Thomas Heckelei is Professor for Economic and Agricultural Policy at the University of Bonn, Germany. He is an experienced researcher in the area of agricultural policy specializing in quantitative policy impact analysis based on econometric and simulation methodologies. He co-coordinated the original development of the CAPRI model from 1997 until 2000 and regularly contributed to the further strategic development of the overall modelling system as well as the empirical specification of the supply module. Beyond large scale modelling of policy impacts, Thomas Heckelei worked extensively on applied econometric methodologies for the analysis of agri-environmental and trade policies as well as farm structural change. Recently he moved towards the use of machine learning techniques in agricultural and applied economics. His publication record demonstrates his basic research interest and competence in quantitative methods and the economics of agricultural policy.
Impacts of robotics and sensing technologies for crop production – an economist’s perspective
Robotics and sensing technologies promise to have a transformative impact on agriculture’s ability to feed a growing global population while protecting nature’s non-material contributions to people. But the assessment of their (potential) impact faces the challenge that such technologies are not yet widely developed for practical use.
Based on ongoing work in the ‘Technology adoption and impact’ core project of the excellence cluster PhenoRob, this presentation aims to (1) briefly characterize what we generally know (and do not know) about the adoption of technologies in agriculture and (2) identify major pathways through which robotics and sensing technologies may transform agriculture. Technology adoption studies in agriculture are abundant and they reveal the importance of individual and farm characteristics beyond profitability considerations for the likelihood to adopt.
However, the studies rarely go beyond a local or regional context and generally focus on specific technologies. Consequently, the relevance of contextual variables and attributes of technologies is not fully understood. In order to understand the relevance of different contexts for the impact of robotics and sensing technologies, the presentation looks at cases varying with respect to production systems (conventional versus organic), region (developed versus developing countries) and position in the supply chain (breeding versus market production). Societal impacts and effects on production systems or farm structures are highly dependent on multiple local context factors and enabling as well as regulatory policies. Innovative approaches to technology impact assessment are needed to inform both technology development and policy design for sustainable outcomes.
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