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The growing pressure on businesses to balance environmental sustainability with profit maximisation has led to the development of green entrepreneurial orientation (GEO), which proactively integrates green practices into core business operations. Grounded in the ecological modernisation theory, GEO acts as a green management practice which helps in achieving competitiveness through environmental innovation. However, despite the growing emphasis on GEO, there remains a gap in understanding how specific drivers influence the organisational structures and processes that lead to GEO. Therefore, the study addresses this gap by analysing the key drivers of GEO using an integrated approach.

In this study, total interpretive structural modelling (TISM) and cross-impact matrix multiplication applied to classification (MICMAC) were used to identify and interpret the interrelationship between key drivers of GEO. Here, TISM technique aided in constructing a contextual relationship-based structural model of drivers, whereas MICMAC assisted in categorising the drivers based on their driving and dependence power. A case evaluation was also carried out in the Indian textile industry to validate the TISM model.

The result indicates that institutional pressure, managerial environment concern, organisational resilience and big data analytical capabilities are the most influential drivers of GEO at organisational level, and other drivers act as secondary and linked variables in this process. The MICMAC analysis further supports the results of TISM. In addition, the overall TISM model is validated in the Indian textile sector.

The study findings will assist researchers and policymakers in adopting a systematic approach to prioritise GEO in pollution intensive industries. Moreover, it will help managers in leveraging GEO to achieve strategic advantages amid environmental challenges.

This study is amongst the first to employ an integrated qualitative approach to analyse drivers of GEO.

The concept of “Smart Cities” is gaining prominence across the world as a solution to effectively address the issues or impediments faced by cities due to rapid urbanization. The purpose of this paper is to identify the key factors which form the primary basis for the implementation of “Smart Cities”. Particularly, this paper aims to analyse the contextual relationship and driving/dependence power of these key factors and model these using the total interpretive structural modelling (“TISM”) framework.

The key factors which form the basis for the implementation of Smart Cities were identified through an evaluation of the literature on “Smart Cities” and expert opinions. Thereon, the contextual relationship between these key factors was examined with the help of experts. Thereafter, these key factors were modelled using the total interpretive structured modelling (“TISM”) framework. Cross-impact matrix multiplication applied to classification (MICMAC) analysis was further applied to classify the factors. It is pertinent to note that the driving power and dependence of these key factors were also reviewed.

This paper establishes a TISM of the key factors for the implementation of “Smart Cities” which will aid in examining the interrelationship among the factors and will also identify the hierarchy among these factors. On extensive examination of the literature and expert opinions on “Smart Cities”, it can be asserted through TISM that quality of life (F1), e-services adoption (F5) and economic growth (F8) are the leading factors in establishing “Smart Cities”. Furthermore, it must be noted that the MICMAC analysis and driving-dependence graph helps in classifying the key factors as autonomous factors, drivers, linkages and outcomes, which assists in comprehending which factors possess driver power and which are exhibiting dependency.

The contribution lies in the authentic manner in which this paper attempts to use the TISM approach combined with MICMAC analysis to model key factors for the implementation of “Smart Cities”; which would aid and assist policymakers and practitioners to construct a structural framework for the implementation of “Smart Cities” through identification of drivers, linkages and outcomes.

This study intends to recognize and prioritize the work-family balance (WFB) enablers for working sole mothers by employing total interpretive structural modelling (TISM) and “Matrice-d’impacts-croisés-multiplication-appliqués-à-un-classment” method (MICMAC).

This paper utilizes the integrated approach in two stages. In initial stage, strategic literature review and expert mining technique have been conducted to recognize and validate WFB enablers. In subsequent stage, TISM has been applied to observe the contextual relationships among WFB enablers in the direction to construct a TISM-based structural model. Furthermore, MICMAC technique has been employed to categorize the WFB enablers based on their driver and dependence power.

