thus, they lose a good deal of the flexibility of short and personalized hours. However, except among the most exploited dependent earners, autonomy remains a positive feature of platform work. There are additional downsides to dependent work such as a higher likelihood of ac­cepting jobs that pose risk, either to personal safety or in terms of the finan­cial payoff (Ladegaard, Ravenelle, and Schor 2022; Ravenelle 2019; Rosenblat 2018). We find that supplemental earners are more likely to disregard ratings and flout company rules in order to ensure their safety or do the work as they prefer. Dependent workers describe more desperation and precarity, even if they prefer platform work to other options.

Finally, on the question of governance and voice, we also find variation over time and across platforms. In the early years, and especially outside of ride-hail, many earners felt heard and part of a community. That has changed as platforms have attempted to grow and increase revenue. On larger plat­forms that provide little “customer service” for earners (such as Uber), work­ers have voiced strong frustration with the lack of support and the absence of voice. Indeed, some platforms have become notorious for failing to consider earners' situations and experiences. For example, a three-day strike by Insta- cart delivery workers in the fall of 2019 was quickly met by the company with a pay cut. While some platforms articulate a discourse of “partnership” with earners, there are almost no formal mechanisms in the sector for effective voice. This is central to what platform cooperatives can offer, as we discuss below.

Race and Class Inequality

The discourse of disruption associated with the emergence of the sector sug­gested that sharing platforms would undermine long-standing inequalities of race and class by providing open access with low barriers to entry. Econ­omists Samuel Fraiberger and Arun Sundararajan (2017) argued that low- income households would benefit disproportionately from the opportunity to rent out assets. However, a growing body of research suggests that racial and class inequality is reproduced on platforms (Ticona and Mateescu 2018; van Doorn 2017). While there is some evidence of reduced barriers (e.g., there are more women ride-hail drivers than taxi operators), most studies find discriminatory behavior by race. We find that the platform sector is repro­ducing a hierarchy of outcomes based on skill and capital that parallels the legacy labor market. A study of TaskRabbit found that the algorithm is less likely to recommend Black Taskers (Hannak et al. 2017), perhaps because they receive lower ratings. Another study of TaskRabbit in Chicago found that low-income residents were disproportionately unlikely to be earning on the platform and that Blacks, and especially Black men, received lower ratings (Thebault-Spieker, Terveen, and Hecht 2015). In our analysis of outcomes on Airbnb across 10 US markets, we find that while residents of neighborhoods with more non-white households are more likely to list their properties, their outcomes are worse on nearly all dimensions than counterparts in areas with higher white populations. Hosts get lower prices for their listings, book less frequently, and receive lower ratings (Cansoy 2018; Cansoy and Schor 2019).

The platforms have also been characterized by “opportunity hoarding” with respect to education and employment status (Schor 2017). From the beginning they have attracted earners with high education levels. Because the kinds of activities done on sharing platforms (driving, cleaning, handy­person, errands) have traditionally been done by people without college educations, this represents a crowding-out effect by educational credential. While there has also been an expansion of demand for these services, in ride­hail and lodging traditional taxi drivers and hotel cleaners seem to have lost out (Dubal 2017; Zervas, Proserpio, and Byers 2014). Hoarding by employment status occurs because of the prevalence of platform earners who hold other full-time jobs (Schor et al. 2020).

While the dystopian fears of some critics are likely overblown, the opti­mistic accounts of the early days are also inaccurate. The track record of plat­forms on issues of work and income suggests that while they have been vital for some participants to earn extra money, they are failing as a new source of full-time livelihood. The question of whether the downward trajectory ex­perienced by ride-hail drivers will be replicated on other platforms is also still unanswered. It is also worth noting that platforms have taken advan­tage of their political clout both to evade existing regulations and restruc­ture the regulatory environments in which they operate (Calo and Rosenblat 2017; Collier, Dubal, and Carter 2018; Rahman 2016; Stemler, Perry, and Haugh 2019; Thelen 2018). While the bulk of the regulatory change has benefited the platforms at the expense of legacy industries and worker protections, more recently that has been changing, with the institution of minimum wage guarantees (in the case of New York City ride-hail drivers), data-sharing re­quirements, and stricter enforcement of limitations on short-term rentals. However, while regulatory action is to be welcomed, it is unlikely to fun­damental change the political economy of the sector. Large platforms will remain dominant and will mainly operate in their own interests. A deeper transformation of power will require new enterprise structures. In the early days of the sharing economy, there was considerable enthusiasm and hope that nonprofits were a dynamic form with a compelling economic model and the ability to scale rapidly. Let us turn now to those experiences.

