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Smart decision engine for performance optimization in enterprise management.

Yucheng Huang1, Qingfeng Wu2

  • 1School of Management, Xiamen University, 361000, Xiamen, China. wbyxm2024@163.com.

Scientific Reports
|January 4, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a smart decision engine using complex picture fuzzy sets (CPSs) to improve enterprise performance optimization. The engine enhances strategic evaluation accuracy and consistency for managers in dynamic business environments.

Keywords:
Decision support systemEnterprise managementHybrid WeightingPerformance optimizationUncertainty modeling

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Area of Science:

  • Decision Sciences
  • Management Science
  • Artificial Intelligence

Background:

  • Effective enterprise management is crucial for competitiveness and growth in dynamic markets.
  • Traditional multi-criteria decision-making (MCDM) methods struggle with uncertainty and subjective expert judgments.
  • Existing MCDM approaches often yield suboptimal or biased outcomes due to data limitations.

Purpose of the Study:

  • To develop a smart decision engine for optimizing enterprise performance under uncertainty.
  • To enhance decision-making accuracy and consistency in strategic evaluations.
  • To provide a scalable and adaptable decision-support tool for enterprise managers.

Main Methods:

  • Utilized complex picture fuzzy sets (CPSs) to model uncertainty with enhanced precision.
  • Employed the integrated determination of objective criteria weights (IDOCRIW) method for objective weight determination.
  • Incorporated the ranking comparison (RANCOM) approach for subjective expert preferences and the MARCOS method for strategy evaluation.

Main Results:

  • The proposed smart decision engine demonstrated superior robustness and reliability compared to traditional techniques.
  • Sensitivity and comparative analyses validated the model's effectiveness in enterprise performance optimization.
  • The engine significantly enhances the accuracy and consistency of strategic evaluations.

Conclusions:

  • The developed smart decision engine effectively addresses limitations of traditional MCDM methods in uncertain environments.
  • This approach offers a powerful tool for managers to optimize enterprise performance and strategic decision-making.
  • The framework provides a flexible and precise method for evaluating and ranking enterprise strategies.