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This paper aims to “identify,” “analyse” and “categorise” the readiness factors of lean sustainability in health-care organisation using total interpretive structural modelling (TISM).

To obtain the data, a closed-ended questionnaire was used in addition to a scheduled interview. To identify how the factors interact, the TISM approach was used, and the matriced’ impacts croise’s multiplication applique’e a UN classement (MICMAC) analysis was used to rank and categorise the lean sustainability readiness factors.

This study identified ten lean sustainability readiness factors for health-care organisation. The identified factors are resources utilization practice (F1), management commitment and leadership (F2), operational flexibility (F3), workforce engagement and time commitment (F4), sustainability motivational factors (F5), awareness of lean and sustainable practice (F6), hospital design (F7), energy efficiency practices in hospitals (F8), responsible autonomy (F9) and new system adoptability training (F10). The key/driving factors are identified in this study are operational flexibility, sustainability motivational factors, management commitment and leadership, new system adoptability training.

The study focussed primarily on lean sustainability factors for the health-care sector.

This research will aid key stakeholders and academics in the better understanding the readiness factors that influence lean sustainability in health-care organisation. This study emphasises the factors that must be considered when applying lean sustainable practices in health care as a real-world application in a health-care organisation. These readiness factors for lean sustainability can be used by an organization to comprehend more about the concept and the components that contribute to health-care lean sustainability.

This study proposes the TISM technique for health care, which is a novel attempt in the subject of lean sustainability in this sector.

The purpose of this study is to identify organisational homeostasis factors in the context of healthcare organisations and to develop a conceptual model for green transformation.

The organisational homeostasis factors were determined by review of literature study and the opinions of healthcare experts. Scheduled interviews and closed-ended questionnaires are employed to collect data for this research. This study employed “TISM methodology” and “MICMAC analysis” to better comprehend how the components interact with one another and prioritise them based on their driving and dependence power.

This study identified 10 factors of organisational homeostasis in healthcare organisation. Recognition of interdependence, hormesis, strategic coalignment, consciousness on dependence of healthcare resources and cybernetic principle of regulations are the driving or key factors of this study.

The study's primary focus was on the organisational homeostasis factors in healthcare organisations. The methodological approach and structural model are used in a healthcare organisation; in the future, these approaches can be applied to other industries as well.

The key drivers of organisational homeostasis and the identified factors will be better comprehended and understood by academic and important stakeholders in healthcare organisations. Prioritizing the factors helps the policymakers to comprehend the organisational homeostasis for green transformation in healthcare.

In this study, the TISM and MICMAC analysis for healthcare is proposed as an innovative approach to address the organisational homeostasis concept in the context of green transformation in healthcare organisations.

Organizations have increasingly been compelled to engage in ecological businesses in recent decades, necessitating identifying environmental practices contributing to enhanced sustainability. One of the main reasons for doing this research is to see how far down the path to green transformational leadership (GTFL) in Green Human Resource Management (GHRM) practices in the healthcare industry in Pakistan. Additionally, this research aims to analyze how this change affects the long-term success of businesses in sustainable performance (SP).

To identify factors related to the study variables, the research utilized master journals, as well as the Web of Science and Scopus databases. The ISM-DEMATEL (Interpretive Structural Modeling - Decision Making Trial and Evaluation Laboratory) technique was employed to establish a hierarchical model. This model facilitated the identification of cause-and-effect relationships among factors, which were further elucidated using the DEMATEL interrelationship diagram.

The analysis of the results indicates that Green Training (F4), Green Job Analysis (F1), Intellectual Stimulation (F10), and Green Product Innovation (F9) are the primary factors that have a significant impact on achieving Environmental Policies and Regulations (F13), and Subjective Environment Norms (F14) of SP factors.

The study is implemented in the healthcare industry of Pakistan, with a focus on practical and managerial aspects. It encourages managers to develop and adapt their human resources policies and environmental strategies. Implementing safety health standards is crucial to mitigate the detrimental effects on the environment. The research was carried out during the period of the pandemic. The scope of this study was restricted to the healthcare industry in Pakistan.

In order to improve SP, this study presents a unique strategy combining sustainability into decision-making procedures with the function of GTFL in GHRM. Implementing safety health standards is crucial to mitigate the detrimental effects on the environment.

The ability of a business to outperform its rivals is known as its competitive edge, and it presents special difficulties in the context of the “digital revolution,” or the fourth industrial revolution. To obtain a competitive edge in the startup operations 4.0 era, this study aims to examine the organizational, technological and competence-related challenges presented by Industry 4.0. It does this by concentrating on the tools, competencies, methods, approaches, tools and strategies that are crucial. Using the Total Interpretive Structural Modeling (TISM) technique, the goal is to find, analyze and classify enablers for startup operations 4.0.

A closed-ended questionnaire and planned interviews were used in the data collection process. In startup operations 4.0, the cross-impact matrix multiplication applied to classification method is used to rank and categorize competitive advantage factors, whereas the TISM technique is used to analyze how components interact.

