Investigating the Determinants of the Big Data Analytics Adoption with SEM and fsQCA Analysis

English (OpenAlex)

Big data is one of the most important driving forces for firms seeking a competitive advantage. This study examines the effects of system quality, information quality, perceived benefits, perceived ease of use, and perceived risks on the adoption of Big Data Analytics (BDA) by firms. The proposed model was tested using survey data collected from 210 firms that employ BDA tools. First, the validity and reliability of the constructs were assessed, and then the hypotheses were tested using both structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The results reveal that (i) information and system quality positively affect perceived benefits, (ii) perceived risk negatively affects perceived benefits, (iii) perceived benefits positively influence perceived usefulness, and (iv) perceived ease of use and perceived usefulness positively affect the intention to adopt BDA systems. This study contributes to the big data literature by developing a comprehensive and empirically grounded research model. While extending the Technology Acceptance Model (TAM), it highlights the role of external factors, specifically information and system quality, in shaping perceived benefits and influencing BDA adoption. Furthermore, by incorporating system and information quality into the TAM framework and applying a dual-method approach (SEM and fsQCA), this study provides novel theoretical and methodological insights into BDA adoption.