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The purpose of this study is to determine the enablers of the quality of work life (QWL) of employees working in the Garment industries.

The study was carried out in a fivefold step. In the first step, the enablers of QWL were identified through an exhaustive literature survey, in the second step identified vital few components through Pareto analysis. Then the third step was followed by exploratory factor analysis (EFA) to further, to identify the precise components and validate the same using confirmatory factor analysis in fourth step. The final step included interpretive structural modeling and Cross-Impact Matrix Multiplication Applied to Classification analysis to model the validated components and determine the interrelationships and linkages.

Predominant QWL enablers of employees working in the garment industries are training and development, satisfaction in job, compensation and rewards, relation and co-operation, grievance handling, work environment, job nature, job security and facilities.

In this study, the interpretive structural model is designed based on the opinion of the experts who are working in the garment industry considering the responses from employees in garment sectors. The framework can be extended further to the other sectors.

In future, the researchers in QWL may develop a model to quantify the level of employees’ QWL who are working in different sectors. Enablers of QWL are essential, and based on this further statistical analysis can be carried out. This study will provide limelight to the researchers in choosing the valid and reliable set of enablers for the empirical studies. Organizations can get benefit by implementing the outcome of this research for the enhancement of the QWL of employees.

The study was carried out in 133 garment industries where 851 workers constituted the final valid responses that were considered for analysis. The outcomes from the study help administrators, policy and decision-takers in taking decisions to enhance QWL.

Small and medium enterprises (SMEs) significantly contribute to economic growth, development, exports and employment of the nations. To maintain competitiveness in today's market, SMEs must explore and identify enablers to enhance their digital transformation process. This paper aims to shed light on some essential enablers SMEs can use to implement digital resilience successfully.

The quantitative assessment and validation of the enablers have been done using powerful and novel techniques, namely, the Delphi method, “fuzzy interpretive structural modelling” (F-ISM) method and “cross-impact matrix multiplication applied to classification (MICMAC)” analysis. The F-ISM model is developed using the information drawn from digital transformation experts and practitioners involved in the digital transformation process for SMEs. Furthermore, the F-ISM model provides four paths to complete the pathway to digital resilience.

The F-ISM and MICMAC analysis revealed four ways to enhance the digital transformation process in SMEs. These enterprises can utilise these path assessments to become digitally resilient in the present dynamic scenario. To enhance digital resilience among SMEs, the study identified ten enablers. Among these, “management competencies” was the most crucial, followed by “knowledge management” and “monitoring and controlling”.

The present study is limited in that the data used to develop the models were collected from a small group of industry experts whose opinions may not exhibit the comprehensive views of the population.

The findings can help SMEs enhance the digital transformation process by taking up different pathways to integrate the various enablers of digital resilience depending on resource availability.

The results indicate the most critical and influential enablers for enhancing digital resilience among SMEs. This research can be valuable to academicians, industry practitioners and researchers for guiding their future work.

This study intends to identify, prioritize and rank the enablers for organizational work–family balance (WFB) planning specifically for working sole mothers by employing the fuzzy Delphi and analytical hierarchy process (AHP) method.

This paper utilizes the integrated methodology in two steps. Initially, a broad literature review and the fuzzy Delphi method have been utilized to recognize and validate the key WFB enablers. Afterward, the AHP approach has been applied to prioritize and detect the relative importance and rank of identified WFB enablers.

This paper has identified 9 WFB sub-enablers for working sole mothers under work, family and personal enablers. The work enablers obtain the first rank based on the highest importance weight followed by personal and family enablers. The findings indicate the top five sub-enablers: organizational work–family culture, work from arrangements, emotional intelligence, flexible work schedule and family support.

The findings offer prioritized areas of concern to the human resource managers and administrators to manage these WFB enablers as per their priority in the direction to formulate the organizational WFB policy-planning specifically for sole mothers.

The prioritized WFB enablers amongst working sole mothers may help sole mothers to manage their social, family and work-related roles in a more effective manner.

Based on the best of the authors' considerations, this study firstly incorporates the fuzzy Delphi-AHP method to prioritize and rank the WFB enablers to organizational WFB planning for sole mothers.

Organisations and industries are often looking for technologies that can accomplish multiple tasks, providing economic benefits and an edge over their competitors. In this context, drones have the potential to change many industries by making operations more efficient, safer and more economic. Therefore, this study investigates the use of drones as the next step in smart/digital warehouse management to determine their socio-economic benefits.

