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General Information
Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
I'm happy to take on the position of editor in chief of IJMO. It's a journal that shows promise of becoming a recognized journal in the area of modelling and optimization. I'll work together with the editors to help it progress.
IJMO 2022 Vol.12(4): 122-130 ISSN: 2010-3697
DOI: 10.7763/IJMO.2022.V12.812

Assessing Suitability of Applying Big Data Analytics within Small to Medium-Sized Businesses via an ROI-Based Graphic Model

Ryan Grizzle and Yanzhen Qu

Abstract—Big data has presented itself as a term, phenomena, and paradigm with the potential for many opportunities and challenges. The new potentials of big data seemingly continue to expand both in possibility and complexity. With efforts to exploit these new potentials requiring investments from businesses and organizations it becomes necessary to understand what value is gained from such efforts. Through the methodology of design science this study develops an artifact which incorporates the return on investment model which can be utilized by SMEs. The artifact provides an abstract process model for the use of value assessment of big data efforts by SMEs. This study finds through using test cases that the ROI model can be applied to a generalized artifact which guides the assessment of big data efforts. Further, it is found that through a graphical design the development of a simple and intuitive artifact can be accomplished.

Index Terms—Big data, big data value, small and medium enterprises, SME, return on investment, ROI, design science.

Ryan Grizzle and Yanzhen Qu are an alumnus of Colorado Technical University, Colorado Springs CO 80907 USA (e-mail: Ryan.Grizzle@alumni.ctuonline.edu, yqu@coloradotech.edu).


Cite: Ryan Grizzle and Yanzhen Qu, "Assessing Suitability of Applying Big Data Analytics within Small to Medium-Sized Businesses via an ROI-Based Graphic Model," International Journal of Modeling and Optimization vol. 12, no. 4, pp. 122-130, 2022.

Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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