Total Interpretive Structural Modeling Research Articles

Leagile supply chains and sustainable business performance: application of total interpretive structural modelling

This study aims to develop an integrated model for the leagile (lean + agile) supply chain strategy to achieve sustainable business performance across the triple bottom line, including economic, environmental, and social performance. We draw upon a literature review and experts’ opinion, using total interpretive structural modelling (TISM), to determine interrelationships among leagile supply chain practices and sustainable business performance measures. To this end, first, unique and common practices of lean and agile supply chain strategies, i.e. leagile building blocks, are identified through a synthesis of the literature. Second, semi-structured interviews with four experts are conducted to gain an understanding of the mutual relationships among the leagile building blocks and to meticulously adjudicate their interactions with sustainable business performance measures. Validated by two independent researchers and literature enfolding, the final TISM model provides a 10-level hierarchical representation of the leagile supply chain strategy for sustainable business performance.

Cost, Usability, Credibility, Fairness, Accountability, Transparency, and Explainability Framework for Safe and Effective Large Language Models in Medical Education: Narrative Review and Qualitative Study

Background The world has witnessed increased adoption of large language models (LLMs) in the last year. Although the products developed using LLMs have the potential to solve accessibility and efficiency problems in health care, there is a lack of available guidelines for developing LLMs for health care, especially for medical education. Objective The aim of this study was to identify and prioritize the enablers for developing successful LLMs for medical education. We further evaluated the relationships among these identified enablers. Methods A narrative review of the extant literature was first performed to identify the key enablers for LLM development. We additionally gathered the opinions of LLM users to determine the relative importance of these enablers using an analytical hierarchy process (AHP), which is a multicriteria decision-making method. Further, total interpretive structural modeling (TISM) was used to analyze the perspectives of product developers and ascertain the relationships and hierarchy among these enablers. Finally, the cross-impact matrix-based multiplication applied to a classification (MICMAC) approach was used to determine the relative driving and dependence powers of these enablers. A nonprobabilistic purposive sampling approach was used for recruitment of focus groups. Results The AHP demonstrated that the most important enabler for LLMs was credibility, with a priority weight of 0.37, followed by accountability (0.27642) and fairness (0.10572). In contrast, usability, with a priority weight of 0.04, showed negligible importance. The results of TISM concurred with the findings of the AHP. The only striking difference between expert perspectives and user preference evaluation was that the product developers indicated that cost has the least importance as a potential enabler. The MICMAC analysis suggested that cost has a strong influence on other enablers. The inputs of the focus group were found to be reliable, with a consistency ratio less than 0.1 (0.084). Conclusions This study is the first to identify, prioritize, and analyze the relationships of enablers of effective LLMs for medical education. Based on the results of this study, we developed a comprehendible prescriptive framework, named CUC-FATE (Cost, Usability, Credibility, Fairness, Accountability, Transparency, and Explainability), for evaluating the enablers of LLMs in medical education. The study findings are useful for health care professionals, health technology experts, medical technology regulators, and policy makers.

Tracing the origins of manipulation: modeling the enablers behind dark patterns usage in e-commerce through TISM and MICMAC analysis

Purpose E-commerce companies often manipulate customer decisions through dark patterns to meet their interests. Therefore, this study aims to identify, model and rank the enablers behind dark patterns usage in e-commerce companies. Design/methodology/approach Dark pattern enablers were identified from existing literature and validated by industry experts. Total interpretive structural modeling (TISM) was used to model the enablers. In addition, “matriced impacts croisés multiplication appliquée á un classement” (MICMAC) analysis categorized and ranked the enablers into four groups. Findings Partial human command over cognitive biases, fighting market competition and partial human command over emotional triggers were ranked as the most influential enablers of dark patterns in e-commerce companies. At the same time, meeting long-term economic goals was identified as the most challenging enabler of dark patterns, which has the lowest dependency and impact over the other enablers. Research limitations/implications TISM results are reliant on the opinion of industry experts. Therefore, alternative statistical approaches could be used for validation. Practical implications The insights of this study could be used by business managers to eliminate dark patterns from their platforms and meet the motivations of the enablers of dark patterns with alternate strategies. Furthermore, this research would aid legal agencies and online communities in developing methods to combat dark patterns. Originality/value Although a few studies have developed taxonomies and classified dark patterns, to the best of the authors’ knowledge, no study has identified the enablers behind the use of dark patterns by e-commerce organizations. The study further models the enablers and explains the mutual relationships.

