Date of Award
Spring 6-30-2022
Degree Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
School
School of Computing
First Advisor
Theresa Steinbach, PhD
Second Advisor
Raffaella Settimi-Woods, PhD
Third Advisor
Olayele Adelakun, PhD
Fourth Advisor
Ioan Raicu, PhD
Fifth Advisor
Zarreen Farooqi, PhD
Sixth Advisor
David Rudden, MA
Abstract
Many organizations have on-premises data storage systems. Data storage systems are evolving in multiple ways. One way is the adoption of Big Data. Big Data is a data storage system with the ability to analyze large volumes, velocity, and a variety of data. Per the Economist, data is now the most valuable resource (Parkins, 2017). Big Data holds the promise of unlocking a substantial value of data stored. Yet many organizations are not implementing Big Data. There is a need to identify key factors affecting adoption for such organizations. The literature review revealed multiple gaps in studied adoption factors (un-studied or under-studied) such as data storage latency, ability to compute, data storage interface compatibilities, open-source software, enterprise sourced software, cost, perceived industry pressure, legislation barriers, and market turbulence. These factors are studied in this research using The Diffusion of Innovation (DOI) theory and Technology-Organization-Environment (TOE) framework with qualitative (semi-structured interviews, Interpretive Phenomenological Analysis (IPA), and structured interviews) and quantitative (survey) methods. Quantitative analysis is based on Partial Least Squares – Structural Equation Model (PLS-SEM) analysis. This analysis revealed that six of the nine studied factors are significant. Industry pressure, enterprise-sourced software, storage interface compatibility, market turbulence, open-source software, and cost are significant factors positively correlated to Big Data adoption.
Recommended Citation
Alnafoosi, Ahmad B., "Empirical assessment of big data technology adoption factors for organizations with data storage systems" (2022). College of Computing and Digital Media Dissertations. 43.
https://via.library.depaul.edu/cdm_etd/43