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Lean Six Sigma (LSS) implementation follows a structured approach called define-measure-analyze-improve-control (DMAIC). Earlier research about its application in emergency healthcare services shows that it requires organizational transformation, which many healthcare setups find difficult. The Kotter change management model facilitates organizational transformation but has not been attempted in LSS settings till now. This study aims to integrate the LSS framework with the Kotter change management model to come up with an integrated framework that will facilitate LSS deployment in emergency health services.

Two-stage Delphi method was conducted by using a literature review. First, the success factors and barriers of LSS are investigated, especially from an emergency healthcare point of view. The features and benefits of Kotter's change management models are then reviewed. Subsequently, they are integrated to form a framework specific to LSS deployment in an emergency healthcare set-up. The elements of this framework are analyzed using expert opinion ratings. A new framework for LSS deployment in emergency healthcare has been developed, which can prevent failures due to challenges faced by organizations in overcoming resistance to changes.

The eight steps of the Kotter model such as establishing a sense of urgency, forming a powerful guiding coalition, creating a vision, communicating the vision, empowering others to act on the vision, planning for and creating short-term wins, consolidating improvements and producing still more change, institutionalizing new approaches are derived from the eight common errors that managers make while implementing change in the institution. The study integrated LSS principles and Kotter’s change management model to apply in emergency care units in order to reduce waste and raise the level of service quality provided by healthcare companies.

The present study could contribute knowledge to the literature by providing a framework to integrate lean management and Kotter's change management model for the emergency care unit of the healthcare organization. This framework guides decision-makers and organizations as proper strategies are required for applying lean management practices in any system.

The proposed framework is unique and no other study has prescribed any integrated framework for LSS implementation in emergency healthcare that overcomes resistance to change.

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 purpose of this study is to integrate Green technology, Lean and Six Sigma methodology under the umbrella of Green Lean Six Sigma (GLSS). Further, the study also proposes an eight facet GLSS framework for small and medium enterprises (SMEs) to enhance organizational sustainability.

In this study, GLSS integration has been proposed based on intangible features like barriers, challenges, toolsets, etc. Moreover, the GLSS framework has been realized based on Six Sigma well-known define, measure, analyze, improve and control (DMAIC) approach.

It has been found that lack of customer involvement, financial constraints and ignorance towards Kaizen are the most pre-eminent barriers for GLSS execution. Further, it has been found that most frequently used GLSS tools are the 5S, environmental value stream mapping (EVSM) and life cycle assessment (LCA). The proposed GLSS framework encompasses systematic application of different GLSS tools that lead improved organization sustainability.

The present study will facilitate industrial managers to incorporate the GLSS approach in their business process through systematic understanding of key elements related to this sustainable approach. This study further prompts practitioner to incorporate GLSS in industry through systematic adoption of the proposed framework for improved environmental performance.

This work provides detailed knowledge for the researchers and academicians by dispensing awareness into integral measures and framework. GLSS toolsets dispensed in this work augments academicians and researchers to make decision which tools to be used at distinct phases of GLSS project execution.

The present study is the first of its kind that provides integral measures and GLSS framework for SMEs.

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.

In the current era, the focus on circular economy (CE) has gained substantial momentum among the research communities across the manufacturing world. It has become the need of the hour to act fast due to the alarming issues of unsustainability such as climate change, global warming, waste generation, environmental pollution, resource scarceness and ecological degradations. This research aims to investigate and model the CE enablers in the product development process related to the moderating effect of net zero.

The significant CE enablers are identified through literature review and expert brainstorming. The Pythagorean fuzzy decision-making trial and evaluation laboratory (PF-DEMATEL) technique has been used to investigate and evaluate the significant CE enablers in product development process. PF-DEMATEL determines the inter-relationship and casual dependency among the selected CE enablers. Indian automobile small and medium enterprises (SMEs) have been considered as a case organization to demonstrate the effectiveness of the proposed method.

The findings reveal that “Top management support and clear vision towards CE adoption” is the most important enabler and “Artificial intelligence in product value chain” is recognized as the least vital enabler. This research aids the managers, decision-makers, policy planners and workforce to develop and formulating efficient blueprints for the effective adoption of CE in Indian SMEs.

This is the first kind of research that explores CE enablers in product development process for Indian SMEs.

This research aims to propose a framework to integrate Green Lean Six Sigma (GLSS) and Industry 4.0 to improve organizational sustainability.

The integration of GLSS and Industry 4.0 is proposed based on theoretical facets of the individual approaches. A generic, conceptual framework of an integrated GLSS-Industry 4.0 approach is then proposed using the application of different tools and techniques of GLSS and Industry 4.0 at different stages of the realization of a project.

Both approaches have common facets related to enablers and barriers, and the integrated application of tools and techniques of each approach supplements the common focus of both related to sustainability enhancement. The proposed, conceptual framework provides systematic guidelines from the project selection stage to the sustainment of the solution, with the enumerated application of different techniques and tools at each step of the framework.

This research is the first of its kind to propose the integration of GLSS and Industry 4.0 under the umbrella of a unified approach, including a conceptual framework of this integrated GLSS-Industry 4.0 approach.

This paper aims to estimate the bearing capacity of a surface strip and circular footings lying on layered sand using numerical limit analysis.

Lower and upper bound limit analysis, as well as finite elements and second-order conic programming (SOCP), are used in this analysis. The yield criterion of Mohr-Coulomb is used to model soil behavior. Using this technique, stringent lower and upper bounds on ultimate bearing capacity can be achieved by assuming an associated flow law.

