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Evidence of global relevance

A Data-Driven Informatics Framework for Evaluating Thai Provinces Using an Additive Weighting-Based Variant Assessment Algorithm and Two-Stage DEA

The framework selected 16 representative provinces from 77 using balanced additive weighting, then applied CCR two-stage DEA to benchmark transformations from investment, tourism and demographics through energy, factories and vehicles to GPP and air-quality indicators.

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Key findings

  • Screening prominence did not guarantee DEA-frontier performance, and overall and super-efficiency varied substantially, separating representativeness from benchmark strength.
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Why this matters globally

The framework is adaptable to regional monitoring that combines economic and pollution indicators while making unit selection explicit.

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Thai researcher contribution

Thai researchers from KMUTNB and Thammasat collaborated with an Italian partner on a full 77-province informatics method.

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Limitations to consider

Reducing to 16 provinces may omit context. CCR assumes constant returns, and results depend on weights, orientation, undesirable-output treatment and data quality; newborns and pollution require careful conceptual justification.

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Verify the original sources

InformaticsRead the original article

DOI: 10.3390/informatics13070111

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