NEW APPROACHES IN RESEARCH METHODOLOGY BASED ON ARTIFICIAL INTELLIGENCE AND BIG DATA

Madalina Cuc
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Madalina Cuc: MIHAI VITEAZUL NATIONAL INTELLIGENCE ACADEMY (MVNIA)

Annals - Economy Series, 2024, vol. 2, 65-81

Abstract: This paper explores how the integration of Artificial Intelligence (AI) into research methodologies is changing the research paradigm by improving data analysis, efficiency and innovation in a variety of fields. All the emerging and disruptive technologies based on AI and BIG DATA will thus allow researchers to model, train, calibrate and ultimately simulate very complex research scenarios by accelerating and simplifying current quantitative testing methods, allowing to work with sample sizes close to those of the analyzed population. Emerging and innovative research methodologies based on the application of AI tools are thus presented, which actually revolutionize traditional ways of research by adopting artificial intelligence algorithms on each hypothesis and creating specific working models for each tested hypothesis, obtaining valuable insights regardless of the validation or not of a hypothesis by classical quantitative analysis. In the particular situation presented, it will be explained how the Elaboration Likelihood Model will be applied to the marketing of social networks, with an emphasis on the cognitive process and the expression of attitude within them, depending on the characteristics of the message and the involvement of users. This proposed research will also consider the ELM framework and increase its dimension, providing a more contemporary perspective on persuasion and cognitive engagement by introducing AI and big data as part of the dimension of ELM methodologies, thus illustrating a paradigm shift in research and representing a model approach to moving from methodologies based on traditional qualitative and quantitative methods to emerging ones based on AI and BIG DATA.

Keywords: Research Methodology; Artificial Intelligence; Big Data; Social networks; Knowledge Management (search for similar items in EconPapers)
Date: 2024
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