The study identifies various enablers impacting drone applications to improve inventory management, intra-logistics, inspections and surveillance in smart warehouses through a literature review, a test of concordance and the fuzzy Delphi method. Further, the graph theory matrix approach (GTMA) method was applied to ranking the enablers of drone application in smart/digital warehouses. In the subsequent phase, researchers investigated the relation between the drone application's performance and the enablers of drone adoption using logistic regression analysis under the TOE framework.

This study identifies inventory man agement, intra-logistics, inspections and surveillance are three major applications of drones in the smart warehousing. Further, nine enablers are identified for the adoption of drone in warehouse management. The findings suggest that operational effectiveness, compatibility of drone integration and quality/value offered are the most impactful enablers of drone adoption in warehouses. The logistic regression findings are useful for warehouse managers who are planning to adopt drones in a warehouse for efficient operations.

This study identifies the enablers of drone adoption in the smart and digital warehouse through the literature review and fuzzy Delphi. Therefore, some enablers may be overlooked during the identification process. In addition to this, the analysis is based on the opinion of the expert which might be influenced by their field of expertise.

By considering technology-organisation-environment (TOE) framework warehousing companies identify the opportunities and challenges associated with using drones in a smart warehouse and develop strategies to integrate drones into their operations effectively.

This study proposes a TOE-based framework for the adoption of drones in warehouse management to improve the three prominent warehouse functions inventory management, intra-logistics, inspections and surveillance using the mixed-method.

Researchers have worked diligently to find the factors that foster organizational trust, but the causal relationships between the enablers of organizational trust have remained unexplored. Therefore, the purpose of this study is to map and analyze the causal link structures of organizational trust enablers.

Data were gathered from employees working in Indian manufacturing organizations. The decision-making trial and evaluation laboratory (DEMATEL) approach was used to test the cause-and-effect linkages among organizational trust enablers.

The empirical evidence shows that 6 out of 14 enablers are causal, namely, organizational justice, person–organization fit, corporate citizenship, positive leadership behavior, relational quality and job satisfaction.

The findings of the study offer a deeper understanding of identified enablers of organizational trust and their linkages with other outcome enablers. Furthermore, the findings provided in the current study will assist top authorities, practitioners and HR managers in focusing on the select causal organizational trust enablers. In addition, the ranking established in this study will help organizations in directing their efforts and resources toward the few select enablers that help to facilitate other consequent enablers of organizational trust. In other words, the results of the study would help in gaining the advantages of efficiency in fostering trust at work.

By providing the empirically valid causal framework of organizational trust enablers, the present study makes a novel contribution to the field. Also, the findings of this study would help organizational policymakers, HR managers and organizational behavior practitioners in developing a better understanding of inculcating trust at work. Furthermore, the use of these enablers will help to foster a trustworthy environment at work.

In the modern digital age technologies like Industry 4.0 has revolutionized the manufacturing sector. There are many economic and technological advantages of digitalization. Along with economic benefits, manufacturing enterprises especially small and medium enterprises (SMEs) need to take advantage of digitalization in strengthening their social performance. Observing the importance of social performance of Indian SMEs and availability of limited research in this direction, the current study has done a holistic analysis of social performance enablers.

A systematic literature review with a series of personal interviews of experts has been conducted to identify the enablers of social performance and supportive digital technologies. A fuzzy decision-making trial and evaluation laboratory (DEMATEL) approach has been applied to find the degree of influence and interrelation between enablers. Sensitivity analysis is also performed to validate the results obtained.

Authors observed that policies of corporate and social responsibility, support by top management, awareness of social performance issues, and ethical practices and collaboration amongst supply chain members are leading causing enablers of social performance. Preparedness for the uncertainty of pandemics, improved work conditions and ergonomics, green practices, improvement in global business and improved living standards of employees and their families are leading the effect group of enablers. Further authors also observed that social media, information and communication technologies (ICT), websites, smart surveillance, e-mails and cloud computing are few supportive digital technologies of social performance issues.

SMEs all over the globe are passing through a transition due to digitalization and influence of pandemics. The finding of current study highlights the importance of strategic management of social performance enablers. Since the research is very limited in the social performance area, especially in Indian SMEs, this study makes a notable contribution to the literature too.

Novelty of this study is that social performance enablers of Indian SMEs in the digital era have been analysed holistically. The content of this research is the original work of the authors and has not been submitted for any other publication.

This study aims to investigate the intellectual capital (IC) dynamics in entrepreneurial ecosystems (EEs) by conceptualizing EEs as systems whose purposes include the (re)generation of the intangible resources needed for effective entrepreneurship. The study proposes a taxonomy of the key enablers of IC and develops a model that captures the unfolding interdependencies across the enablers of explorative and exploitative human, relational and organizational capital in EEs.

