Leveraging smart farming technologies for enhanced agricultural production

Abstract

Precision agriculture and smart farming technologies offer significant potential to enhance agricultural productivity and sustainability in Germany. The central issues covered within this thesis are an analysis of the main drivers that contribute to agricultural innovation and a particular look at the determinants influencing technology adoption decision-making among contemporary German agriculturists. Drawing on a comprehensive literature review, a survey of different farmers and interviews with agricultural professionals, this mixed-methods approach was executed. The data analysis based on the diffusion of innovation theory, the technology acceptance model, resource-based view and SWOT analysis additional to the Maturity Model which compared the results from the PWC results to this survey results. Major findings include financial barriers such as the upfront costs for new technologies and doubt on how to recover them. Concerns such as technical complexity and data security also mitigate adoption. For instance, innovation can be expedited by policy incentives and subsidies, which often fall short of motivation. Knowledge exchange emerges as crucial for aiding adoption, but German bureaucratical barriers are persistent regarding foreign advancements. This study is an attempt to bring in more clarity to the multifaceted sphere of innovation processes in German agriculture. The nature of priority areas, such as cost reduction and improved training, are emphasized for stakeholders aimed at promoting adoption in digital-forward productivity technologies. Ultimately, overcoming barriers and realizing the promise of precision agriculture requires a multidimensional strategy.

Date of Award	25 Jan 2024
Original language	English
Awarding Institution	Universidade Católica Portuguesa
Supervisor	Peter V. Rajsingh (Supervisor)