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Corporate social responsibility (CSR) ISO standards have been noted as an essential marketing strategy by which firms can achieve consumer trust while improving environmental, social, and quality factors. This study discloses the contextual relationship between CSR ISO standards and sustainable impulse buying behavior. This study also looks to uncover the CSR ISO driving and linkage factors that motivate consumers to make sustainable impulsive purchases.

Three distinct research methods were employed in this research. First, a consumer expert opinion-based Interpretive Structural Modeling (ISM) approach was adopted to reveal the contextual relationship between CSR ISO factors and sustainable impulse buying behavior. Secondly, Matrice Impacts Croises Multiplication Appliques Classement (MICMAC) was used to examine these factors' driving and dependent power. In addition, Minitab package software was also used to check the statistical validation of ISM-MICMAC results.

The results indicate that although environmentally responsible CSR ISO 14001, socially responsible CSR ISO 26000, and consumer perception of product quality CSR ISO 9001 standards contain strong driving power, their dependent power was weak. All these CSR ISO factors (14,001, 26,000, and 9001) strongly impact each other and sustainable impulse buying. Therefore, these three CSR ISO factors have been placed at the bottom of the ISM model. The CSR ISO 14020 standard (labeling of the product), knowledge of CSR ISO standards, consumer trust, and advertising about CSR ISO standards have been placed in the middle. The mentioned factors have intense driving and dependent power and are classified as linkage factors for sustainable impulse buying. Impulse buying behavior has weak driving and strong dependent power, yet this factor strongly depends on other CSR ISO factors. Hence, this factor is placed at the top of the ISM model. In addition, the Minitab package software results indicate that ISM-MICMAC results are statistically valid.

To the best of our knowledge, this research is unique and examines the influence of CSR ISO factors on sustainable impulse buying in the context of Pakistani consumers. Secondly, our study has thoroughly investigated several CSR ISO factors and allied these factors in the context of consumer buying behavior. Third, several CSR ISO factors and impulse buying behavior were examined using a mix of ISM-MICAC and Minitab methods. Thus, including these steps in our study has led to the development of a novel technique.

Open innovation has attracted the attention of experts and business entities for the sustainable survivability of firms, especially in the post-COVID-19 era. The food and beverage industry has been facing sustainable survivability problems. It is important to identify and evaluate the factors of open innovation from the perspectives of the food and beverage industry. This study serves that purpose by identifying and evaluating the factors of open innovation in the post-COVID-19 era with a special reference to Pakistan's economy.

The present study integrates the Fuzzy Delphi Method (FDM), Interpretive Structural Modelling (ISM) and Matrice d’ Impacts Croises Multiplication Applique a Classement (MICMAC) methods to analyze the factors involved in the adoption of open innovation in the food and beverage industry in Pakistan. Firstly, based on an extensive literature review of the most relevant studies, the factors affecting open innovation have been identified and finalized using FDM and experts' opinions. Secondly, the hierarchical framework has also been prepared by implementing the ISM approach. Thirdly, the MICMAC approach was employed to evaluate the factors to examine the driving and dependence powers of the factors of open innovation adoption.

The study identified 17 factors of open innovation adoption in Pakistan's food and beverage industry and 16 factors were finalized using FDM. The ISM-MICMAC matrix unveiled that awareness seminars and training, along with a lack of executive commitments, were strong factors with high driving power, but these factors proved to be weakly dependent powers regarding the other factors. Moreover, a lack of innovation strategy, R&D and non-supportive organizational culture exhibited low driving power but strong dependent power.

The findings of the study could help firms and business entities understand the driving and dependent factors involved in open innovation for the sustainable survivability of the food and beverage industry. The study provides strong reasons to believe that an open innovation strategy, along with stakeholder collaboration, the adoption of rules and regulations and managerial commitment, could stimulate open innovation. Moreover, governments should promote the business sector, especially the food and beverage industry, to facilitate the sector while also providing awareness seminars and training, creating environments conducive to reducing innovation costs.