Critical factors for capacity building of NGOs working in the intellectual disability sector in India: a TISM-MICMAC approach

Purpose This study aims to identify the critical factors contributing to India-based non-governmental organizations (NGOs) capacity building and value creation for beneficiaries. Design/methodology/approach 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. Findings 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). Practical implications 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. Originality/value 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.

Where there is a will there is a way: A strategy analysis for electric vehicles sales in India

The present study evaluates the strategies to promote Electric Vehicles (EVs) sales in India. Through the triangulation process of exhaustive literature review, expert opinions, and the support of a knowledgeable team, 12 potential strategies based on Motivation-Opportunity-Ability (MOA) theory to improve electric vehicle sales are developed. The developed plans are evaluated using Total Interpretive Structural Modeling (TISM) and Matriced’ Impacts Croisés Multiplication Appliquée áun Classement (MICMAC) analysis. The TISM method is used to examine the strategies and understand the interrelationships among them to develop an adoption model. MICMAC analysis is used to categorize strategies on the ground of driving and dependence power. The results indicate that infrastructure development, manpower development, and establishment of driving schools/centers are the most effective strategies. These strategies can have a significant impact on improving sales of EVs and might also influence other proposed strategies. The development of a structural model and categorization is used to propose a roadmap for strategies adopted to enhance sales. The present results can be extended to other developing economies. Marketers and policymakers are acknowledging the importance of embracing EVs as central to future mobility and the present study triangularly (in-depth interviews, literature review, and empirically) guides the mobility of EVs.

Implementation of blockchain – IoT-based integrated architecture in green supply chain

PurposeDigital supply chains require nascent technologies like blockchain and Internet of Things (IoT). There is a need to develop a roadmap for the implementation of these technologies, as they require a huge amount of resources and infrastructure. The purpose of this paper is to analyze the challenges of implementing blockchain-IoT integrated architecture in the green supply chain and develop strategies for the same.Design/methodology/approachAfter a thorough literature survey of Scopus-indexed journals and books, 37 barriers were identified, which were then brought down to 15 barriers after confirming with industry and academic experts using the Delphi method. Using the total interpretive structural modeling (TISM) method and cross-impact matrix multiplication applied to classification (MICMAC) analysis, the barriers were modeled, and finally, strategies were formulated using a concept map to handle the barriers in the blockchain-IoT integrated architecture for a green supply chain.FindingsThis paper presents the research on barriers that can be considered for incorporating blockchain and IoT in the green supply chain. It was found from the TISM model that environmental concerns are Level-1 barriers and need to be addressed by developing appropriate technology and allocating funds for the same. An integrated ecosystem with blockchain and IoT is developed.Research limitations/implicationsThe focus of this study was on the challenges of blockchain and IoT; hence, it is required to extend the research and find challenges for different industries and also analyze the criteria using other multi-criteria decision-making (MCDM) methods. Further research is required for the integration of blockchain-IoT with supply chain functions.Practical implicationsThe transformation of a traditional supply chain into a green supply chain is possible with the integration of technologies. This research work and the strategies developed are useful to managers and practitioners working on technology implementation. Planning resources and addressing key barriers is possible with the concept maps and architecture developed.Social implicationsGreen supply chain management (SCM) is gaining importance in industry as well as the academic sector due to government Policies and norms worldwide for reducing emissions and encouraging environment-friendly production systems. Incorporating blockchain and IoT in a green supply chain will further digitize and increase transparency in supply chains.Originality/valueWe have done a categorization of all barriers based on the expert survey by academicians and industry experts from industries in India. The concept map helps in identifying possible solutions for the challenges and initiatives to be taken for the smooth integration of technologies in the green supply chain.