Are Nonprofits the Alternative?

In each of the three subsegments of the “sharing economy,” there are non­commercial entities engaged in similar activities to the commercial compa- nies.⁷ The nonprofits also promised many of the benefits that were expected to flow from platform technology: the expansion of P2P exchange, putting idle capacity to use, safe stranger exchange, and meeting needs the market was failing to address. While the activities of the nonprofit segment have not resulted in the negative externalities (e.g., congestion, rising rents) associ­ated with a number of the for-profit companies, in the United States they have largely failed to scale and many have failed altogether.⁸ Given that many of these sites used similar technology to their commercialized comparators, albeit in simpler, lower-cost versions, this divergence in trajectory needs ex­planation. In our research we have identified two factors to account for the slow development of this sector: a lack of instrumental value for users, and practices of social exclusion (Attwood-Charles and Schor 2019; Fitzmaurice and Schor 2018; Fitzmaurice et al. 2020; Schor et al. 2016).

All the nonprofit sites were founded to promote social benefits. These include reducing inequality and bridging social class (timebanks, surplus food redistribution, goods gifting), lower carbon and eco-footprints (used- goods loaning and exchange sites, repair efforts, most food-related efforts), and building community (nearly all). Yet many have failed or grown slowly despite their appealing missions.⁹ Among our cases, the swap failed alto­gether (Fitzmaurice and Schor 2018), the timebank had limited trading vol­ume (Dubois, Schor, and Carfagna 2014), and the makerspace was success­ful but highly socially and culturally exclusionary (Attwood-Charles 2017; Attwood-Charles and Schor 2019). In the first two cases, many participants joined because of ideological commitment to mission and values, but they were not motivated to make trades because they had no need for the goods and services on offer. Some timebank members treated it like a charity activ­ity, accumulating hours for services they performed with no desire to spend them. Food-swap participants left events with their own offerings. The lack of instrumental value for users has also been found in case studies of other nonprofits. Bellotti and colleagues explained low trading volume in a Cali­fornia timebank by a mismatch between ideologically and instrumentally oriented participants (Bellotti et al. 2015, 2014). A study of a Finnish goods and service exchange site for university students found that while they ap­preciated the goals of the site it offered limited utility (Suhonen et al. 2010). A study of neighborhood initiatives in the UK designed to create innovative, nonmonetized markets had similar findings (Light and Miskelly 2015).¹⁰ A US national survey of sharing practices found that fewer than one-third of respondents indicated they were interested in engaging in higher levels of sharing of tools and household items.¹¹ This is likely due in part to the low cost of durable goods in the US (Schor 2010, ch. 2) in comparison to the time and inconvenience of P2P trading.

In some cases, the structure of the market is responsible for low activity.

This was especially the case in the timebank. A key principle of timebanks is that every person's time is valued equally. While this is an ideologically appealing attraction that members frequently referenced as a motive for joining, in practice they are reluctant to price their own specialized skills at the wage level associated with generalized skills such as driving, child care, or household help. Furthermore, many members failed to offer the valuable skills they had (legal advice, coding) in preference to their amateur avoca­tions. These practices reduced trading volume and the objective of bridging social class.

Socially exclusionary practices in these sites also contributed to the ab­sence of instrumental value. One example is that critiques of capitalism, which were common, included a critical attitude toward money itself. Ex­changes in gift, barter, or alternative currencies were sacralized, in contrast to the profanity of trades in legal tender.¹² Some members of the timebank we studied aimed to live in what one termed a “de-monied” state. At the maker­space we found that trades (for help) took place using both money and beer. The former was used for “profane” trades between high-status makers and ordinary participants; the latter was the “sacred” medium of choice among an exclusionary elite of highly-skilled makers (Attwood-Charles and Schor 2019). More generally, the critique of money is evidence of the class privi­lege of participants on these sites, as their comfortable lifestyles made this rejection possible (Bourdieu 1984). By conflating the medium of exchange with the social relations of exchange, many nonprofit sites failed to attract participants who had urgent needs for income, in contrast to the for-profit platforms that offered easy opportunities for earning.

