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Energy-efficiency leads to productivity gains as it can lower operating and maintenance costs, increase production yields per unit of manufacturing input and improve staff accountability. Implementation of energy-efficient technologies amongst industries, the factors influencing them and the barriers to their adoption have been the subject of several studies during the past three to four decades. Though energy-use behaviours of individuals or households are sufficiently explored, industrial energy conservation behaviour is scarcely studied. This study identifies the relationship between the different behavioural elements to open up a door for behaviourally informed intervention research.

Total interpretive structural modelling technique was used to determine the relationship between different elements of the behaviour of energy managers. Expert responses were collected to understand the relationship between the behavioural elements, through telephone interviews.

The study identified the relationship between the behavioural elements and found imperfect evaluation as the key element with the highest driving power to influence other elements.

The authors postulate that a behaviourally informed intervention strategy that looks into the elements with high driving power such as imperfect evaluation, lack of focus on energy-saving measures and the lack of sharing energy-saving objectives can lead to: an increase in the adoption of energy efficiency measures and thereby a reduction in the energy efficiency gap; greater productivity gains and reduced greenhouse gas (GHG) emissions; Preparation of M&V protocol that incorporates behavioural, organisational and informational barriers.

Various policy level interventions and regulatory measures in the energy field which did not address the behavioural barriers are found unsuccessful in narrowing the energy-efficiency gap, reducing the GHG gas emissions and global warming. Understanding the key driving factor of behaviour can help to design an effective intervention strategy to address the barriers to energy efficiency improvement.

Understanding the key driving factor of behaviour can help to design an effective intervention strategy to address the barriers to energy efficiency improvement. This study argues that through the systematic analysis of the imperfect evaluation of energy audit recommendations, it is possible to increase the adoption of energy efficiency measures that can lead to greater productivity gains and reduced GHG emissions.

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.

This study aims to identify the agile-sustainability readiness factors and analyze them in the context of health-care organization. In this study, agile-sustainability refers to “adapt to the changing environment and respond quickly by maximum using the resources as well as supporting the three pillars of sustainability”.

The “total interpretive structural modelling” (TISM) is used to examine the interrelationships of the identified readiness factors, and to classify the identified readiness factors based on its power to drive and depend on other factors, “Matrice d’impacts croisés multiplication appliquée á un classment (MICMAC) analysis” was used.

This study used a “literature review and experts’ opinion” to identify ten agile-sustainability preparedness characteristics. Organizational leadership, multi-skilled and multi-knowledgeable employees and decision-making autonomy were identified as critical elements in this study.

The research focuses primarily on readiness for agile-sustainability in health-care sector.

This research aids health-care administrators and managers in their decision-making. This study suggests that the evaluation of the readiness factors would promote in raising service standards, ensuring an agile and sustainable health-care operations. The readiness elements that support effective implementation of agile-sustainability in health care require a higher priority from health-care management.

This study created a structural model for health-care organizations based on the TISM-based preparedness for agile-sustainability framework, which is a novel effort for adopting agile-sustainability in health care.

Resilience, the ability of start-ups to deal with anticipated instabilities and probable disruptions, is becoming an important success element during coronavirus disease 2019 (Covid-19). To survive in this pandemic situation, resilience is an important concept for start-ups. The present paper aims to “identify”, “analyse” and “categorize” the resilience factors for start-ups during the Covid-19 pandemic using total interpretive structural modelling (TISM).

The resilience elements of start-ups during Covid-19 were identified and shortlisted during the first phase, which included literature analysis and extensive interaction with experts. TISM was used in the second phase to investigate or to determine how the factors interplayed between the resilience factors of start-ups during Covid-19. The Matrice d'impacts Croises Multiplication Appliquee a un Classment (MICMAC) method is used to rank and categorize the factors. Closed-ended questionnaire with the scheduled interview was conducted to collect the data.