Barrier analysis to improve big data analytics capability of the maritime industry: A mixed-method approach

The maritime industry is facing increasing challenges due to decarbonization requirements, trade disruptions, and geoeconomic fragmentation, such as International Maritime Organization (IMO) sets out clear framework to reach net zero emissions by 2050, Russia-Ukraine war disrupted maritime activities in the Black and Azov seas, and increased trade tensions between the United States and China. To enhance their sustainability, operational efficiency, and competitiveness, maritime organizations are therefore very keen to build big data analytics capability (BDAC). However, various barriers, mean that only a handful are able to do so. We adopt a mixed-method approach to analyze these barriers. Thematic analysis is used to identify five categories of barriers and 16 individual barriers based on empirical data collected from 26 maritime organizations. These are then prioritized using the analytic hierarchy process (AHP), followed by total interpretive structural modelling (TISM) to understand their interrelationships. Finally, cross-impact matrix multiplications applied to classification (MICMAC) is employed to differentiate the role of each barrier based on its driving and dependence power. This paper makes several theoretical contributions. First, China's hierarchical cultural value orientation encourages competition and obedience to rules, resulting in unwillingness to share knowledge, lack of coordination, and lack of error correction mechanisms. These cultural barriers hinder BDAC development. Second, organizational learning category barriers are found to be the most important in impeding BDAC development. This study also raises practitioners' awareness of the need to tackle cultural and organizational learning barriers.

Analyzing the Hierarchical Structure 
of Enablers Affecting Indian Banks’ Merger and Acquisition Financing Decisions

Mergers and acquisitions have been important means of company expansion, restructuring, and diversification. In mergers and acquisitions, Indian banks play a critical role. The study aimed to discover, determine, and create an empirical model that evaluates the interdependence and interaction of enablers. Through literature and unstructured interviews, 10 enablers influencing Indian banks’ financing decisions for merger and acquisition transactions were identified. Total interpretive structural modelling (TISM) and the Matrice d’Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) technique establish the relationship between identified enablers. Governance and regulatory framework, political stability, and economic stability are major independent enablers for financing mergers and acquisitions. Transparency and disclosure, infrastructure, technical skills, and information communication technology act as linkage enablers for the participation of banks in merger and acquisition transactions. The study makes a novel contribution by identifying enablers through a literature search and ‘experts’ opinions. The TISM model determines the priority of the enablers by displaying hierarchical interconnection and dependency. This study reviews the literature to generalize the findings and focus on significant drivers for increased investment. To encourage merger and acquisition activity, practitioners must focus on elements with significant driving power. It will assist the practitioners, managers, and authorities in prioritizing their efforts.

An integrated approach for modeling critical success factors for supply chain finance ecosystem

Purpose Supply chain finance (SCF) has become a vital ingredient that fosters growth and provides flexibility to the global supply chain. Thus, it becomes essential to understand the factors that contribute to the success of the supply chain finance ecosystem (SCFE). This study aims to identify the critical success factors (CSFs) for the development of an efficient and effective SCFE. Based on their characteristics, the study intends to classify the factors into constructs and further establish a hierarchical relationship among the CSFs. Design/methodology/approach The study is based on empirical data collected from 221 respondents based on administered questionnaires. Exploratory factor analysis (EFA) is carried out on 16 selected factors (out of 21 proposed factors) based on the feedback of the experts and the factors were classified into four constructs. The total interpretive structural modeling (TISM) model was developed by identifying and finalizing CSFs of the SCFE. The model developed a hierarchical relationship between the various factors. Findings The study identified significant CSFs for the efficient and effective SCF ecosystem. Four constructs were developed by analyzing CSFs using the EFA. The finalized 16 CSFs modeled through the TISM and further hierarchical relationship established between the CSFs concludes that governmental policies and sectoral growth are the strongest driving forces and financial attractiveness is the weakest driving force. Based on the CSFs and the constructs identified, it was found that for the success of the SCF ecosystem, the existence of an economic ecosystem provides a facilitating framework for the overall development of the SCFE. Also, the trustworthiness among the partners fosters better relationships and results in financial feasibility and offers business opportunities for all the stakeholders. Practical implications This study will help the SCF partners across the globe understand the CSFs that ensure development of mutually beneficial SCF ecosystems and provide flexibility to the supply chain partners. The CSFs would provide insights to the policymakers and the financial intermediaries for providing a conducive environment for the development of a better SCF ecosystem. Also, the buyers and sellers would understand the CSFs that would develop better relationships among them and ultimately help in development of business across the globe. Originality/value The study identifies the CSFs for the SCF ecosystem. The study ascertains the significant factors and classifies them into clusters using EFA. Unlike the literature available, the paper develops the hierarchical relationship between the CSFs and develops a model for an efficient and effective SCF ecosystem.

