Kanchana Sethanan
Biographic Data
| ID | 9711512 |
|---|---|
| NAME | Kanchana Sethanan |
| GIVEN NAMES | Kanchana |
| FAMILY NAME | Sethanan |
| SIGNATURE | SETHANAN K |
| AFFILIATIONS | Khon Kaen University Research Unit on System Modeling for Industry, Department of Industrial Engineering, Faculty of Engineering, , Khon Kaen |
| ORCID | 0000-0002-3340-2538 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2026 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Technology transfer challenges in circular supply chain: Insights from expanded absorptive capacity- dynamic capability view
Sustainability-oriented vehicle routing with multi-depot, multi-period planning, precedence constraints, and selective backhauling: A hybrid particle swarm optimization with cheetah optimizer
Identifying innovation in environmental management within higher education institutions: An artificial intelligence text mining-driven model
Purpose This study aims to develop a valid attribute structure aimed at increasing innovation in environmental management (IEM) within higher education institutions (HEIs) using an artificial intelligence (AI) text mining-driven model. Design/methodology/approach This study uses a technology–organization–environment framework and leverages an AI text mining-driven model in a hybrid method to develop a hierarchical attribute structure of IEM attri…
No prominent works on this page.
Technology transfer challenges in circular supply chain: Insights from expanded absorptive capacity- dynamic capability view
Sustainability-oriented vehicle routing with multi-depot, multi-period planning, precedence constraints, and selective backhauling: A hybrid particle swarm optimization with cheetah optimizer
Identifying innovation in environmental management within higher education institutions: An artificial intelligence text mining-driven model
Purpose This study aims to develop a valid attribute structure aimed at increasing innovation in environmental management (IEM) within higher education institutions (HEIs) using an artificial intelligence (AI) text mining-driven model. Design/methodology/approach This study uses a technology–organization–environment framework and leverages an AI text mining-driven model in a hybrid method to develop a hierarchical attribute structure of IEM attri…
Benchmarking (1 works) · Competitive advantage (1 works) · Facilities and Workplace Management (1 works) · Genetic algorithm (1 works) · Higher education (1 works) · Institution (1 works) · Minification (1 works) · Particle swarm optimization (1 works) · Reputation (1 works) · Stakeholder (1 works)