Digital Irrigated Agriculture: Towards a Framework for Comprehensive Analysis of Decision Processes under Uncertainty

Abstract

Several studies address the topic of Information and Communication Technologies (ICT) adoption in irrigated agriculture. Many of these studies testify on the growing importance of ICT in influencing the evolution of the sector, especially by bringing down information barriers. While the potentialities of such technologies are widely investigated and confirmed, there is still a gap in understanding and modeling decisions on ICT information implementation. This gap concerns, in particular, accounting for all the aspects of uncertainty which are mainly due to a lack of knowledge on the reliability of ICT and on the errors of ICT-information. Overall, such uncertainties might affect Decision Makers’ (DM’s) behavior and hamper ICT uptake. To support policy makers in the designing of uncertainty-management policies for the achievement of the benefits of a digital irrigated agriculture, we further investigated the topic of uncertainty modelling in ICT uptake decisions. To do so, we reviewed the economic literature on ambiguity, in the context of the wider literature on decision making under uncertainty in order to explore its potential for better modeling ICT uptake decisions. Findings from the discussed literature confirm the capabilities of this approach to yield a deeper understanding of decision processes when the reliability of ICT is unknown and provides better insights on how behavioral barriers to the achievement of potential ICT-benefits can be overcome. Policy implications to accompany the sector in the digitalization process include mainly: (a) defining new approaches for ICT-developers to tailor platforms to answer heterogeneous DMs’ needs; (b) establish uncertainty-management policies complementary to DM tools adoption.

Keywords

• information and communication technologies
• digital irrigated agriculture
• artificial intelligence
• ambiguity
• risk