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The aim of this paper is to identify and analyze critical factors/elements influencing standards compliance and their level of influence in a developing country food industry, with specific reference to India.

A total of 13 critical elements were identified and structured using pair‐wise comparisons. Structural and reachability matrices were formed and iterated to yield levels of hierarchical influence of each element. MICMAC analysis was also performed to determine dependency and driving power of these elements.

The analysis brought out a compelling need for “sensitive and responsive” action by developing country governments while competing globally. Food industries in developing countries tend to detour while complying with standards, owing to costs involved in setting up systems and procedures. While a strong surveillance mechanism is the high point of a good compliant system this has to be preceded by supporting measures such as linking of domestic and international markets, consolidation of institutional structures, strengthening of legal/regulatory systems, etc.

Use of interpretative structural modeling (ISM) is inspired by the versatility displayed by this method, as reported by researchers, across a wide spectrum of economic and competitive complexities affecting businesses.

The study is a hitherto unexplored attempt, using interpretative structural modeling, to analyze standards compliance in a developing country's food industry.

The purpose of this paper is to focus on studying the concept of “Smart Organization” and providing a comprehensive framework for the various factors as barriers for the smart organization, identifying and classifying the key criterion of these factors based on their direct and indirect relationships.

In this paper an extensive literature survey and experts’ opinion have been used to identify major barriers of smart organization. These barriers are then modeled using interpretative structural modeling (ISM) methodology. The model so developed has been further improved and an integrated model has been developed using fuzzy-MICMAC.

Various barriers of smart organization have been identified and a structural model has been developed for barriers using the ISM methodology. The critical barriers have been found out by fuzzy-MICMAC analysis. The driver power and dependence graph has been plotted for barriers. The barriers are classified into four categories which are, autonomous, linkage, dependent and independent according to their driver power and dependence. From the ISM model and the integrated model, and from further discussions with the experts, it has been found that the barriers “(B1) organizational structure” and “(B6) Managerial actions” are the two most important barriers, every other barrier is directly or indirectly driven by these.

The basis of developing the ISM model, i.e, the structural self-interaction matrix is based on experts’ opinion, therefore the result may get influenced if there is any biasing in judging the barriers. The future research scope for this paper will be to test the model generated in this paper. The testing of the model can be done by applying structural equation modeling technique, it has the capability of testing the hypothetical model. Further a framework of smart organizations can be created to find out the smartness of different organizations.

The paper can be used by organizations in understanding the barriers in becoming “smart” on the basis of their inter-relationships. This model can help manufacturing organization of North India in understanding the barriers which needs to be worked upon and the inter-relationship among these factors. This model-based study may be helpful in understanding and implementing the practices of smart organization by removing the possible critical barriers.

This is the first study to identify the barriers of smart organizations and to develop a model of these barriers using ISM and fuzzy-MICMAC.

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.

Risk management in defence aircraft industry has considerable interest among academics and practitioners. The purpose of this paper is to develop interactions among risk factors dimensions (RFDs) and inspect the importance relationship among the performance measures in Indian aircraft industry and, finally, understand the effect of involvements provided by the managerial team on risk reduction process.

An extensive literature review was carried out to identify 26 risk parameters and 13 performance measure indices relevant for an aircraft industry. Survey method was used to obtain the importance of these parameters and measures. Further, these factors are grouped into five risk dimensions based on the brain storming session by the project managers. Initially, Risk factors for defense aircraft industry (RFDs) analyzed by Interpretative structural model (ISM) to know the contextual relationship among the RFDs and then applied Interpretive ranking process (IRP) to inspect the pre-eminence relationship among them. Finally, SD is applied to understand the effect of involvements provided by the managerial team on risk reduction process.

Government policy and legal RFDs has emerged as the key driving RFDs. In IRP modelling, technology RFD has emerged as more influential RFD which is the more relevant factor with respect to performance measure indices and this result is supported by detailed sensitivity analysis of system dynamic model.

The outcomes of this research can help project management team to identify the high severity risk factors which need immediate risk reduction/mitigation action.