This paper has identified novel 13 key enablers of WFB among working sole mothers and constructed a unique TISM-based hierarchical model. Moreover, WFB enablers have been categorized into four clusters using MICMAC analysis. In the developed TISM model, working sole mother-related WFB personal enablers are primarily at the upper level, family-related WFB enablers are in the center and work-related WFB enablers are in the lowest level.

The developed framework on WFB enablers among working sole mothers can provide a resolution to difficulties faced by sole mothers in managing WFB by providing a pathway to enhance their performance by improving the organizational effectiveness through improving WFB policies.

Based on the best of authors' awareness, this study first incorporates the TISM-MICMAC technique to recognize and prioritize the WFB enablers for working sole mothers.

The study tries to identify the barriers influencing supply chain resilience and examine the inter-relationships between them. These relationships are built on the basis of how one barrier drives or is driven by the changes in another barriers.

In the first phase, literature review and with due discussion with experts, the barriers have been identified and shortlisted for an Indian automotive case company. In the second phase, total interpretive structural modelling (TISM) has been applied to examine inter-relationships between the barriers for an Indian automobile case company. Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) analysis has also been performed to analyse the driving and dependence power of the barriers.

In total, 11 barriers are identified from the first phase of the study. In the second phase, the TISM digraph is created which qualitatively explains the reason behind how one barrier leads to another. MICMAC analysis classifies these variables in four clusters namely autonomous, linkage, dependent and independent. These clusters characterise the barriers based on their driving and dependent power which helps managers in strategically tackling them while taking understanding from the TISM digraph.

Three research implications can be made from the study. First, a comprehensive definition of supply chain which helps in understanding of resilience based on disruption phases and recovery. Second, 11 barriers are identified which hinder resilience in automotive sector. Their relationships are modelled using TISM which also gives why a particular relationship exists. Last, MICMAC analysis classifies barriers based on how high or low the driving and dependence power exists.

The study offers significant implications for supply chain managers helping them in building resilience by identifying barriers and reducing their effect. Barriers are identified for case company which might help managers to tackle them during disruptions. The final TISM digraph depicts the “why” between the inter-relationships between the barriers to resilient supply chains. TISM shows that non-commitment of top management is the major root barrier which has been causing the other problems. MICMAC analysis is also performed along with discussion as to how autonomous, linkage, dependent and independent barriers can be tackled to build resilience.

TISM is considered as an effective methodology for conceptual framework development as it also explains “why” between the relationships besides explaining the “what” as against ISM. Identification and understanding of barriers and their interrelationship will help supply chain managers to analyse the influence and inter-dependence of barriers on the resilience of the supply chain. Such understanding will help in mitigating/averting these barriers hence improving the resilience capability. It also adds to the knowledge base in the area of supply chain resilience where several authors have pointed the lack of research.

The purpose of this paper is to examine Philip B. Crosby’s 14 quality principles and analyze the interaction between them. Hitherto no research has been published on the implementation of total quality management (TQM) using Crosby’s 14 principles. To fill this gap, interpretive structural modeling (ISM) and Matrix Impact Cross-Reference Multiplication Applied to a Classification (MICMAC) analysis have been designed to prioritize, sequence and categorize variables to find both the dependence and driving power of these variables.

At the initial stage experts from industry as well as from academia were contacted to provide an input for ISM methodology and examine interactions between identified variables. In this approach, interpretations of the interrelationships among variables have been discussed, whereas MICMAC analysis is used to discover dependence and driving power.

The results of the investigation revealed that “Management Commitment,” “Quality Improvement Team,” “Quality Awareness,” “Supervisor Training,” “Goal Setting” and “Cost of Quality Evaluation” are strategic requirements; “Corrective Action,” “Zero Defects Day” and “Error Cause Removal” are tactical requirements. “Recognition,” “Quality Measurement,” “Quality Councils” and “Do It Over Again” are operational requirements for TQM applications.

ISM is used as a part of this research to provide valuable insights into interrelationships among Crosby’s quality principles through a systematic framework. The research opens up a new focus area on the implementation of TQM for services as well as for the manufacturing industry.

