Case Study

Cambodia is a poor economy, experiencing a sustained period of rapid growth after decades of conflict. As with many developing countries, urbanisation is rapidly shifting the flows of Ecosystem Service use. Coupled with expected shifts and variability in climate, the modes through which Cambodians across the rural-urban spectrum receive Ecosystem Services could change in ways that are difficult to plan for, straining the resilience of households to shock, the environmental sustainability of their practices and choices, as well as the equity enjoyed among households and communities. As such, the National Strategic Development Plan (2014-18) calls for more information on how to better manage availability, access, utilisation and stability of Ecosystem Services.

MobilES will distribute 480 smartphones to participants: 240 within urban wards of Phnom Penh, and 240 in the rural region of Preah Vihear. The rural sample will be stratified equally across areas that practice i) conventional and ii) wildlife-friendly farming, within the Wildlife-Friendly Ibis Rice Project. All participants will have the opportunity to respond to short qualitative and quantitative survey response tasks on a regular basis, from a daily to monthly timescale (with a maximum of 10 short tasks per week), over a one year period in a ‘microtasks for micropayments’ model (in the form of data, sms, or credit toward device ownership).

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The microtasks approach via smartphones offers numerous advantages vis-a-vis conventional data collection, such as the ability to capture high-frequency variation (such as shifts in access to ES, or changes in use patterns) without requiring participants to try to recall events of weeks or months in the past. Half the participants (i.e. 120 urban households and 120 rural households, the latter divided equally between conventional and wildlife-friendly farming) will respond to short survey response tasks coded in the Android Open Data Kit (ODK) platform. Using ODK, short tasks that can be fit into a moment of downtime enabling a more representative sample than conventional surveys, which can only capture those respondents willing and able to take time away from work to participate – a critical advantage in comparative analysis across strata of income and economic opportunity.

Our study design addresses the current challenge associated with this emergent mobile-based mode of data collection – difficulty in validating survey responses – by performing an equivalent telephone survey with the remaining half of our sample.

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