Due to the growing dominance of the millennials in the secondhand clothing (SHC) market, it is crucial to understand the dynamics of their SHC buying behavior. Despite such significance, it has yet to be explored in the current literature. To address such a gap, this paper aims to explore the antecedents of the SHC buying behavior of millennials.

A purposive survey is conducted to establish relationships between the antecedents. As such, the interrelationships of the antecedents are modeled using the interpretative structural modeling (ISM) approach.

Results reveal that SHC antecedents exhibit several characteristics depending upon their characterization of being driving, dependence, linkage and autonomous variables.

This work pioneers the identification of SHC buying behavior antecedents specifically for the millennial market, as well as in the provision of a holistic analysis of the complex contextual relationships of these antecedents. The findings of this work provide insights that are crucial to the extant literature in developing theoretical frameworks and paradigms that help in understanding the dynamics of the SHC buying behavior. Moreover, such results are beneficial to marketing managers and practitioners in innovating their strategies to capture the millennial market better.

The purpose of this paper is to evaluate the interplay of various measures used by different governments around the world in combatting COVID-19.

The research uses the interpretative structural modelling (ISM) for assessing the powerful measures amongst the recognized ones, whereas to establish the cause-and-effect relations amongst the variables, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is used. Both approaches utilized in the study aid in the comprehension of the relationship amongst the assessed measures.

According to the ISM model, international support measures have the most important role in reducing the risk of COVID-19. There has also been a suggestion of a relationship between economic and risk measures. Surprisingly, no linkage factor (unstable one) was reported in the research. The study indicates social welfare measures, R&D measures, centralized power and decentralized governance measures and universal healthcare measures as independent factors. The DEMATEL analysis reveals that the net causes are social welfare measures, centralized power and decentralized government, universal health coverage measure and R&D measures, while the net effects are economic measures, green recovery measures, risk measures and international support measures.

The study includes a list of numerous government measures deployed throughout the world to mitigate the risk of COVID-19, as well as the structural links amongst the identified government measures. The Matrice d'Impacts croises-multiplication applique and classment analysis can help the policymakers in understanding measures used in combatting COVID-19 based on their driving and dependence power. These insights may assist them in employing these measures for mitigating the risks associated with COVID-19 or any other similar pandemic situation in the future.

This paper aims to clarify the resistance degree of group road logistics to flood disaster resilience. The paper measures the resilience of group road logistics by establishing network structure model. The purpose of this study is to improve the resilience of road log.

This paper adopts Delphi method to collect data, interviews mainly flood management experts and supply chain risk management experts, and then analyzes the data through the network structure model combined with interpretative structure model (ISM) and analytical network process (ANP).

The results show that flood frequency and drainage systems are the main factors affecting the resilience of road transport logistics in urban areas. These research results provide useful guidance for the effective planning and design of urban road construction and infrastructure.

However, the main factors affecting the resilience of road transport logistics are likely to change with the development of factors such as climate, economy and environment. Therefore, in future work, the authors' research will focus on the further application of this evaluation method.

The results show that the impact of flooding on the four dimensions of road logistics resilience varies. This shows that in deciding what intervention measures are to be taken to improve the resilience of the road network to flooding, various measures need to be considered.

This paper provides a more scientific analysis of the risk management ability of the road network in the face of floods. In addition, it also provides a useful reference for urban road planners.

This paper addresses a clear need to study how to build models to improve the resilience of road logistics in flood risk.

The purpose of this paper is to identify and analyze the critical success factors (CSFs) behind the successful implementation of lean-green practices in Indian small- and medium-scale enterprises (SMEs).

The analysis employs two modeling approaches such as interpretive structural modeling (ISM) and interpretive ranking process (IRP) for examining the contextual relationships among the CSFs and ranks them with respect to key lean-green performance areas. A critical review of literature has led to the identification of total 25 CSFs for lean-green implementation. The list is reduced to 18 most relevant CSFs for the context of Indian SMEs based on experts’ (from industry and academia) opinions. The ISM is utilized to develop ten-level hierarchical model of CSFs. In order to gain greater insights into the nature of variables, the matrix of cross-impact multiplications applied to classification (MICMAC) analysis has been conducted.

