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The purpose of this study is to examine variables and their relationships that hinder socially responsible behaviours in the supply chain of small- and medium-sized enterprises (SMEs) in the Gulf Cooperation Council (GCC). countries.

The study uses the mixed-method approach that includes the survey method and soft mathematical modelling. Empirical data were collected from 130 SMEs and their suppliers based in Qatar and Oman. Furthermore, to understand the barriers and their interrelationships, interpretive structural modelling approach is applied.

The results of empirical study reveal lack of coherence among SMEs and their suppliers in prioritising social responsibility issues in their supply chain. The hierarchy-based model reveals that shortages of incentive, short-term objectives, the lack of cooperation and willingness among supply chain partners, constraints (financial, managerial and technological) and the pressure from customers were the independent barriers and have strong driving power.

The findings of this study are expected to provide an insight to further improve and promote socially responsible supply chain in emerging economies in Gulf region. Future research could compare the socially responsible activities of SMEs from different Gulf countries and expand the understanding of the barriers that outline the responses of suppliers situated in different Gulf economies.

The results contribute to the field of supply chain sustainability as the first academic attempt to shed light on how SMEs in GCC are dealing with supply chain social responsibility issues and one of the few in the emerging economy perspective that probes the key role of barriers to improve the socially responsible behaviour of Gulf-based SMEs.

Recent years have witnessed a significant rise in Indian healthcare establishments (HCEs) which indicate that there is a constant need to improve the healthcare quality services through the adoption and implementation of TQM enablers. The purpose of this paper is to identify such enablers and then propose a ranking model for TQM implementation in Indian HCEs for improved performance.

The study identifies 20 TQM enablers through comprehensive literature survey and expert’s opinion, and classifies them into five main categories. The prominence of these enablers is established using a recently developed novel multi-criteria decision making (MCDM) method, i.e. best-worst method (BWM). The importance of the various main category and sub-category enablers is decided on the basis of their weights which are determined by the BWM. In comparison to other MCDM methods, such as analytical hierarchy process, BWM requires relatively lesser comparison data and also provides consistent comparisons which results in both optimal and reliable weights of the enablers considered in this paper. Further, a sensitivity analysis is also carried out to ensure that the ranking (based on the optimal weights) of the various enablers is reliable and robust.

The results of this study reveal that out of five main category enablers, the “leadership-based enablers (E1)” and the “continuous improvement based enablers (E5)” are the most and the least important enablers, respectively. Similarly, among the 20 sub-category enablers, “quality leadership and role of physicians (E14)” and “performing regular survey of customer satisfaction and quality audit (E52)” are the most and the least dominating sub-category enablers, respectively.

This study does not explore the interrelationship between the various TQM enablers and also does not evaluate performance of the various HCEs based on the weights of the enablers.

The priority of the TQM enablers determined in this paper enables decision makers to understand their influence on successful implementation of the TQM principles and policies in HCEs leading to an overall improvement in the system’s performance.

This study identifies the various TQM enablers in HCEs and categorizes them into five main categories and ranks them using the BWM. The findings of this research are quite useful for management of the HCEs to properly understand the relative importance of these enablers so that managers can formulate an effective and efficient strategy for their easy and smooth implementation which is necessary for continuous improvement.

In recent years, sustainable issues have gained increasing importance in the higher education sector across the country. To remain competitive, higher education institutions (HEIs) have to engage themselves in providing world-class opportunities for higher education and research so that the beneficiaries may not be at a disadvantage in the international level. However, many HEIs still encounter barriers that can affect their growth. The purpose of this study is to identify and interpret the most significant barriers affecting the growth of HEIs in India and understand the mutual interactions and interdependence among them.

In this study, 12 barriers affecting the growth of HEIs in India were identified and sorted by literature review, and these were validated through discussion with experts. Contextual relationships were drawn between them during brainstorming sessions. A hierarchical, seven-level structural model of these barriers affecting the growth of HEIs was developed by utilizing the total interpretive structural modeling (TISM) approach.

