Using smartphone app collected data to explore the link between mechanization and intra-household allocation of time in Zambia

Abstract

Digital tools may help to study socioeconomic aspects of agricultural development that are difficult to measure such as the effects of new policies and technologies on the intra-household allocation of time. As farm technologies target different crops and tasks, they can affect the time-use of men, women, boys, and girls differently. Development strategies that overlook such effects can have negative consequences for vulnerable household members. In this paper, the time-use patterns associated with different levels of agricultural mechanization during land preparation in smallholder farming households in Zambia were investigated. A novel data collection method was used: a pictorial smartphone application that allows real-time recording of time-use, which eliminates recall bias. Existing studies analyzing the intra-household allocation of resources often focus on adult males and females. This study paid particular attention to boys and girls as well as adults. The study addressed seasonal variations. Compositional data analysis was used to account for the co-dependence and sum constraint of time-use data. The study suggests a strong gender differentiation for land preparation activities among mechanized households; for households using manual labor, such differentiation was not found. There is some evidence that the surplus time associated with mechanization is used for off-farm and domestic work. The study cannot confirm concerns about negative second-round effects: mechanized land preparation is not associated with a higher workload for women and children during weeding and harvesting/processing. The study provides a proof-of-concept that smartphone applications can be used to collect socioeconomic data that are difficult to measure but of high relevance.

The forgotten agriculture-nutrition link: farm technologies and human energy requirements

“…6 Future studies may also use compositional regression approaches to better capture the inherent trade-offs between different time-use activities, which may affect the outcome variable "farm share time". However, insights from a prior study using the same timeuse data and compositional data (Daum et al, 2021) suggest that this does not undermine the findings. Daum et al (2021) also find that the "farm share time" during land preparation and weeding are significantly correleated with the degree of mechanization and gender and that "farm share time" during harvesting is significantly correlated with gender.…”

“…However, insights from a prior study using the same timeuse data and compositional data (Daum et al, 2021) suggest that this does not undermine the findings. Daum et al (2021) also find that the "farm share time" during land preparation and weeding are significantly correleated with the degree of mechanization and gender and that "farm share time" during harvesting is significantly correlated with gender. Another limitation is that the study provides only limited insights into the adequacy of calorie intake for individuals in different household categories (manual, animal, and tractor).…”

Mechanization and sustainable agri-food system transformation in the Global South. A review

“…In a study in Nigeria, tractor use raised real incomes by 13% (Takeshima and Lawal 2020). Rising agricultural labor productivity often enables households to allocate time away from agriculture and pursue off-farm work (Daum et al 2021a;Kansanga et al 2020;Ma et al 2018;Theis et al 2019). Pingali (2007) argues that "poor households benefit the most since the released labor can be reallocated for other income-earning activities or leisure" (p. 2800).…”

“…Mechanization may be of particular relevance to reducing child labor in agriculture (Takeshima and Vos 2022). Seventy percent of child labor is in agriculture, affecting the present and future livelihoods of 112 million children (ILO 2021), by negatively affecting their well-being and health as well as the ability to play or go to school (Daum et al 2021a;ILO 2021). Mechanization may also affect mental health as it can be associated with higher social status (Daum et al 2021a) and increased resilience, as shown above.…”

Window dressing inequalities and constructing women farmers as problematic—gender in Rwanda’s agriculture policy

“…In the current neoliberal development paradigm, critics argue that development theory and practice should (re-)connect with feminist theories of care, justice, and emancipation to achieve substantive and sustainable social change (Cornwall and Rivas 2015;Nyambura 2015;Wallace 2020). In contemporary African agricultural restructuring and transition, known as the New Green Revolution for Africa (GR4A), scholars highlight and challenge the gendered, unequal outcomes of interventions for, among others, agricultural mechanization (Daum et al 2021;Kansanga et al 2019), new and improved seeds and varieties (Addison and Schnurr 2016;Bergman Lodin 2012), new breeds (Wangui 2008), irrigated agriculture (Nation 2010), inorganic fertilizer and pesticide use (Christie et al 2015;Luna 2020), market integration (Quisumbing et al 2015;Tavenner and Crane 2018) and commercialization (Gengenbach 2020). Recent studies of national agriculture policy in Africa consider its limitations with regard to advancing equality.…”