The results show “Government support” as the most significant to the successful lean-green implementation in Indian SMEs and it is placed at the base of the ISM hierarchy. The CSF “Green disposal initiatives” is identified at the top level of the ISM hierarchy. Further, MICMAC analysis identifies five independent variables, eight linkages variables, four dependent variables and none autonomous variable. This may help SME managers to decide about resource priorities toward successful implementation of lean-green initiatives. Subsequently, the IRP has examined the dominance relationship and identifies “Organizational capabilities” as the most significant CSF.

This research intends to enable practitioners in prioritizing and managing strategic and tactical challenges involved in lean-green implementation in Indian SMEs.

This study makes an initial attempt in analyzing factors critical to successful implementation of integrated lean and green manufacturing practices in Indian manufacturing SMEs using ISM. The analysis is further enhanced by applying IRP to rank the CSFs by investigating the influence lean-green integration on various performance measures.

Recent socioeconomic events, not least the Covid-19 pandemic, have led farms to rethink their traditional production methods. Innovation, new technologies and the establishment of relationships could be crucial for farms to remain competitive and sustainable over time. These factors can be assumed as structural and relational capital, two of intellectual capital's components. In this stream, the aim of this paper is to analyze how structural and relational capital could contribute to farm's sustainability in terms of competitiveness during its normal life cycle and in terms of resilience during an uncertain period, such as the coronavirus emergency.

The paper is supported by the qualitative methodology of a single case study. To reach the declared goal, the paper applies the C.A.O.S. (Characteristics, Ambience, Organizations, Start-up) model, an interpretative model for analyzing the small and medium enterprise dimension. In this way, the main aspects that allowed the farm to be competitive and to react at the emergency period were described.

The findings show that innovation technology involved the farm's internal processes, improving execution, control and feedback phases. Thanks to the two main introduced innovations, the farm reduced staffing costs and minimized cultivation risk related to climatic factors. These innovations are the main factors allowing the farm to increase its efficiency. Moreover, the proactive and reactive roles of the structural and relational capital to face the emergency period are confirmed.

The paper contributes to the literature in several ways. Regarding innovation literature, the paper shows how technology helps farms to improve their performance and their global competitiveness. Insight into structural and relational capital enhances the knowledge of intangible assets, such as intellectual capital. In the light of the Covid-19 emergency, the work demonstrates how the main resilience factors (proactive, i.e. structural capital, and reactive, i.e. relational capital) ensure the farm's survival.

The study proposes to determine the impending challenges to lean integration with Industry 4.0 (I4.0) in manufacturing that aims at achieving desired operational performance. Integrating lean and Industry 4.0 as the two industrial approaches is synergetic in providing operational benefits such as increasing flexibility, improving productivity, reducing cost, reducing delivery time, improving quality and value stream mapping (VSM). There is an urgent need to understand the integrated potential of OPEX strategies like lean manufacturing and also to determine the challenges for manufacturing SMEs and further suggest a strategic roadmap for the future.

The current work has used a combined approach on interpretative structural modeling (ISM) and fuzzy Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) approach to structure the multiple level analysis for the implementation challenges to integrate OPEX strategies with Industry 4.0.

The research has found that the indulgence of various implementation issues like lack of standardization, lack of vision and lack of trained support, all are the major challenges that inhibit the integration of OPEX strategies with I4.0 technologies in manufacturing.

The research has investigated the internal factors acting as a roadblock to lean and Industry 4.0 adoption. Further studies may consider external factors to lean and Industry 4.0 implementation. Also, further research may consider other operational excellence approaches and extend further to relevant sectors.

This study provides the analysis of barriers that is useful for the managers to take strategic actions for implementing OPEX strategies with I4.0 in smart manufacturing.

The research determines the adoption challenges towards the integrated framework. This is the first study to explore challenges in integrating OPEX strategies with I4.0 technologies in manufacturing SMEs.