Exploring the Factors Influencing Big Data Technology Acceptance

Abstract

This research aims to determine the factors influencing big data technology acceptance with an industrial- organizational context. By using existing technology acceptance theories, literature review and industrial technical research on data management technologies, six external factors have been formulated for the quantitative study of this research. The Technology Acceptance Approach provides the theoretical basis for this model. External variables may be plugged into this model's latent construct of perceived ease of use. The quantitative study's primary data collected within big Hadoop User Groups in Sri Lanka who operate in a variety of sectors. Using 432 survey answers, we empirically verified and validated our proposed model using the structural equation modeling (SEM) software Smart PLS 3. The hypothesis tests are significant for seven out of nine route connections, according to the structural model analysis. Scalability, storage and processing, analytics capability, and output quality are four external factors that this research effectively evaluates and verifies in terms of technical capabilities in adopting new technologies. The suggested model finds flexibility and dependability to be non-significant external factors. These results contribute significantly to the advancement of theoretical knowledge and contribute to the groundwork for future study to improve our knowledge in the field of user acceptance behavior. This study advises businesses on what technical characteristics and capabilities to look for when purchasing a complicated piece of equipment.