Assessing Mobile App Influence on Farmers’ Decision-Making in Pest Management

Thesis Abstract

In the face of escalating pest infestations that threaten crop yields and jeopardize food security, farmers' decision-making processes regarding pest management have become increasingly reliant on emerging digital technologies, particularly mobile applications. This study investigates the influence of mobile app usage on farmers’ pest management decisions, aiming to elucidate the extent to which technology shapes agricultural practices within a developing country context. The specific objectives include (1) to assess the adoption rate of pest management mobile applications among farmers; (2) to identify the factors influencing farmers’ decision to utilize these apps; (3) to evaluate the impact of app usage on pest control practices and crop yields; and (4) to determine the overall influence of mobile app-based information on decision-making efficacy. The research adopts a mixed-methods design, integrating quantitative surveys and qualitative interviews across a representative sample of 400 smallholder farmers in the maize-producing region of the country. The quantitative component involves structured questionnaires designed to quantify app adoption levels, decision-making patterns, and pest management outcomes. The qualitative component includes semi-structured interviews with 20 key informants—comprising extension officers and highly experienced farmers—to garner in-depth insights into user experiences, perceptions, and contextual factors impacting app utilization. Data collection instruments were validated through pilot testing and expert review, ensuring content validity and internal consistency, with reliability confirmed via Cronbach’s alpha coefficients exceeding 0.8. Quantitative data is analyzed using multiple regression analysis to assess the relationship between mobile app usage and pest management decisions, controlling for socio-economic and demographic variables. Thematic analysis is employed for qualitative interview transcripts to explore contextual factors, user perceptions, and barriers to app adoption. The study is anchored within the Technology Acceptance Model (TAM) and the Diffusion of Innovations theory, which provide a theoretical framework for understanding adoption behavior and information dissemination processes. Structural equation modeling (SEM) will be used to test the hypothesized pathways between app usability, decision-making confidence, and pest control outcomes. Expected findings indicate a significant positive relationship between mobile app usage and improved pest management decisions, resulting in reduced pesticide misuse, enhanced timely interventions, and increased crop yields. Additionally, factors such as digital literacy, trust in app information, and extension support are anticipated to significantly influence adoption rates. Findings are expected to demonstrate that mobile applications serve as effective decision-support tools, especially when integrated with farmer training and extension services. This research contributes to existing knowledge by empirically validating the role of ICT in transforming pest management practices among smallholder farmers, addressing gaps related to contextual and behavioral determinants of technology adoption in rural agricultural settings. It highlights the potential of mobile apps as scalable interventions for agricultural extension and pest control strategies. The main conclusion emphasizes that mobile applications can significantly enhance farmers’ decision-making efficacy and pest management outcomes when designed with user-centric features and supported by adequate extension services. Recommendations include enhancing app usability, expanding extension programs around digital literacy, and promoting policy frameworks that foster technology adoption. Future research should explore longitudinal impacts of sustained app use and consider integrating ecological and economic analyses for comprehensive evaluation. Ultimately, the study advocates for broader deployment of mobile decision-support tools as an essential component of modern sustainable agriculture efforts.