We also found evidence of widespread practices of social exclusion across our sites, which were highly skewed by class and race. The sites were all ra­cially segregated, with very few or zero African Americans and Latinx par­ticipants. There was also strong gender segregation across and, in the case of the makerspace, within the site. Education levels were not merely high but stratospheric. The most extreme case was the timebank where all respon­dents had a BA degree, more than half had a master's level degree, and more than half had at least one parent with a graduate degree. The high cultural capital of participants led to a variety of snobbish and distinguishing prac­tices, such as the rejection of trading partners on account of bad grammar or unprofessional profiles, or in the food swap for failure to adhere to new foodie tastes (Carfagna et al. 2014;Johnston and Baumann 2007; Fitzmau- rice and Schor 2018). At the makerspace, cultural capital took the form of ex­treme “distancing from necessity,” with exotic, impractical, and idiosyncratic creations. Functional making and repair (valuable to income-constrained households) was largely invisible and clearly devalued (Attwood-Charles and Schor 2019).

While the relative lack of instrumental value has inhibited the growth of the nonprofits, they do have a strong asset that a number of the for-profit platforms have largely forfeited—credible claims to deliver multiple com­mon good benefits. The desire for fair economic outcomes, sustainable eco­logical impact, and more social connection is widespread among the popula­tion, especially among younger generations. We found this was not only the case with respondents in our nonprofit sites, but participants on commer­cialized platforms expressed the hope that their activities would contribute to these goals (Fitzmaurice et al. 2020). Despite their “hostile worlds” (Zelizer 2000) view of the relation between the market and nonmarket society, they were optimistic that sharing platforms were capable of constructing an al­ternative, more humane, and sustainable market. This suggests the possi­bilities of hybrid models, which have genuine commitments to the common good outcomes but which also offer instrumental value to users. Potential examples include TimeRepublik, a for-profit online timebank with its own (time) currency that has been able to attract large numbers of users,¹³ and the first decade-plus of Etsy, an online marketplace for handmade goods that operated as a B corporation with a small fee and a commitment to social benefit.¹⁴ The lesson of these examples, however, is that in both instances, the need to meet investors' profit expectations led to a reorientation toward financial goals. That tension has led to a movement for a new digital form, the platform cooperative, which operates in the interest of its user-owners rather than investors.

Platform Cooperativism

The failures of the for-profit platforms to deliver good outcomes to workers on the three dimensions we identified above (compensation, autonomy, and voice), in combination with the lack of growth in the nonprofit sector, have resulted in the emergence of a movement for platform cooperatives. They are a subset of the larger class of worker cooperatives that date from the early nineteenth century in England. While this is still a new form, the innova­tions associated with platform technology may help to solve long-standing questions about cooperatives.

In the literature there are two broad classes of questions and research about the cooperative form—economic performance and democratic gover­nance. Key economic questions are the cooperative's relative performance on productivity, employment, and wages in comparison to conventionally man­aged firms. There is now quite a bit of evidence to conclude that employee- owned and governed firms are economically sustainable and that they return more economic value to workers, reduce turnover, and motivate work effort (Blasi, Freeman, and Kruse 2017; Cheney et al. 2014; Pencavel 2013). While there may be differences between conventional and cooperative firms in terms of rates of innovation, how employment responds to reduced demand, and other economic outcomes, the cooperative form is clearly viable. The big­gest economic challenge to the scaling of this model remains one that was identified decades ago: access to capital (Gintis 1989). If this problem were solved, it is likely that the cooperative sector could grow and prosper. Indeed, that seems to be occurring in many places in the world (Cheney et al. 2014). One challenge is what researchers have termed “degeneration,” or the decline of worker ownership and devolution to a conventional setup in which owners hire workers (Cheney et al. 2014; Pencavel 2013). One explanation is the “iron law of oligarchy,” in which an owner-elite comes to dominate.

