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Gazelle companies are characterized by rapid growth in a short time. Identifying the determinants of this exponential expansion is important as these firms have a significant impact on the economy. They generate increased employment and investment by investors interested in new opportunities. Previous studies have failed to reach a consensus about what fosters high growth in gazelle companies as each firm’s geographical, political and economic context is different. The present research uses cognitive mapping and interpretive structural modeling (ISM) to overcome the limitations of prior investigations and identify factors that can potentially accelerate growth in gazelle companies.

Two sessions were held with an expert panel with knowledge about and experience with these firms. In the first session, data were collected to create a group cognitive map, while the second meeting comprised ISM-based analyses of the high-growth determinants identified and the causal relationships between them. A final consolidation session was held to discuss the results with two members of the Committee for Central Region Coordination and Development (i.e. Comissão de Coordenação e Desenvolvimento Regional do Centro – a public entity that grants gazelle awards in Portugal).

The analysis system created was tested, and the results demonstrate that the dual methodology used can increase our understanding of the dynamics of high-growth determinants and lead to more informed and potentially better evaluations of gazelle companies. Indeed, once high-growth determinants in gazelle companies are understood, this information can help other firms implement the same business model to achieve similarly rapid growth. The strengths and shortcomings of this new structured analysis model are also analyzed.

The authors know of no prior work reporting the integrated use of cognitive mapping and ISM in this study context.

The automotive industry appears to overcome much of its obstacles, despite the constant struggle facing COVID-19. The pandemic has resulted in significant improvements in the habits and conduct of consumers. There is an increased preference for personal mobility. In this dynamic environment with unexpected changes and high market rivalry, automotive supply chains focus more on executing responsive strategies with minimum costs. This paper aims to identify and model the drivers to the responsiveness of automotive supply chain.

Seventeen drivers for supply chain responsiveness have been identified from the extensive literature, expert interview. An integrated methodology of fuzzy decision-making trial and evaluation laboratory–interpretive structural modelling (DEMATEL–ISM) is developed to establish the interrelationship between the drivers. The cause–effect relationship between the drivers was obtained through fuzzy DEMATEL technique, and a hierarchical structure of the drivers was developed using the ISM technique.

The result of the integrated methodology revealed that strategic decision-making of management, accurate forecasting of demand, advanced manufacturing system in the organisation and data integration tools are the critical drivers.

This study has conceptual and analytical limitations. In this study, a limited number of drivers are examined for supply chain responsiveness. Further research may examine the role of other key performance indicators in the broad field of responsiveness in the automotive supply chain or other industry sectors. Future study can uncover the interrelationships and relative relevance of indicators using advanced multi-criteria decision-making methodologies.

The authors proposed an integrated methodology that will be benefitted to the supply chain practitioners and automotive manufacturers to develop management strategies to improve responsiveness. This study further helps to compare the responsiveness of the supply chain between various automotive manufacturers.

The purpose of this study is to examine the determinants impacting consumer behaviour in organic food consumption in Bangladesh. This study aims to identify the key factors facilitating organic food consumption and establish a framework by analysing their contextual relationships.

The study used interpretive structural modelling (ISM), relying on expert perspectives from experienced academicians and marketing professionals. A Matrice d'Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) analysis was performed to assess the driving forces and interdependencies among these determinants.

The MICMAC analysis grouped determinants influencing organic food purchases into four categories. The dependent factors, like attitude and food safety, showed moderate driving forces and high dependence. Linkage determinants, such as environmental concern and price, exerted considerable influence with moderate dependence. Independent variables, especially knowledge about organic food, had a strong impact with relatively low dependence.

This study’s insights offer valuable guidance for managers in the organic food industry, providing strategies to address consumer behaviour. Prioritising education on environmental benefits, transparent pricing, collaborating on policies, ensuring food safety and understanding determinants impacting purchase intent can aid in designing effective marketing strategies and product offerings aligned with consumer needs, ultimately promoting sustainability.

To the best of the authors’ knowledge, this study is the first to investigate the interconnections and relative significance of determinants influencing organic food purchases, using the ISM approach and MICMAC analysis. It delves into the previously unexplored territory of understanding the relationships and hierarchical significance of these determinants in shaping consumer behaviour towards organic food purchases.

Today, with the increasing involvement of the environment and human beings business units, paying attention to fulfilling social responsibility obligations while making a profit has become increasingly necessary for achieving sustainable development goals. Attention to profit by organizations should not be without regard to their social and environmental performance. Social responsibility accounting (SRA) is an approach that can pay more attention to the social and environmental performance of companies, but it has many barriers. Therefore, the purpose of this study is to identify barriers to SRA implementation and provide strategies to overcome these barriers.

In this study, the authors identify barriers to social responsibility accounting implementation and provide strategies to overcome these barriers. By literature review, 12 barriers and seven strategies were identified and approved using the opinions of six academic experts. Interpretive structural modeling (ISM) has been used to identify significant barriers and find textual relationships between them. The fuzzy technique for order performance by similarity to ideal solution (TOPSIS) method has been used to identify and rank strategies for overcoming these barriers. This study was undertaken in Iran (an emerging market). The data has been gathered from 18 experts selected using purposive sampling and included CEOs of the organization, senior accountants and active researchers well familiar with the field of social responsibility accounting.

Based on the results of this study, the cultural differences barrier was introduced as the primary and underlying barrier of the social responsibility accounting barriers model. At the next level, barriers such as “lack of public awareness of the importance of social responsibility accounting, lack of social responsibility accounting implementation regulations and organization size” are significant barriers to social responsibility accounting implementation. Removing these barriers will help remove other barriers in this direction. In addition, the results of the TOPSIS method showed that “mandatory regulations, the introduction of guidelines and social responsibility accounting standards,” “regulatory developments and government incentive schemes to implement social responsibility accounting,” as well as “increasing public awareness of the benefits of social responsibility accounting” are some of the essential social responsibility accounting implementation strategies.

