Uncovering the Structure & Dynamics of the Sharing Economy: Evidence from a Food Sharing Platform
In this research, we aim to reveal insights into the nature and dynamics of the sharing economy through a deep dive into a real-world food sharing network that aims to reduce household food waste.
It is often claimed that the “sharing economy,” as implemented via networks of mobile apps and users, yields environmental benefits through the efficient redistribution of already-existing assets and resources. Yet, little is known about how these networks actually function and, indeed, whether they deliver on their promises. In this research, we aim to reveal insights into the nature and dynamics of the sharing economy through a deep dive into a real-world food sharing network that aims to reduce household food waste.
Each year, approximately 1.3 billion tons of food are not consumed, an extraordinary waste of embodied resources and energy, not to mention the ethical travesty of wasting a full third of the global food harvest while one in nine humans on Earth suffers from chronic undernourishment. In developed countries food waste occurs predominantly at the retail and household levels. Since most of this food is edible when disposed of, redistributing edible yet unwanted food from primary to secondary consumers could yield substantial environmental and social benefits.
Relying on 20 months’ worth of data from OLIO, a popular food sharing app that originated in the UK, we explore whether the sharing economy can provide meaningful assistance in addressing the challenge of food waste in a relatively low impact and environmentally sound way. Specifically, we study the dynamics between supply and demand on OLIO, the structure and evolution of the local sharing networks structure, and the types and quantities of the food shared, to ascertain the environmental and social implications of P2P food sharing networks.
This project has two main facets. The first involves the environmental impacts of the sharing economy.
- To what extent can the sharing economy reduce food waste?
- What types of food items are successfully and unsuccessfully shared via this platform?
- What are the environmental costs and benefits of food sharing?
The second facet involves the nature of the networks themselves.
- How do sharing networks (and the roles of users within them) emerge and evolve over time and space?
- What are the underlying structures of digital food sharing networks?
- What “sells” in the sharing economy? What are the key drivers to successful sharing transactions?
- To systematically evaluate food sharing patterns and assess whether the sharing economy could help mitigate food waste, we first characterized what types of food items are listed and collected using a supervised deep learning long short-term memory (LSTM) network. To create the LSTM network-based classifier for OLIO listings, we first manually sorted and tagged over 53,000 listings into 15 product categories. We then used this corpus to train, validate, and test the LSTM network. Next, we used the classifier to assign all OLIO listings to specific product categories and calculate collection rates for each food category over time.
- To investigate the social structure of the OLIO network and whether it represents a form of collaborative consumption (i.e., users act as both suppliers and collectors) or is more akin to a digital form of food redistribution (i.e., users are predominantly suppliers or collectors, but not both) we examine individual users’ activity on the platform. Specifically, we calculate the ratio between the number of listings each user had supplied vs. collected and use network analysis to examine the role of individual users as well as the flow of foods among them.
- To examine the full life cycle environmental impacts of reducing food waste via P2P sharing, we compared the environmental benefits associated with food sharing with the environmental costs associated with added transport required for sharing. Environmental benefits were estimated based on the overall mass of food exchanged via OLIO and location specific emissions factors for avoided food waste. Environmental costs resulting from added transport were estimated for different transport scenarios based the road distance collectors needed to travel to pick-up the food items from suppliers, and relevant emissions factors for the transport mode used (e.g., car, bus, walk).
Given the scalability, flexibility, and potential for high-speed exchange, digital sharing platforms seem ideal for realizing the environmental gains from food sharing and redistribution, especially via Peer to Peer exchange. Gaining a better understanding of supply, demand, user behavior, and network dynamics of food sharing platforms is an important step toward answering many open questions regarding the environmental impacts of sharing activities, their potential welfare effects, and the drivers behind their adoption (or lack thereof).