A related set of questions involves the extent of democratic participation. There is less literature on this issue, although ensuring robust participation by workers and maintaining democratic control over elected management are ongoing challenges. One argument is that robust democracy is difficult when participatory firms are embedded in larger societies that have few democratic structures (Varman and Chakrabarti 2004). A second issue is a potential trade-off between democracy and efficiency, which has been noted in some cooperatives (Ng and Ng 2009). However, there is also evidence in the literature of “regeneration,” when enterprises revitalize their governance mechanisms and practice (Cheney et al. 2014). How might platform coopera­tives fare on these issues?

The platform cooperative is an online enterprise that is owned and gov­erned by those who work on it (Scholz 2014, 2016a; Schneider 2018; Chase 2015).¹⁵ This form harnesses the benefits of the technology with a structure that is oriented to fair treatment and self-determination for producers. If governance is robust, it can also create social ties and even solidarity. Plat­form cooperatives have the potential to overcome some of the weaknesses of both the for-profit and nonprofit forms as discussed earlier. With respect to the former, they deliver a larger fraction of the revenue to the workers and are more likely to institute rules and policies that a majority of work­ers consider fair and equitable. For example, algorithmic management is less problematic if workers help develop the algorithms and the software remains accountable to worker-owners. Democratic governance also allows members to reject clients or projects they are ethically opposed to, an issue that has become a particular flashpoint at tech companies (Fang 2019; Shaban 2018).

At the same time, if the cooperative is successful it can deliver valuable in­strumental benefits to members.

In conventional economic theory, the ownership and governance of the platform should be largely irrelevant. Capital receives only the reward that it earns through its contribution to the value of the product. Labor earns the same. Optimal policies are generally assumed to be attributable primarily by the requirements of technology.¹⁶ Of course, the conventional economic per­spective is obviated in cases where markets are not perfectly competitive and capital can extract more than its marginal product, which is true of many segments of the sharing economy. Indeed, most advocates of platform co­operatives depart from the conventional economic wisdom and believe that the owners of capital typically have power that they exert over workers. If so, worker ownership should result in meaningful differences in outcomes. Of particular importance is the fact that algorithms and crowdsourced reputa­tional information can take over management functions such as vetting and ensuring the quality and character of providers, and some of the value from these tasks can be retained by worker-owners. This is particularly important in care work, cleaning, and other personal services with high-risk potential so that agencies are able to capture a large fraction of the product. These oc­cupations are ideal for the platform cooperative form (Schor 2014).

To date, there are relatively few platform cooperatives in operation, par­ticularly in the US.¹⁷ Large international examples include SMart, a freelanc­ers co-op in Europe with 35,000 members,¹⁸ and Fairmondo, a German retail cooperative selling ethical and sustainable products, which has 2000 mem- bers.¹⁹ In the United States, there are small sharing economy cooperatives of taxi drivers and housecleaners currently operating, with health care coopera­tives in formation.²⁰ The literature on platform cooperatives is small (Ben- kler 2016; Fedosov et al. 2019; Jackson and Kuehn 2016; Lampinen, Huotari, and Cheshire 2015; Schneider 2018; Scholz and Schneider 2016). Our team did what we believe to be the first case study of a platform cooperative—a stock photography company called Stocksy United (Sulakshana, Eddy, and Schor 2018). At 1000 members, it is the largest and most well-established North American producer-owned platform cooperative currently in operation. (In contrast to our other cases, it is not a “sharing economy” company because its customers are mainly businesses. One difference is that they do not use a public reputation system and there is no direct contact between the artists and the customers. However, at the time we were undertaking our research, there were no other viable options to study.)

Stocksy was founded by Bruce Livingstone and Brianna Wettlaufer, two owners of a stock photo platform that they sold to Getty, the industry leader.

The acquisition resulted in artists' dissatisfaction with pay and policies un­der the new regime. The former owners then decided to organize a new coop­erative to foster creativity, provide higher returns to artists, and enable dem­ocratic governance. Founded in 2012, Stocksy is a multistakeholder²¹ co-op in which the staff and a governing board²² also hold shares. The biggest obstacle to establishing cooperatives, financing, was not relevant, as the founders of­fered a $1.3 million loan from the proceeds of the original sale. Stocksy also began with high levels of industry-specific knowledge and expertise and a proven track record. While it is impossible to know how much that mattered, it seems obvious that it did.

