The Impact of Big Data Analytics on Sustainable Competitive Advantage Through Operational Engagement and Knowledge Process

The main goal of this study is to assess the maturity of BDA-AI technology implemented by medical equipment suppliers in the healthcare industry. Furthermore, it aims to measure the influence of this technology on the supplier's sustainable competitive advantage, which is mediated by operational business engagement and knowledge processes. This study utilised a cross-sectional design and an explanatory survey as a deductive method for hypothesis formation. The principal data gathering strategy entailed the self-administration of a questionnaire to medical equipment suppliers situated in the GCC. Out of 656 questionnaires distributed to medical equipment vendors, 483 were deemed usable, resulting in a response rate of 73.6%. The study employed Partial Least Squares Structural Equation Modelling (PLS-SEM) and Artificial Neural Network (ANN) methodologies to assess the collected data.

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Publication Details

Journal
International Journal of Information Systems and Supply Chain Management
Published
2025-09-19
DOI
https://doi.org/10.4018/ijisscm.389021
Primary Topic
Big Data and Business Intelligence
Type
article
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article

The Impact of Big Data Analytics on Sustainable Competitive Advantage Through Operational Engagement and Knowledge Process

Ahmad Aburayya
International Journal of Information Systems and Supply Chain Management
Big Data and Business Intelligence
article

The Impact of Big Data Analytics on Sustainable Competitive Advantage Through Operational Engagement and Knowledge Process

Ahmad Aburayya
article en

Abstract

The main goal of this study is to assess the maturity of BDA-AI technology implemented by medical equipment suppliers in the healthcare industry. Furthermore, it aims to measure the influence of this technology on the supplier's sustainable competitive advantage, which is mediated by operational business engagement and knowledge processes. This study utilised a cross-sectional design and an explanatory survey as a deductive method for hypothesis formation. The principal data gathering strategy entailed the self-administration of a questionnaire to medical equipment suppliers situated in the GCC. Out of 656 questionnaires distributed to medical equipment vendors, 483 were deemed usable, resulting in a response rate of 73.6%. The study employed Partial Least Squares Structural Equation Modelling (PLS-SEM) and Artificial Neural Network (ANN) methodologies to assess the collected data.

International Journal of Information Systems and Supply Chain ManagementVol. 18(1)
City University Ajman (AE)
Openalex Percentile: Top 58%
Big Data and Business Intelligence
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