Enhancing Employee Motivation Through AI: The Role of Corporate Culture in the Workplace

Motivating the employees is a vital factor for the success of an organization but measuring motivation is challenging, especially with the conventional tools and techniques that do not capture current situations and flexible working organizational environments. Presumably, this paper came up with an AI model that incorporates machine learning algorithms with corporate culture measures to estimate employees' motivation levels. The model relies on the IBM HR Analytics dataset that focuses on employee behavior and feedback data, for performance records. Approaches used herein are Principal Component Analysis for feature extraction and XGBoost and Logistic Regression for modeling. The proposed model obtained an accuracy of 90.5%, 89.2% precision, and an AUC of 0.92, surpassing typical models. Also, the system analyzed different employees and labeled them as high-risk employees with an accuracy level of 87.5%. The findings also show how AI can boost employee motivation by offering precise information on their requirements. Future research will involve applying the model with more substantial datasets and making the model more suitable for complex working contexts.

Authors

Institutions

Publication Details

Published
2024-12-12
DOI
https://doi.org/10.1109/icses63760.2024.10910789
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancing Employee Motivation Through AI: The Role of Corporate Culture in the Workplace

Saikrishna Prakash, S Gokul, S Pavithrashree., Karthick Raja.K
Impact of AI and Big Data on Business and Society
article

Enhancing Employee Motivation Through AI: The Role of Corporate Culture in the Workplace

Saikrishna Prakash, S Gokul, S Pavithrashree., Karthick Raja.K
article en

Abstract

Motivating the employees is a vital factor for the success of an organization but measuring motivation is challenging, especially with the conventional tools and techniques that do not capture current situations and flexible working organizational environments. Presumably, this paper came up with an AI model that incorporates machine learning algorithms with corporate culture measures to estimate employees' motivation levels. The model relies on the IBM HR Analytics dataset that focuses on employee behavior and feedback data, for performance records. Approaches used herein are Principal Component Analysis for feature extraction and XGBoost and Logistic Regression for modeling. The proposed model obtained an accuracy of 90.5%, 89.2% precision, and an AUC of 0.92, surpassing typical models. Also, the system analyzed different employees and labeled them as high-risk employees with an accuracy level of 87.5%. The findings also show how AI can boost employee motivation by offering precise information on their requirements. Future research will involve applying the model with more substantial datasets and making the model more suitable for complex working contexts.

G.S. Science, Arts And Commerce College (IN)
Decent work and economic growth
Openalex Percentile: Top 66%
Impact of AI and Big Data on Business and Society
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.