Increasing engagement in price crowdsourcing initiatives: Using nudges in Nigeria

African agriculture is yet to reach its full food production potential. One way of addressing this is a better distribution of market signals to farmers and other market participants, which can help them make better-informed decisions, leading to increased income and capacity for investment. Hence, increasing the availability of market information in Africa is a priority and alternative data sources, and new Information Communication Technologies (ICTs) offer huge potential to complement classic official statistics. This has given rise to a number of ICTs and citizen science projects to monitor data in real time, of which food price crowdsourcing in Africa is one. However, one of the main challenges faced by crowdsourcing initiatives is to ensure that individuals feed useful information into the system. In this paper, we test the potential of behavioural interventions to help sustain crowd contributions by leveraging intrinsic and/or extrinsic motivations. We used two randomised control trials (RCTs) to evaluate whether the inclusion of two nudges (one based on social norms and one based on information disclosure) in the design of a food price crowdsourcing initiative can improve crowd engagement. Our results show that social norms increase crowd participation while disclosing price information does not. The latter highlights the need for further research to identify which type of information and format to make it accessible would best help to sustain crowd effort levels. These findings have the potential to be useful in designing future crowdsourcing (or other types of) initiatives that require sustained citizen engagement over time.

Using crowd-sourced data for real-time monitoring of food prices during the COVID-19 pandemic: Insights from a pilot project in northern Nigeria

The COVID-19 pandemic and related lockdown measures have disrupted food supply chains globally and caused threats to food security, especially in Sub-Saharan Africa. Yet detailed, localized, and timely data on food security threats are rarely available to guide targeted policy interventions. Based on real-time evidence from a pilot project in northern Nigeria, where food insecurity is severe, we illustrate how a digital crowdsourcing platform can provide validated real-time, high frequency, and spatially rich information on the evolution of commodity prices. Daily georeferenced price data of major food commodities were submitted by active volunteer citizens through a mobile phone data collection app and filtered through a stepwise quality control algorithm. We analyzed a total of 23,961 spatially distributed datapoints, contributed by 236 active volunteers, on the price of four commodities (local rice, Thailand rice, white maize and yellow maize) to assess the magnitude of price change over eleven weeks (week 20 to week 30) during and after the first COVID-related lockdown (year 2020), relative to the preceding year (2019). Results show that the retail price of maize (yellow and white) and rice (local and Thailand rice) increased on average by respectively 26% and 44% during this COVID-related period, compared to prices reported in the same period in 2019. GPS-tracked data showed that mobility and market access of active volunteers were reduced, travel-distance to market being 54% less in 2020 compared to 2019, and illustrates potential limitations on consumers who often seek lower pricing by accessing broader markets. Combining the price data with a spatial richness index grid derived from UN-FAO, this study shows the viability of a contactless data crowdsourcing system, backed by an automated quality control process, as a decision-support tool for rapid assessment of price-induced food insecurity risks, and to target interventions (e.g. COVID relief support) at the right time and location(s).