The obtained results indicate that the exact collapse load is typically being bracketed to within 6% about a mean of both the bounds. The obtained results are compared with the existing literature wherever applicable.

To the best of the authors’ knowledge, no study has used lower and upper bound limit analysis, as well as finite elements and SOCP, to estimate the bearing capacity of a surface strip and circular footings lying on layered sand.

The purpose of this study is to identify the leadership characteristics that make a health-care organization ready for lean implementation, analyse the interdependence among them and determine the rank of each characteristic based on their influence in the overall phenomenon.

The leadership characteristics were identified through a review followed by an expert interview. Then, total interpretive structural modelling (TISM) was used to analyse the interdependence and determine the rank, driving power and dependence of each characteristic.

The results suggest that modesty is the most crucial leadership characteristic that makes a health-care organization ready for the successful incorporation of lean practices. Apart from that, attributes such as transparency, accountability, a leader’s ability to empower the employees and communication play a significant role in making the change management programme impactful and effective. A leader’s team building capacity was found to be the dependent characteristic and was ranked the last in the overall phenomenon.

Though this study throws light on various leadership dispositions that prepare a health-care organization to become a lean, it is still not an exhaustive exploration to be generalized. Because the leadership characteristics required for successful lean implementation may vary from one organization to the other depending on the purpose, intensity and priority of the implementation programme, these parameters along with the complexity of the scenario would determine what other leadership characteristics need to be included in the model to make it more robust and holistic.

The novelty of the study lies in capturing the leadership characteristics for organizational readiness in the health-care sector and using the TISM approach to identify the critical characteristics in the context of lean implementation in hospitals.

Organizations are fast adopting new technologies such as automation, analytics and artificial intelligence, collectively called intelligent automation, to drive digital transformation. When adopting intelligent automation, there is a need to understand the success factors of these new technologies and adapt agile software development (ASD) practices to meet customer expectations. The purpose of this paper is to explore the success factors of intelligent automation and create a framework for managers and practitioners to meet dynamic business demands. Total interpretive structural modeling (TISM) framework is a suitable approach to integrate quantitative measurement with qualitative semi-structured interviews capturing the context of the individual organization environment.

This paper identified agility factors and their interrelationships using a TISM framework. TISM results were validated using a one-tailed t-test to confirm the interrelationships between factors. Furthermore, the agility index of a case project organization was assessed using a graph-theoretic approach (GTA) to identify both the triggering factors for agility success and improvement proposals.

Results showed that leadership vision, organization structure and program methodology were driving factors. The TISM model was validated statistically and the agility index of the intelligent automation case project organization was calculated to be79.5%. Here, a GTA was applied and the triggering factors for improvement of the agility index were identified.

The limitations of the study are described along with the opportunities for future research as the field evolves through the rapid innovation of technology and products.

The increasing role of digital transformation in enterprise strategy and operations requires practitioners to understand how ASD practices must be planned, measured and/or improved over time through the implementation of automation, analytics and artificial intelligence programs. The TISM digraph provides a framework of hierarchical structure to organize the influencing factors, which assists in achieving organizational goals. This study highlights the driving factors which contribute to the success of intelligent automation projects and project organizations.

This is a first attempt to analyze the interrelationships among agility factors in intelligent automation projects (IAP) using TISM and the assessment of the agility index of a case IAP organization using a GTA.

This study aims to investigate the implementation of lean human resource management (HRM) practices in manufacturing small- and medium-sized enterprises (SMEs) and explore how various factors interact to influence their successful adoption. By exploring the interplay among these factors, the research seeks to identify key drivers affecting the adoption of lean HRM in manufacturing SMEs. Ultimately, the research intends to provide insights that can guide organisations, practitioners and policymakers in effectively implementing lean HRM practices to enhance operational efficiency, workforce engagement and competitiveness within the manufacturing SME sector.

The study combined total interpretive structural modelling (TISM) and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis. TISM helped in understanding the hierarchical relationship among different factors influencing lean HRM implementation, whereas MICMAC analysis provided insights into the level of influence and dependence of each factor on others.

The research revealed that “top management support” emerged as the most independent factor, indicating that strong support from top management is crucial for initiating and sustaining lean HRM practices in manufacturing SMEs. On the other hand, “employee involvement and empowerment” was identified as the most dependent factor, suggesting that fostering a culture of employee engagement and empowerment greatly relies on the successful implementation of lean HRM practices.

While the study provided valuable insights, it has certain limitations. The research was conducted within the specific context of manufacturing SMEs, which might limit the generalizability of the findings to other industries. Expert opinions introduce subjectivity in data collection. Additionally, the study may not cover all critical factors, allowing room for further exploration in future research.

The findings have practical implications for manufacturing SMEs aiming to implement lean HRM practices. Recognising the pivotal role of top management support, organisations should invest in cultivating a strong leadership commitment to lean HRM initiatives. Furthermore, enhancing employee involvement and empowerment can lead to better adoption of lean HRM practices, resulting in improved operational efficiency and overall competitiveness.

This research contributes to the field by offering a comprehensive exploration of the interplay among factors influencing lean HRM implementation. The use of TISM and MICMAC analysis provides a unique perspective on the relationship dynamics between these factors, allowing for a nuanced understanding of their roles in the adoption of lean HRM practices in manufacturing SMEs. The identification of “top management support” as the most independent and “employee involvement and empowerment” as the most dependent factors adds original insights to the existing literature.