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Researchers have studied processes of improving road traffic-safety culture by explicitly evaluating the socio-psychological phenomenon of traffic-risk. The implicit traffic-system cues play an important role in explaining urban traffic-culture. This paper aims to ascertain an interpretive framework of the alternative processes of road traffic safety culture is antecedent to promote traffic-safety behaviour in Indian urban context. Subsequently, the authors discussed the reasons for those relationships exists.

Four experts of the urban traffic-safety domain participated in total interpretive structural modelling (TISM) study by completing an interpretive consensus-driven questionnaire. The drafted interpretive model was evaluated for road users proactive action orientation about the traffic-safety decision.

The evolved directed graph (digraph) of the culture of urban traffic-safety management was a serial three-mediator model. The model argued: In the presence of traffic-risk cues, people may become apprised to safety goals that initiate traffic-safety action. Consequently, expectancy-value evaluation motivates the continuation of traffic-safety intention that may lead to the implementation of adaptation plan (volitional control), thus habituating road users to traffic-safety management choice.

The modellers of traffic psychology may empirically estimate and test for the quality criteria to ascertain the applicability of the proposed mechanism of urban traffic-safety culture. The decision-makers should note the importance of arousal of emotions regarding traffic-risk, reduce the impact of maladaptive motivations and recursively improve control over safety actions for promoting safety interventions.

The authors attempted to induce an interpretive model of urban traffic-safety culture that might augment extant discussion regarding how and why people behave in an urban traffic system.

It would not be an exaggeration to say that healthcare is the most crucial one in today's perspective. The healthcare sector, in general, is engaged in working on various dimensions simultaneously like the safety, care, quality and cost of services, etc. Still, the desired outcomes from this sector are far away, and it becomes pertinent to address all such issues associated with healthcare on a priority basis for sustaining the outcomes in a long-term perspective. The present study aims to explore the healthcare sector and list out the directly associated enablers contributing to increasing the viability of the healthcare sector. Besides, the interrelationship among the enlisted enablers needs to be studied, which further helps in setting-out the priority to deal with individual enablers based on their impedance in the contribution towards viability increment.

The authors have done an extensive review to list out the enablers of the healthcare sector to perform efficiently and effectively. Further, the attempt has been made on the enablers to rank them by using the modified Total Interpretative Structure Modelling (m-TISM) approach. The validation of the study reveals the importance of enablers based on their position in the hierarchical structure. Further, the MICMAC analysis on the identified enabler is performed to categorize the identified enablers in the different clusters based on their driving power and dependence.

The research tries to envisage the importance of the healthcare sector and its contribution towards national development. The outcomes of the m-TISM model in the present study reveal the noteworthy contribution of the organizational structure in managing the healthcare facilities and represented it as the perspective of future growth. The well-designed organizational structure in the healthcare industry helps in establishing better employee–employer cooperation, workforce coordination and inter-department cooperation.

Every research work has limitations. Likewise, the present research work also has limitations, i.e. input taken for developing the models are from very few experts that may not reflect the opinion of the whole sector.

The healthcare sector is the growing sector in the present-day scenario, and it is essential to keep the quality of treatment in check along with the quantity. The present study has laid down the practical foundations for improvement in the healthcare sector viability. Besides, the study emphasized on accountability of the healthcare sector officials to go with the enablers having the strong driving power for effective utilization of all the resources. This would further help them in customer (patients) satisfaction.

Despite an increase in demand for good quality healthcare facilities worldwide, the growth of this sector is bounded by the economic, demographic, cultural and environmental concerns, etc. The present study proposed a unique framework that provides a better understanding of the enablers. It would further help in playing a key role in increasing the viability of the healthcare sector. The hierarchy developed with the help of m-TISM and MICMAC analysis will help the viewers to recognize the important enablers based on their contribution to the viability improvement of the healthcare sector.

