Enhancing Human Resource Management Practices in Marketing Companies Using Dual Graph Attention Networks

Marketing organization features and strategy implementation have been studied for over 30 years. These include organizational structure, culture, leadership, and processes. HR regulations can motivate marketing professionals to support group and individual goals when correctly implemented, but this part of HR has gotten little attention. Model preparation, feature extraction, and training comprise the suggestive technique. It reviewed data quality, evaluated dataset structure, and described data types during pre-processing. Principal component analysis (PCA) ranked and evaluated decision-making units to reduce dimension. Model training used MGGAN. In comparison to GAN and CNN, the proposed model performed well. With an average accuracy rate of 94.36%, it surpassed earlier approaches and captured all dataset peculiarities. MGGAN modeling can increase predictive performance, and marketing organizations should integrate HR regulations, according to this study. This study opens up new organizational analysis and strategy execution methods.

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Publication Details

Published
2025-02-21
DOI
https://doi.org/10.1109/icicacs65178.2025.10968426
Primary Topic
AI and HR Technologies
Type
article
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article

Enhancing Human Resource Management Practices in Marketing Companies Using Dual Graph Attention Networks

N. Roopalatha, K. Dhanalakshmi, Govind Babu, P. Vamsi Krishna et al.
AI and HR Technologies
article

Enhancing Human Resource Management Practices in Marketing Companies Using Dual Graph Attention Networks

N. Roopalatha, K. Dhanalakshmi, Govind Babu, P. Vamsi Krishna, Anvesh Perada, Harun Kumar Mulagapati
article en

Abstract

Marketing organization features and strategy implementation have been studied for over 30 years. These include organizational structure, culture, leadership, and processes. HR regulations can motivate marketing professionals to support group and individual goals when correctly implemented, but this part of HR has gotten little attention. Model preparation, feature extraction, and training comprise the suggestive technique. It reviewed data quality, evaluated dataset structure, and described data types during pre-processing. Principal component analysis (PCA) ranked and evaluated decision-making units to reduce dimension. Model training used MGGAN. In comparison to GAN and CNN, the proposed model performed well. With an average accuracy rate of 94.36%, it surpassed earlier approaches and captured all dataset peculiarities. MGGAN modeling can increase predictive performance, and marketing organizations should integrate HR regulations, according to this study. This study opens up new organizational analysis and strategy execution methods.

SRM Institute of Science and Technology (IN), SRKR Engineering College, Christ University (IN), Drexel University (US), GITAM University (IN)
Decent work and economic growth
Openalex Percentile: Top 90%
AI and HR Technologies
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