Analysing the artificial intelligence of e-marketing adoption in the b2b enterprise market

Introduction: This research examines the factors influencing the adoption of e-marketing by B2B organizations in Jordan and its impact on overall business performance. It draws on relationship marketing, innovation adoption theories, and integrates concepts from Artificial Intelligence Driven Big Data Analytics (AI DBDA) and Cognitive Service Analytics (CSA). The study is framed around the Diffusion of Innovation (DoI) theory and the Technology Acceptance Model (TAM), providing a comprehensive view of the determinants that drive e-marketing adoption. Methods: A quantitative research approach was employed, using Structural Equation Modelling (SEM) for data analysis. A survey was administered via a Google Form, collecting 226 valid responses from B2B organizations in Jordan. The theoretical framework was tested using advanced statistical techniques to evaluate the relationships between e-marketing adoption and various influencing factors. Results: The findings indicate that e-marketing adoption is significantly influenced by AI-DBDA, CSA, perceived compatibility, relative advantage, perceived ease of use, and market performance. These factors were found to be crucial in determining the extent to which B2B organizations in Jordan embrace e-marketing. Conclusions: This study emphasizes the importance of environmental factors, such as technological capabilities and organizational perceptions, in the adoption of e-marketing. The results contribute to the limited empirical research on e-marketing adoption in developing countries, offering insights into how these factors enhance business performance. These findings suggest that for successful e-marketing implementation, organizations need to focus on technological innovations and alignment with their business objectives.