Evaluating prioritization of strategic business model for efficient wastewater resource management system

In recent decades, the world has witnessed a sudden rise in population and rapid urbanization. This has led to an increase in the water demand and consequently an upsurge in wastewater. Water scarcity, coupled with untreated wastewater, has become a major concern throughout the world. Municipalities are challenged with the task of treating wastewater and meeting domestic, agricultural, and industrial demands. Mismanagement of wastewater results in economic, social and environmental loss. The high concentration of population, lack of sanitation and water security, reduced awareness, and evident pollution have made India a home full of opportunity and innovation in the wastewater management (WWM) business. The paper gives a comprehensive review to understand the wastewater management and business approach. The research uses Total Interpretive Structural Modelling (TISM) to identify, acknowledge, and interpret the major factors for the stakeholders and for future companies who wish to venture into the wastewater management business. The study provides insight into developing a circular economy solution and gives a vivid framework highlighting the relevant factors for a successful WWM business. The study also provides direction to the practitioners who are involved in the WWM industry and helps evaluate their options, prioritizing resource-efficient solutions.

Assessing the factors influencing the adoption of geothermal energy to support the national grid in emerging economies: Implications for sustainability

The ongoing Russia-Ukraine conflict has made the global energy crisis a severe issue, particularly for emerging economies with a sharp rise in load shedding in communities, disruptions in industrial operation, and an increased cost of living. Shifting our focus from fossil fuel-based energy to sustainable and promising renewable energy sources, like geothermal energy (GE), is crucial to addressing the ongoing energy crisis. Therefore, this study aims to evaluate the significant factors influencing the adoption of GE to support the national grid of an emerging economy like Bangladesh. An integrated framework consisting of the Delphi method, fuzzy total interpretive structural modeling (TISM), and fuzzy Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis was utilized in this study to evaluate the hierarchical interrelationships among the significant factors. The findings indicate that the top two influencing factors are the “scope for new investments and employment” and the “growing need for inexpensive and renewable energy sources”. The study's findings can offer significant insights to decision-makers and policymakers, which can aid in the development of long-term strategic plans to facilitate the successful adoption and integration of GE and promote sustainability and low-carbon economy in the energy sector.

Ontological basis of the creative accounting phenomenon as a financial misstatement

PurposeThis article aims to contribute to the accounting knowledge literature by presenting the framework of creative accounting factors and evaluating their identified factors through an argumentation-based total interpretive structural modeling (TISM) approach.Design/methodology/approachThis study adopted mixed, inductive and deductive approaches to develop an integrated framework, validate its practicability and verify its effectiveness in selected manufacturing firms listed on the Tehran Stock Exchange (TSE), respectively. In developing the framework and implementation procedure, the study employed an exploratory data collection (qualitative) approach to review the phenomenon of creative accounting factors. Then, in this study’s second phase, TISM is used to develop the framework of creative accounting design. This study used two types of theoretical sampling in the qualitative part, including theoretical and snowball sampling. Also, the participants in the TISM process in this study were specialized analysts of the TSE.FindingsBased on the mixed method of this study, the result in the qualitative part provides the creative accounting framework of the existence of three categories. There are 6 components and 35 themes during 12 interviews. In the quantitative section, it was determined that two factors, namely the type of ownership firms and intrinsic objectivity, are the most effective drivers for the formation of creative accounting in TSE firms.Originality/valueSo far, it is rare to find preceding studies that have proposed, validated and practically tested an integrated creative accounting framework within the context of financial markets. Thus, the authors understand that this is the very first research focused on the development of a framework for capital market companies to continuously be competitive and could help financial decision-makers, practitioners and academicians in their perception of knowing more about the financial functions of firms.

Factors influencing competitive advantage in start-ups operations 4.0

Purpose 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. Design/methodology/approach 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. Findings 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. Research limitations/implications The main focus of the study is on the variables that affect startup operations 4.0’s competitive advantage. Practical implications Academics and important stakeholders can better understand the factors influencing competitive advantage in startup operations 4.0 with the help of this research. Originality/value 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.

