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Evaluation Method of Human Resource Management Efficiency of Chain Retail Enterprises Based on Distributed Database.

Xiaolong Jiang¹, Mishal Sohail²

¹Guangdong Mechanical & Electrical Polytechnic, Faculty of Logistics, Guangzhou 510515, China.

Computational and Mathematical Methods in Medicine

|February 14, 2022

Summary

This study introduces a novel human resource management efficiency evaluation method for chain retail enterprises using a distributed database and genetic algorithms. The proposed approach enhances data consistency and improves technical and scale efficiency for better management decisions.

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Area of Science:

Business Management
Information Systems
Operations Research

Background:

Evaluating human resource management (HRM) efficiency in chain retail is complex, with existing methods impacting technical and scale efficiency outcomes.
Traditional methods may not fully leverage data capabilities for comprehensive HRM assessment.

Purpose of the Study:

To propose an advanced HRM efficiency evaluation method for chain retail enterprises.
To enhance data management and utilization for more accurate efficiency assessments.

Main Methods:

Utilizing a distributed database for storing and managing HRM data of chain retail enterprises.
Applying genetic algorithms for optimal data allocation within the distributed database.
Developing a management efficiency evaluation index system and constructing a Data Envelopment Analysis (DEA) model.

Main Results:

The proposed distributed database approach ensures data consistency and information availability.
The DEA model, informed by selected input/output elements, provides a robust efficiency evaluation.
The new method demonstrates higher technical and scale efficiency compared to principal component analysis and fuzzy comprehensive evaluation.

Conclusions:

The developed HRM efficiency evaluation method offers superior performance for chain retail enterprises.
This approach supports improved management decision-making through more accurate efficiency metrics.