Sustainability is a very important factor to be considered in the supply chain (SC) of any industry. Agricultural industry needs to be addressed even more importantly with the tools of sustainability as it concerns the life of millions. This paper explores the critical barriers (CBs) in the sustainable supply chains (SSCs) of makhana industry located in the northern part of India and seeks to design a model for the researchers and the managers who want to work in this industry.

Initially, the CBs were identified with the help of an extensive literature review of sustainability in SCs for agri-industry and discussion with makhana industry experts (consisting of managers and senior managers) and academicians (consisting of professors and research scholars). The study uses the multi-criteria decision-making (MCDM) technique, namely interpretive structural modeling (ISM) and fuzzy ISM to develop the model. The study finally validates the model using Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) analysis.

The obtained results indicate that, in the SSC of makhana industry, the role of “Lack of adoption of organic agricultural management techniques” (CB2), “Lack of modern techniques (CB4)”, “Multiple intermediaries” (CB5), “Weak socio-economic conditions” (CB7) and “Lack of proper knowledge” (CB1) are very significant. These barriers are needed to be addressed first as they have the highest driving power and other barriers are directly driven by these CBs.

The paper has included seven experts, and the interrelationship between CBs has been developed on the basis of their knowledge and discussion, so the results may be a little bias. Moreover, the paper has obtained the results using the ISM and fuzzy ISM by considering ten CBs; the researchers can explore this research by including more CBs and validate the results using other MCDM techniques like fuzzy-decision making trial and evaluation laboratory (DEMATEL), fuzzy-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Best Worst Method (BWM).

This study is unique as per industry point of view and may help the researchers and managers to explore the field of makhana.

The recent pandemic caused by coronavirus disease 2019 (COVID-19) has significantly impacted the operational performances of pharmaceutical supply chains (SCs), especially in emerging economies that are critically vulnerable due to their inadequate resources. Finding the possible barriers that continue to impede the sustainable performance of SCs in the post-COVID-19 era has become essential. This study aims to investigate and analyze the barriers to achieving sustainability in the pharmaceutical SC of an emerging economy in a bid to help decision-makers recognize the most influential barriers.

To achieve the goals, two decision-making tools are integrated to analyze the most critical barriers: interpretive structural modeling (ISM) and the matrix of cross-impact multiplications applied to classification (MICMAC). In contrast to other multi-criteria decision-making (MCDM) approaches, ISM develops a hierarchical decision tool for decision-makers and cluster analysis of the barriers using the MICMAC method based on their driving and dependency powers.

The findings reveal that the major barriers are in a four-level hierarchical relationship where “Insufficient SC strategic plans to ensure agility during crisis” acts as the most critical barrier, followed by “Poor information structure among SC contributors,” and “Inadequate risk management policy under pandemic.” Finally, the MICMAC analysis validates the findings from the ISM approach.

This study provides meaningful insights into barriers to achieving sustainability in pharmaceutical SCs in the post-COVID-19 era. The study can help pharmaceutical SC practitioners to better understand what can go wrong in post-COVID-19, and develop actionable strategies to ensure sustainability and resilience in practitioners' SCs.

This paper aims to identify future scenarios and convergent technologies regarding the plantain chain in the region of Quindío, Colombia. It proposes the definition of key variables, convergent technologies, future objectives, future scenarios and hypotheses based on stakeholders’ and experts’ opinions collected through questionnaires, surveys and workshops.

The present analysis seeks to identify and anticipate the future routes for the improvement of scientific, technological, innovative and skills management of the plantain agroindustrial chain in the region of Quindío, Colombia using the foresight-by-scenarios and, Delphi methodologies and finally validating the results with artificial intelligence code and natural language processing.

After the analysis of 100 initial variables, the results suggested the identification of five key variables defined by the stakeholders and matrix-based multiplication applied to a classification (MICMAC) analysis such as “weather,” “financing and economy,” “grouping and associativity,” “crop” and “territorial planning and raw material.” Moreover, the definition of four future objectives along with the matrix of alliances and conflicts, tactics, objectives and recommendations (MACTOR) analysis suggested scenarios according to the probability. The most possible, probable and desirable scenario, was the cooccurrence of the five proposed hypotheses. Furthermore, the Delphi analysis allowed us to define nine subgroups from 116 subtopics including: “plantain varieties,” “plantain agroindustry,” “waste use” and “crop,” among others.

