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Despite differing strategies towards environmental sustainability in developed and developing nations, the manufacturing sector in these regional domains faces substantial environmental issues. The purpose of this study is to examine the green-lean-six sigma (GLSS) enablers and outcomes for enhancing environmental sustainability of manufacturing firms in both, a developed and developing country context by using an environment-centric natural resource-based view (NRBV).

First, a framework of GLSS enablers and outcomes aligned with the NRBV strategic capabilities is proposed through a systematic literature review. Second, this framework is used to empirically investigate the GLSS enablers and outcomes of manufacturing firms through in-depth interviews with lean six sigma and environmental consultants from New Zealand (NZ) and Pakistan (PK) (developed and developing nations).

Analysis from both regional domains highlights the use of GLSS enablers and outcomes under different NRBV capabilities of pollution prevention, product stewardship and sustainable development. A comparison reveals that NZ firms practice GLSS to comply with environmental regulatory requirements, avoid penalties and maintain their clean-green image. Conversely, Pakistani firms execute GLSS to reduce energy use, satisfy international customers and create a green image.

This paper provides new insights on GLSS for environmental sustainability which can assist industrial experts and academia for future strategies and research.

This is one of the early comparative studies that has used the NRBV to investigate GLSS enablers and outcomes in manufacturing firms for enhancing environmental performance comparing developed and developing nations

Green, lean and six sigma (GLSS) practices are widely used and well accepted techniques that have the capability to improve the economic, social and environmental performance of Pakistani small and medium enterprises (SMEs). However, implementation of these practices in an integrated approach has not yet been witnessed in Pakistani SMEs due to a variety of challenges. To overcome the implementation challenges, this study has analyzed the impact of GLSS implementation over the sustainability in Pakistani SMEs.

This study consists of two phases. In phase 1, interviews were conducted to scrutinize the elements of GLSS implementation to simplify the model and in phase 2, a questionnaire survey was conducted to collect the data from the SMEs. The partial least squares structural equation modeling (PLS-SEM) approach is used to analyze the relationships among the latent variables and constructs.

Results showed that, leadership for GLSS, understanding GLSS techniques and technology upgradation are considered the most important elements for GLSS implementation in Pakistani SMEs. The environmental and social perspectives have been given more weightage compared to economical perspective. This inferred that there is a need to focus more on environmental and social perspectives in SMEs as compared to economic perspectives to achieve sustainable growth. Moreover, the results of the hypothesis testing revealed that GLSS implementation has a significant positive impact over the sustainability in SMEs considering the Pakistani scenario (β = 0.529, STDEV = 0.078, t = 6.81, p = < 0.001).

This study is the first of its kind for Pakistani SMEs. The structural model developed in this study for Pakistani SMEs will help practitioners to understand the important elements of GLSS implementation and sustainability dimensions.

The study aims to identify Green Lean Six Sigma (GLSS) barriers in the context of Higher Education Institutions (HEIs) and prioritize them for executing the GLSS approach.

A systematic literature review (SLR) was used to identify a total of 14 barriers, which were then verified for greater relevance by the professional judgments of industrial personnel. Moreover, many removal measures strategies are also recommended in this study. Furthermore, this work also utilizes Gray Relational Analysis (GRA) to prioritize the identified GLSS barriers.

The study reveals that training and education, continuous assessment of SDG, organizational culture, resources and skills to facilitate implementation, and assessment of satisfaction and welfare of the employee are the most significant barriers to implementing this approach.

The present study provides an impetus for practitioners and managers to embrace the GLSS strategy through a wide-ranging understanding and exploring these barriers. In this case, the outcomes of this research, and in particular the GRA technique presented by this work, can be used by managers and professionals to rank the GLSS barriers and take appropriate action to eliminate them.

The ranking of GLSS barriers gives top officials of HEIs a very clear view to effectively and efficiently implementing GLSS initiatives. The outcomes also show training and education, sustainable development goals and organizational culture as critical barriers. The findings of this study provide an impetus for managers, policymakers and consultants to embrace the GLSS strategy through a wide-ranging understanding and exploring these barriers.

The GLSS barriers in HEIs may significantly affect the society. HEIs can lessen their environmental effect by using GLSS practices, which can support sustainability initiatives and foster social responsibility. Taking steps to reduce environmental effect can benefit society as a whole. GLSS techniques in HEIs can also result in increased operational effectiveness and cost savings, which can free up resources to be employed in other areas, like boosting student services and improving educational programs. However, failing to implement GLSS procedures in HEIs could have societal repercussions as well. As a result, it is critical for HEIs to identify and remove GLSS barriers in order to advance sustainability, social responsibility and operational effectiveness.

