5.1.1. Analysis of SDGs Alignment with Sustainability Qualities of the Platform Economy
This research has used the Multidisciplinary Balance of Platform Economy, which considers the dimensions of governance, economic strategy, technological base, knowledge policies, impacts, and social responsibility toward the externalities of the platforms [19
] to analyze how sustainability qualities of the platform economy relate to Sustainable Development Goals (SDGs).
The results show that most of the SDGs (1, 2, 3, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, and 17) are related to social responsibility and impact dimensions. For instance, the platform economy, through job creation, could help to end poverty (SDG 1) and foster employment and decent work (SDG 8). Moreover, the platform economy reinforces the global partnership for sustainable development (SDG 17), involving different types of quadruple helix actors (government, business, research, and civil society) while promoting cooperation among them. The Multidisciplinary Balance of Platform Economy also considers gender in terms of participation and platform ownership, which is correlated to promoting inclusive economic growth considering equality (SDG 1), such as education (SDG 5), decent work (SDG 8), and inclusive society (SDG 16). The Multidisciplinary Balance of Platform Economy also considers if the platform design is adapted or available to people with functional diversity, paying attention to the needs of disadvantaged and marginalized populations (SDG 10). Finally, social responsibility and impact also refers to political responsibility, ensuring city sovereignty, which links with the goal of making cities inclusive, safe, resilient, and sustainable (SDG 11).
Environmental responsibility is also incorporated, taking into account if the platform promotes recycling and circularity of materials (SDGs 2, 3, 7, 12, 13, 14, and 15), if it is hosted in green energy servers (SDGs 2, 3, 7, 9, 11, and 13), whether it offers a type of service or product improving energy efficiency (SDGs 2, 3, 7, 9, 11, and 13), or if it promotes sustainable mobility (SDGs 2, 7, 8, 9, 11, and 13).
A sustainable platform economy incorporates economic responsibility, prioritizing providers of Social and Solidarity Economy when a provider is needed. Therefore, this dimension corresponds with the following SDGs: ensuring sustainable consumption and production patterns (SDG 12) and resilient economies (SDG 13). The economic model defined by the sustainability qualities of the platform economy matches with the goal to ensure a sustainable livelihood (SDG 1), promoting well-being for all (SDG 3), providing a quality education (SDG 4), and inclusive and sustainable economic growth, employment, and decent work for all (SDG 8).
Regarding the technological policies, sustainable platform economy links with the goal to build resilient infrastructure to promote sustainability and foster innovation (SDG 9), supporting open software and decentralized platform infrastructure architecture. Finally, neither data policies nor governance elements are considered in the description of SDGs. Nevertheless, these are key elements and areas to take into account, as explained in the following subsections.
5.1.2. Platform Economy Models and Their Contribution to Sustainable Development
As stated in the introduction, there is confusion about the platforms that present themselves as collaborative, when actually they are not, and there are similar uncertainties and ambiguities associated with diverse models. In the article, the redefined the Multidisciplinary Balance of Platform Economy has been applied to analyze how each platform economy model contributes to sustainability in four sectoral areas. The main results of this analysis are thereupon synthesized.
Regarding participation in terms of gender (SDGs 1, 5, 8, and 16), it has been stated that, as users, on average platforms are equal. However, no project that considered itself as having an equal representation in workforce gender terms has been found. Previous research performed by Huws, Spencer, and Coates [37
] finds that male platform workers are dominant, even in domestic work (which includes jobs such as carpenter or plumber) in those countries studied, with the exception of Italy, where women are dominant in transport and delivery activities (6.3% compared to 5.4% men) and domestic work (9.8% compared to 8% male). This difference can be explained by the fact that most of the cases studied are part of the urban food delivery sector (largely male represented) or the care and cleaning sector (largely female represented). In this regard, most of the platforms studied in the care and cleaning sector do not include tasks related to jobs such as carpenter or plumber. Another important finding of this research relates to gender representation of the owners of the platforms. Only one platform had equal representation in terms of gender, while the remainder had more men than women as owners. Moreover, most platforms are not taking concrete measures to change this situation. Just six of the 20 platforms mentioned having explicit policies to promote gender equality. Inside this group, platforms of all the legal types are found. In this regard, most of the policies established by platforms are focused on increasing women’s participation in tech sectors.
In terms of inclusion (SDG 10), the results show that, depending on the type of legal form, platforms differ in the social responsibility measures. First, while three of the nine commercial platforms are adapted or available to people with functional diversity, six out of the 11 non-profit platforms (cooperatives and associations) are adapted. Second, eight out of the 11 non-profit platforms are promoting the involvement of people on low incomes, while just three out of the nine for-profit platforms are doing so. Third, five of the nine commercial companies studied consider that they promote the involvement of people with just a basic education, while seven out of 11 non-profit models were doing so.
Regarding environmental responsibility (SDGs 2, 3, 7, 8, 9,11, 12, 13, 14, and 15), the analysis displays that six of the non-profit platforms are promoting the recycling and circularity of materials, compared to just two commercial platforms. Moreover, approximately the same proportion of platforms (two commercial companies and two alternative platforms) stated that their platforms are hosted on green energy servers. However, four of the non-profit platforms studied are offering a type of service or product improving energy efficiency, and four of the commercial platforms studied are doing so. Finally, regarding the provision of educational materials to raise awareness about sustainable consumption, six of the non-profit platforms are active in this area, compared to just two of the commercial companies.
