Big data for small and medium-sized enterprises (SME): a knowledge management model

• Published in: Journal of knowledge management Vol. 24; no. 4; pp. 881 - 897
• Main Authors: Wang, Shouhong, Wang, Hai
• Format: Journal Article
• Language: English
• Published: Kempston Emerald Publishing Limited 29.05.2020; Emerald Group Publishing Limited
• Subjects: Big Data; Data analysis; Data collection; Ethics; Explicit knowledge; Information technology; Knowledge management; Project planning; Qualitative analysis; Small & medium sized enterprises-SME; Small business; Value creation; Qualitative research; Data administration; Knowledge management; Small to medium-sized enterprise
• ISSN: 1367-3270; 1758-7484
• DOI: 10.1108/JKM-02-2020-0081

Purpose Big data has raised challenges and opportunities for business, the information technology (IT) industry and research communities. Nowadays, small and medium-sized enterprises (SME) are dealing with big data using their limited resources. The purpose of this paper is to describe the synergistic relationship between big data and knowledge management (KM), analyze the challenges and IT solutions of big data for SME and derives a KM model of big data for SME based on the collected real-world business cases. Design/methodology/approach The study collects eight well-documented cases of successful big data analytics in SME and conducts a qualitative data analysis of these cases in the context of KM. The qualitative data analysis of the multiple cases reveals a KM model of big data for SME. Findings The proposed model portrays the synergistic relationship between big data and KM. It indicates that strategic use of data, knowledge guided big data project planning, IT solutions for SME and new knowledge products are the major constructs of KM of big data for SME. These constructs form a loop through the causal relationships between them. Research limitations/implications The number of cases used for the derivation of the KM model is not large. The coding of these qualitative data could involve biases and errors. Consequently, the conceptual KM model proposed in this paper is subject to further verification and validation. Practical implications The proposed model can guide SME to exploit big data for business by placing emphasis on KM instead of sophisticated IT techniques or the magnitude of data. Originality/value The study contributes to the KM literature by developing a theoretical model of KM of big data for SME based on underlying dimensions of strategic use of data, knowledge guided big data project planning, IT solutions for SME and new knowledge products.