This will not be an overstatement to state that the micro, small and medium enterprise (MSME) industry is crucial and the vital driver of the world economy. It covers different fields and dimensions such as defense products, electrical components and low-cost products. The sector plays a vital role in rendering work with low capital expenditure and is one of the emerging pillars of the Indian economy. Given the significance of this sector in contributing towards India's gross domestic product (GDP), it becomes appropriate to resolve all the issues related to MSME on a primary basis for ensuring required support. The recent global pandemic of COVID-19 has impacted this sector to a great extent. This research study targets the MSME industry and points out the directly linked enablers adding to improve the sector's resiliency and sustainability. Therefore, identification and the interrelationship between the MSME enablers need to be studied, which helps make a preliminary list that deals with their impedance benefaction towards resiliency increment.

The writers have done a comprehensive literature analysis of the enablers for the MSME sector to enable effectively and efficiently during emergencies and pandemics. An endeavor has been made on the enablers to order them by utilizing the modified Total Interpretative Structure Modelling (m-TISM) technique. Authentication of this research work highlights the significance of enablers and their position in a hierarchical structure. Further, MICMAC investigation on the recognized enablers is performed to arrange them in the four quadrants on their dependence and driving power.

The authors have attempted to predict the significance of the MSME sector and its essential contribution to the development of India's economy. The result of m-TISM in the current research work revealed the essential commitment of a hierarchical design dealing with the MSME considering the viewpoint of future development. The well-planned traditional design in the MSME helps establish better government policies and programs and transport infrastructure.

Every research study has a few restrictions. Likewise, the boundaries of the current study are that inputs collated for fostering the models are from a few specialists that may not mirror the assessment of the whole MSME sector.

The MSME sector is the developing sector in the current day, and it is needed to keep supporting the sector for the country's development. The current study has set out the functional establishment to improve MSME practicality. In addition, the research highlights the accountability of the MSME authorities to go with the identified enablers having solid driving power for successful usage of the available resources. This will help the MSME development and add value to practitioners and policymakers in the future.

The growth of this sector is essential for the development of the economy and the development of a nation. The current study presents a unique structure that gives a superior comprehension of the enablers. It will help play a crucial role in developing the MSME area. The structure model developed with the assistance of m-TISM and MICMAC examine the identified enablers with inputs from experts in the field. The hierarchy developed from the study recognized the enablers located on their commitment of suitability development of the MSME field.

In the realm of energy behaviour studies, very little research has been done to understand industrial energy behaviour (IEB) that influences the willingness to adopt (WTA) energy-efficient measures. Most of the studies on energy behaviour were focused on the residential and commercial sectors where the behaviour under investigation was under volitional control, that is, where people believe that they can execute the behaviour whenever they are willing to do so. The purpose of this paper is to examine the factors influencing the industry’s intentions and behaviour that leads to enhanced adoption of energy efficiency measures recommended through energy audits. In particular, this paper aims to extend the existing behaviour intention models using the total interpretive structural modelling (TISM) method and expert feedback to develop an IEB model

TISM technique was used to determine the relationship between different elements of the behaviour. Responses were collected from experts in the field of energy efficiency to understand the relationship between identified factors, their driving power and dependency.

The results show that values, socialisation and leadership of individuals are the key driving factors in deciding the individual energy behaviour. WTA energy-saving measures recommended by an energy auditor are found to be highly dependent on the organisational policies such as energy policy, delegation of power to energy manager and life cycle cost evaluation in purchase policy.

This study has a few limitations that warrant consideration in future research. First, the data came from a small sample of energy experts based on a convenience sample of Indian experts. This limits the generalizability of the results. Individual and organizational behaviour analysed in this study looked into a few select characteristics, derived from the literature review and expert feedback, which may pose questions about the standard for behaviours in different industries.

Reasons for non-adoption of energy audit recommendations are rarely shared by the industries and the analysis of individual and organisational behaviour through structured questionnaire and surveys have serious limitations. Under this circumstance, collecting expert feedback and using the TISM method to build an IEB model can help to build strategies to enhance the adoption of energy-efficient measures.

