Analysis of the Variables Affecting the Adoption of Artificial Intelligence and Big Data Tools Among Moroccan Agricultural and Chemical Fertilizer Industry Firms: Research Model Development

Artificial intelligence and big data are two technologies that are revolutionizing today’s world; countries and companies that adopt them have an undeniable competitive advantage over their competitors and can face various problems. With the phenomenon of hydric stress that is facing Morocco and the challenges confronting its chemical fertilizer industry that provides raw materials for the agricultural sector, the country has to introduce precision agricultural process and virtual sensing techniques in the chemical manufacturing to ensure performance and economic competitiveness. But to do so, we must first analyze the variables that can delay and even block the adoption process. This paper presents a new proposal for a research model based on the TAM and TOE models that will help us to answer, through an exploratory empirical study, the question of the variables that positively or negatively influence the process of adoption of these technologies by organizations. To describe the model, we introduce its various constructs and its main variables, as well as the hypotheses to be analyzed based on the literature review and adapted to the purpose of the study. Then we present the results of our exploratory empirical study aimed to refine the research model we developed earlier. Finally, we discuss the main implications of this research model, the opportunities that could arise from this proposal and the future of this research.