i-Pulse: A NLP based novel approach for employee engagement in logistics organization
This addresses the challenge of employee engagement and retention for logistics organizations, offering a novel AI-based solution, though it appears incremental in applying existing NLP methods to a specific domain.
The paper tackles the problem of understanding employee engagement in logistics organizations by developing i-Pulse, an AI tool that uses deep natural language processing to analyze pulse survey comments, providing actionable insights from hundreds to thousands of feedback entries.
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.