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Many types of research have already investigated the lean, green or agile manufacturing systems in a discrete manner or as combinations of two of them. In today’s competitive scenario, if industry wants to perpetuate its name in the market, then it has to supervene proper thinking and smart approach. Therefore, the combination of lean, green and agile manufacturing systems can provide better and beneficial results. The purpose of this paper is to discern the barriers to the combined lean green agile manufacturing system (LGAMS), understand their interdependence and develop a framework to enhance LGAMS by using total interpretive structural modeling (TISM) and MICMAC (Matriced’ Impacts Croise’s Multiplication Appliquée a UN Classement) Analysis.

This paper uses TISM methodology and MICMAC analysis to deduce the interrelationships between the barriers and rank them accordingly. A total of 13 barriers have been identified through extensive literature review and discussion with experts.

An integrated LGAMS has been presented that balances the lean, green and agile paradigms and can help supply chains become more efficient, streamlined and sustainable. Barriers are identified while referring to all three strategies to showcase the clear relevance. TISM models the barriers in different levels showcasing direct and important transitive relations. Further, MICMAC analysis distributes the barriers in four clusters in accordance with their driving and dependence power.

The inferences have been drawn from a model developed on the basis of inputs from a small fraction of the industry and academia and may show variations when considering the whole industry.

The outcome of this research can contribute to bringing the change to the manufacturing systems used in most developing nations. Also, top managers considering adoption of LGAMS can be cautious of the most influential barriers.

A TISM-based model of the barriers to an integrated LGAMS has been proposed with evaluation of the influence of the barriers.

This paper aims at developing an interpretive structural model of drivers for environmentally conscious manufacturing (ECM). It will demonstrate how interpretive structural modeling (ISM) supports policy makers in the government and industry in identifying and understanding interdependencies among drivers for ECM. Interdependencies among drivers will be derived and structured into a hierarchy to derive subsystems of interdependent elements with corresponding driving power and dependency.

ISM has been used to identify hierarchy and inter-relationships among drivers for ECM adoption and to classify the drivers according to their driving and dependence power using MICMAC analysis. The drivers for ECM adoption are identified through the review of literature followed by developing a model of drivers using ISM.

The main findings of the paper include the development of an ISM model of drivers for ECM adoption. The developed model divided the identified drivers into five levels of hierarchies showing their inter-relationship and depicting the driving-dependence relationship. These five levels have been classified into four categories – awareness, external, organizational and benefits.

The developed ISM model is expected to provide a direction to the policy makers in the government and industry and the top management of the organizations to leverage their resources in a timely manner to adopt ECM successfully.

The purpose of this paper is to develop hierarchy and inter-relationship among barriers to environmentally conscious manufacturing (ECM) adoption using an interpretive structural modeling (ISM) technique. The paper will demonstrate how ISM supports policy makers in the government and industry in identifying and understanding interdependencies among barriers to ECM. Interdependencies among barriers will be derived and structured into a hierarchy in order to derive subsystems of interdependent elements with corresponding driving power and dependency.

ISM was used to identify hierarchy and inter-relationships among barriers to ECM adoption and to classify the barriers according to their driving and dependence power using MICMAC analysis. The barriers to ECM adoption are identified through the review of literature followed by developing a model of barriers using ISM based on the inputs from experts from industry and academia.

The main findings of the paper include the development of hierarchy and inter-relationship and ISM model of barriers to ECM adoption. The developed model divided the identified barriers into five levels of hierarchies showing their inter-relationship depicting the driving-dependence relationship. These five levels have been classified into three categories – internal barriers, economy barriers, and policy barriers category.

The developed ISM model is expected to provide a direction to the policy makers in the government and industry and the top management of the organizations to leverage their resources in timely manner to adopt ECM successfully.

Manufacturing firms consume energy and natural resources in highly unsustainable manner and release huge amounts of green house gases leading to many economic, environmental and social problems; from local waste disposal to climate change. Consciousness about these issues has lead to a new manufacturing paradigm of environmentally conscious manufacturing (ECM). There exist many social, legislative, policy, economic, internal, and environmental factors which can motivate and/or force industry to adopt ECM. The purpose of this paper is to identify the drivers for ECM, developing a model of these drivers using statistical analysis and testing the model using structural equation modeling (SEM) technique.

The basic steps of methodology are ECM driver development, survey instrument development, data collection, model proposition, and model validation. The main data analysis approaches are exploratory factor analysis, confirmatory factor analysis, and SEM to develop a model of drivers and validating the same based on the data collected from the manufacturing industry.

The reliable, valid, and tested model has three types of drivers – internal, policy, and economic. It has been found through hypothesis testing that internal drivers for the implementation of ECM are positively related to policy and economic drivers; and policy drivers are positively related to economy drivers. This research is expected to help government and industry in developing policies and strategies for the successful implementation of ECM.

The novelty of this study is that it provides the relationship among the drivers which can be leveraged by the managers to focus on the root drivers for smooth and effective implementation of ECM.

This paper provides new theoretical insight into the factors motivating the industry to implement ECM systems in the industry with special focus on manufacturing sector of emerging economies.

The purpose of this paper is to review the green manufacturing and similar frameworks in order to trace the origin, definitions, scope, similarities, differences, and publications of these manufacturing frameworks.

A review of 113 research articles is conducted for various terms, namely, green manufacturing (GM); environmentally conscious manufacturing; environmentally responsible manufacturing; environmentally benign manufacturing; sustainable manufacturing; clean manufacturing; cleaner production; sustainable production with reference to triple bottom line, product life cycle engineering, systems approach, resource and energy efficiency, supply chain, pollution prevention and closed loop system/6R.

It can be said with reasonable confidence that all these eight frameworks have been used interchangeably by researchers but it requires some standardization. It has been observed during literature review that to standardize the terminology researchers have to clear emphatically in their research the use of various life cycle engineering approach; clarity on the end-of-life strategies used; clarity in use of various components of triple bottom line perspectives; inclusion of the whole supply chain and integration of environmental improvement strategies with the business strategy.

The literature reviewed for the study is the literature available online using Google scholar.

This is one of the first known studies to review the GM and similar frameworks for their origin, definition, scope, similarities, and differences.