GLSS is a comprehensive methodology that facilitates the optimum utilization of resources, reduces waste and provides the pathway for sustainable development so, the novelty of this study stands in the inclusion of its barriers and HEIs to prioritize them for effective implementation.

Green Lean Six Sigma (GLSS) is a comprehensive approach that aims to reduce waste, emissions and non-value added activities, thus mark an effective impact on sustainability of firms. Despite the numerous benefits of GLSS implementation, it is evident that Micro Small and Medium Enterprises (MSMEs) are still struggling to understand, integrate and implement this strategy. This research work provides a comprehensive analysis of GLSS within MSMEs and proposes a conceptual integration framework of GLSS for improving economic and environmental dimensions of sustainability MSMEs.

A systematic literature review (SLR) methodology was planned to assess and analyse the research articles from 2007 to 2022. Different key elements of GLSS such as barriers, enablers and tool sets have been thoroughly reviewed and analysed for MSME organisations to understand their behaviour and effectively adopt the GLSS approach in their operations.

This study provides the analysis of different perspectives of GLSS and this will contribute to improve different metrics related to emissions and quality in MSMEs. It provides MSMEs industrial managers with a comprehensive knowledge base of GLSS elements, enabling effective deployment.

The present study provides a significant knowledge base and know-how of GLSS to researchers that will assist in deploying this sustainable approach in different industrial domains. The study also assists industrial managers by providing a systematic framework of GLSS for MSMEs. Further, the study also supports society by proving pathway to improve the environmental dynamics through the execution GLSS.

The study is of the first kind that review different facets of GLSS related to MSME. The study not only enhances theoretical know how of GLSS but also guides practitioners how to implement comprehensive GLSS program for improved environmental sustainability.

Green lean six sigma (GLSS) is a sustainable development approach that leads to improved patient care with improved safety and quality of service to patients. This study aims to identify, study, model and analyze GLSS success factors for the Indian health-care facility.

Interpretive structural modeling (ISM) and Impact Matrix Cross-Reference Multiplication Applied to a Classification analyses have been used to understand the hierarchical structure among the GLSS success factors. This enabled the development of dependency relationships between success factors, in particular, which factors support the development of other factors.

Specifically, this study found that the success factors “commitment of management” and “financial availability” are the most critical to GLSS implementation success, as they support the development of all other success factors. Meanwhile “embedding sustainable measures at each stage of the service”; “the capability and effectiveness of real-time data collection”; and “feedback and corrective actions” most directly support the GLSS implementation in the health-care facility and serve as the final indicators of implementation progress.

The major implication of this research work lies in suggesting a direction for practitioners to execute the GLSS approach through a systematic understanding of classification and structural relationships among different enablers. This study also facilitates health-care managers to explore different GL wastes in hospitals and challenges to sustainability pursuits in health-care that assist in an organization’s efforts toward sustainable development.

This research work is the first of its kind that deals with the identification and analysis of the prominent factors that foster the inclusive implementation of GLSS within the health-care facility.

The main purpose of this study is to explore different aspects of the Green Lean Six Sigma (GLSS) approach, application status and potential benefits from a comprehensive review of the literature and provide an avenue for future research work. This study also provides a conceptual framework for GLSS.

To do a systematic analysis of the literature, a systematic literature review methodology has been used in this research work. From the reputed databases, 140 articles were identified to explore hidden aspects of GLSS. Exploration of articles in different continents, year-wise, approach-wise and journal-wise was also done to find the execution status of GLSS.

This study depicts that GLSS implementation is increasing year by year, and it leads to considerable improvement in all dimensions of sustainability. Enablers, barriers, tools and potential benefits that foster the execution of GLSS in industrial organizations are also identified based on a systematic review of the literature.

The study’s uniqueness lies in that, to the best of the authors’ knowledge, this study is the first of its kind that depicts the execution status of GLSS, and its different facets, explores different available frameworks and provides avenues for potential research in this area for potential researchers and practitioners.

The coronavirus (COVID-19) pandemic has led to a surge in demand for health-care facilities, medicines, vaccines and other health-care items. The purpose of this study is to investigate different facets of integrated Green Lean Six Sigma and Industry 4.0 approach in the context of COVID-19 for better healthcare management. Integrating Green Lean Six Sigma (GLSS) and Industry 4.0 (I4.0) has the potential to meet the modern demand of health-care units and also leads to improving the quality of inpatient care with better safety, hygiene and real-time diagnoses. A systematic review has been conducted to determine the tools/techniques, challenges, application areas and potential benefits for the adoption of an integrated GLSS-I4.0 approach within health-care facilities from the perspective of COVID management. Further, a conceptual framework of integrated GLSS-I4.0 has been proposed for better COVID management.

