MODERATING ROLE OF ORGANIZATIONAL FACTORS IN DATA FACTORS-PROFIT MAXIMIZATION LINK: BIG DATA ADOPTION IN CHINESE SME RETAIL

Abstract

In the era of digital transformation, small and medium-sized enterprises (SMEs) in the retail sector face increasing pressures to adopt data-driven strategies to maximise profitability and competitiveness. However, the mechanisms through which data-related factors and organisational dynamics influence profit maximisation remain underexplored. This study investigates the relationships between data security, data management practices, big data adoption, organisational factors, and profit maximisation outcomes in SMEs operating in China’s retail sector. Using a quantitative approach, data were collected via online questionnaires from 168 SMEs and analysed with SmartPLS to examine direct, mediating, and moderating effects. The findings reveal that data security, data management practices, and big data adoption significantly enhance profit maximisation, with big data adoption mediating these relationships and organisational factors serving a moderating role. This research contributes to the literature by uncovering the complex interplay between data-related factors, organisational dynamics, and financial performance, offering both theoretical insights and practical guidance for SMEs aiming to leverage data-driven strategies to enhance profitability and competitiveness.