The cluster employs the following tools and technologies.
Analytical Protocols and Methods: Developing and utilizing standardized analytical protocols and methods to ensure consistent and rigorous analysis of research outcomes and impact assessments.
Quantitative Analysis Tools: Utilizing statistical analysis software and modeling tools to conduct quantitative analysis, assess impacts, and measure cost-effectiveness of agricultural research and development interventions.
Qualitative Research Techniques: Employing qualitative research methods, such as interviews, focus group discussions, and case studies, to gather in-depth insights and understand the context, drivers, and constraints related to technology adoption and impact.
Ex-ante Analysis Tools: Using tools like system dynamics and agent-based bioeconomic modeling to conduct ex-ante analysis, enabling the assessment of potential impacts and outcomes of current and future innovations before implementation.
Ex-post Impact Analysis Methodologies: Applying rigorous ex-post impact analysis methodologies to evaluate the impacts of projects, technologies, markets, social organization, and other development interventions. This may include impact evaluation frameworks, surveys, and data analysis techniques.
Data Science and Big Data Analytics: Utilizing data science techniques, including big data analytics and machine learning, to analyze large-scale datasets, extract insights, and identify patterns related to technology adoption and impact.
Foresight and Scenario Analysis Tools: Using foresight and scenario analysis tools to explore different future scenarios, identify system-level leverage points, and inform research priorities and strategies.
Cost-Effective Data Collection Tools: Developing innovative tools and approaches for cost-effective large-scale data collection, including mobile data collection platforms, remote sensing technologies, and digital survey tools.
Panel Datasets: Establishing and maintaining panel datasets that track medium- and long-term impacts of projects, technologies, and other development interventions, providing credible evidence for impact assessment.
Geographic Information Systems (GIS): Utilizing GIS technology to map and analyze spatial data related to technology adoption, impact assessments, and identifying target areas for interventions.
By leveraging these tools and technologies, the TAI cluster at ICRISAT enhances its capacity to conduct robust and evidence-based analysis of technology adoption and impact, contributing to effective decision-making, policy formulation, and systems transformation in agricultural research and development.