By most metrics, Stocksy has been extremely successful. It has robust rev­enues and was able to repay its loan and begin profit-sharing in its second year. It has carved out a lucrative market niche with a unique positioning in the industry—as a boutique shop with a distinctive aesthetic style. We found that members report high levels of satisfaction. The cooperative structure attracted highly talented and successful artists who ordinarily will not sell in the low-prestige stock portion of the industry. Members did not complain about exploitation or unfair treatment. Artists receive 50 percent of one­time sales, in comparison to the 15 percent industry standard, and 75 percent for extended licenses (versus 45 percent). Some take advantage of the com­munity aspects of the site, getting support from the online forum and, in some cases, meeting up with other Stocksy members.

Stocksy differs from most platforms because membership is by applica­tion and has been subject to limits. It has been extremely competitive to join, with a 6 percent initial acceptance rate, which rose to 10 percent. Demand to participate is a good metric for how well the cooperative is serving its members' interests. Total membership was capped at 1000 and expansion has been controversial. However, management would like to grow, and after a few proposals to add artists were rejected by members, they found a compro­mise that is enabling modest annual growth, with accountability to mem­bership. More generally, balancing provider supply and consumer demand is a key question for platform cooperatives. Capping membership may reduce the flexibility to choose hours and schedules, but it also allows the coopera­tive to maintain a good balance between supply and demand. By contrast, freelancer cooperatives such as SMart do not maintain membership limits.

In our research we found that members were mostly satisfied with gover­nance. Communication occurs in an online forum, which is also the mecha­nism for taking decisions. Approximately 200 to 300 of the 1000 members participate. Members come from 65 countries (spanning many time zones) and speak different languages, therefore it is not possible to hold conven­tional real-time meetings and decisions must be made by nonsynchronous participation. It is our impression that nonparticipation does not stem from dissatisfaction, but either low overall involvement with the platform and a general satisfaction with decisions and operational practices.

The success of Stocksy is especially impressive in view of a dynamic that we find endemic to most platforms in the sharing space: diversity of partici­pant orientations. As we found in our other case studies, there is variation in the extent to which earners rely on platforms for income, with the coex­istence of supplemental and dependent earners. This range is found on the labor and capital platforms we studied and has been found on marketplaces such as Etsy (2013) and digital platforms Upwork and Amazon Mechanical Turk (Caraway 2010; Gray and Suri 2019; Popiel 2017). In Stocksy, the distinc­tion manifests itself between professionals and what are called hobbyists (or more derogatorily by the former, “mom-tographers”). The high quality of smartphone cameras has allowed participation with low investment in equipment—an example of the low barriers to entry that characterize many sharing platforms. On Stocksy, a second axis of differentiation is between those with an artistic versus a commercial orientation, which does not over­lap fully with the professional/hobbyist divide. In our research, we found some low-level tension among these groups.

Another issue, also common to the platforms noted above, is that Stocksy is a winner-take-all market. In 2016, 87 of the 1000 members earned 66.2 per­cent of the total royalties. Among those 87, the top nine contributors earned 26.5 percent.²³ Stocksy's perhaps uniquely extreme concentration is due to a number of factors. One is the presence of highly talented artists, who are attracted by the cooperative setup. The second is the diversity noted previ­ously, and specifically the presence of a small number of highly commercially oriented producers who invest considerable sums on shoots (up to $20,000 for one shoot) and submit large portfolios alongside hobbyists who rarely submit. This “challenge of individual contribution” is especially an issue with online co-ops because conventional worker co-ops are more likely to make collaborative products. Online, individual contribution is the norm, members are competing against each other, and scarce skills can earn rents. Where the skill distribution is more equal, such as in driving, delivery, care, and homework, earnings distributions are more equal, driven more by hours worked than hourly remuneration. Those cooperatives may also set fixed rates or narrow hourly wage ranges. For Stocksy, the replicability of each pho­tograph means a few very popular images can yield high earnings.

Stocksy is an instructive example for advocates of the platform cooper­atives, however, it is also in many ways a best case. Its founders had deep experience in the industry and ample financing. It also carved out an upscale, profitable niche in a competitive market. Cheney and colleagues (2014) note that to be successful in global markets, cooperatives may now need to not merely respond to markets, but may have to create and lead them. Stocksy is a successful example of doing just this.

