AI in Green HRM Research
Prompt
Write a detailed research article titled "Mapping the Terrain: AI Applications in Green HRM for Sustainable Manufacturing in Coimbatore – A Preliminary Study." The article should present the objective, methodology, key interview questions, and the expected outcome of a qualitative exploratory study on AI adoption in Green Human Resource Management (GHRM) within manufacturing firms in Coimbatore. Objective: - Identify, document, and categorize AI technologies adopted by manufacturing firms in Coimbatore. - Focus on implications for GHRM and sustainability practices. Methodology: - Qualitative, exploratory approach. - Data collection through semi-structured interviews with 10–15 participants including HR managers, plant/operations heads, and IT/technology leads. - Sample should represent diverse manufacturing sectors: textiles, engineering, and pump industries in Coimbatore. Key Interview Questions: 1. Awareness & Adoption: Inquiry about AI tools known or currently in use. 2. Functional Applications: How AI is used across HR functions like recruitment, training & development, performance management, and employee engagement. 3. Sustainability Linkages: Connection of AI tools with environmental and sustainability goals such as waste reduction, energy efficiency, and carbon footprint management. 4. Perceived Benefits: Organizational and HR-related benefits from AI adoption. 5. Barriers & Challenges: Issues faced like cost, skill gaps, resistance to adoption, lack of awareness, data privacy concerns, and infrastructure constraints. Expected Outcome: - Develop a preliminary framework categorizing AI-enabled GHRM use cases, including AI-based training modules for sustainable practices, AI for logistics and workforce optimization to minimize carbon emissions, and AI-driven analytics for ESG reporting and compliance. - This framework will provide foundational empirical and contextual guidance for the forthcoming quantitative phase of a PhD study. Structure the article clearly with titled sections reflecting these points, use formal academic language, and provide logical flow connecting methodology to expected outcomes.
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