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The modern business community understands the importance of long-term satisfaction of consumer. Enabling the consumer to return products is a significant part of the equation. The purpose of this paper is to analyze the sustainable boundaries in terms of their relationship toward greening a supply chain.

Using interpretive structural modeling the research presents a hierarchy-based model to realize the driving power and dependence of sustainable boundary enablers.

The research shows that there exists a group of enablers having a high driving power and low dependence requiring maximum attention and of strategic importance while another group consists of those variables which have high dependence and are the resultant actions.

This classification provides a useful tool to supply chain managers to differentiate between independent and dependent variables and their mutual relationships which would help them to focus while making strategic, tactical or operational decisions as and when required while designing a green supply chain.

This research assumes importance in context of greening a supply chain when globally enterprises are getting a lot of pressure from consumers as well as the regulatory measures from the government. Sustainability demands that the resources be used in lean manner through information coordination with all partners in a supply chain. The findings of this study would help delineate those variables that should to be necessarily considered to design a sustainable supply chain.

This paper aims to intend to help focal firms which are keen to develop a sustainable supply chain by identifying enablers, in knowing the interrelationships involved and in ranking the enablers.

Interpretive structural modeling and fuzzy MICMAC were used for the modeling and clustering of the enablers and fuzzy analytical hierarchy process has been used for the ranking purpose.

Awareness about sustainability incentives, pressure from stakeholders, support from supply chain partners and demand from customer for sustainable products were found very important for developing a sustainable supply chain.

This research will help practitioners to appreciate the importance of the enablers to focus on the making sustainability adoption feasible across the supply chain. This would also facilitate focal firm management to develop a sustainability culture across the supply chain.

Similar work has not been carried before in which interaction among enablers and their priorities were analyzed using hybrid methodologies in developing country context.

The purpose of this paper is to quantify, evaluate and compare the environmental sustainability performance of supply chain for Indian steel industry using graph theoretic approach (GTA).

Broadly 12 environmental sustainability enablers (ESEs) were identified and they were classified into four significant categories (SCs). Featuring these SCs and ESEs under each SC, a methodology was proposed using GTA for evaluating the environmental sustainability performance of Indian steel companies. The analysis was further extended to compare the results with performance in different situations and accordingly set the future targets.

In order to demonstrate the utility of the proposed methodology, it was applied to an Indian steel company. The results obtained indicated that there have been significant growths achieved in the environmental sustainability performance over a period of five years. It was also found that a performance gap exists and it will reach the target value after two years.

The proposed approach is aimed at providing a procedure for evaluating the environmental sustainability performance. This study is an attempt to assist a steel industry to assess its sustainability program and accordingly define its course of actions.

Although many issues related to environmental sustainability have been widely recognized and studied, there are no specific studies available in the literature to assess the environmental sustainability performance along the timeline. The proposed model has the ability to capture the performance and interdependencies of SCs, ESEs under each SC and also to quantify the environmental sustainability performance along the timeline.

The purpose of this paper is to establish the structural relationships between the environmental sustainability enablers (ESEs) for the steel supply chain in India and also to classify them on the basis of driving and dependence power with an objective of achieving enhanced environmental sustainability performance.

The ESEs were identified through extensive literature review and discussion held with experts from the Indian steel industry. The interpretative structural modeling (ISM) approach was applied to an Indian steel supply chain to arrange these 12 ESEs in different hierarchies of the structural framework on the basis of their driver dependence power and also diagraph was developed to classify them.

The water pollution control system, air pollution control system and soil pollution control system were found to be in the bottom hierarchy of the ISM framework and these enablers were also observed in the driving quadrant of the diagraph. These driving enablers should be given priority for its full-scale development, management and monitoring to sustain and enhance the environmental sustainability in the Indian steel supply chain, whereas top management commitment, environment compliance certification and government regulation and incentives are the antecedents for carrying out the sustainability program.

The outcomes of the current study are limited to the Indian steel manufacturing company in specific but the results will not change significantly for the steel sectors in India. However, an empirical analysis can be used to explore and validate the structural framework for its acceptability.

