Internal Publication

A process framework for big data research: social network analysis using design science

Managing and harnessing big data is increasingly being reported as an approach to generate business value, optimize decision-making, and achieve competitive advantage. There is strong evidence that research on big data has gained significant attention from both the academic community and analytics community. To date, research has largely focused on the technical aspects of big data and its applications in specific contexts, but with limited attention given to the underlying process. Yet, it is well accepted that understanding the processes required to leverage big data is a critical factor to realize the claimed benefits of big data. We address this knowledge deficit by designing a process framework to guide novice users to effectively apply social network analysis and improve the outputs of big data research projects. The framework is the artifact that emerged after applying the principles of design science research. The artifact was validated by a social network analysis of credit networks in India.

Uploaded by: John Oredo
Author: Oredo, John | ORCID: 0000-0002-7855-5175
Co-author: Dennehy Denis | ORCID: 0000-0001-9931-762X
Co-author: Gupta Samrat | ORCID: 0000-0002-3999-1177
Institution: University of Nairobi | Centre: Sustainable Operations for Resource Management and Food Supply (SCO)
Type: Chapter in book | English | Peer Reviewed
Subjects: ICT

Published in: Handbook of big data research methods, ISBN 9781800888548, EISBN 9781800888555 | Chapter 14
Publisher of document: Cheltenham: Edward Elgar Publishing Limited
Date: June 2023 | Pages: 27
Copyright: Copyright Edward Elgar Publishing 2023 | License: Author copy submitted