Various policy level interventions and regulatory measures in the energy field, adopted across the globe, are found unsuccessful in narrowing the energy-efficiency gap, reducing the greenhouse gas (GHG) emissions and global warming. Understanding the key driving factors can help develop effective intervention strategies to improve energy efficiency and reduce GHG emissions.

The industry energy behaviour model with driving, linking and dependent factors and factor hierarchy is a novel contribution to the theory of organisational behaviour. The model takes into consideration both the individual and organisational factors where the decision-making is not strictly under volitional control. Understanding the key driving factor of behaviour can help design an effective intervention strategy that addresses the barriers to energy efficiency improvement. The results imply that it is important to carry out post energy audit studies to understand the implementation rate of recommendations and also the individual and organisational factors that influence the WTA energy-saving measures.

The purpose of this study is to identify, evaluate and develop a structured model to measure the interrelation between critical failure factors (CFFs) that affects the implementation of the sustainable Lean Six Sigma (SLSS) framework in a manufacturing organization. Further solution approaches have been provided that inhibit those CFFs and help in successful implementation of the framework.

To find the interrelation among the selected CFFs and develop a systematic structured model, a total interpretive structural modeling (TISM) approach has been used. A 13-level model for selected CFFs has been formed after the application of the TISM approach. Further classification of CFFs has been performed for a better understanding of their nature through MICMAC analysis.

A total of 26 SLSS CFFs have been identified through a detailed study of case organization, various literature reviews and experience of panel experts toward developing a systematic model of CFFs. The solution approach has been provided by panel experts based on their industrial experiences after observing the role of CFFs in the developed model. Based on the analysis, it was found that most dependent and dominant CFFs affect the implementation of the SLSS framework in the case organization.

This study helps SLSS practitioners, project managers, decision-makers and academicians of manufacturing industries to a better understanding of the failure factors and their interrelations while implementing the SLSS framework in manufacturing organizations. This study also guides the systematic solution approach which helps in tackling such problems that occurred in manufacturing organizations.

In this study, the TISM-based structural model of CFFs for implementing the SLSS framework in manufacturing organizations has been proposed which is a very new effort in the area of a manufacturing environment.

Environmental sustainability (ES) is an increasing tendency in the healthcare industry as it seeks to enhance the environmental friendliness and reduces waste in operations to save money. The objective of research article is to identify the factors that contribute to improving the performance of ES in hospitals. Understanding the factors that contribute to the improvement of healthcare services may be helpful for practitioners, who need to address and implement an effective framework to enable an environment-friendly practice in hospitals.

The current study utilised the technique called total interpretive structural modelling (TISM) to identify the factors and understand the interconnection between the identified factors. A literature review revealed 12 factors, which were then refined with the input of hospital experts. Based on a questionnaire survey, a planned interview is conducted in chosen Indian hospitals. The matrix impact cross multiplication applied to classification (MICMAC) study employs dependency and driving power to identify the hierarchical relationship between the detected factors.

Green building initiatives, water consumption, resource usage, and renewable energy were identified as key factors in the study. Other factors such as staff behaviour, procurement of goods and management of hazardous substance would be influenced by these fundamental components. With the implementation of green initiatives in the hospital, ES is primarily used to reduce the excessive use of scarce resources.

The ES programme begins at the hospital grounds, with awareness and specific training provided to all personnel, including doctors, nurses, and managers at all levels. The training programme is intended to raise awareness; sessions are divided into targeted groups; a new organisational structure is created; and a consultant agent is hired to commence ES.

Existing literature has focussed mostly on ES factors such as carbon emissions, water conservation, and effective waste disposal, while ignoring organisational viewpoints and their interrelationships. As a result, the current study used TISM to show the relationship between various organisational and environmental perspective components in order to comprehend the reasoning behind improving performance.

