The Power of Big Data in Small and Medium-Sized Enterprises (SMEs): Creating Competitive Advantage Based on the Dynamic Capabilities Theory

Objective: The digitalization era has prompted researchers to explore the benefits of big data analytics as a tool for enhancing competitive advantage in organizations. Substantial evidence indicates that the information and insights generated by big data analytics lead to innovation and competitive advantage. However, the direct relationship between these two factors may also be mediated by other influencing mechanisms. Thus, the question arises: how can small and medium-sized enterprises (SMEs) utilize big data analytics and marketing to support innovation and create competitive advantages in dynamic environments? To address this question, this study leverages the dynamic capabilities model as a framework to investigate these complex relationships and introduces a conceptual model to examine data-driven innovation capabilities. The model has been empirically tested, and the findings reflect the theoretical importance of dynamic capabilities in fostering innovative capacities and achieving competitive advantages.

Method: This study employs path modeling using structural equation modeling (PLS= Partial least squares) methods to test the hypotheses. The Gamma-exponential methods was used to determine the sample size. Given that the study includes 7 latent variables and 44 observed variables, the required sample size was estimated to be 247 at a 95% confidence level. Questionnaires were distributed through the LinkedIn platform to 247 senior managers of small and medium-sized enterprises (SMEs). Measurement and structural models were evaluated using statistical analyses based on the collected data.

Results: Out of the nine proposed hypotheses, seven were supported. The findings indicate that big data analytics and marketing analytics have a positive impact on knowledge integration and innovation in medium-sized enterprises (SMEs). Knowledge integration has been identified as a critical factor in fostering innovation and creating competitive advantage. However, environmental dynamism had no moderating effect on the relationships between the variables.

Conclusion: The results of this research provide new insights into the pathways and interrelationships necessary to support medium-sized enterprises ( SMEs ) in a data-driven context to enable innovation and achieve competitive advantage. The study demonstrates that medium-sized enterprises ( SMEs ) can only succeed and sustain themselves if they possess the capabilities to recognize, utilize, and transform big data and internal and external information into knowledge, thereby fostering innovation. Knowledge integration is identified as a key process that enables medium-sized enterprises (SMEs ) to leverage these tools and create sustainable competitive advantages. The study recommends that managers and researchers focus on developing capabilities related to big data and marketing analytics and emphasize the critical role of knowledge integration in innovation processes. Additionally, the study highlights that small enterprises, compared to larger firms, demonstrate a higher capacity to exploit analytics and utilize big data for profitability, innovation, and creating competitive advantages..

Keywords: Big Data, Marketing Analytics, Innovation, Competitive Advantage, Knowledge Integration, Dynamic Capabilities Theory