To conduct the literature review, the authors used the preferred reporting items for systematic reviews and meta-analysis and covers relevant papers from the arrival of COVID-19. Based on the systematic understanding of the different facets of the integrated GLSS-I4.0 approach and through insights of experts (academicians and health-care personnel), a conceptual framework is proposed to combat COVID-19 for better detection, prevention and cure.

The systematic review presented here provides different avenues to comprehend the different facets of the integrated GLSS-I4.0 approach in different areas of COVID health-care management. In this study, the proposed framework reveals that the Internet of Things, big data and artificial intelligence are the major constituents of I4.0 technologies that lead to better COVID management. Moreover, integration of I4.0 with GLSS aids during different stages of the COVID management, right from diagnosis, manufacture of items and inpatient and outpatient care of the affected person.

This study provides a significant knowledge database to the practitioners by understanding different tools and techniques of an integrated approach for better COVID management. Moreover, the proposed framework aids to grab day-to-day information from the affected people and ensures reduced hospital stay with better space utilization and the creation of a healthy environment around the patient. This inclusive implementation of the proposed framework will enhance knowledge base in medical areas and provides different novel prospects to combat other medical urgencies.

To the best of the authors’ knowledge, this study is the first of its kind to review different facets of the integrated GLSS-I4.0 approach with a view of the COVID health-care perspective and provides a conceptual framework.

Because of the COVID-19 pandemic and changing market demands, competition for manufacturing industries is increasing and they face numerous challenges. In such a case, it is necessary to use multiple strategies, technologies and practices to improve organizational performance and, as a result, to integrate them for ease of adoption. The purpose of this research is to identify advanced Industry 4.0 technologies, operational excellence (OPEX) strategies and reconfigurable manufacturing system (RMS) practices. The study also computes their weights, as well as identifies and prioritizes the performance metrics for the same.

A thorough review of relevant articles was conducted to identify 28 OPEX strategies, RMS practices and advanced technologies, as well as the 17-performance metrics. The stepwise weight assessment ratio analysis approach was used to compute the weights of the selected practices, while the WASPAS approach was used to prioritize the performance metrics. While developing the framework, the industry expert’s expertise was incorporated in the form of their opinions for pairwise comparison.

According to the study findings, advanced Industry 4.0 technologies were the most prominent for improving organizational performance. As a result, integrating Industry 4.0 technologies with OPEX strategies can assist in improving the performance of manufacturing organizations. The prioritized performance metrics resulted in the production lead time ranking first and the use of advanced technologies ranking second. This emphasizes the significance of meeting dynamic customer needs on time while also improving quality with the help of advanced technologies.

The developed framework can help practitioners integrate OPEX strategies and advanced technologies into their organizations by adopting them in order of importance. Furthermore, the ranked performance metrics can assist managers and practitioners in evaluating the manufacturing system and, as a result, strategic planning for improvement.

According to the authors, this is a novel approach for integrating OPEX strategies with advanced Industry 4.0 technologies, and no comparable study has been found in the current literature.

The purpose of this study is to understand how risk attitudes drive demand for different types of insurance amongst Ghanaians.

This study uses data from a nationally representative survey of Ghanaian households (Ghana Living Standards Survey Round 7). Risk aversion is measured following the approach of Holt and Laury (2002) in the use of hypothetical questions about investment. Probit regressions are used to estimate the effect of risk aversion on insurance outcomes.

The paper finds evidence that supports the theory that risk attitudes influence insurance demand. Specifically, risk aversion is positively related to the uptake of insurance in general and in particular, public health insurance. Unlike previous literature, the authors do not find the sex of the respondent to affect the relationship between risk aversion and insurance demand except for private health insurance. Socio-economic factors such as wealth, age and education were found to strongly predict insurance demand.

The findings confirm that risk attitude influence the demand for insurance in developing countries but socio-economic factors play a strong role in explaining low insurance penetration in such contexts.

Theoretically, attitudes towards risk have been strongly linked with insurance demand. Yet, empirical evidence on this relationship is limited in developing countries where insurance penetration is very low. This study is among the first to document the influence of risk attitude on the demand of a range of insurance products using a large nationally representative sample of individuals in a developing country.