The authors purposefully selected a successful EE around an entrepreneurial university in Latin America as empirical case. Specifically, they investigated the IC dynamics of the EE in the context of a series of internationally awarded hackathons and related activities organized at the ecosystem level over three years (2019–2021). The research leveraged participant observations, in-depth interviews with multiple EE actors and archival documents. For the data analysis, this study combined the Gioia method with an abductive approach.

First, the study identified 27 operationalizable enablers of IC at the EE level clustered into human, relational and organizational capital and further differentiated these enablers considering the explorative and exploitative facets of IC. Second, it determined that the dynamic interplay across IC enablers is critical for an EE to flourish and evolve adaptively. This study concludes that assessing IC enablers and their dynamics can aid the understanding, evaluation and management of EEs.

To the best of the authors’ knowledge, this study is the first to conceptualize EEs as systems whose purposes include creating the conditions for an effective interplay of explorative and exploitative IC at the system level. The resulting taxonomy of IC enablers provides formative constructs that will benefit both scholars and practitioners investigating the crucial role of intangible resources in EEs and guide managers, entrepreneurs and policymakers in their decision-making processes.

Drawing from boundary-spamming knowledge processes and knowledge-based theory, the purpose of this paper is to study enablers of the knowledge management (KM) process using robust multi-criteria decision-making (MCDM) tools like interpretive structural modeling (ISM) and decision-making trial and evaluation laboratory (DEMATEL) method.

Drawing on the knowledge-based view and through the detailed literature review among different KM success, eight enablers were identified. By using the ISM-DEMATEL approach, a systematic framework was designed, and further cause–effect relationship diagram visualized a causal relationship among the enablers.

The combined approach of ISM-DEMATEL showcase that “knowledge creation” and “knowledge capture” are essential enablers. These two identified enablers have considered being pillars for KM implementation. On the other side, knowledge organization, knowledge application are dependent enablers.

From a practical viewpoint, the findings of this research work enable the industry consultants to identify the most prominent driving enablers for KM implementation. Additionally, it provides a clue for the effective implementation of KM in a systematic approach.

The integrated method depending on the hierarchical model and cause–effect relationship between enablers of the KM process is a novel approach that opens a new research area in this domain. Moreover, this is the first-ever attempt to combine ISM along with DEMATEL to identify enablers of the KM process.

The vision of Industry 4.0 concept is to create smart factories that will change the current processes of production and manufacturing system using smart machines to produce smart and intelligent products. The main aim of this research is to explore the enablers with regard to Industry 4.0 application in manufacturing industry in India as the available literature shows that manufacturing sector is still doubtful about the implementation of Industry 4.0.

Seventeen enablers that can affect the adoption of Industry 4.0 in the manufacturing industry in India have been explored through an extensive review of available literature and viewpoints of industry and academic experts. Total Interpretive Structural Modelling methodology (TISM) has been used to evaluate the interrelationships among these factors. A TISM model has been developed to extract the key enablers influencing Industry 4.0 adoption.

The result shows that Internet facility from government at reduced price, financial support and continued specialized skills training are the major enablers as they have strong driving power.

Proper understanding of these enablers will help the managers and policymakers to explore the impact of each enabler on other enablers as well as the degree of relationships among them and to take concrete steps so that Industry 4.0 can be implemented successfully in the manufacturing sector in India.

This study is pioneer in exploring the enablers Industry 4.0 which is the most advanced concept that has the capability to change the future of Indian manufacturing sector if implemented judiciously and cautiously.

The purpose of this research paper is to study the enablers of Six Sigma and to establish relationship among them using interpretive structural modeling (ISM).

The research paper presents a blend of theoretical framework and practical applications. In the paper, 11 enablers of Six Sigma are identified from literature survey and experts' opinion and then these are validated by questionnaire survey in India. Finally, ISM is used to obtain structural relationship among these enablers of Six Sigma.

The ISM‐based model indicates that “effective top management leadership role”, “availability of funds” and “availability of expert training” are strategic requirements; “organizational culture”, “organizational infrastructure”, “quality maturity level of organization”, and “employees' adaptability and flexibility towards learning” are tactical requirements. “Statistical thinking”, “committed work force”, “reliable data gathering and retrieval system”, and “technical competence” are operational requirements for Six Sigma applications.

Enablers are the building blocks for deployment of Six Sigma. To know the key enablers and relationship among them can help many organizations to develop Six Sigma competences. It is one of the foremost attempts to model enablers of Six Sigma. The paper provides useful insights to the Six Sigma implementers, consultants, and researchers.