The outcomes from the methodology provide the basis for an Indian steel manufacturing industry to develop the right strategy in their quest for environmental sustainability.

Although the study on ESEs of various industries was reported in the literature, the comprehensive study to identify the significant ESEs related to the Indian steel supply chain for environmental sustainability in specific have been hardly carried out. The current study will definitely be a valuable addition to environmental sustainability literature in general and steel supply chain environmental sustainability in specific.

The purpose of this paper is to analyze the Environmental Sustainability Enablers (ESEs) for an Indian steel manufacturing company to select the appropriate set of ESEs for implementing and enhancing environmental sustainability.

A methodology using fuzzy Decision-Making Trail and Evaluation Laboratory (DEMATEL) is proposed to analyze ESEs capturing multiple experts’ qualitative judgments on their mutual impacts. It is applied to an Indian steel manufacturing company to understand the salient features of the concept.

The relevant 18 ESEs were classified into cause and effect group and also interactions (i.e. influencing and influenced) of each ESE with other ESEs were evaluated. It was observed that the five ESEs (i.e. competitors’ environmental sustainability strategy, environmental compliance certification, government regulations and incentives, influence of external factors and air pollution controlling system) are the most prominent in the cause group.

The results obtained are specific to an Indian steel manufacturing company and it cannot be generalized for steel manufacturing sector. However, the current paper can show direction to carry out such work in other manufacturing companies.

The proposed methodology will be helpful for allocating efforts and resources to enhance the impact of ESEs for successful achievement of environmental sustainability.

No such paper has been reported in the literature with an objective to develop structural framework for Indian steel manufacturing company to improve environmental sustainability.

Unsustainable actions have resulted in the deterioration of the environment. Higher education institutions are social entities responsible for developing future leaders who have the skills and abilities to solve societal challenges. This study aims to develop a conceptual assessment model of environmental sustainability in higher education and apply the model to test the environmental sustainability level of a higher education institution.

The fuzzy logic method is used to develop the conceptual model, and a higher education institution in India was selected for evaluating the environmental sustainability level.

The fuzzy environmental sustainability index for the higher education institution selected for the study was computed as (3.58, 4.95, 6.33). The computed value identifies the institution as “environmentally sustainable”. The calculation of the fuzzy performance importance index further helped in identifying weak attributes that need improvement.

The result of this study would help the management understand their current environmental sustainability level and take corrective measures to improve the weak attributes. It would also assist the institution in reworking its processes and practices.

This study has contributed to the literature of environmental sustainability assessment by creating a conceptual model for evaluating environmental sustainability in higher education. This model can be applied to any higher education institution.

The purpose of this paper is to raise awareness on the need for a more comprehensive approach on the interdependence between artificial intelligence (AI) and environmental sustainability. It provides an overview of existing sustainable AI policy initiatives at the national and regional level. More precisely, it discusses whether existing European Union (EU) environmental policies are suitable for the AI era or whether new regulations are needed in this field. Finally, this paper assesses cross-fertilisation opportunities between the EU and non-EU countries.

This study is based on a qualitative analysis of sustainable applications of AI and the sustainability of AI. Emphasis is laid on the latter, and a “sustainable by design” approach is proposed, which in essence is a prerequisite for transparent, responsible and human-centred AI systems. The analysis primarily focuses on environmental sustainability.

The majority of studies focus on how to use AI to protect the environment with very little attention paid to sustainable design of AI. On the other hand, the EU’s comprehensive approach towards sustainable AI is closest to promoting “sustainable by design” AI. Several ways have been identified in which the EU’s actions can be translated beyond its borders.

One of the largest limitations of this study is its moderate scope. This paper is confined to the EU and as such provides a limited assessment of global policies and measures on the interplay between sustainability and AI. Consequently, the paper did not provide an in-depth analysis of environmental policies worldwide that could help provide a better picture of possible cooperation areas or common grounds. Another limitation of this study is that it primarily focuses on environmental aspects and as such accords little attention to the economic and social pillars of sustainability.

