Big data analytics implementation in small and medium sized enterprises: The perspectives of managers and data analysts

Abstract

While many large firms have implemented Big Data Analytics (BDA), it is unclear whether Small and Medium-sized Enterprises (SMEs) are ready to adopt and use this technology. This study investigates BDA implementation from the perspective of both managers and data analysts. Managers are mostly influenced by factors from the external environment, while data analysts are mostly influenced by technological factors. Hence, in this study, it is contended that managers imitate the behavior of external institutions, while data analysts mostly evaluate technology characteristics in the process of BDA implementation. The present study draws on institutional, organizational change, and diffusion of innovation theories through the lens of an imitation-evaluation perspective to investigate readiness and adoption behaviours. Accordingly, a theoretical research model was developed to explore the salient variables that impact organizational and data analysts’ readiness for implementing BDA in SMEs. To test these assertions, two surveys were conducted with 340 responses including 170 managers and 170 data analysts in SMEs in North America. The findings demonstrate that: (1) an imitation perspective plays a significant role in organizational readiness to adopt BDA; (2) uncertainty in big data technologies can intensify the effect of normative pressures on organizational readiness; (3) big data complexity, trialability, and relative advantage impact data analysts’ readiness to use big data analytics; and (4) the influence of relative advantage is attenuated by the high level of data analytics skills. These findings provide valuable contributions to the theory and practice of BDA implementation in SMEs in the BDA adoption and use literature.