The purpose of this paper is to identify and analyse the interactions among various enablers which are critical to the success of big data initiatives in operations and supply chain management (OSCM).

Fourteen enablers of big data in OSCM have been selected from literature and consequent deliberations with experts from industry. Three different multi criteria decision-making (MCDM) techniques, namely, interpretive structural modeling (ISM), fuzzy total interpretive structural modeling (fuzzy-TISM) and decision-making trial and evaluation laboratory (DEMATEL) have been used to identify driving enablers. Further, common enablers from each technique, their hierarchies and inter-relationships have been established.

The enabler modelings using ISM, Fuzzy-TISM and DEMATEL shows that the top management commitment, financial support for big data initiatives, big data/data science skills, organizational structure and change management program are the most influential/driving enablers. Across all three different techniques, these five different enablers has been identified as the most promising ones to implement big data in OSCM. On the other hand, interpretability of analysis, big data quality management, data capture and storage and data security and privacy have been commonly identified across all three different modeling techniques as the most dependent big data enablers for OSCM.

The MCDM models of big data enablers have been formulated based on the inputs from few domain experts and may not reflect the opinion of whole practitioners community.

The findings enable the decision makers to appropriately choose the desired and drop undesired enablers in implementing the big data initiatives to improve the performance of OSCM. The most common driving big data enablers can be given high priority over others and can significantly enhance the performance of OSCM.

MCDM-based hierarchical models and causal diagram for big data enablers depicting contextual inter-relationships has been proposed which is a new effort for implementation of big data in OSCM.

The purpose of this paper is to examine the elements of asymmetric motives, i.e., initial cross-border joint venture (CBJV) conditions and relative partner characteristics in emerging nations. The two main objectives of the present research are to identify the elements affecting asymmetric motives in Indian bilateral CBJV and to construct modified total interpretive structural modelling (TISM) for the identified elements of asymmetric motives.

For the current study, the qualitative technique named total interpretive structural modelling was used. The TISM (Sushil, 2012) is a novel extension of interpretive structural modelling (ISM) where ISM helps to understand the “what” and “how” of research (Warfield, 1974) and TISM answers the third question, i.e., “why” in the form of TISM; further checks for the correctness of TISM are given in Sushil (2016). TISM provides a hierarchical model of the elements selected for study and the interpretation of each element by iterative process and also a digraph that systematically depicts the relationship among various elements. TISM is an innovative modelling technique used by researchers in varied fields (Srivastava and Sushil, 2013; Wasuja et al., 2012; Nasim, 2011; Prasad and Suri, 2011). Steps involved in TISM are shown in Figure 1. It uses reachability matrix and partitioning of elements similar to ISM. Also, along with traditional TISM, the modified TISM process was also used where both paired comparisons and transitivity checks were done simultaneously which helped in minimising the redundant comparisons being made in the original process. Furthermore, for identifying the elements of study, SDC Platinum database was used, which was taken from research papers of major journals namely British Journal of Management, Administrative Science Quarterly, Strategic Management Journal, Management Science, Academy of Management Journal and Organization Science (Schilling, 2009). The database included all joint ventures that were formed in India, having India as one of the partner firms during fiscal year April 2000 and March 2010. From these, 361 CBJVs and 76 domestic joint ventures were identified. Although 54 CBJVs were excluded from these, a total number of 307 CBJVs were studied in the current research. Among these 307 CBJVs, 201 were from super-advanced nations (G7), 40 CBJVs from developing nations and 66 CBJVs from other developed nations. As 65 per cent of the CBJVs came from G7 nations (France, Italy, Japan, Canada, Germany, USA and UK), in the current study, we tried to examine Indian CBJVs with G7 partners only for a period of ten years as mentioned above.

