Big Data Analytics-Enabled Dynamic Capabilities and Market Performance: Examining the Roles of Marketing Ambidexterity and Competitor Pressure

Abstract

This study, rooted in dynamic capability theory and the developing era of Big Data Analytics, explores the transformative effect of BDA EDCs on marketing. Ambidexterity and firms market performance in the textile sector of Pakistans cities. Specifically, focusing on the firms who directly deal with customers, investigates the nuanced role of BDA EDCs in textile retail firms potential to navigate market dynamics. Emphasizing the exploitation component of marketing ambidexterity, the study investigated the mediating function of marketing ambidexterity and the moderating influence of competitive pressure. Using a survey questionnaire, the study targets key choice makers in textile firms of Faisalabad, Chiniot and Lahore, Pakistan. The PLS-SEM model was employed as an analytical technique, allows for a full examination of the complicated relations between BDA EDCs, marketing ambidexterity, rival pressure, and market performance. The study Predicting a positive impact of Big Data on marketing ambidexterity, with a specific emphasis on exploitation. The study expects this exploitation-orientated marketing ambidexterity to significantly enhance the firms market performance. This research contributes to the existing literature on dynamic capabilities-based frameworks from the perspective of the retail segment of textile industry. The study emphasizes the role of BDA-EDCs in the retail sector, imparting insights into the direct and indirect results of BDA EDCs on market performance inside the retail area. The study s novelty lies in its contextualization of BDA-EDCs in the textile zone of Faisalabad, Lahore and Chiniot, providing a unique perspective on the effect of BDA on marketing ambidexterity and market performance in firms. Methodologically, the study uses numerous samples of retail sectors to make sure broader universality, contributing realistic insights.