Crowdsourcing High-Frequency Food Price Data in Rural Indonesia

Abstract

This feasibility study used crowdsourcing to track commodity prices in near real-time in areas where the availability of other data sources was limited. High-resolution and high-frequency food price trends were derived from reports generated by “citizen reporters”. The study was conducted in Nusa Tenggara Barat, one of Indonesia’s poorest provinces, comprised almost exclusively of informal, cash-only markets and stalls. The study involved recruiting a trusted network of local citizen reporters to submit food price reports via a customized mobile phone application. The tested crowdsourcing method could be improved by developing a standardised approach to the “bunch measurement” of staples so that it could be effectively deployed in locations where standardised weights and measures are absent. Crowdsourcing technologies, which capture high-frequency data on local trends, are best deployed in areas where traditional data collection methods are difficult or costly due to a lack of geographic proximity, high insecurity, or high food price volatility.

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