Browsing by Subject "Data collection"

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The potential of smartphone apps to collect self-recorded data in agricultural households : a study on time-use in Zambia
(2019) Daum, Thomas; Birner, Regina
Mobile information and communication technologies (ICTs) have spread across the developing world and are used increasingly by smallholder farmers. While the potential of ICTs, such as smartphone applications, to provide new opportunities for agricultural development is widely acknowledged, the potential to use them as research tools has not been explored. This thesis assesses the potential of smartphone applications for the collection of data from agricultural households in developing countries. Can smartphone applications that use visual tools be used for self-recording of data by the respondents themselves where literacy levels are low? Can such smartphone applications that allow for real-time data recording increase the accuracy of the collected data? Answering these questions is important as, so far, data from agricultural households are usually collected using surveys, which are prone to recall biases. This is a problem, as researchers, policymakers and development practitioners need reliable data for their work. Poor data can lead to misguided policy recommendations and actions with adverse effects on vulnerable population groups. This can lead to agricultural development trajectories that are socially unequal and unsustainable. To assess the potential of smartphone apps to collect self-recorded data, a smartphone application called Timetracker was developed as part of this thesis. The Timetracker allows study respondents to record data in real time with the help of illustrations. Recording data in real time reduces recall bias, and using pictures ensures that participants with low literacy can use the application. In its current form, the Timetracker can be used to collect data on time-use and nutrition. Collecting reliable data on time-use and nutrition is key for various strands of research. For example, time-use data are needed to calculate labor productivity and analyze how productivity is affected by new technologies. Time-use data can also help reveal gender-based power relations and asymmetries by pointing out unpaid domestic work. Similarly, nutritional data are crucial for various academic fields and debates. For example, nutritional data are needed to explore the factors determining food and nutrition security, to study how farm diversity affects consumption diversity and to monitor food and nutrition policies and programs. This study is based on three main chapters, which reflect the main objectives of the whole thesis: 1) to explore and test whether smartphone applications can be used to collect data from rural households in developing countries focusing on time-use and nutrition data, 2) to assess the accuracy of data collected with smartphone applications vis-à-vis recall-based data collection methods, and 3) to use the data to understand the effects of agricultural mechanization on the intrahousehold allocation of time-use within smallholder farming households in Zambia. The first two chapters have a primarily methodological focus. The last chapter is an empirical study. This thesis concludes that in addition to improving the accuracy of socioeconomic data collection, smartphone applications may open new research pathways, including through the opportunities provided by real-time data collection and by combining self-recorded data with sensor-recorded data, which may open interesting transdisciplinary research pathways. This thesis suggests that there is a large and still untapped potential for using smartphone applications to collect data on complex agricultural systems in the digital age.