The results of this study showed “lack of climate change research” as the topmost outcome of the model having the highest dependence and lowest driving power. “Facilitator domination over academic experts” occupied the bottom-level input, compared to other barriers of the model, with highest driving power and lowest dependence. Further, Matrice d'Impacts Croisés – Multiplication Appliquée à un Classement (MICMAC) analysis was also performed to categorize the identified barriers for better understanding. Under MICMAC analysis, five barriers were categorized as driver barriers, four barriers as dependent barriers and the rest as linkage barriers, while none as autonomous. A TISM-based model that partitioned the barriers into different levels was developed, showcasing direct and important transitive relations.

The TISM-based model developed in this study may provide a more realistic approach to the problems faced by decision-makers, academicians and top managers in the growth of HEIs in India. Thus, it will provide a roadmap to focus on the most influential barriers and reduce or eliminate them.

The present study identified major barriers that when dealt with can help overcome the effect of other barriers preventing the growth of HEIs in India. It also introduces a model to identify and manage the barriers by understanding the effectiveness of each barrier and minimizing the overall effect in Indian HEIs. Moreover, the analysis of interdependence and interactions studied among these barriers may also help decision-makers, academicians and top managers to find deeper insights, prioritize and rectify them, to re-establish the growth of HEIs and gain a competitive advantage.

The purpose of this paper is to identify the potential barriers of telecom services and develop relationships among them using interpretive structural modeling (ISM) in the Indian telecom sector. Further, this paper intends to find the driving and dependence powers of telecom barriers, using MICMAC (Matriced' Impacts Croise′s Multiplication Applique′ea′un Classement) analysis.

A group of experts from telecom sector and academia was consulted and the ISM was used to develop the contextual relationship among identified barriers of telecom services. The results of ISM are used as an input to MICMAC analysis, to further classify identified barriers based on their driving and dependence powers.

This paper has identified 11 barriers of telecom services from the literature review and opinion of experts, and a contextual relationship model was developed using the ISM technique. The paper further studied barriers based on their driving and dependence powers using MICMAC analysis that classifies them into four clusters. The results identified the barriers such as “lack of adequate investment in infrastructure expansion”, “interference of private operators”, “legal and regulatory issues”, “lack of maintenance culture” and “lack of financial resources and high cost” as strategic-level barriers that, if dealt with carefully, can help overcome the effect of other barriers preventing the effective performance of the Indian telecom sector.

Although, there are a number of barriers that affect the performance of telecom services, existing theories, models and frameworks have focused on identification of factors, their implementation and benefits, and thus, these theories lack a holistic view in understanding those barriers which hinder the performance of the telecom sector. Top-managers and policymakers need to be more concerned about these barriers so that the performance of the Indian telecom sector could be improved.

A thorough literature review has revealed that no such study has been undertaken that provides any clear understanding of the barriers of telecom services, linkages between them and hierarchical relationships among the barriers.

Typically, adoption of sustainability in organizations are often done in an unstructured way without the consideration of other partners in the supply chain. The purpose of this paper is to suggest a coherent plan to improve sustainability in the supply chains utilizing ISO standards for environment and social responsibility.

This paper draws on literature on ISO14000 and ISO26000 to derive a set of variables applicable to supply chains, which are then prioritized for real organizations utilizing analytic hierarchy process.

The findings highlight that not all the variables of environmental, social and economic responsibility are equally important. Besides, the work reported in this paper justifies the application of multi-criteria decision-making (AHP) to prioritize elements of sustainability in context supply chains. The suggested method is illustrated using inputs from large manufacturing companies in Qatar.

ISO14000 and ISO26000 are well known standards; however, there was no effort to integrate these standards to improve sustainability in supply chains. The suggested methodology provides invaluable help to the managers to implement sustainability in a coherent manner across the supply chain.

The research contributes to the extant literature by proposing a new methodology based on the integration of three-approaches: Analytic Hierarchy Process, ISO14000 and ISO26000 systems.