Some previous studies have analyzed the factors involved in green innovation from the perspective of the manufacturing industry and environmental protection. The present study is a pioneer study to examine the factors involved in the adoption of open innovation in the food and beverage industry in Pakistan from the perspective of the post-COVID-19 era. For this purpose, the present study uses an integrated Fuzzy Delphi-ISM-MICMAC approach for the analysis.

Various publications have extensively documented the advantages of a circular economy in ensuring sustainability and limiting climate change. Despite academic records emphasising the need to adopt this business strategy, entrepreneurs in developing countries prefer linear economies. This reluctance is attributable to several factors, including insufficient infrastructure and technology, limited financial access, inadequate education systems and the prevalence of informal enterprises. Therefore, a thorough analysis of the underlying economic, political and social conditions is required to identify the drivers of circular economies (CEs) and their contribution to entrepreneurship in developing countries.

In this study, the authors first conducted a comprehensive quantitative literature review based on LangChain to identify the critical CE drivers from the social, technological and organisational perspectives. Based on the input from the expert panel of Iranian academic and industry professionals, the authors applied an integrated fuzzy interpretive structural modelling and cross-impact matrix multiplication approach to classification (Fuzzy-ISM-MICMAC) to investigate the chronology of entrepreneurial drivers.

Level-based model results reveal entrepreneurial drivers in developing nations and their interrelationships, specifically underlining the importance of supply chain factors and stakeholder preferences. Thus, the differences between the perception of the main drivers in developed and developing economies can be identified, with the former paying particular attention to legislative and financial factors. The study's findings contribute to conserving resources, reducing waste and adopting more sustainable corporate practices, thereby assisting developing countries in achieving development goals.

This study employs an innovative quantitative systematic literature review approach that relies on a large language model to identify the drivers of the CE. Furthermore, it adopts a systematic approach to examine the enablers of the CE rather than a narrow and individual perspective of the entrepreneurial drivers. The study employs the fuzzy ISM MICMAC technique to showcase the prioritisation of entrepreneurial prospects in emerging economies.

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.

The novel blockchain technology can be leveraged, owing to the growth in computing power and its widespread applications. This study aims to understand the challenges of adopting blockchain technology in the financial sector, organise them into a model and classify them for systematic address.

Interpretive Structural Modeling (ISM) has been carried out along with MICMAC (Matrice d’impacts croisés multiplication appliquée á un classment) analysis to hierarchically structure blockchain adoption problems and categorise the challenges into four classes-autonomous, dependent, linkage and independent for better addressing. The study also uses content analysis using NVivo software.

The digraph depicts the hierarchical challenge model. Vulnerability to financial crimes and glitches, privacy issues and geopolitical tensions due to cross-border transactions are the dependent variables. Complex architecture to comprehend, code and fix, the need for new financial intermediaries, complexity in auditing and the lack of unified governance and coordination among institutions and regulators are the independent variables. The digraph, which is also justified by the qualitative content analysis, is beneficial for stakeholders to systematically address the interdependent challenges associated with blockchain implementations in finance to foster its favourable adoption.

The challenges in the adoption of blockchain should be resolved to allow the implementation of this technology in various finance domains. This study enables organisations to carry out resource planning and systematically address these challenges to leverage the advantages of blockchain.

The results of the present study can help in promoting the proliferation of blockchain for faster, cost-effective, transparent and secure financial transactions and foster innovative and new business models for economic growth.

The development of technology has brought about significant changes in the financial sector. Blockchain is a technological advancement that aims to bring security and transparency to transactions. There has been no research leveraging ISM-MICMAC to hierarchically organise and classify the blockchain challenges in the financial sector, a critical one. The research also uses content analysis which is seldom found along with ISM-MICMAC.