The results of the study indicate that asymmetric motives are directly affected by critical activity alignment and interdependency. Thus, we can conclude that critical activity alignment of partners in CBJV is an antecedent of CBJV motive and thereby minimises the number of asymmetric motives. Bottom level variables such as culture difference and relative capital structure are considered as strong drivers of asymmetric motives. Diversification, resource heterogeneity and inter-partner conflict are middle level elements. Effect of these elements on asymmetric motives can only be improved and enhanced when improvement in bottom level variables is found. It has been believed that as the relative capital structure among firm increases, CBJVs’ asymmetric motives also increase, the reason being that as the difference in capital structure occurs, gradual change in bargaining power will also occur.

TISM used in the present study provides valuable insights into the interrelationship between identified elements through a systematic framework. The methodology of TISM used has its implications for researchers, academicians as well for practitioners. Further study also examines driver-dependent relationship among elements of interest, i.e., relative partner characteristics and initial CBJV conditions by using MICMAC analysis, which can be viewed as a significant step in research related to bilateral CBJV.

This study aims to identify and prioritize various growth-accelerating factors in the Indian automotive industry. It further develops a hierarchical model to examine the mutual interactions between the factors, their dependence and their driving power.

This study first identifies the growth-accelerating factors and then uses the modified total interpretive structural modeling (m-TISM) framework, which is an extended version of TISM. It further uses MICMAC analysis to analyze the mutual interrelation between the identified factors.

This study highlights the interrelation amongst the factors using m-TISM model. A hierarchical model shows the level of autonomous, dependence, linkage and independent factors considering the Indian automotive industry. This study also provides the understanding related to the interdependence of growth-accelerating factors.

The government and practitioners could evaluate the growth-accelerating factors which have higher driving power for implementing efficient policies and strategy formulation. By implementing m-TISM model in the Indian automotive industry, auto manufacturers can become more productive and profitable. Future studies could use other methods such as expert opinion to derive the factors, and further model could be verified using structural equation modeling technique.

This study uses a novel m-TISM framework for the analysis of growth-accelerating factors in the context of the Indian automotive industry. It further provides a detailed theoretical and conceptual understanding relating to the philosophy and establishes an interrelation amongst these under-researched growth-accelerating factors.

This study aims to examine the enablers of productivity of enterprise-level Agile development process using modified total interpretative structural modeling (TISM). The two main objectives of the current study are to determine the variables influencing enterprise-level agile development productivity and to develop modified TISM for the corresponding components.

To identify enablers of the productivity of enterprise-level agile software development process a literature review and opinions of domain experts were collected. A hierarchical relationship among variables that show direct and indirect influence is created using the modified TISM (M-TISM) technique with Cross Impact Matrix-Multiplication Applied to Classification analysis. This study examined and analyzed the relationships between the determinants within the enterprise using a M-TISM technique.

With the literature review, the study could identify ten enabling factors of the productivity of Agile development process at the enterprise level. Results depict that program increment (PI) planning and scalable backlog management, continuous integration and continuous delivery (CI/CD), agile release trains (ART), agile work culture, delivery excellence, lean and DevOps practices, value stream mapping (VMS), team skills and expertise, collaborative culture, agile coaching, customer engagement have an impact on the productivity of enterprise-level Agile development process. The results show that team collaboration, agile ways of working and customer engagement have a greater impact on productivity improvement for enterprise-level Agile development process.

The developed model is useful for organizations employing scaled Agile development processes in software development. This study provides a recommended listing of key enablers, that may enable productivity improvements in the Agile development process at the enterprise level. Strategists should focus on team collaboration and Agile project management. This study offers a modified TISM model to academicians to help them understand the effects of numerous variables on maintaining the productivity of an enterprise-level Agile. The identified characteristics and their hierarchical structure can help project managers during the execution of Agile projects at the enterprise level, more effectively, increasing their success and productivity.

The study addresses the gap in the literature by interpretative relationships between the identified enabling factors. The model validation is carried out by a panel of nine experts from several information technology organizations deploying Agile software development at the enterprise level. This unique method broadens the knowledge base in Agile software development at scale and provides project managers and practitioners with a practical foundation.