The study highlights the critical significance of the “Internet of Things (IoT),” “information technologies,” “technological platforms,” “employee empowerment,” “augmented reality (AR)” and “operational technologies” in its identification of 12 enablers for startup operations 4.0.

The main focus of the study is on the variables that affect startup operations 4.0’s competitive advantage.

Academics and important stakeholders can better understand the factors influencing competitive advantage in startup operations 4.0 with the help of this research.

Large businesses have been profoundly impacted by Industry 4.0 principles; however, startup operations 4.0’s competitive advantage has not received as much attention. This paper offers a fresh take on the concept of competitive advantage in startup operations 4.0 research.

Green transformation is more than simply a trend; it is a way of life, a set of habits, a field of knowledge and a dedication to resource conservation. Going green is surely a creative and transformative process for both individuals and organizations. This paper aims to “identify,” “analyse” and “categorise” the readiness factors for green transformation process in health care using total interpretive structural modelling (TISM) and neutrosophic-MICMAC.

To address the study objectives, the study used TISM and neutrosophic-MICMAC analysis. To identify the readiness factors, a literature study was conducted, and the factors were face-validated by the healthcare experts. The factors influence on one another were captured by using a scheduled interview with a closed ended questionnaire. The TISM addressed the identification and analysing of factors and the categorization and ranking the readiness factors is addressed by using neutrosophic-MICMAC analysis.

This study identified 11 green transformation process readiness factors for healthcare organizations. The study states that the key factors or driving factors are awareness of green governance principle, environment leadership and management, green gap analysis, information and communication technology and innovation dynamics.

The factor ranking is sensitive to the respondents’ ratings. The study relied on the past literature and experts’ opinion may result in the subjective biases. The complex nature of healthcare ecosystem challenges to capture all the factors. The study focussed on Indian hospitals.

Study significantly impacts the healthcare practitioners, academicians and policymakers by providing critical insights into the readiness factors required for the healthcare green transformation process. The study offers a better understanding of the crucial or key or driving factors that aid in embracing green and sustainable practices.

Identifying a gap in conceptual and theoretical frameworks for green transformation readiness factors in healthcare organizations and in Indian context. The study addresses this gap by aiming to create a thorough theoretical framework and highlighted by its focus on Indian hospitals.

This study aims to identify the critical factors contributing to India-based non-governmental organizations (NGOs) capacity building and value creation for beneficiaries.

A total interpretive structural modeling technique has been used to develop a hierarchical model of critical factors and understand their direct and indirect interrelationships. The driving force and dependence force of these factors were determined by using cross-impact matrix multiplication applied to classification analysis.

This study identifies 12 critical factors influencing NGO capacity building in India’s intellectual disability sector across four dimensions. Internal organizational capabilities include infrastructure, staff qualifications, fundraising, vocational activities and technical resources. Second, coordination and stakeholder engagement highlight government and agency collaboration, dedicated board members and stakeholder involvement. Third, adaptability and responsiveness emphasize adjusting to external trends and seizing opportunities. Finally, impact and value creation emphasis on improving value for persons with disabilities (PWDs).

The findings of this study have practical implications for Indian NGOs working for PWDs. The study provides NGOs with a structural model for improving organizational capacity by identifying and categorizing critical factors into the strategic model.

There is a scarcity of literature on capacity building for disability-focused NGOs in India. This study seeks to identify critical factors and develop a hierarchical model of those factors to assist policymakers in India in building the capacity of NGOs.

The advancements in internet technologies and the use of sophisticated digital devices in supply chain operations incessantly generate enormous amounts of data, which is termed as big data (BD). The BD technologies have brought about a paradigm shift in the supply chain decision-making towards profitability and sustainability. The aim of this work is to address the issue of implementation of the big data analytics (BDA) in sustainable supply chain management (SSCM) by identifying the relevant factors and developing a structural model for this purpose.

Through a comprehensive literature review and experts’ opinion, the crucial factors are found using the PESTEL framework, which covers political, economic, social, technological, environmental and legal factors. The structural model is developed based on the results of the total interpretive structural modelling (TISM) procedure and MICMAC analysis.

The policy support regarding IT, culture of data-based decision-making, inappropriate selection of BDA technologies and the laws related to data security and privacy are found to affect most of the other factors. Also, the company’s vision towards environmental performance and willingness for material and energy optimization are found to be crucial for the environmental and social sustainability of the supply chain.

The study is focused on the manufacturing supply chain in emerging economies. It may be extended to other industry sectors and geographical areas. Also, additional factors may be included to make the model more robust.

The proposed model imparts an understanding of the relative importance and interrelationship of factors. This may be useful to managers to assess their strengths and weaknesses and ascertain their priorities in the context of their organization for developing a suitable investment plan.

The study establishes the importance of BDA for conservation and management of energy and material. This is crucial to develop strategies for enhancing eco-efficiency of the supply chain, which in turn enhances the economic returns for the society.

