i-Pulse: A NLP based novel approach for employee engagement in logistics organization

TL;DR

This paper introduces i-Pulse, an AI-driven NLP approach that analyzes employee feedback in logistics organizations to improve engagement, retention, and operational efficiency.

Contribution

It presents a novel NLP-based method for analyzing employee survey comments, providing actionable insights for logistics firms.

Findings

i-Pulse effectively evaluates large volumes of feedback

Provides clear, actionable insights for management

Enhances understanding of employee engagement dynamics

Abstract

Although most logistics and freight forwarding organizations, in one way or another, claim to have core values. The engagement of employees is a vast structure that affects almost every part of the company's core environmental values. There is little theoretical knowledge about the relationship between firms and the engagement of employees. Based on research literature, this paper aims to provide a novel approach for insight around employee engagement in a logistics organization by implementing deep natural language processing concepts. The artificial intelligence-enabled solution named Intelligent Pulse (I-Pulse) can evaluate hundreds and thousands of pulse survey comments and provides the actionable insights and gist of employee feedback. I-Pulse allows the stakeholders to think in new ways in their organization, helping them to have a powerful influence on employee engagement, retention, and efficiency. This study is of corresponding interest to researchers and practitioners.