The first part of the study found ten resilience elements in total. The TISM digraph was constructed in the second step to show why one resilience component led to another. The MICMAC analysis divided these factors into four groups: autonomous, linkage, dependent and independent. These groups represented resilience variables based on their driving and dependent power, which assist executives and managers in proactively addressing them while using the TISM digraph as a guide.

During the Covid-19 epidemic, this study focused primarily on resilience characteristics for Indian start-ups.

This study will help key stakeholders and scholars to better understand the elements that contribute to start-up's resilience.

The TISM method for start-up's resilience is suggested in this paper, which is a novel attempt in the field of resilience in this industry.

Using total interpretive structural modelling (TISM), this paper aims to “identify”, “analyse” and “categorise” the sustainable-resilience readiness factors for healthcare during the Covid-19 pandemic.

To obtain the data, a closed-ended questionnaire was used in addition to a scheduled interview with each respondent. To identify how the factors interact, the TISM approach was employed and the cross-impact matrix multiplication applied to a classification method was used to rank and categorise the sustainable-resilience readiness factors.

This study identified ten sustainable-resilience readiness factors for healthcare during the Covid-19 pandemic. The study states that the major factors are environmental scanning, awareness and preparedness, team empowerment and working, transparent communication system, learning culture, ability to respond and monitor, organisational culture, resilience engineering, personal and professional resources and technology capability.

The study focused primarily on sustainable-resilience readiness characteristics for the healthcare sector.

This research will aid key stakeholders and academics in better understanding the factors that contribute to sustainable-resilience in healthcare.

This study proposes the TISM technique for healthcare, which is a novel attempt in the subject of readiness for sustainable-resilience in this sector. The paper proposes a framework including a mixture of factors for sustainability and resilience in the healthcare sector for operations.

This paper intends to discover, analyze and construct a model that may be used to measure the interactions between major factors which are identified by expert opinion and literature review for sustainable maintenance specific to manufacturing industries using the total interpretive structural modeling (TISM) approach.

In total, 12 factors were acknowledged from the literature review and the opinions of experts from manufacturing industries. Scheduled interviews with the employees were conducted by using the questionnaire which is developed from the identified 12 factors in order to find the interrelationships among these factors. The TISM approach is used for analyzing factors' interrelationships. The Matrice d'Impacts Croises Multiplication Appliques a un Classement (MICMAC) approach is used to identify the key factors which influence sustainable maintenance.

This paper found 12 factors that have ascendancy over the sustainable maintenance practices in the industry by reviewing the literature and consulting industry experts to realize the linkage between the factors. The results found that availability rate, adopting government policies, training and education are key factors that influence sustainable maintenance.

The proposed model would be valuable for experts to understand the factors influencing sustainable maintenance in the industry. This model can be used by an organization's maintenance managers to implement sustainable maintenance practices in their plants.

This study analyzes the interrelationship between factors influencing sustainable maintenance in manufacturing industries, which is a new effort in this domain of practice.

The purpose of this paper is to “identify”, “analyze” and “construct” a framework to quantify the relationships between several determinants of organizational preparedness for change in the start-ups during the COVID-19 emergencies.

Total interpretive structural modelling (TISM) is used to find characteristics that assist in analyzing the readiness or preparedness level before initiating a change deployment process in start-ups. A cross-impact matrix multiplication applied to classification (MICMAC) analysis is performed to determine the driving and dependent elements of change in start-ups.

From literature research and an expert interview, this study selected ten variables of change preparedness to explore inner interconnections and comprehend the inner connections factors. The findings depict that clarity of mission and goals, reward system, technological advancement and motivational readiness have been considered the most important readiness factor for deploying organizational change in start-ups during the COVID-19 emergencies.

This research will aid the management and researchers gain a better understanding of the factors that influence change preparedness. Constant observation of current changes in the start-ups and the external environment will aid in improving the quality of products or services provided by the start-ups during the COVID-19. The start-ups can use these criteria linked to change readiness. The priority of each element is determined using MICMAC analysis and ranking using the TISM technique, which assists start-ups in ordering the enablers from highest to lowest priority.