With less than 10 years to go before reaching the sustainable development goal deadline, this study can help stakeholders better understand what is being done worldwide in terms of sustainable AI. Moreover, given that the technology is still in its early phase, this study can inspire a “sustainable by design” approach to the development of AI technologies.

All national AI strategies published by 1 June 2021 were analysed to identify whether and to what extent they prioritise the interplay between environment and AI. Furthermore, the authors also looked at the EU policy and how it aims to address AI from a sustainable perspective.

The purpose of this paper is to revisit lean manufacturing and process management to review how these have targeted environmental sustainability and determine whether these have the potential to achieve environmental sustainability in small- and medium-sized companies within the freight transport sector.

The methodology for this paper was divided into three steps. The first step involved a narrative literature review, including previously designed search strings. The second step involved a snowball approach, where the identification of new sources departed from previously selected articles. The third step included a completing narrative review to search for the most recent articles published related to the purpose. The analysis was based on the identification of benefits, challenges and the potential of lean and process management to deal with environmental demands among transport companies.

The findings suggest a potential of lean and process management for achieving environmental sustainability, if adapted appropriately. The potential is on the operative and strategic levels, respectively.

This study included two of the concepts from the quality movement from a literature perspective. Hence, there is a need for research to evaluate these results empirically. Additionally, other aspects should be studied within the quality movement for achieving environmental sustainability.

This paper aims to be a basis and a path for further theoretical and empirical research for the quality movement to support environmental sustainability. This paper particularly aims to fill part of the gap in the literature on how the freight transport sector can enhance environmental sustainability in its operations.

As an enabler of environmental sustainability, Green information technology (IT) has become an emerging topic of interest in both academic and business communities. Despite its importance, confusions exist in the content and scope of Green IT practice. The purpose of this paper is to provide an overview of the current state of Green IT practice.

First 14 widely accepted Green IT practice topics were identified from prior research and a taxonomy was developed to categorize them. Using the content analysis method, these topics were examined in the sustainability reports of 30 IT companies in 2014 Fortune 500. A quantity–quality portfolio framework was developed and applied to measure and assess the Green IT practices of the selected samples.

Currently, the Green IT practice is still in its infancy. Both research and practice attention are now focusing on IT’s direct impacts and enabling impacts, while overlooking the systemic impacts, on natural environment. The possible reasons for the current state and the recommendations for future research and practice are provided.

Theoretically, this paper identified 14 widely accepted Green IT practice topics and developed a taxonomy for categorizing them. The taxonomy and topics provide a theoretical basis for future examination on Green IT practice-related issues. Practically, the findings of this paper provide guidelines for Green IT practice and directions for both Green IT developers and adopters in their decision-making.

The purpose of this study is to discuss the construction of a structural measurement model utilizing structural equation modelling (SEM) to confirm the link between Industry 4.0 technologies, sustainable manufacturing practices and organizational sustainable performance. Relationship among the paradigm has yet to be fully investigated, necessitating a more conceptual and empirical examination on what impact they have on organizational sustainable performance when used together.

Industry 4.0 and sustainable production practices aim to progress a company's business competitiveness, forming sustainable development that benefits manufacturing companies. The aim of the study is to analyze the relationship between constructs that lead to operational excellence in firms that use Industry 4.0 technologies and sustainable manufacturing techniques. Experts from diverse automotive industries, who are applying both Industry 4.0 and sustainable manufacturing practices, provided data for the study.

Statistical estimations (hypotheses) are created to substantiate the measurement model that has been developed. The structural model was analysed, and the findings were discussed. The statistical estimate is either approved or rejected based on the findings. According to the conclusions of this study, strong link exists between Industry 4.0 technologies and sustainable manufacturing practices that affect organizational sustainable performance environmentally, economically and socially.

The research was conducted in the framework of automobile component manufacturing companies in India. The outcomes of the study are practically feasible.

The authors' novel contribution is the construction of a structural model with Industry 4.0 technologies and sustainable manufacturing practices into account.