Factors Affecting Intention to Use Big Data Tools: An Extended Technology Acceptance Model

Abstract

The purpose of this study is to examine the factors affecting the intention to use big data tools, using an extended technology acceptance model. The model includes job relevance, big data dimensions, compatibility, self-efficacy, complexity, and anxiety. The study was conducted on a Turkish airline company, and data were gathered from its employees through an online survey. A total of 252 questionnaires were collected. The results show that behavioral intention to use big data technology is explained by perceived usefulness and perceived ease of use. Of these, perceived usefulness has a higher direct influence on behavioral intention to use big data tools. Another result of this study is that perceived usefulness is explained by perceived ease of use, job relevance, compatibility, and big data dimensions, where big data dimensions have a higher direct influence on perceived usefulness. The final result is that perceived ease of use is explained by self-efficacy and anxiety. Of these two factors, self-efficacy has a higher direct impact on the perceived ease of use.