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Visualizing Bayesian Duality Optimization Model From Google Review on Hospital Service Performance in Thailand

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  • Praowpan Tansitpong

    (NIDA Business School, National Institute of Development Administration, Thailand)

Abstract

The study utilizes online reviews to predict hospital service outcomes by employing an optimization framework that incorporates four key healthcare dimensions: patient care, medical treatment, facilities, and staff efficiency. This approach combines real-time, user-generated feedback with advanced analytical techniques, providing a robust model for assessing hospital performance. The model predicts Bayesian inference to determine posterior distributions for parameters, including previous information and estimating uncertainty in predictions. The duality optimization method improves predicted accuracy by reducing error while accounting for parameter uncertainty. The hospital review dataset is derived from 5,548 hospital reviews in Thailand. The outcome of this study offers practical insights for hospital administrators and policymakers and enhances hospital operations, patient satisfaction, and strategic decision-making in the Thai healthcare sector by integrating probabilistic modeling with optimization techniques.

Suggested Citation

  • Praowpan Tansitpong, 2025. "Visualizing Bayesian Duality Optimization Model From Google Review on Hospital Service Performance in Thailand," Journal of Electronic Commerce in Organizations (JECO), IGI Global Scientific Publishing, vol. 23(1), pages 1-18, January.
    • Handle: RePEc:igg:jeco00:v:23:y:2025:i:1:p:1-18
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