The Assessment of Big Data Adoption Readiness with a Technology–Organization–Environment Framework: A Perspective towards Healthcare Employees

Ebrahim A A Ghaleb,Amgad Muneer,P D D Dominic,Rao Faizan Ali,Suliman Mohamed Fati

doi:10.3390/su13158379

Ebrahim A A Ghaleb, Amgad Muneer + Show 3 more

Open Access

https://doi.org/10.3390/su13158379

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Abstract

Big data is rapidly being seen as a new frontier for improving organizational performance. However, it is still in its early phases of implementation in developing countries’ healthcare organizations. As data-driven insights become critical competitive advantages, it is critical to ascertain which elements influence an organization’s decision to adopt big data. The aim of this study is to propose and empirically test a theoretical framework based on technology–organization–environment (TOE) factors to identify the level of readiness of big data adoption in developing countries’ healthcare organizations. The framework empirically tested 302 Malaysian healthcare employees. The structural equation modeling was used to analyze the collected data. The results of the study demonstrated that technology, organization, and environment factors can significantly contribute towards big data adoption in healthcare organizations. However, the complexity of technology factors has shown less support for the notion. For technology practitioners, this study showed how to enhance big data adoption in healthcare organizations through TOE factors.

Highlights

These include digital health with emerging technologies such as cloud computing (CC) and big data analytics (BD), which entail the aggregation of large amounts of structured and unstructured health information and sophisticated analyses using artificial intelligence (AI) [3]; natural language processing techniques [4,5]; and precision-health approaches for identifying individual-level risk and determinants of wellness and pathophysiology [6,7]
The study utilized partial least squares (PLS), SmartPLS version 3.0., like the authors in [169], as a statistical tool to investigate the structure and measurement model since it does not require the assumption of normality because data collected through survey instruments are rarely normal [170]
This study aimed to identify factors influencing the acceptability of BD ready in the healthcare industry of developing countries

Summary

Introduction

Developed and fastemerging technology-based innovations play a critical role in this shift [1] These include digital health with emerging technologies such as cloud computing (CC) and big data analytics (BD), which entail the aggregation of large amounts of structured and unstructured health information and sophisticated analyses using artificial intelligence (AI) [3]; natural language processing techniques [4,5]; and precision-health approaches for identifying individual-level risk and determinants of wellness and pathophysiology [6,7]. TOE tualadopted framework enables an context understanding of how technology and informationthe sysmodel combines innovation theory to help explain how organizations absorb technology tems are adopted in an organizational context rather than individually [62]. The analysis of contingency variables influencing firm decisions is one of the most comprehensive approaches to studying creativity [73] Such considerations can be grouped into infrastructure, TOE, and organizational effects to justify the results in organizations [74]. Since the variables in the TOE setting can vary from one context to the certain additional variables must be added for enrichment

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