Search

One challenge of collecting socioeconomic data, such as data on time-use, is recall biases. While time-use researchers have continuously developed new methods to make data collection more accurate and easy, these methods are difficult to use in developing countries, where study participants may have low literacy levels and no clock-based concepts of time. To contribute to the closing of this research gap, we developed a picture-based smartphone app called Time-Tracker that allows data recording in real time to avoid recall biases. We pilot tested the app in rural Zambia, collecting 2,790 data days. In this article, we compare the data recorded with the app to data collected with 24-hours recall questions. The results confirm the literature on recall biases, suggesting that using the app leads to valid results. We conclude that smartphone apps using visual tools provide new opportunities for researchers collecting socioeconomic data in developing countries.

Conservation Agriculture (CA) continues to gain relevance among small and medium-scale farmers in African countries, including Zambia, in response to food insecurity and the adverse effects of climate change. The rise in the number of market-oriented farmers, known as 'emergent farmers,' who acquire and utilize tractors and associated implements for agricultural production, has brought new dynamism to Zambian agriculture. While prior studies emphasize the significance of considering socio-economic and psychological factors in understanding farmers' adoption decisions, the underlying socio-economic and psychological determinants influencing emergent farmers' interest in CA have not been explored. This study examined the behavioral intentions of Zambian emergent farmers concerning Mechanized Conservation Agriculture (MCA) using the Decomposed Theory of Planned Behavior constructs: attitudes, perceived behavior control, subjective norms, and farmers' background factors. We surveyed 119 emergent farmers from selected districts and analyzed their responses through descriptive statistics and Spearman's rank correlation coefficient. We employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the relationships among behavioral constructs (attitude, perceived behavioral control, and social norms) and the intention to adopt MCA. The results indicated that the positive attitude of Zambian emergent farmers had a significant impact (path coefficient = 0.24) on their intention (mean = 4.51) to adopt MCA on at least part of their farms. Perceived behavioral control, which measures perceived ability, resources, and skills for practicing MCA, also had a significant impact on intention (path coefficient = 0.37). Factors such as media influence, social influence, technical training, and extension services had positive but insignificant effects on farmers' intention to adopt MCA. Background factors, including overall farm size, farmer's age, area under CA, and years of CA use, showed a positive and significant correlation with farmers' intention to adopt MCA. These findings underscore the crucial socio-psychological facets of emergent farmers, which can be valuable for policymakers and practitioners aiming to harness their potential in promoting and enhancing sustainable agricultural approaches like MCA in Zambia. • Effects of climate change foster the practice of Conservation Agriculture in Zambia. • Farmers embracing mechanization for increased production is on the rise in Zambia. • Understanding their perceptions and intentions about mechanized agriculture is key. • Results reveal farmers' positive attitude and intention about mechanized CA. • Sustainable agricultural mechanization can boost economic and food security. [ABSTRACT FROM AUTHOR]