A decision-support framework for Lean, Agile and Green practices in product life cycle stages

Abstract

Improving operations performance is often achieved through the application of practices such as Lean, Agility and Green (LAG) practices. However, the wide choice of LAG practices available to address customer requirements can be challenging for those with limited knowledge of LAG practices and their efficacy. Therefore, this research provides a framework for selecting appropriate LAG practices that considers product life cycle (PLC) stages for more effective application of practices. The framework was developed following thorough literature review to capture LAG practices. These form the basis for decision making tools incorporated within the framework including an analytic hierarchy process (AHP), statistical inference and regression analysis, ensuring a systematic approach to the analysis and decision support. The framework was verified and validated through a Delphi study and case study respectively. This research makes a contribution to the body of knowledge by providing a framework which could serve as a guide for businesses in the fast moving consumer goods (FMCG) industry to systematically integrate and adopt LAG to better manage their processes and meet customer requirements.

Keywords:

• Lean
• agile
• green
• product life cycle
• FMCG

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Chinonso Udokporo

Dr. Chinionso Udokporo is an Associate Lecturer at Derby Business School, University of Derby, UK. His current research interests include: Lean, Agile and Green supply chain; circular economy and process improvement. Dr. Chinonso Udokporo has published on these topics, however, he has a keen interest in other research areas including but not limited to supply chain resilience, process redesign and eco-efficient supply chain networks.

Anthony Anosike

Dr. Anthony Anosike is Senior Lecturer at the Centre for Supply Chain Improvement, Derby Business School, University of Derby, UK. His current research interests include: modelling and simulation of manufacturing systems and supply networks; Lean, Agile and Green supply chain, circular economy; ICT and Industry 4.0 applications in businesses. As well as publishing in a range of articles in leading international journals and conferences, he is also active in delivering business improvements in a wide range of business areas including manufacturing, supply chains and logistics.

Ming Lim

Prof. Ming K. Lim is Professor of Supply Chain and Operations Management at Coventry University (UK). Prof Lim’s research is multi-disciplinary, integrating engineering, computer science, information technology and operations management. Most of his recent research work revolved around Radio-frequency Identification (RFID) technology, incorporated with Industry 4.0, Internet of Things, cloud manufacturing and big data analysis. His other research expertise includes circular economy, sustainable supply chain management, green/low carbon logistics, lean & agile manufacturing, responsive & reconfigurable manufacturing/supply chain, meta-heuristics, and cost & system optimisation. Prior to this role, he was Head of Centre of Excellence for Supply Chain Improvement and Professor of Supply Chain and Logistics Operations at University of Derby (UK). Prof Lim is Co-Editor-in-Chief of International Journal of Logistics Research and Applications and editorial board member of a number of leading journals, including Resources, Conservation and Recycling, Industrial Management & Data Systems and Management of Environmental Quality: An International Journal.