Furthermore, it did not face issues that are central for consumer-oriented service labor cooperatives (e.g., ride-hail, cleaning, and caring labor), such the “tyranny of the market,” when consumers are not willing to pay living wages or there is a sharp trade-off between prices and demand. For a dis­cussion of this kinds of dilemmas, see Sandoval (2019). Stocksy artists were generally insulated from these economic dilemmas.²⁴

Envisioning a Pluralist Economy

It is too early to know whether cooperatives will become widespread. How­ever, if they do, they may prove to be an important innovation in the plat­form ecosystem that can protect workers against exploitative employers and provide the opportunity for self-determination. The costs of the basic technology are in decline, and there are efforts underway to create open­source toolkits that will make establishing a platform cooperative relatively easy. For providers, platform cooperatives are likely better than monopolis­tic companies. However, they are not a panacea. Their ability to shape the larger labor market in which they operate is limited except in the case of sub­stantial monopsonist power or cross-industry collaboration among coopera­tives. However, that type of price setting is likely illegal. This suggests that platform cooperativism, even in its most successful incarnation, can only be one component of a system-wide restructuring that is capable of producing economic democracy and justice. Furthermore, platform cooperatives have little inherent advantage over for-profits on issues of ecological and carbon sustainability. To deliver those outcomes, this enterprise structure must be paired with a robust regulatory regime that internalizes key externalities and an expanding culture of solidarity and ecological responsibility.

In our view, platform cooperatives should be seen as one, albeit impor­tant, type of enterprise form in a hybrid or pluralist economy (Alperovitz 2011; Benkler 2006; see also Rodrik and Sabel's chapter in this book). Coopera­tives, both offline and online, address working conditions and help to create democratic workplaces. But other forms of economic organization are also feasible and desirable. Municipally-owned platforms are a close cousin that may be well suited to certain kinds of services. More conventional options in­clude small businesses and self-employment. Resources held in common by local and regional communities are another important form that has become increasingly popular. Some of these may function as not-for-profits. Land and housing trusts are another building block of a new hybridized economic ecosystem. The global community must also find a structure for managing the atmospheric commons sustainably. We do not yet know what that will be. What we do know is that there is now growing excitement and energy around various alternative forms of economic organization. If these forms expand, they hold the possibility for creating a more democratic and just economy.

Notes

This chapter was prepared for the workshop on Political Economy and Justice, Edmond J. Safra Center for Ethics, Harvard University, June 24-26, 2019. We would like to thank the members of our research team—William Attwood-Charles, Mehmet Cansoy, Luka Carfagna, Connor Fitzmaurice, Isak Ladegaard, and Robert Wengronowitz—for collaboration on the research discussed in this chapter. We are also indebted to colleagues in the MacArthur Research Network on Digital Media and Learning and members of the Political Economy and Justice Working Group, who provided very useful feedback and inspiration. Thanks are especially due to the organizers, Danielle Allen, Yochai Benkler, and Rebecca Henderson. Generous funding for this research was provided by the MacArthur Foundation.

1. Connected Consumption and Connected Economy (https://www.bc.edu/bc -web/schools/mcas/departments/sociology/connected.html).

2. For example, ride-hailing services require a car, used-goods exchange re­quires cleaning and shipping materials, and accommodation rentals require the labor of cleaning and hosting. However, the mix of capital and labor across these three segments varies considerably.

3. Another segment of the gig economy is online, digital labor contracted through platforms such as Amazon Mechanical Turk. This type of work is typically not included in the “sharing economy,” although it is considered gig or platform work (Gray and Suri 2019; Irani 2015).

4. Statistic on Uber drivers at https://www.uber.com/newsroom/company -info/. For more information on Care.com, see “Company Overview,” https:// www.care.com/company-overview.

5. The discourse associated with the sector also focused on two other types of claims: social and ecological. The social claim linked the P2P structure to the creation of ties among transactors and to a widely perceived sense of disconnection within society. The ecological claim argued that the develop­ment of used-goods markets and the more intensive use of “capacity” would reduce the demand for new goods, thereby lowering ecological and carbon footprints. The ecological claim is particularly dubious given that sharing services reduced prices considerably and the two largest platforms are in transport and travel (Schor 2020).