The primary aim of this research is to conduct a comprehensive investigation into the essential elements of Industry 4.0 implementation within Indian Micro, Small and Medium Enterprises (MSMEs). Acknowledging the MSME sector as a crucial contributor to the Indian economy and industrial development, the study delves into the assessment of MSMEs based on Industry 4.0 components. Additionally, it explores the profound impact of these components on various performance factors, including organizational performance, sustainability performance and human-related aspects. The paper further ranks these identified components based on their significance within the MSME sector.

Employing a combination of methodological approaches, the research utilizes the Best and Worst Method (BWM), Data Envelopment Analysis (DEA) and calculates the Maturity Index for Industry 4.0 components. The BWM, a recognized multi-criteria decision-making technique, is initially applied to determine the weights and rankings of the identified components. Furthermore, the study evaluates 30 MSMEs, spanning manufacturing and service sectors, through the DEA approach. Industry 4.0 components are treated as inputs, and performance factors serve as outputs. Data for the analysis are collected through questionnaires distributed to the selected MSMEs. Lastly, the Maturity Index for MSMEs is also calculated.

From the result of the BWM method “assistive manufacturing” was found to be a highly weighted key component of Industry 4.0. From the DEA analysis out of 30 MSMEs 13 SMEs were highlighted as being efficient, whereas 17 MSMEs were judged to be inefficient. Furthermore, from the maturity index calculation, overall Maturity Index was determined to be 3.33 which shows that Industry 4.0 is in its initial stage of implementation, but it has gained pace in its implementation.

The research contributes to practical implications by offering a more accurate assessment of the state of Industry 4.0 implementation within MSMEs. The introduced maturity index proves instrumental in pinpointing key components that have received inadequate attention. This information is crucial for MSME managers and policymakers, guiding them in allocating resources effectively, addressing areas requiring attention and facilitating progress in the implementation of Industry 4.0. The study serves as a valuable tool for MSMEs to enhance their overall operational efficiency.

The research’s originality lies in its application of a comprehensive approach, combining BWM, DEA and the introduction of a maturity index for Industry 4.0 components in the MSME context. By employing these methodologies, the study not only identifies influential components but also provides a nuanced understanding of their relative significance. The research contributes significantly to the broader understanding of Industry 4.0 adoption, particularly, in the vital MSME sector within the Indian context. The findings are valuable for researchers, practitioners and policymakers seeking insights into improving the efficiency and effectiveness of MSMEs in the era of Industry 4.0.

This review paper aims to explore and investigate the Quality 4.0 current knowledge, emerging areas, and trends available in the literature and provide insights for future research directions. The bibliometric analysis determines the most prominent journals, authors, countries, articles, and themes. The Citation and PageRank analysis identifies the most influential and prestigious articles. The author's keyword analysis identifies the research theme, patterns, and trends within a particular area of research.

This study utilised the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analysis) declaration as a review protocol, and the data is retrieved accordingly. Therefore, 104 articles from Scopus and 28 from Web of Science were combined in R-Environment, and 25 duplicates were removed using RStudio. Finally, 107 papers were selected for further analysis. After the abstract level screening, the study reviewed 99 articles bibliographically published in peer-reviewed journals from prominent academic databases Scopus and WoS between 2011 to April 2023. We used the VOSviewer software tool for analysing bibliometric networks that allow the construction, visualisation, and exploration of maps based on any form of network data.

The review identified emerging themes: artificial intelligence, digitalization, sustainability, root cause analysis, topic modelling, and digital voice-of-customers. To establish the intellectual structure of the field and identify gaps, co-citation and content analysis were used. The content of 49 papers in the identified clusters was then carefully analysed. The four primary themes are the relationship of Quality 4.0 with Industry 4.0, the conceptualization of Quality 4.0, recommendations for the new Quality 4.0 model, and the impact of Quality 4.0. The findings provide an excellent foundation for future research in this field for policymakers, managers, practitioners, and academia.

This is the first systematic literature review-cum-bibliometric analysis on quality 4.0 that covers the field comprehensively. Based on the present review, the paper proposes six possible future research directions to investigate.

