Big data analytics and market performance: the roles of customization and personalization strategies and competitive intensity

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Abstract

Purpose: Big data analytics (BDA) plays a crucial role in understanding customer behavior through Customer Relationship Management (CRM), especially in a rapidly changing business environment. This paper investigates the direct effect of BDA use on market performance, besides the mediating effect through Big Data-enabled CRM strategies adoption (e.g. customization and personalization). The paper also examines the moderating role of competitive intensity in these effects. Design/methodology/approach: Drawing from a knowledge-based view (KBV) and Organizational Information Processing Theory (OIPT), the authors formulated the research model. Subsequently, the measurement model and hypotheses were tested through PLS-SEM on online survey data of 229 managers from 167 companies out of Egypt's top 500. Findings: The results indicated that BDA use does not directly affect the market performance, but this effect was significant through customization and personalization strategies adoption. The results also revealed a positive association between BDA use and the adoption of these strategies. Furthermore, competitive intensity only moderates the relationship between BDA use and personalization strategy adoption. Research limitations/implications: Companies can use BDA to improve customer knowledge and experience through customization and personalization, leading to better market performance and moving towards becoming a Big Data-driven organization. This study is limited to companies in the Egyptian context, which restricts the generalizability of the results. Originality/value: This study conceptually and empirically explores how BDA usage, customization and personalization strategies impact market performance under competitive intensity situations, especially in the context of emerging markets.

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APA

Kamel, M. A. (2023). Big data analytics and market performance: the roles of customization and personalization strategies and competitive intensity. Journal of Enterprise Information Management, 36(6), 1727–1749. https://doi.org/10.1108/JEIM-04-2022-0114

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