6. This is a potential result in part because public reputation systems suffer from ratings bias and may not be very effective in excluding malfeasants (Cansoy 2018). It seems likely that the small number of problematic ex­changes in the early days of the sector was less a function of a robust rating system than the absence of ill-intentioned actors on the sites. Over time, the largest platforms seem to have attracted more problematic actors.

7. In the used-goods sector, Freecycle, Yerdle, and other sites were organized us­ing practices other than conventional cash trading (e.g., gift, platform-specific currency). The counterparts to monetized rental platforms are tool and toy li­braries that have free loans. In space-sharing, examples include Couchsurfing, Landshare, and co-working offices. In the labor services segment, timebanks and child care co-ops are alternatives to TaskRabbit and similar sites.

8. Efforts to establish cooperative, commons, and collaborative initiatives seem to have been more successful in Europe, particularly in those areas with a long tradition of this type of activity (Bauwens and Onzia 2017; Morell 2018).

9. For example, the Repair Cafe movement (https://repaircafe.org/en/visit/), which is supported by a European Foundation and offers a replicable model, has only about 100 listed sites in the US in comparison to more than 1500 in Europe.

10. Another factor undermining instrumental value is that some of the new sharing entities attempted to create networks of reciprocity in areas where informal economies were already operating, but which were invisible be­cause the innovators were not members of the relevant communities (Light and Miskelly 2015).

11. Survey results are available at “New American Dream Poll 2014," New Dream, https://newdream.org/resources/poll-2014.

12. Many participants and organizations held a "hostile worlds" (Zelizer 2000) view of the relationship between market and nonmarket activity. This anti- monetary stance is also found in anarchist and left initiatives.

13. On TimeRepublik, see https://timerepublik.com/. In 2017 the company pivoted toward a B2B orientation: https://www.startupticker.ch/en/ news/january-2017/the-leading-banking-group-in-italy-to-test-the-b2b -timerepublik-platform

14. David Gelles, "Inside the Revolution at Etsy," New York Times, November 25, 2017, https://www.nytimes.com/2017/11/25/business/etsy-josh-silverman.html.

15. Benkler's contributions (Benkler 2004, 2006) were formative.

16. Worker preferences can also play a role in policies such as working hours or worker autonomy. Standard theory suggests that if there are significant differences in preferences, workers will sort into firms that reflect those differences.

17. Schneider (2018) maintains a list of platform cooperatives at his site entitled Internet of Ownership (http://ioo.coop/); a Google sheet is avail­able at https://docs.google.com/spreadsheets/d/1RQTMhPJVVdmE7 Yeop1iwYhvj46kgvVJQnn11EPGwzeY/edit#gid=674927682. See also the Platform Cooperativism Consortium: https://platform.coop/.

18. See Smartcoop in Europe (https://smart.coop/). A hybrid cooperative that has its own currency is the Brazilian Fora do Eixo (http://foradoeixo.org.br/), which is a network of musicians, artists, producers, and venues with 200 collectives and 2000 employees.

19. SeeFairmondo (https://www.fairmondo.de/).

20. Co-ops have already formed: see Up & Go (https://www.upandgo.coop/), Green Taxi Cooperative (http://greentaxico-op.com/), and Shift (https:// www.shift.coop). NursesCan Cooperative is discussed in Nithin Coca, “Nurses Join Forces with Labor Union to Launch Health Care Platform Co­operative,” Truthout, September 4, 2017, https://truthout.org/articles/nurses -join-forces-with-labor-union-to-launch-health-care-platform-cooperative/.

21. Some cooperatives are structured so that multiple stakeholders have owner­ship and voting rights. See Chase (2015) for an argument for this form.

22. The board also has the possibility of vetoing proposals that have passed the membership.

23. Management not only gave us these numbers, they also permitted us to pub­licize them. The contrast with for-profit platforms is striking.

24. They did face cultural tyrannies, in the form of customers' biases. Buyers hold a “neo-imperialist aesthetic,” with preferences for pictures of afflu­ent, white Westerners. Artists felt they needed to comply in order to be successful.

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