Predicting big data analytics adoption intention among small and medium enterprises in the Philippines - Victor James C. Escolano; Wei-Jung Shiang; Alexander A. Hernandez; Darrel A. Cardaña (Universitas Ahmad Dahlan, 2025)
Big data analytics (BDA) has increasingly become popular both in theory and practice in recent years. Globally, larger businesses have used BDA to collect, study, and evaluate vast volumes of data to identify market trends and insights that lead to sound and intelligent business decisions. However, its adoption in small and medium enterprises (SMEs) is not fully maximized because of a variety of factors, including a lack of expertise and financial repercussions. As such, this paper seeks to delve into the predictors of BDA adoption intention among SMEs in a developing nation by extending the technology acceptance model (TAM). The quantitative surveys obtained from 438 SMEs were analyzed using partial least squares and structural equation modeling (PLS-SEM). The results revealed that perceived benefits, namely system quality, information quality, and predictive analytics accuracy, had positive relationships with perceived ease of use and usefulness, subsequently leading to attitude towards using BDA. Likewise, perceived security significantly influences perceived benefits, perceived ease of use, and attitude towards use of BDA. Further, attitude towards use was the most significant predictor of intention to adopt BDA among SMEs. Generally, the study indicates a positive interest in adopting BDA among Philippine SMEs.