Due to the specificity of the analyzed agro-chain, the study only encompasses the plantain and banana sectors. However, the implications are related to the generation of projects in the selected technologies.

This paper includes implications for the development of prospective studies combining two or more different methodologies such as foresight-by-scenarios and Delphi method at the same time and further comparing the results with artificial intelligence analysis.

The generation of public policies in the sector and input for governmental analysis and tools for decision-making with a well-grounded, systematic and rational point of view.

This work describes for the first time, the implementation of the Delphi method regarding an important agroindustry sector such as plantain and banana prospective study. Furthermore, it explains the alignment of two methodologies; foresight-by-scenarios and the Delphi method related to the sectorial approaches, and convergent technologies and innovations, respectively. Moreover, a complementary bibliometric analysis with global terms related to the plantain or banana agroindustry was also included. In a novel way, we also applied an artificial intelligence code using Python software to contrast the results previously obtained in the foresight-by-scenarios method.

Behavioral characteristics and the existence of personal knowledge and skills that are essential in forming a capable manager with specialized insight, is one of the most important evaluation processes in appointing a manager. Wisdom as a trait of a set of personal characteristics and cognitive knowledge of a capable manager will gain competitive advantages for the company and external stakeholders. The purpose of this study is to present the framework of managerial financial wisdom through qualitative and quantitative research methodologies.

The study uses grounded theory methodology to identify factors for managerial financial wisdom and uses a MICMAC process to evaluate the power of driving and dependence among factors. MaxQDA software was used for data coding and analysis. The MICMAC process by determining the location of each of the sub-themes in the four-dimensional matrix, seeks to determine the most effective criterion in the context of the study. The method of data collection is mixed and in terms of philosophical nature, this study is inductive/comparative.

The results of the research in the qualitative part indicate the presentation of a framework based on two categories, four components, and thirty themes. The results of the quantitative part of the study also showed that the most important factor of managerial financial wisdom is market-oriented values. Finally, it was found that the social trust caused by managerial financial wisdom is considered a factor in gaining more shares in the capital market due to the positive stimulus in this dimension.

The study is relevant for both practitioners and academia and has significant implications. For practitioners, the structural linkages identified will help enhance managerial wisdom effectiveness and drive the critical metrics for financial decisions and shareholders' rights protection. The study may help financial market practitioners better understand future policies. Academia and researchers can take reference from methodologies used in this study for exploring factors of interest and developing matrix linkages among them.

The purpose of this paper is to identify the information and communication technology management enablers (ICTMEs) and establish the hierarchical relationship among them using interpretive structural modelling (ISM) and analyse their driving and dependence power, using integrated ISM fuzzy-MICMAC analyses.

For identifying the ICTMEs, along with extensive literature review a large number of academicians and practitioners of repute are consulted. The contextual relationships between ICTMEs are established with the help of a well-established ISM methodology and further ICTMEs are analysed on the basis of their driving and dependence power and classified them into four different clusters by using fuzzy-MICMAC.

This paper has identified 25 key ICTMEs related to human resource, organization culture, technology, strategic planning, ICTM practices and organizational performance measurement and created a diagraph representing hierarchical relationship among them. Further these enablers are analysed and classified into four clusters on the basis of their driving and dependence power.

The developed relational model is based on the inputs of academicians and practitioners and any biasing from the person judging the ICTM enablers might influence the power of this model.

Top management of the organization could formulate and execute their strategies keeping in mind these identified critical enablers and relationship among them which will finally result into higher performance of ICTM.

This is the first kind of study which has identified 25 key enablers of ICTM, established hierarchical relationship among them and analysed them on the basis of their driving and dependence power using integrative ISM fuzzy-MICMAC analysis.