Lean and green strategies are good options to increase the environmental and operational performance of manufacturing industries. The purpose of this paper is to identify the critical success factors (CSFs) to implement green lean practices (GLPs) in manufacturing industries through the review of the literature and to develop a conceptual model after analysing the fundamental facilitating factors by using ISM-MICMAC approach.

The methodology consists of identifying 12 critical success factors (CSFs) for the green lean implementation by reviewing the relevant available literature. The views of eight experts are valued for inter-relationships of these factors. ISM-MICMAC approach is used for analysing the relations between factors and to develop a conceptual model for green lean implementation.

Twelve CSFs are identified through a review of the literature to adopt GLPs in manufacturing industries. This paper has established the relationships among 12 identified CSFs using the ISM methodology. This paper analyses the dependence power and the driving power of identified CSFs with the help of MICMAC analysis. “Top management commitment” and “Government support” are the most significant CSFs implement GLPs successfully.

The ISM model presented in this study is based on expert opinions. But expert opinions may be biased as these are based on their own judgements. However, the proposed ISM based model needs statistically validations. The ISM model in the present study may be tested in real-world situations of manufacturing industries where results obtained may be different.

This study may provide a useful input for academicians and managers of industries to differentiate between independent and dependent CSFs and their mutual relationships which would help them to focus on those key CSFs that are most significant to implement GLPs.

A conceptual ISM model of identified CSFs shows the different levels of these CSFs. This model may help the manufacturer to implement the green-lean strategies. It may also support policymakers towards adopting GLPs. Arranging CSFs in a hierarchy and to categorise the CSFs into different levels with the help of ISM-MICMAC is an exclusive effort in the area of green lean engagement.

The premature closure of microbusinesses has become a prevalent issue that demands to be seriously addressed due to the major economic contribution it provides particularly to developing countries. The purpose of this paper is to establish and further analyze a set of critical failure factors (CFFs) that aid in the systematic decision-making and strategic management of stakeholders.

A comprehensive literature review is conducted to gather CFFs and an interpretative structural modeling with Matriced’ Impacts Croise’s Multiplication Appliquée a UN Classement (ISM-MICMAC) analysis is applied to investigate the structural relationships among CFFs by extracting its inherent characteristics according to its driving power and dependence power. In order to illustrate the methodology, a case study is conducted in Cebu, the Philippines.

It is interesting to note that inadequate government programs information is deemed the most crucial for stakeholders to tackle as its impact on the premature closure of microbusinesses is highly significant. Drawing from this key result, directions for potential strategies for getting evidence-based research into policy and practice in the micro-business sector in the Philippines, and other developing countries, are provided.

Lastly, the contribution of this work is two-fold and is aimed at policymakers and managers. For one, this study is the first to establish a set of CFFs specifically aimed at the level of microbusinesses, a seriously under-researched business sector, which can aid and influence domestic policymakers. For another, a framework that will facilitate business managers in carrying out organization’s strategy development process have been provided.

The purpose of this study is to explore and model the strategies to overcome the barriers of Lean Six Sigma (LSS) implementation in Indian small manufacturing enterprises (SMEs).

In this research, 31 strategies of LSS implementation in SMEs have been identified through detailed literature review and out of them, 13 are finalized using statistical tools like CIMTC and Importance-Index analysis. Moreover, the consistency of finalized strategies was examined through reliability test using SPSS software version 22. The finalized strategies are modelled through interpretive structural modelling (ISM) and classified them using MICMAC based on their driving and dependency power.

The key findings of this techno-managerial study are identification and modelling of 13 strategies to overcome adoption challenges of LSS in context of Indian SMEs. The usage of ISM-MICMAC approach provides the guidance to industrialist consider the mutual interaction of strategies during planning and scheduling for LSS projects.

Due to human involvement and judgements, there may be chance of biasness and subjectivity during construction of self-interaction matrix. Also, the number of identified strategies to overcomes barriers of LSS adoption may vary by altering nature, scope and region of research.

