| dc.description.abstract | There are many factors in adopting BDA, especially based on DOI (Diffusion of Innovation Theory), in agriculture organizations. Thus, the goal of the present study is to analyze the influencing factors in adopting Big Data Analytics (BDA) in agriculture organizations. The research was made using a qualitative approach, encompassing multiple cases, collecting the experiences participants had, trying to understand the manifestation of the phenomena where they took place and, from different perspectives. Through this study it was possible to validate the attributes of adopting innovation (BDA) in the agriculture sector under Roger’s theoretical DOI lens (1971), identifying and discussing emerging subcategories in the sense of adopting BDA, thus contributing to new discussions regarding the topic. Based on these attributes, seven propositions were generated in order to evaluate the adoption of BDA in agriculture organizations, five of which, through this research, have been confirmed. The propositions are: technological compatibility as a positive influence in adopting BDA in such a sector, the technological complexity in a sense of negatively influencing the decisions of adopting BDA in agriculture, the relative advantage perceived as a positive influence in adopting BDA instruments in agriculture organizations, the possibility of experimenting and observing as previous evaluations positively influencing the adoption of BDA in these organizations, while only two were not confirmed. They are: willingness in the sense of the pressure made by suppliers positively influencing to adopt BDA and the talent capability in BDA analysis also as a positive influence in deciding to adopt BDA solutions in the agriculture sector. It was noticed that the factors of adopting BDA solutions in agriculture are aligned with the DOI features presented by Rogers (1971), apart from presenting, in the approaches, subcategories that have come to complement them. The non-confirmed propositions were exactly the ones based in complementary features to the DOI specifically for this study. | en |
