Antecedents of big data adoption in financial institutions

Abstract

Big data (BD) adoption is still relatively slow despite the numerous business opportunities that it embodies. Within the context of financial institutions in South Africa, the specific drivers of big data adoption remain largely indeterminate. Consequently, this study explores the possible relationships between perceived usefulness and perceived ease of use and actual big data adoption, while being duly cognisant of the role that behavioural intention to adopt big data could play. The study employed a survey research approach and relied on data collected from a purposive sample of 195 management level employees of financial institutions. Regression analysis to test the hypothesised relationships in the study revealed that perceived usefulness and perceived ease of use were statistically significant predictors of big data adoption. Instructively, this relationship was subject to the extent of behavioural intention of respondents. For respondents with a low behavioural intention to adopt big data, perceived usefulness and perceived ease of use displayed a statistically insignificant relationship with big data adoption. Conversely, the regression model for the group of respondents with a high behavioural intention to adopt big data is statistically significant. These findings enrich literature related to big data from a developing country context while concurrently identifying veritable antecedents of big data adoption in financial institutions.