Literature is full of studies regarding LSS barriers and its rankings. Also, few studies explored the solutions of LSS barriers and prioritized them. To the best of the authors’ knowledge, our study is very rare to witness which expose the strategies to overcome the barriers and frame the mutual interaction are per the driving and dependence power of strategies. The application of ISM-MICMAC approach suggests a roadmap for implementing LSS approach efficiently through considering developed ISM model of strategies in context of SMEs.

Today the role of industry 4.0 plays a very important role in enhancing any supply chain network, as the industry 4.0 supply chain uses Big Data and advanced analytics to inform the complete visibility. Latest data are available to bring clarity and support real-time decision-making in the entire supply chain that’s why adopting optimization techniques such as lean manufacturing and lean supply chain concept for enhancing the supply chain network of the organizations is a good idea and would benefit them in increasing their cost efficiency and productivity. The purpose of this work is to develop a technique, which may be useful for future researchers and managers to identify and classification of the significant lean supply chain enablers.

In this paper, the authors considered hybrid analytical hierarchy process to find the ranking of the identified lean supply chain enablers by calculating their weightage. Interpretive structural modeling (ISM) is applied to develop the structural interrelationship among various lean supply chain management enablers. Considering the results obtained from ISM the Matrices d'Impacts Croises Multiplication Appliqué a un Classement (MICMAC) analysis is done to identify the driving and dependence power of Lean Supply Chain Management Enablers (LSCMEs).

Further, the best results applying these methodologies could be used to analyze their inter-relationships for successful Lean supply chain management implementation in an organization. The authors developed an integrated model after the identification of 20 key LSCMEs, which is very helpful to identify and classify the important enablers by ISM methodology and explore the direct and indirect effects of each enabler by MICMAC analysis on the LSCM implementation. This will help organizations optimize their supply chain by selective control of lean enablers.

For lean manufacturing practitioners, the result of the study can be beneficial where the manufacturer is required to increase efficiency and reduce cost and wastage of resources in the lean manufacturing process, as well as in enhancing the supply chain.

This paper is the first research paper that considered firstly deep literature review of identified lean supply chain enablers and second developed structured modeling of various lean enablers of supply chain with the help of various methodologies.

Lean six sigma (LSS) has attained a prominent position in mature organizations but small- and medium-sized enterprises (SMEs) are struggling in the proper implementation of LSS in their core business. This study aims to make a comprehensive analysis of LSS implementation barriers in SMEs so that LSS execution can be much fluent in SMEs.

This research work is carried out based on investigation of LSS barriers through extensive literature review. For validating the identified barriers, a questionnaire survey was conducted, and out of 400 samples, 260 responses received back. The collected responses are analyzed statistically and found 16 significant barriers. The finalized barriers are modeled using interpretive structural modeling (ISM) and clustered them through matrice d’impacts croisés-multiplication appliquée a un classement (MICMAC) analysis. Furthermore, to check the consistency of results, ISM-MICMAC outcomes are validated through structural equation modeling (SEM).

The result reveals that 16 LSS implementation barriers are finalized through expert’s opinion and validated through statistical reliability test with Cronbach’s alpha value of 0.820. The ISM model reveals that the management relevant barriers are exhibiting the leading role to influence the implementation of LSS in SMEs. Moreover, the obtained results validated through SEM are found in good agreement.

During pairwise comparisons, there may be some prejudice and subjectivity as human judgments are engaged.

This study provides impetus to practitioners and consultant for the initiation of LSS in the business organization through tackling the LSS barriers as per their driving and dependence power.

In the past, limited studies had explored the LSS barriers, but a few studies analyzed the mutual relationship between barriers. No such study is reported in literature that validates the mutual interaction model of LSS barriers. Hence, this paper presents the original research work of identification and modeling of barriers associated with LSS implementation in SMEs through hybrid ISM-SEM approach.