BIG DATA AND MARKETING ANALYTICS IN SMES' INNOVATION AND COMPETITIVE ADVANTAGE

Abstract

In the contemporary digital economy, Small and Medium-sized Enterprises (SMEs) in Pakistan face unprecedented challenges and opportunities. This thesis examines how SMEs can leverage Big Data (BD) and Market Analytics Use (MAU) to foster Innovation (IN) and achieve a Sustained Competitive Advantage (SCA). Grounded in the Dynamic Capabilities view and the Resource-Based View (RBV), this study proposes a conceptual framework structured around four sequential stages: 'Sense', 'Seize', 'Transform', and 'Outcomes'. The 'Sense' stage involves perceiving market shifts, driven by Environmental Dynamism (ED) and an Entrepreneurial Orientation (EO). The 'Seize' stage focuses on capturing opportunities through the adoption of BD and MAU. The 'Transform' stage highlights the critical role of Knowledge Integration (KI) in converting data-driven insights into organizational capability. Finally, the 'Outcomes' stage measures the impact on IN and SCA. This research proposes a quantitative study using a survey methodology targeting SME managers in Karachi, Pakistan. Data will be analyzed using Structural Equation Modeling (SEM) to test a series of hypotheses derived from the framework. The study controls for variables such as Industry, Firm Size, and Job Title to ensure the robustness of the findings. Expected results will demonstrate that KI is a crucial mechanism that mediates the relationship between data analytics capabilities and firm outcomes. The findings aim to provide actionable insights for SME managers on developing data-driven strategies, theoretical contributions to the literature on digital transformation in emerging economies, and policy recommendations for governmental bodies like SMEDA to foster a more competitive SME sector in Pakistan.