Evaluating the adoption of sensor and robotic technologies from a multi-stakeholder perspective: The case of greenhouse sector in China

Abstract

Emerging digital technologies are transforming greenhouse production, yet it remains unclear which technologies are likely to achieve widespread adoption. This study evaluates greenhouse sensor and robotic technologies from an innovation-oriented perspective, aiming to bridge the gap between technology assessment and innovation adoption. Using the Diffusion of Innovation theory as a framework, we defined evaluation criteria based on the perceived technology attributes. Our evaluation process involved multiple stakeholder groups within the Chinese greenhouse sector—growers, investors, technology suppliers, and policy makers. The Bayesian best-worst method was used to elicit stakeholder preferences and expert-rated technology scores for each attribute. These were combined to produce a probabilistic overall performance score for each technology. The results highlighted the heterogeneous preferences among stakeholders. The leaf temperature sensor received the highest score among growers and policy makers. Investors and technology suppliers favored the scouting and harvesting robots, respectively. These findings underscore the importance of tailoring technology promotion strategies to the specific priorities of each stakeholder group.