The findings of the study have implications for both professional accounting bodies for developing the necessary standards and for policymakers for adopting policies that facilitate the implementation of social responsibility accounting to achieve sustainability.

This paper creates a new perspective on the practical implementation of social responsibility accounting, closely related to improving environmental performance and increasing social welfare through improving sustainability.

Experts believe that the strategies mentioned above will be very effective and helpful in removing the barriers of the lower level of the model. To the best of the authors’ knowledge, for the first time, this study develops a model of social responsibility accounting barriers and ranks the most critical implementation strategies.

The primary purpose of this study is to examine the factors leading to shopping cart abandonment and construct a model depicting interrelationship among them using interpretive structural modeling (ISM) and Matriced Impact Croises Multiplication Appliquee an un Classement (MICMAC).

Initially, 20 factors leading to shopping cart abandonment were extracted through a systematic literature review and expert opinions. Fifteen factors were finalized using the importance index and CIMTC method, for which consistency has been checked in SPSS software through a statistical reliability test. Finally, ISM and MICMAC approach is used to develop a model depicting the contextual relationship among finalized factors of shopping cart abandonment.

The ISM model depicts a technical glitch (SC8), cash on delivery not available (SC4), bad checkout interface (SC9), just browsing (SC11), and lack of physical examination (SC12) are drivers or independent factors. Additionally, four quadrants have been formulated in MICMAC analysis based on their dependency and driving power. This facilitates technical managers of e-commerce companies to focus more on factors leading to shopping cart abandonment according to their dependency and driving power.

Taking an expert’s opinion as a base may affect the results of the study due to biases based on subjectivity.

This study’s outcomes would accommodate practitioners, researchers, and multinational or national companies to indulge in e-commerce to anticipate factors restricting the general public from online shopping.

For the successful running of an e-commerce business and to retain the confidence of e-shoppers, every e-commerce company must make a strategy for controlling factors leading to shopping cart abandonment at the initial stage. So, this paper attempts to highlight the main factors leading to shopping cart abandonment and interrelate them using ISM and MICMAC approaches. It provides a clear path to technical heads, researchers, and consultants for handling these shopping cart abandonment factors.

This study aims to examine adolescents’ social media environment connected to unhealthy food marketing. As social media have become a ubiquitous part of young people’s everyday lives, marketers have also shifted their focus to these channels. Literature on this phenomenon is still scarce and often takes a quite narrow view of the role of marketing in social media. Furthermore, the experiences of the adolescents are seldom considered.

Using a sociocultural approach and netnographic methodology, this study presents findings from a research project conducted in Finland. The data consist of both social media material and focus group interviews with adolescents.

The findings elaborate on unhealthy food marketing to adolescents in social media from two perspectives: sociocultural representations of unhealthy foods in social media marketing and social media influencers connecting with adolescents.

The study broadens and deepens the current understanding of unhealthy food marketing to adolescents taking place in social media. The study introduces a novel perspective to the topic by looking at it as a sociocultural phenomenon.

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.

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

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

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

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

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

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

Today’s marketplace has witnessed intense competitive pressures and high levels of uncertainty and disruption. Therefore, supply chains require agility to obtain a sustainable competitive advantage and cope with uncertainties as well as disruptions. Although a wide range of studies exists on supply chain agility (SCA) from the perspective of antecedents or consequences, there is little research on the investigation of enablers of SCA and their relations among them. Furthermore, the literature has investigated proactive and reactive enablers for enhancing SCA, but most studies have not sufficiently framed their analysis of both aspects synchronically. This paper aims to find out the interrelationships among the proactive and reactive enablers for enhancing SCA.

An extensive literature review has been conducted to identify SCA enablers and a Delphi study has been performed to elucidate SCA enablers in the manufacturing industry in Turkey. Interpretive structural modeling (ISM) has been used to identify the contextual relationship among the SCA enablers, and the model has been validated based on Matriced Impact Croises Multiplication Appliquee a un Classement (MICMAC) analysis.

On theoretical and practical levels, the proposed ISM model in this study can help organizations analyze and interpret interrelationships among enablers of SCA. For managers, it can provide better insights and understanding of the facilitators of SCA to enhance the effectiveness of the supply chain and cope with uncertainties and turbulence. According to results, enhancing “supply and demand side competency”, “delivery speed” and “strategic sourcing” are the most significant enablers of SCA.

The study extends the existing literature related to the enablers of SCA by modeling the proactive and reactive enablers of SCA based on the Al Humdan et al. (2020) classification. Arranging the enablers of SCA in a hierarchy and classifying the enablers into different levels with the help of the ISM-MICMAC approach is an exclusive effort to achieve successful management of the supply chain.

Supply chain vulnerability (SCV) analysis is vital for manufacturers globally because it creates a pathway for building resilient supply chains in uncertain environments. This study aims to identify drivers of SCV in the Indian manufacturing sector.

Sixteen drivers were identified from the literature review and followed by expert interviews. Interpretive structural modeling was used to determine the hierarchical structural relationship among identified SCV factors.

It was found that risk is not a board room agenda. Misaligned performance measures with incentives and lack of risk dashboard are the causal factors of SCV. Supply chain security, centralized production and distribution and lack of trust in the supply chain were driven factors.

This provides new insights to assess and prioritize initiatives for supply chain sustainability in terms of continuing business operations. The structural model provides a systemic view of SCV and helps reduce vulnerability.