Title: Evaluating green manufacturing drivers: an interpretive structural modelling approach

Authors: Minhaj Ahemad A. Rehman; R.R. Shrivastava; Rakesh L. Shrivastava

Addresses: Department of Mechanical Engineering, St. Vincent Pallotti College of Engineering and Technology, Gavsi Manapur, Wardha Road, Nagpur, 441108, India ' Department of App. Chemistry, G.H. Raisoni College of Engineering, Hingna Road, S.R.P.F, Nagpur, 441110, India ' Department of Mechanical Engineering, Yeshwantrao Chavan College of Engineering, Hingna Road, Wanadongri, Nagpur, 441110, India

Abstract: Green manufacturing (GM) is a sustainable method of manufacturing that minimises waste and pollution. GM covers the entire product life cycle from conceptual design to disposal in a benign, harmless manner. It causes no or minimal adverse impact on environment by optimum use of resources and reduction of waste and pollution. 4R's (reduce, reuse, recycle, remanufacture) is slowly being accepted and adopted as the model of growth and sustainability the world over. Its implementation is supported by few factors which are known as GM drivers. There are many drivers which are expanding the boundaries for green manufacturing. These drivers could facilitate to adopt Green manufacturing. The aim of this paper is to develop a relationship amongst the identified GM drivers; including management commitments, regulatory pressure, pressure from stakeholders etc. This paper is also helpful in understanding mutual influences of drivers. It helps in identifying those drivers which support other drivers as well as those drivers which are most influenced by other drivers (dependent) using interpretive structural modelling (ISM) and it classifies these drivers depending upon their driving and dependency on power.

Keywords: green manufacturing drivers; sustainable manufacturing; interpretive structural modelling; ISM; sustainability; sustainable development; management commitments; regulatory pressure; stakeholder pressure.

DOI: 10.1504/IJPQM.2014.062223

International Journal of Productivity and Quality Management, 2014 Vol.13 No.4, pp.471 - 494

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 02 Jun 2014 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article