Analysis of the enablers to deal with the ripple effect in food grain supply chains under disruption: Implications for food security and sustainability

Because of the massive globalization process, market volatility, and today's ever-changing business environment, managing grain supply chains (GSCs) is becoming increasingly challenging. In addition, the ongoing Russia–Ukraine conflict is causing significant disruptions in global supply chains, adding to the challenges imposed by the COVID-19 pandemic in the last couple of years. The ongoing socio-economic disruptions have created a ripple effect in the global supply chains worldwide, especially in emerging economies, which also happen to be the major global exporters of food grains. In this regard, the key enablers of the GSC must be identified to address the impact of the ripple effect and ensure sustainability and food security. This paper addresses these challenges and amalgamates the knowledge on ripple effects, sustainability, and food security. The study aims to identify, prioritize, and delineate the systemic interrelationships among enablers to address the ripple effect of GSC in emerging economies like Bangladesh. A multi-method approach integrating Pareto analysis, total interpretive structural modeling (TISM), and matrice d'impacts croisés multiplication appliquée à un classement (MICMAC) was employed for this purpose. The findings of this study indicate that geological sourcing diversification, governing cash flow to avoid the liquidity crisis, and supplier clustering according to disruptive risks are the most significant enablers. The insights from this study can potentially assist industry leaders and GSC practitioners in making strategic decisions to achieve sustainability in the grain management sector and thus improve future food security in emerging economies.

Readiness for green transformation process in healthcare organizations

PurposeGreen 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.Design/methodology/approachTo 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.FindingsThis 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.Research limitations/implicationsThe 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.Practical implicationsStudy 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.Originality/valueIdentifying 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.

Lean HRM practices in manufacturing SMEs: exploring the interplay among the influencing factors

Purpose 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. Design/methodology/approach 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. Findings 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. Research limitations/implications 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. Practical implications 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. Originality/value 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.

Presenting an evolutionary model of entrepreneurial intelligence components in women: approaches to opportunity discovery and creation

PurposeA better understanding of the characteristics and capabilities of women entrepreneurs can significantly improve their chances of success. Therefore, three studies were conducted for this exploratory paper. We have discovered the characteristics of entrepreneurial intelligence among female entrepreneurs through semi-structured interviews based on conventional content analysis. According to the second study, qualitative meta-synthesis was utilized to identify characteristics of women's entrepreneurial intelligence at the international level. As a third study, we examined the evolutionary relationships of entrepreneurs' intelligence components following the discovery and creation of opportunities.Design/methodology/approachThe present paper was based on three studies. In the first study, 15 female entrepreneurs were interviewed using purposive sampling in the Guilan province of Iran to identify the characteristics of entrepreneurial intelligence at the national level. An inductive content analysis was performed on the data collected through interviews. Using Shannon entropy and qualitative validation, their validity was assessed. In the second study, using a qualitative meta-synthesis, the characteristics of women's entrepreneurial intelligence were identified. Then the results of these two studies were compared with each other. In the third study, according to the results obtained from the first and second studies, the emergence, priority and evolution of entrepreneurial intelligence components in two approaches to discovering and creating entrepreneurial opportunities were determined. For this purpose, interviews were conducted with 12 selected experts using the purposeful sampling method using the fuzzy total interpretive structural modeling (TISM) method.FindingsIn the first research, this article identified the components of entrepreneurial intelligence of women entrepreneurs in six categories: entrepreneurial insights, cognitive intelligence, social intelligence, intuitive intelligence, presumptuous intelligence and provocative intelligence. In the second study, the components of entrepreneurial intelligence were compared according to the study at the national level and international literature. Finally, in the third study, the evolution of the components of entrepreneurial intelligence was determined. In the first level, social intelligence, presumptuous intelligence and provocative intelligence are formed first and social intelligence and provocative intelligence have an interactive relationship. In the second level, entrepreneurial insight and cognitive intelligence appear, which, in addition to their interactive relationship, take precedence over the entrepreneur's intuitive intelligence in discovering entrepreneurial opportunities. With the evolution of the components of entrepreneurial intelligence in the opportunity creation approach, it is clear that intuitive intelligence is formed first at the first level and takes precedence. At the second level, there is cognitive intelligence is created. At the third level, motivational intelligence and finally, at the last level, entrepreneurial insight, social intelligence and bold intelligence.Originality/valueThis study has the potential to discover credible and robust approaches for further examining the contextualization of women's entrepreneurial intelligence at both national and international levels, thereby advancing new insights. By conceptualizing various components of entrepreneurial intelligence for the first time and exploring how contextual factors differ across nations and internationally for women's entrepreneurship, this paper challenges the assumption that the characteristics of women's entrepreneurial intelligence are uniform worldwide. It also depicts the evolution of the components of entrepreneurial intelligence.