In terms of concern toward economic responsibility (SDGs 11, 12, and 13), the research indicates clear differences are observed according to the different platform economy models. For example, regarding prioritizing social responsibility when choosing service providers, it was found that nine of the non-profit platforms studied were actively doing so, as opposed to only two of the commercial platforms. Perhaps not surprisingly, eight out of nine commercial companies have designed or are using a system to control fake accounts, while just three out of 11 non-profit companies are taking similar measures. Finally, four commercial companies stated that they have asked permission to operate at city level, compared to only one non-profit platform.
In terms of an economic model (SDGs 1, 3, 4, and 8), the analysis shows that regarding legal entities there is also a diverse ecosystem. Although most cases studied have a commercial type of business entity, there are also a great number of platforms under non-profit legal forms. The analysis shows that most of the projects studied (75%) are still not economically sustainable. In this sense, there does not seem to be a clear relationship between legal entity and economic sustainability, and all the platforms analyzed plan to reinvest their benefits into the project rather than dividing it amongst its owners. Nevertheless, even though a limited number of cases have been analyzed, three recognized that the goal of the project is to grow as much as is possible in order to sell as a form of exit whereby the platform is sometimes seen as a way to speculate.
Despite that, there are some forms of funding shared by all the platforms, and the most used forms by the overall sample of projects are “family savings” and “public funds”. The proportion of non-profit projects (the sum of the number of cooperatives and associations) is equal to the proportion of commercial companies that have received public funds. Apart from the main sources of funding mentioned above, nine out of the 20 cases studied rely on compulsory member fees, and six out of 20 use non-monetary donations. It has also been seen that five out of 20 offer premium products and services through their platform, four out of 20 have launched campaigns of direct micro-participation, and just four out of 20 have sold merchandising. Other sources of funding, such as research grants (three out of 20) or using the platform as a means for advertising companies (two out of 20), are relatively unused. This is the same for alternative sources of funding related to donations; considering the whole sample, six out of 20 had non-monetary donations from the community, three cases had non-monetary donations from the external actors, and four out of 20 cases had monetary donations.
When analyzing the various sources of funding used depending on the legal entity type, several differences are found. On the one hand, concerning non-profit business, the most used sources of funding are public and non-monetary donations from the community. On the other hand, for the commercial companies studied, the most used sources of funding are family savings, equity investment, debt investment, and public funds. Regarding non-monetary donations from the community, non-monetary donations from external actors, monetary donations, and direct micro-participation, only the latter is mentioned, but by only one project out of nine.
Also related to the platform’s economic model is their labor model. In this regard, it is found that the most followed type among both for-profit business and not-for-profit organizations is a mixed model with a combination of self-employed workforce and paid-employees (10 out of 20). We therefore have to consider that for “mixed models”, those who perform commercial activities through the platform are not considered as workers of the platforms’ legal entities.
According to the results, a combination of self-employed workforce and paid-employment workforce is sometimes made as an adaptation strategy to local laws and agreements. This means that in one territory, platform workers are considered self-employees, while in another territory, the workforce—doing the same tasks—is considered paid-employment figures. Lastly, as stated above, there are cases in which platform workers (hosts, platform couriers, car drivers, platform cleaners, and so forth) are not considered as workforce by the platform and instead are considered as “providers” or “producers”, with the platform considering itself as an intermediary in which the different users can interact with each other. For instance, some alternative models formed by different local instances explained that in each local instance or each node, members independently decide the type of juridical recognition that they want to give to its workers, understanding that workers are the ones under the daily development and maintaining of the platform. Usually they are members of the cooperative, which does not consider platform workers as a workforce.
Regarding the use of new technologies such as geolocation, algorithmic management, and gamification techniques, several findings can be stated. First, between those 11 platforms that are not using geolocation techniques, we find seven alternative platforms in the networked hospitality business (three out of three alternative platforms studied in this sector), urban food delivery (three out of six alternative platforms studied on this sector), and in the on-demand home services and care (one out of the two alternative platforms studied in this sector). We also found that four out of five lean platforms studied in the on-demand home services sector are not using them. In this regard, most platforms, including non-profit ones, with variations depending on the sector, find geolocation techniques decisive for the platform’s functioning. Second, regarding the use of algorithmic management, a total of nine cases out of 20 are using them. However, here there is a clear difference between alternative business models and unicorn platforms. While just three out of 13 alternative platforms use algorithmic management, 86% of the unicorn platforms (six out of seven) do. We highlight here Case 19, which mentioned that among the variables that they are taking into account are the amount of time that the platform courier has used the platform, the number of deliveries done, if working in peak hours, and the consumers score given to the platform courier service. Third, regarding the use of gamification techniques, three out of seven unicorn platforms are using them, compared to just one out of 13 of the alternative platforms studied. Finally, just two of the 20 platforms stated that platform workers can reject both algorithmic management and gamification techniques. More importantly, these two platforms are alternative platforms. No unicorn platform has stated that platform workers are able to reject both algorithmic management and gamification techniques.
Regarding the technological policies (SDGs 9), the results show that 66.7% of the platforms use copyrighted software, while 33.3% adopted open source technological infrastructures.
As it has been observed in the description of the framework of the analysis, SDGs do not focus at all on data policies. In addition, the results of the research demonstrate the lack of attention to the subject by the platform economy cases studied. First, there is a high level of copyright or non-licensing regarding website content, and second, only one out of the 60 platforms allows its content to be downloaded.
As well as data policies, governance is not considered in the description of SDGs. This lack of attention is relevant because the analysis points to several insights about platforms’ governance models. First, it is found that the alternative platforms usually enable users’ and/or workers’ participation in the definition of formal rules and policies, as well as acting as spaces for workers’ collective organization. Conversely, most lean business models do not consider that this is something they are participating in. Second, regarding participation processes, it is found that all the for-profit business models studied in depth have not established any type of system for democratic decision-making, while 11 out of 13 alternative business models have.