In a globalized environment, small and medium enterprises (SMEs) are facing formidable challenges. Not only do they have to keep up their profitability, but there is also a pressure from various stakeholders to add to their environmental and quality performance .The solution obviously lies in continuously adopting and improving upon lean-green practices in their operations. This work aims at identifying, classifying and building up a duly tested robust ranked-order model of such “enablers”, related to lean-green practices, that puts them (the enablers) in an order of being the most significant to being the least significant further to be accorded the same or similar weight in strategy formulation and implementation stage by Indian SMEs for enhancing their overall organizational performance.

The study identifies 20 enablers (12 lean and 08 green manufacturing enablers) through extensive literature review and experts' opinion survey and classifies them into three main categories. The ranking and significance of each of the main and subcategory enablers is evaluated according to its weight which is determined by the best-worst method (BWM) approach, one of the novel multi-criteria decision-making (MCDM) methods. Further, the results have been drawn after running accuracy check of the rankings (based upon optimal weights) and testing the robustness of the ranked-order model through sensitivity analysis.

The results of this study reveal that out of the three main category enablers, “operational performance enablers (E1)” and “quality performance enablers (E3)” are the most and the least significant enablers, while in the group of 20 subcategory enablers, “Kaizen (E17)” and “environment emission control (E28)” are the most and the least significant subcategory enablers, respectively.

The prioritization model or ranked-order model of the lean-green manufacturing enablers proposed through this study may serve as a standard model to managers to help them decide and allocate their efforts and resources accordingly in managing their operations. This will also help them adopt high-ranking lean-green manufacturing enablers in their firms and benchmark and standardize their existing practices accordingly, leading to greater competitive advantage.

The study identifies various green-lean manufacturing enablers in SMEs, classifies them into three main categories and ranks them using BWM approach. The findings of this study should be extremely relevant to managers, manufacturing engineers and practitioners in Indian SMEs from the perspective of developing deeper appreciation of these enablers as per their relative ranked importance to further formulating an effective and efficient strategy for their implementation resulting in optimal results.

The purpose of this study is to identify and rank total quality management (TQM) enablers and information technology (IT) resources to provide a reliable and valid measurement instrument for evaluation in Indian information and communications technology (ICT) organizations.

Based on a literature review of TQM enablers and IT resources, 17 factors are identified, of which, 9 are TQM enablers and 8 are IT resources. The empirical data, retrieved from 801 ICT organizations, is tested by descriptive analysis and factor analysis (FA). FA is used to ensure that items in each scale sufficiently reflect the scope of each factor.

This paper has developed an instrument that can be used to evaluate items to implement TQM enablers and IT resources. The instrument identifies 17 reliable and valid factors, out of which 16 are input factors, while 1 is an outcome factor.

This instrument will provide a practical understanding to enable the monitoring of TQM enabler and IT resource activities in ICT organizations. Along with this, these instruments will help to build models related to constructs that will further achievement of customer satisfaction (CS).

This paper presents an instrument which validates the different items of TQM enablers and IT resources. It also shows the relationship between the two in terms of CS.

Despite various governmental efforts, female entrepreneurship in the UAE is still not a popular option among women. The purpose of this study is to identify the enablers to female entrepreneurship and to establish relationships among them.

This research uses a two-phased approach. In the first-phase, an empirical study on female entrepreneurs was conducted to find out the most important enablers from among a set of variables identified through a comprehensive literature review. In the second-phase, using interpretive structural modeling, a hierarchy-based model is developed among the most important enablers. Further, these enablers are also classified depending on their driving power and dependence.

Survey results indicate that female entrepreneurs consider enablers as the driving force in creating an entrepreneurial culture. Further, the hierarchy-based model developed in this research helps to identify variables that are of strategic importance and require utmost attention.

The framework presented in this study can be used effectively by the policymakers to develop suitable strategies for improving entrepreneurial behavior among women in the United Arab Emirates.

The novelty of this approach is the integration of questionnaire and interpretive structural modeling methodology and classifying enablers in four clusters. The research provides useful insights about the perception of female entrepreneurs about the entrepreneurial culture in the United Arab Emirates, and a relationship model that may serve as a decision tool for improving female entrepreneurship.