An integrated total interpretive structural modeling and MICMAC model for uncovering enterprise agility barriers in the insurance industry

The study aims to identify, analyze, and understand the barriers to enterprise agility in the insurance industry. Initially, the barriers are identified by a review of available literature and expert opinion. Next, an integrated approach consisting of total interpretive structural modeling (TISM) and matrix impact cross multiplication applied to classification (MICMAC) was used to uncover the interrelationship among these barriers. The identified barriers are inefficient information management, employee skill gap, lack of management support, lack of agile workforce, change resistance, lack of training, organizational silos, and lack of digital mindset. Lack of management support drives the other identified barriers with the highest driving power, and lack of an agile workforce was found to have maximum dependence power. The identified framework will assist firms in increasing their enterprise agility by deepening their awareness of the various components and their interdependence and prioritizing the critical barriers. The research contributes to the theoretical and practical understanding of enterprise agility barriers in insurance.

Sustainability reporting for boosting national commitment and overcoming challenges: A hierarchical model

AbstractSustainability reporting (SR) has emerged as a critical mechanism for organizations and nations to communicate their performance in terms of environmental, social, and governance (ESG). The present study investigates the challenges that prevent SR from being useful for system transparency and accountability. It identifies formidable barriers such as intentions, knowledge gaps, resource constraints, and the intricate nature of measurement metrics which necessitating a global collaborative efforts to improve SR's adaptability and acceptance within diverse systems. In addition, this pioneering research examines the factors that influence SR adoption and commitment at the national level. In the study, total interpretive structural modelling (TISM) is used to investigate the hierarchical relationship between factors while MICMAC analysis is administered to identify driver‐dependent connections. It reveals a multi‐layered structure in which macroeconomic factors such as political stability and resource availability drive regulatory effectiveness, operational factors such as administrative efficiency and awareness synergise for progress, and performance factors provide comprehensive insights into SR maturity at national level. The findings contribute significantly to the refinement of theoretical frameworks while emphasizing the importance of SR in advancing the 2030 Agenda for Sustainable Development. It emphasizes on political will, resource allocation, and tailored regulatory frameworks for comprehensive reporting of sustainability. This study provides practical insights for managers, policymakers, and businesses navigating sustainability reporting. It identifies drivers of national SR commitment and guides corporate practices towards sustainable development goals. Understanding these issues strengthens risk management and governance, while advanced measurement tools facilitate assessment and communication. Overall, it empowers stakeholders to elevate their engagement in enhancing sustainability practices, refining governance structures, and informing policy formulation.

Are we really addressing the roadblocks to adoption of renewable and sustainable energy technologies? Total interpretive structural modeling approach.

Urban areas serve as a vital contribution to the global structural change towards renewable and sustainable energy technologies which also influence climate change. The aim of this paper is to identify the adoption roadblocks to renewable and sustainable urban energy technologies. This research has three parts: a mini-systematic literature study was conducted to identify the most prevalent roadblocks. Using total interpretive structural modeling (ISM), the relationships between the roadblocks and the source of causation were then examined. The roadblocks are classified based on their dependence and driving powers using MICMAC analysis in the third part of this research. The principal results and major conclusions demonstrate that all roadblocks are necessary for renewable and sustainable urban energy technologies. The roadblocks at level I are insufficient infrastructure, lack of coordination among authorities, lack of quality and reliable data and information, and competition with non-renewable technologies; roadblocks in level II are lack of skilled and trained personnel, limited public participation, awareness, and consumer interest, and lack of standardized technology; roadblock in level III is high initial investment cost; and lastly, roadblocks in level IV are lack of subsidies and financial support programs and absence of coherent related policies. Furthermore, as a result of theMICMAC analysis, none of the aforementioned roadblocks are classified as autonomous variables, implying that they are all required. The dependent roadblocks to renewable and sustainable energy technologies are defined as lack of coordination among authorities, lack of information, and competition with non-renewable technologies. Moreover, linkage roadblocks have high dependence and driving powers which are insufficient infrastructure, limited awareness and consumer interest, and lack of standardized technology. Lastly, high initial investment costs, lack of subsidies and financial support programs, absence of coherent related policies, and lack of skilled and trained personnel are the driving roadblocks with high driving power however not dependent.