The objective of the study was to determine the factors that influence the perceptions of smallholder farmers towards the adoption of digital technologies. A purposively selected sample of 250 smallholder farmers who were cross-sectionally surveyed from Port St Johns and Ingquza Hill Local Municipalities in South Africa was used in the study. The Technology Acceptance Model (TAM) and the Attention, Desire, and Action (AIDA) model were used to analyse the data. The results showed that digital technologies were perceived to be expensive, cause a digital divide, and discouraged the use of Indigenous Knowledge even though they increased production. Positive perception towards digital technologies was associated with cattle rearing, with extreme negative perception for sheep and goat rearing. Educational level, employment status, monthly income, household size, being part of a cooperative (1% level), age, and source of income (10% level) were significant factors affecting smallholder farmers’ perceptions of digital technologies. In conclusion, there are economic, social justice, and traditional perceptions towards digital technologies by smallholder farmers, with socio-economic factors affecting the perceptions. The study recommends providing low-cost digital technologies that promote Indigenous Knowledge, which should target the youth and young farmers with less education in small households who are full-time farmers with moderate-to-high incomes and are part of farmer groups/organisations.

This study relates agricultural income and agricultural carbon dioxide (CO₂) emissions in the context of environmental Kuznets curves for South Africa. We posit likely relationships between UN Sustainable Development Goals (SDG) 1, 2 and 13, relating food production to climate change action. CO₂ emissions, income, coal energy consumption and electricity energy consumption time series data from 1990 to 2012 within the South African agricultural sector were used. The autoregressive distributive lag bounds-test and the error correction model were used to analyse the data. The results show long-run relationships. However, agricultural income was only significant in the linear and squared models. Changes in agricultural CO₂ emissions from the short run towards the long run are estimated at 71.9%, 124.7% and 125.3% every year by the linear, squared and cubic models, respectively. Exponentially increasing agricultural income did not result in a decrease in agricultural CO₂ emissions, which is at odds with the Kuznets hypothesis. The study concludes that it will be difficult for South Africa to simultaneously achieve SDGs 1, 2 and 13, especially given that agriculture is reliant upon livestock production, the largest CO₂ emitter in the sector_. The sector needs to shift to renewable energy consumption with fewer CO₂ emissions.

Purpose: The purpose of this study is to estimate the determinants of household food insecurity in the Gauteng City-Region, South Africa. This is motivated by the fact that food insecurity remains a key challenge at the household level in South Africa. Furthermore, the Gauteng Province has been rapidly urbanising due to a migrant influx, both locally and internationally. The findings will assist the country in achieving its mandate on the local economic development policy, Agenda 2063 and the Sustainable Development Goals 1 and 2.Design/methodology/approach: The study adopted a quantitative cross-section design, utilising the binary logistic regression technique, drawing on the Gauteng City-Region Observatory Quality of Life 2020/2021 data, consisting of 13,616 observations, randomly drawn from nine municipalities in Gauteng City-Region.Findings: The main findings of the study highlight unemployment, health status, education, household size, indigency and income as the main determinants of food insecurity in Gauteng City-Region. Policies towards sustainable urban agriculture, improving access to education, increasing employment and income, and health for all can help improve the food insecurity status of households in the Gauteng City-Region.Research limitations/implications: Further studies would require an in-depth assessment of household coping mechanisms, as well as the influence of household income (notably government social grants) and access to credit on household food security status, to better understand the dynamics of food security in the Gauteng City-Region.Practical implications: Determinants of food insecurity should be considered when developing and implementing policies to reduce food insecurity in urban municipalities.Social implications: The study is of interest as it interdicts food insecurity issues, which have an effect on socio-economic well-being.Originality/value: The study adds value by providing evidence on the determinants of food insecurity in an urban setting in a developing country. Gauteng is the richest of all provinces in South Africa and is also at the receiving end of internal and international migration. Factors affecting food insecurity have changed in the nine cities. This compromises nutrition safety and calls for targeted policy interventions.

Food is one of the essential areas of service delivery required for a household’s wellbeing and development. Against this background, the literature suggests a high level of food insecurity among rural households in South Africa. Thus far, this study has investigated drivers of household-level food insecurity. Data were collected from 283 randomly selected respondents from Melani and Hamburg communities using a structured questionnaire. An ordered logit regression model was used to investigate drivers of household food insecurity. Descriptive statistics results revealed that most of the respondents from the study areas were food secure to mildly food secure (Melani-inland −73%; Hamburg-coastal −77.5%). The findings suggest that overall, the two communities were food secure. Econometrics results further revealed that factors like gender, household size, energy security, access to credit, farming, land ownership, and being able to afford to pay for water influence food insecurity of households in Melani and Hamburg. Therefore, to reduce household food insecurity, the study recommends that priority should be given to these socio-economic and institutional factors. This could be through improving gender and cultural policies which restrict women from generating income, training households about credit usage, and family planning to limit household sizes.