Construction of Decision Support System for Enterprise Sustainable Management Based on Big Data

In this study, a decision support system for sustainable management of enterprises based on big data is constructed to address the challenges of sustainable development faced by enterprises in the era of big data. The system integrates real-time data flow analysis and prediction models to realize an integrated process from data collection, processing, analysis to decision support. The study improves the efficiency of data flow and value mining by developing a system model with a four-tier architecture, and establishes a comprehensive system of sustainability management indicators by applying advanced technologies such as machine learning. The system also provides a visualization interface with interactive tools to assist management in making quick decisions. Practical results show that the system significantly improves the efficiency and accuracy of corporate decision-making, effectively promotes the balanced development of economic benefits and social responsibility, and provides strong support for corporate sustainable development.

Authors

Publication Details

Journal
Frontiers in Business Economics and Management
Published
2025-02-21
DOI
https://doi.org/10.54097/30r93p85
Primary Topic
E-commerce and Technology Innovations
Type
article
Field-Weighted Citation Impact
0.00
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article

Construction of Decision Support System for Enterprise Sustainable Management Based on Big Data

Rain Hou
Frontiers in Business Economics and Management
E-commerce and Technology Innovations
article

Construction of Decision Support System for Enterprise Sustainable Management Based on Big Data

Rain Hou
article en

Abstract

In this study, a decision support system for sustainable management of enterprises based on big data is constructed to address the challenges of sustainable development faced by enterprises in the era of big data. The system integrates real-time data flow analysis and prediction models to realize an integrated process from data collection, processing, analysis to decision support. The study improves the efficiency of data flow and value mining by developing a system model with a four-tier architecture, and establishes a comprehensive system of sustainability management indicators by applying advanced technologies such as machine learning. The system also provides a visualization interface with interactive tools to assist management in making quick decisions. Practical results show that the system significantly improves the efficiency and accuracy of corporate decision-making, effectively promotes the balanced development of economic benefits and social responsibility, and provides strong support for corporate sustainable development.

Frontiers in Business Economics and ManagementVol. 18(2)
Openalex Percentile: Top 95%
E-commerce and Technology Innovations
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