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Ndou, Kharendwe 2026 2026-06-22T06:37:38Z 2026-06-22T06:37:38Z 2026-05-19 Ndou, K. 2026. Developing a fourth industrial revolution adoption framework for South African rural small-scaled maize-producing farms. . . https://univendspace.univen.ac.za/handle/11602/3268 Ndou K. Developing a fourth industrial revolution adoption framework for South African rural small-scaled maize-producing farms. []. , 2026 [cited yyyy month dd]. Available from: Ndou, K. (2026). <i>Developing a fourth industrial revolution adoption framework for South African rural small-scaled maize-producing farms</i>. (). . Retrieved from Ndou, Kharendwe. <i>"Developing a fourth industrial revolution adoption framework for South African rural small-scaled maize-producing farms."</i> ., , 2026. TY - Dissertation AU - Ndou, Kharendwe AB - The Fourth Industrial Revolution (4IR) represents the use of cutting-edge technologies like artificial intelligence, automation, the Internet of Things (IoT), and big data in a variety of sectors. Within agriculture, these technologies have the ability to support small-scale farming significantly towards efficiency and productivity. This study strives to develop a framework for small-scale rural maize producers to optimise their use of 4IR technologies in managing resources. This study examines the factors influencing the adoption of 4IR technology by small-scale rural maize-producing farmers in Vhembe District. Drawing on the diffusion of innovation theory (DOI) and the technology acceptance model (TAM), the study explores farmers’ knowledge and perception of the relative advantage of the technology, compatibility, complexity, trialability, observability, and perceived usefulness of 4IR tools. The study employed a quantitative approach using multistage sampling through stratified sampling, random sampling and snowball sampling to achieve the main objectives of this study. The researcher collected quantitative data by distributing structured online questionnaires to 222 respondents, constituting rural small-scale maize-producing farmers in Vhembe District, in Limpopo Province. The quantitative data were analysed using the IBM Statistical Package for Social Science (SPSS) v. 29 and presented the results in tables, graphs, and pie charts as percentages and frequencies. The findings indicate that perceived relative advantage, compatibility, trialability, observability, perceived ease of use (PEOU), and perceived usefulness (PU) are significant predictors of technology adoption. The results reveal barriers, such as a lack of infrastructure, inadequate training provision, high costs, and data security concerns. Consequently, this study recommends a consolidated framework that encompasses awareness campaigns, cost-effective solutions, capacity development, infrastructure investment, using simple designs, practical demonstrations, a supportive policy environment, resolving safety issues, and monitoring and evaluating the process. Small-scale rural maize-producing farms can use the proposed framework to guide their adoption of 4IR to manage and allocate their resources effectively. DA - 2026-05-19 DB - ResearchSpace DP - Univen KW - Fourth Industrial Revolution (4IR)n KW - Artificial intelligence (AI) KW - Small-scale farms KW - Rural maize-producing KW - Diffusion of innovation theory (DOI) KW - Technology acceptance model (TAM) LK - https://univendspace.univen.ac.za PY - 2026 T1 - Developing a fourth industrial revolution adoption framework for South African rural small-scaled maize-producing farms TI - Developing a fourth industrial revolution adoption framework for South African rural small-scaled maize-producing farms UR - ER - MCom in Business Information Systems Department of Business Information Systems The Fourth Industrial Revolution (4IR) represents the use of cutting-edge technologies like artificial intelligence, automation, the Internet of Things (IoT), and big data in a variety of sectors. Within agriculture, these technologies have the ability to support small-scale farming significantly towards efficiency and productivity. This study strives to develop a framework for small-scale rural maize producers to optimise their use of 4IR technologies in managing resources. This study examines the factors influencing the adoption of 4IR technology by small-scale rural maize-producing farmers in Vhembe District. Drawing on the diffusion of innovation theory (DOI) and the technology acceptance model (TAM), the study explores farmers’ knowledge and perception of the relative advantage of the technology, compatibility, complexity, trialability, observability, and perceived usefulness of 4IR tools. The study employed a quantitative approach using multistage sampling through stratified sampling, random sampling and snowball sampling to achieve the main objectives of this study. The researcher collected quantitative data by distributing structured online questionnaires to 222 respondents, constituting rural small-scale maize-producing farmers in Vhembe District, in Limpopo Province. The quantitative data were analysed using the IBM Statistical Package for Social Science (SPSS) v. 29 and presented the results in tables, graphs, and pie charts as percentages and frequencies. The findings indicate that perceived relative advantage, compatibility, trialability, observability, perceived ease of use (PEOU), and perceived usefulness (PU) are significant predictors of technology adoption. The results reveal barriers, such as a lack of infrastructure, inadequate training provision, high costs, and data security concerns. Consequently, this study recommends a consolidated framework that encompasses awareness campaigns, cost-effective solutions, capacity development, infrastructure investment, using simple designs, practical demonstrations, a supportive policy environment, resolving safety issues, and monitoring and evaluating the process. Small-scale rural maize-producing farms can use the proposed framework to guide their adoption of 4IR to manage and allocate their resources effectively. 1 online resource (vi, 128 leaves) en PDF University of Venda Fourth Industrial Revolution (4IR)n Artificial intelligence (AI) Small-scale farms Rural maize-producing Diffusion of innovation theory (DOI) Technology acceptance model (TAM) UCTD 635.670968257 Farms, Small -- South Africa Farms, Size -- South Africa Family farms -- South Africa Agriculture and state Corn -- South Africa Corn -- Computer programs Corn -- Technological innovations -- South Africa Developing a fourth industrial revolution adoption framework for South African rural small-scaled maize-producing farms Dissertation embargo