Investment decisions in agricultural research and development (R&D), particularly in plant breeding, often face significant ambiguity. Without clear market intelligence, funds may be spread across many breeding pipelines rather than concentrated in those with the greatest potential impact. A recent study explored how plant breeding professionals use market information to prioritize R&D investments and how the quality and source of information influence their decision-making.
The Challenge: Managing Uncertainty in Breeding Investments
Public-sector breeding programs invest millions annually to develop improved crop varieties, particularly for smallholder farmers in the global South. Many breeding decisions are based on informal processes of gathering information on demand rather than systematic market research. While transdisciplinary approaches that include social scientists are gaining traction, market research remains underutilized in prioritizing breeding pipelines.
To examine how plant breeding professionals respond to different types of market information, researchers conducted an online experiment. In this experiment, participants from around the world allocated investment funds between two breeding pipelines with varying probabilities of success. Market information ranging from high-quality, rigorous studies to small-scale participatory research was provided at different stages, sometimes free and sometimes at a cost.
Key Findings: The Role of Market Information in Investment Decisions
Better information leads to more prioritization. Without market information, participants split investments almost evenly. When market research such as rigorous scientific studies, participatory varietal selection, or conversations with local value chain stakeholders helped reduce ambiguity, participants concentrated investments in the pipeline that appeared most promising to them based on the projected probability that a pipeline’s varieties would be valued.
Participants over-extrapolate from noisy data. Many participants took estimates of pipeline success at face value, even when signals were noisy or biased. Breeding funds could be misallocated if decision-makers fail to assess information quality.
Strong willingness to pay for market insights—but not always for quality. Most participants were willing to pay for market research, but nearly half preferred lower-quality information that was biased due to non-representative sampling procedures or imprecise due to a small sample size (for instance, conversations with local value chain stakeholders). This occurred even when higher-quality data with higher precision and reduced bias (framed as a rigorous scientific study) was available at the same price.
Bias toward familiar disciplines. While the source of market information (e.g., whether an agronomist versus an economist was conducting the rigorous scientific study) did not impact investment choices, it did influence willingness to pay. Participants were more likely to purchase research from experts in their own field.
Implications for Breeding Programs and Market Intelligence
Incentives alone are not enough. Encouraging breeding programs to focus on market demand is insufficient. Addressing cognitive biases and promoting evidence-based decision-making is crucial.
Quality of market research matters. Market research often involves small-scale participatory studies. Investing in broader, more representative surveys and training decision-makers to interpret market data accurately could enhance funding allocations.
Strengthening transdisciplinary collaboration. While social scientists play a growing role in breeding programs, they, too, are susceptible to biases. Better integration of expertise across disciplines can improve decision-making.
This research highlights the need for a more systematic approach to market intelligence in plant breeding. Improving how professionals use market data can ensure that R&D investments align with market needs and impact opportunities, leading to more widely adopted high-impact crop varieties.
