This initial study's key purpose was to investigate whether absorptive capacity performed a mediating role on the relationship between business analytics capability and small-to-medium-sized enterprises (SMEs) performance in the United States. The study's findings are more relevant now as the COVID-19 pandemic continues to impact small-to-medium-sized enterprise (SME) businesses in the United States. The study derived from the resource-based view approach, the dynamic capabilities dimension perspective, through the theoretical lens of the reconceptualization of absorptive capacity by Zahra and George (2002). The study empirically tested mediation through a series of regressions based on Baron and Kenny (1996). As recent extensions of the resource-based view theory, absorptive capacity and business analytics embody the dynamic capabilities, business intelligence, and knowledge management for modern business firms to align, modify, and reconfigure during a dynamic and volatile global business environment. Throughout the pandemic, it appears businesses have had to continually regain economic ground. This paper is an effort to apply the findings of research on the importance of absorptive capacity and business analytics capability as it pertains to the reality of the COVID-19 pandemic on SMEs. The study contributed to the theoretical body of knowledge on dynamic capabilities by empirically demonstrating how SMEs may manifest improvement in performance in the twenty-first century by utilizing data in collaboration with business analytics at the realized absorptive capacity dimension. In wake of the ongoing COVID-19 pandemic, exploring the research study's findings may provide insight to help SMEs survive during these difficult times, and even thrive, by increasing their absorptive capacity to utilize data analytics effectively.
Keywords: Resource-Based View, Absorptive Capacity, Business Analytics, Dynamic Capabilities, Information Technology, Small-To-Medium-Sized Enterprise (SME), COVID-19
This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.
Copyright (c) 2022 Array