Unboxing the Collaborative Economy: Sharing Definition and Indicators
After few years of empirical analysis in different contexts, sharing economy is still a vague concept and its analytical categories remain unclear. This heterogeneity is also confirmed by the number of synonyms we use to define the term sharing economy: "collaborative consumption", "circular economy", “peer-to-peer economy” . Many of the proposed definitions or classifications (Botsman and Rogers, 2010; Schor, 2014; Pais and Provasi, 2015) are still unable to account fully the nature and the aims of a plurality of practices between online and offline, formality and informality, profit and non-profit. The current scholarly production is not adequately developed and coherent, often descriptive (Rifkin, 2014; Botsman e Rogers, 2010; Benkler e Nissembaum 2006) or apologetic (Garner, 2015; Moeller and Wittkowski 2010; Gansky 2010).
Recently, some critical issues are beginning to emerge: 1) tax avoidance, also because of the inadequacy of national legislation; 2) regressive welfare and job matching (Arcidiacono, 2016) empowered by the national policy of deregulation of the labour market; 3) the risk of extraction of value by traditional companies with potential "share-washing" practices (Kalamar 2013); 4) uncertainty outcomes of the regulation about sharing (Koopman et al., 2014; Romano 2015); limited “sustainability” on the environmental side (Martin and Shaheen 2010); 5) production of a low quality social capital (Fenton, 2013; Parigi and State, 2014), also with cases of racial and social discrimination (Hardin and Luca, 2014; Schor and Fitzmaurice, 2015).
So many things we know about sharing economy but more things we continue to ignore because a fully understanding of the phenomenon needs a shared definition and a common dashboard of indicators. It could be evident that not all the socio-institutional environment are equally fertile for the sharing economy as well as not all the sharing platforms are the same. The ambiguity and plurality of practice of sharing in the absence of reliable and valuable indicators, useful to measure its impact, impose a stronger effort to understand the phenomenon.
The proposed paper aims to define a research agenda of on the topic of the collaborative economy through a detailed overview of the literature and research on this issue, in order to identify a common definition and building an analytical toolbox of drivers and indicators to measure its potential and impact in different institutional environments.
One of the most interesting aspects of sharing is its variety of enterprises, not necessarily centered in the expressed aim of "hacking" the dominant system of economic exchange. It is not always true that sharing economy it’s a fully disintermediated or indiscriminately cohesive and inclusive.
In this perspective, the sharing economy is a sub-category of a wider framing that we could call the collaborative economy. It could be defined as the model of economic exchange of the overcapacity of a good/service, based on different mechanisms (collaboration, reciprocity, common-pooling) and focused more on access than property, reducing the boundaries between production and consumption and the levels of intermediation. This model could be divided into specific three sub forms of exchanges:
1) on-demand economy: where transactions are based on the asset owned by an individual or collective actor through (but not exclusively) the use of digital platforms or apps owned in many cases by multinational companies. In this case, there is always a monetary exchange and the owner of the platform extract more of the value generated. It is an exchange in which the mechanisms of trust allocating follow the traditional market mechanisms (advertising and reputation of the brand). Eg: Netflix, Uber, Car2go, AirBnB;
2) circular economy: where transactions are within networks of equals, often territorially defined and, above all, at the local level, with no monetary mediation and where technology acts only as a facilitating factor and not as an enabler. The value remains between the nodes of the network and it is also expressed in the form of strengthening ties and trust among them. Eg: barter, book-running, tool library, social street, traditional time banks, purchasing groups;
3) sharing economy: where transactions are focused on P2P networks, enabled necessarily through a digital platform that somehow regulates the bargaining between the parties, even when it takes a monetary nature and there is some form of appropriation of the value created. Despite some global ambitions, in most of the cases this platforms operate more on local or national markets. Relationships are more instrumental and mediated by ratings of digital reputation. Eg: digital time-banking (TimeRepublik), complementary currencies (Sardex), car pooling online (Blablabla car, GogoBus), file sharing (Emule, bitTorren), services of accommodation (Couchsurfing), or social eating ( Eatwith, Feastly, Gnammo), etc.
Using this distinction, we could focus better on what could are the specific drivers of sharing economy, trying also to understand the different levels of success and development in the different socio-economic environment. We could distinguish four categories of drivers: market drivers (eg: role of private Equity Funds, procedures of customer engagement and crowdsourcing, incidence ICT sector, traditional gift economy practices, etc.); policy drivers (public incentives and investments in digital infrastructure, physical and cultural ones, internet governance model, smart cities policies, consumer protection systems, open gov practice, etc.); consumption drivers (prosumer orientations, e-commerce expansion, diffusion and use of social networks and digital payment devices, ect.); labor market drivers (expansion of freelance and gig economy workers, increasing deregulation, personal branding strategies, dualistic career paths, etc.) At the same time, we could define four areas of socio-economic impact of sharing practices: market (in terms of active platforms, added value, number of transactions, consumers ability to pay, etc.), environment (in terms of carbon emissions, converted spaces, incidence of collaborative service with an environmental impact, etc.), labor (in terms of number of employees, type of employment, etc.) and networks (number of collaborations profitnon-profit, incidence of litigation, level of transparency of digital reputation algorithms, etc.).