There is no research regarding factors influencing organizational readiness for change in start-ups during the COVID-19 emergencies. This research gap is filled by analyzing aspects linked to organizational readiness for change in start-ups. This gap inspired the present study, which uses the “Total Interpretive Structural Modelling (TISM)” technique to uncover change determinants and investigate hierarchical interconnections among factors influencing organizational readiness to change in start-ups during the COVID-19 emergencies.

When coping with uncertainties, three characteristics distinguish firms: agility, adaptability and alignment (triple-A). Based on significant field research, the triple-A highlights the significance of coordinating agility, adaptability and alignment. Start-ups are facing a lot of challenges in this turbulent environment. However, this sector is undergoing a major transformation. Agility, adaptability and alignment concepts have had a major influence on the supply chain, but their implementation in start-ups has been less visible. This paper aims to identify, analyze and categorize the enablers for agility, adaptability and alignment in start-ups using the total interpretive structural modeling (TISM) approach.

In addition to the scheduled interview, a closed-ended questionnaire was used to collect data. To identify how the factors interact, the TISM technique is used, and the Matriced’Impacts Croises-Multipication Applique’ and Classment method is used to rank and categorize the agility, adaptability and alignment enablers.

This study identified ten agility, adaptability and alignment factors for start-ups. It has been found that the key importance should be given to management involvement, conflict management, collaboration and information integration.

This study primarily focused on the agility, adaptability and alignment factors in start-ups.

This study will help academics and key stakeholders understand the aspects that lead to agility, adaptability and alignment in start-ups.

Agility, adaptability and alignment concepts have had a major influence on the supply chain, but their implementation in start-ups has been less visible. Therefore, this is a novel attempt in this industry’s agility, adaptability and alignment.

Startups across all sectors are affected by the COVID-19 pandemic and are facing a formidable challenge in terms of marketing and operations. Most of the startups have experienced a downturn in demand and supply due to COVID-19 led disturbances in sourcing networks. This paper aims to identify, analyze and categorize the significant risks influencing sourcing operations in startups during the COVID-19 era in India, using the total interpretive structural modeling (TISM) approach.

Eight enablers were identified through literature review and expert opinions from various startups in India. This study adopted the TISM approach to analyze the inter-relationships between the enablers. Multiplication Applied to Classification (MICMAC) analysis was used to rank the sourcing risk enablers and classify them as autonomous, independent, linkage and dependent enablers.

The results indicate “insufficient fund” as the most critical enabler. Network issues and employee flexibility risk were among the other critical enablers that have a high driving power. Supplier risk, quality risk and demand risk were found to have highly dependent on other enablers for implementation.

This study mainly focuses on the sourcing risks in startup operations in India. This study can be extended to many other countries.

This study will help startup industry managers and practitioners understand the interactions of enablers and identify critical enablers to mitigate risks in startup sourcing operations in the COVID-19 era.

The present study identifies the sourcing risk enablers in the COVID-19 era. It is the first attempt to analyze the interrelationship among sourcing risks in startups using the TISM approach.

The purpose of this study is two-fold. First, to identify and encapsulate the enablers that can facilitate technology integration in higher education and second, to understand and analyze the interplay between technology agility enablers.

The study used the Total Interpretive Structural Modeling (TISM) approach to construct a theoretical model of the technology agility enablers in higher education and MICMAC analysis for ranking and segregating the enablers based on their dependence power into four categories: Autonomous, Dependent, Linkage and Independent.

The study helped identify eight technology agility enablers, with the Covid-19 pandemic as the most significant enabler. The Covid-19 pandemic has catalyzed the diffusion of technology across the education sector in India, including tertiary higher education. The study revealed government initiatives and institutional commitment as other enablers that can promote technology agility in higher education.

The results of this study would assist the policymakers and management of universities and colleges in understanding the important enablers that can facilitate technology integration in higher education.

Research in the past on technology adoption in higher education has looked into each enabler in isolation. This research provides a comprehensive view of the enablers and has attempted to establish a multidirectional interplay between the enablers.