What new economic models does the sharing economy create? New book offers an analytic treatment of issues like model differentiators, employment, and taxation in the sharing economy.
Will the sharing economy create a world of empowered entrepreneurs who enjoy professional flexibility and independence, or disenfranchised drones searching for piecemeal tasks? New York University professor Arun Sundararajan explores these issues in his book, The Sharing Economy: The End of Employment and the Rise of Crowd-Based Capitalism.
The nine chapters span 240 pages, covering trends, drivers,Â and social implications. The material is written in a mix of conversational and academic style, though there tends to be some repetition and name-dropping. For insights into business models and strategy of sharing platforms, see my book review of Peers Inc: How People and Platforms Are Inventing the Collaborative Economy and Reinventing Capitalism by Robin Chase.
Arun uses the term â€œcrowd-based capitalismâ€� to describe what is also known as the sharing economy, gig economy, on-demand economy, collaborative economy, renting economy, or peer economy â€“ with some elements of a gift economy. The book draws on examples such as Airbnb, Lyft, Uber, Etsy, TaskRabbit, France’s BlaBlaCar, China’s Didi Kuaidi, and India’s Ola.
Arun shows how gift, market, networked and hierarchical models are converging, throwing up a number of opportunities as well as challenges in the space of assets and skills. Dialogue and research are needed to negotiate the emerging tradeoffs.
â€œThe sharing economy is the value in taking underutilised assets and making them accessible online to a community, leading to a reduced need for ownership of those assets,â€� explains Alex Stephany, author of The Business of Sharing. Some participants are altruistic, others expect payment.
Asset-light sharing platforms have emerged around the world with a wide array of offerings: accommodation (CouchSurfing, AirBnB), crafts (Etsy), home exchange (LoveHomeSwap), peer-to-peer car rentals (GetAround, Turo, Drivy, SnappCar, YourDrive, Easy Car Club), social dining in homes (EatWith, Feastly, VizEat), home labour (TaskRabbit, Handy, Thumbtack), parking spaces (JustPark, SpotOn), personal parking valet (Luxe), getting lifts (Lyft), and inter-city ridesharing (BlaBlaCar).
There are other platforms and services in home delivery (PostMates), packing and shipping (Shyp), laundry (Washio), walking your dog (Wag), gourmet meals (Munchery), drinks delivery (Minibar, Drizly), film equipment rental (KitSplit), neighbourhood rental products (NeighbourGoods), tool library for makerspaces (myTurn), apparel rentals (StyeLend, Rentezvous, Rent the Runway, Rent My Wardrobe), goods barter (OurGoods), exchange of pre-owned goods (Yerdle, Listia), reciprocal training (Trade School), and farmer-neighbourhood matching (La Ruche Qui Dit Oui).
Players are also emerging in bike-sharing, co-working and crowdfunding (Kickstarter, Kiva, Funding Circle, AngelList), and some of the original players have also expanded their offerings. AirBnB allows not just sharing of rooms but also tree-houses, beach homes, boats and more; Uber allows not just individual rides but pooling and delivery.
These platforms are redefining the way consumers find, use, and pay for services, as well as how they engage with, assess and award service providers. For example, we cannot choose which Uber driver will drive us, but we can choose a crafts provider on Etsy. Designers need to market themselves on Etsy, but drivers need not create marketing collaterals on Uber. Uber provides some driver financing but Etsy artisans are self-funded.
Evolution and driving forces
Community exchanges are not new, and have existed in the pre-industrial era as well; many of them blend for-profit commerce and free community service. Older economic models marginalised under capitalism are experiencing a transformation, according to Harvard Professor Yochai Benkler.
However, they are expanding to â€œstranger sharingâ€� at massive speed and scale, thanks to use of digital technology (particularly smartphones and social media) to tap into decentralised excess capacity. Other trends identified by Arun are IoT, 3D printing, digitisation of trust, blockchain, and â€œtaskificationâ€� along with offshoring.
Digitisation is reducing the coordination cost, effort and time for many multi-party activities. Feedback-based reputation systems also strengthen the value and brands of sharing platforms (though there have been cases of inadequate background checks of fraudsters, offenders and criminals).
The first major Internet-enabled P2P market, eBay, was founded in 1995. The power of the crowd also emerged with models like Wikipedia, as well as CraigsList and Kozmo. Platform-based service matching works particularly well in urban clusters.
Broader trends are access without ownership and replacement of hierarchies with networks. In crowd-based networks, capital and labour come from crowds of individuals rather than corporate or state aggregators.
Arun charts how platforms differ in terms of whether they provide centralised funding, mentoring, training, logistics, pricing levels, and insurance. But most provide transparent feedback and augmentation via external trust indicators.
Crowd-based service platforms are blurring the lines between professional and personal activities, between full-time and part-time labour. The sharing platforms yield a number of benefits such as new jobs, flexibility (work at your own hours), planning (schedule work and free time in advance), increased business (for creators), and new connections (between provider and consumer).
The sharing economy has also created new mechanisms of peer-based trust, over and above brand-based trust. Thus, user-generated reviews of Yelp have helped it eclipse Zagat, which had a traditional expert-driven rating model.
Macro-impacts are democratised economic opportunity (via creation of micro-entrepreneurs), increased socialisation, two-sided network effects, inclusive growth, and environmental benefits (eg via car sharing). Aggregated data can also yield insights on larger economic consequences, which other measures like GDP, Human Development Index, and OECD Better Life Indicator may not adequately capture.
Arun cautions there are also worrying issues such as loss of social safety net for labour, possibility of unethical practices, consumer safety, concentration of capital, and avoidance of taxes. There is increased work, but potential job loss.
Critics have even derided some sharing economy players as â€œshare the scrapsâ€� economy who create â€œdisenfranchised drones.â€� More rigour is needed in defining how such platforms should provide assurance and insurance.
Peer regulation, self-regulation and regulation are called for, but in a manner that enables innovative business models while also providing workforce guarantees. There also needs to be a buffer to allow for some amount of learning from unintended consequences, Arun urges.
High-profile media reports have put the spotlight on some public protests against unethical practices and management shortcomings of sharing platforms. Broader analysis and dialogue are the need of the hour. Creative regulatory models have been proposed, such as â€œmincomeâ€� (minimum income), â€œflexirutyâ€� (flexible worker arrangements along with security), and ownership structures of cooperatives.
The book opens the door to deeper research into the hybrid business models of sharing platforms, investor dynamics, accountability, wage trends, transparency, ethics, worker rights, safety nets, data portability of member ratings across platforms, and regulatory practices.
â€œWe are still very early in the labour transition induced by the sharing economy,â€� Arun signs off.