This study addresses the implementation of BDA in SSCM in the context of emerging economies. It uses the PESTEL framework for identifying the factors, which is a comprehensive framework for strategic planning and decision-making. This study makes use of the TISM methodology for model development and deliberates on the social and environmental implications too, apart from theoretical and managerial implications.

In academics and industry, significant efforts have been made to lead planners and control teams in evaluating project performance and control. In this context, numerous control metrics have been devised and put into practice, often with little emphasis on analyzing their underlying concepts. To cover this gap, this research aims to identify and analyze a holistic list of control metrics and their functionalities in the construction industry.

A multi-step analytical approach was conducted to achieve the study’s objectives. First, a holistic list of control metrics and their functionalities in the construction industry was identified. Second, a quantitative analysis based on social network analysis (SNA) was implemented to discover the most important functionalities.

The results revealed that the most important control metrics' functionalities (CMF) could differ depending on the type of metrics (lagging and leading) and levels of control. However, in general, the most significant functionalities include managing project progress and performance, evaluating the look-ahead level’s performance, measuring the reliability and stability of workflow, measuring the make-ready process, constraint management and measuring the quality of construction flow.

This research will assist the project team in getting a comprehensive sensemaking of planning and control systems and their functionalities to plan and control different dynamic aspects of the project.

The fresh food supply chain industry faces significant challenges in risk management because of the complexity, immature development and unpredictable external environment of imported fresh food supply chains (IFFSCs). This study aims to identify specific risk factors in IFFSCs, demonstrate how these risks are transmitted within the system and provide an analytical framework for managing these risks.

A total of 15 risk factors for IFFSCs through extensive literature review and expert consultation are identified and classified into seven levels using interpretive structural modeling (ISM) to demonstrate the risk transmission path. Fuzzy Matrice d’Impacts Croises-Multiplication Appliance Classement (MICMAC) analysis is then used to analyze the role of each factor.

The interactions of the 15 identified risk factors of IFFSCs, classified into seven levels, are visualized using ISM. The fuzzy MICMAC analysis classifies the factors into four groups, namely, dependent, independent, linkage and autonomous factors, and identifies the relatively critical risk factors in the system.

The findings of this research provide a clear framework for enterprises operating in IFFSCs to understand the specific risks they may face and how these risks interact within the system. The fuzzy MICMAC analysis also classifies and highlights critical risk factors in the system to facilitate the formulation of appropriate mitigation measures.

This study provides enterprises in IFFSCs with a comprehensive understanding of how the risks can be effectively managed and a basis for further exploration. The theoretical model constructed is also a new effort to address the issues of risk in IFFSCs. The ISM and the fuzzy MICMAC analysis offer clear insights for researchers and enterprises to grasp complex concepts.

This study aims to identify the factors influencing agile readiness in start-ups. Start-ups are being confronted with increased competition, customer demands, technological innovations and changes in the market environment. Adopting agile readiness for sustainable operations is a profitable and dependable way to improve the competition and reduce the number of failures of start-ups. The start-ups may investigate “how” after understanding the “whys.” The answers to these questions will be crucial to develop a strategy and a plan for luring clients, users, investors and partners. Therefore, this study will help in answering these crucial questions by using Total Interpretive Structural Modeling (TISM), whose main aim is to answer the key question of “what,” “how” and “why.” Using the “Total Interpretive Structural Modeling (TISM)” technique, this research tries to “describe,” “analyze” and “categorize” the agile readiness for sustainable operations enablers in start-ups.

Expert feedback and literature reviews from various start-ups led to the discovery of 10 enablers. In this study, the TISM technique was used to examine the inter-relationships between the enablers. The agile readiness for sustainable operations enablers was ranked and classified using the “Multiplication Applied to Classification (MICMAC)” technique. They were divided into four different categories: “autonomous,” “independent,” “linkage” and “dependent enablers.”

The results show that executive-level aid is the key agile readiness factor for sustainable operations. The next priority has been capability, experienced and skilled employees, market knowledge and environment agility. Leadership and clear vision have been given further priority. The next important is flexibility. The last and the least priority is given to receptive and strategic agility. This directional flow assists management in attaining adaptable sustainability, leading to continued growth in this dynamic environment.

The study focuses primarily on the agile readiness for sustainable operations of start-ups. This study offers a recommended list of crucial elements for start-ups, which may aid in creating guidelines for implementing agility for sustainable operations. This study provides academics with a TISM model that illustrates how start-ups can be ready to implement agility for sustainable operations. Future researchers could add more agility readiness variables to this study and validate this model across different start-ups.

Before implementing agile readiness for sustainable operations in start-ups, this study will aid managers and practitioners in the start-up business in understanding the relationships of enablers and identifying important readiness enablers.

The current study analyzes the agile readiness for sustainable operations in Start-ups. To the best of the authors’ knowledge, it is the first endeavor to use the “TISM approach” to examine the interrelationships across agile readiness for sustainable operations characteristics in start-ups.