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The Impact of Big Data Adoption on SMEs Performance

Authors :
Javaneh Ramezani
Mahdi Nasrollahi
Mahmoud Sadraei
UNINOVA-Instituto de Desenvolvimento de Novas Tecnologias
CTS - Centro de Tecnologia e Sistemas
Source :
Big Data and Cognitive Computing, Vol 5, Iss 68, p 68 (2021)
Publication Year :
2020
Publisher :
Research Square Platform LLC, 2020.

Abstract

Funding Information: Acknowledgments: This work was supported by the Portuguese Foundation for Science and Technology (FCT) and the Center of Technology and Systems (CTS). Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. The notion of Industry 4.0 encompasses the adoption of new information technologies that enable an enormous amount of information to be digitally collected, analyzed, and exploited in organizations to make better decisions. Therefore, finding how organizations can adopt big data (BD) components to improve their performance becomes a relevant research area. This issue is becoming more pertinent for small and medium enterprises (SMEs), especially in developing countries that encounter limited resources and infrastructures. Due to the lack of empirical studies related to big data adoption (BDA) and BD’s business value, especially in SMEs, this study investigates the impact of BDA on SMEs’ performance by obtaining the required data from experts. The quantitative investigation followed a mixed approach, including survey data from 224 managers from Iranian SMEs, and a structural equation modeling (SEM) methodology for the data analysis. Results showed that 12 factors affected the BDA in SMEs. BDA can affect both operational performance and economic performance. There has been no support for the influence of BDA and economic performance on social performance. Finally, the study implications and findings are discussed alongside future research suggestions, as well as some limitations and unanswered questions. publishersversion published

Details

Database :
OpenAIRE
Journal :
Big Data and Cognitive Computing, Vol 5, Iss 68, p 68 (2021)
Accession number :
edsair.doi.dedup.....2b879b827bda53baa762e621dbb6258f
Full Text :
https://doi.org/10.21203/rs.3.rs-66047/v1