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The paper aims to clarify the relationship of various enablers of supply chain (SC) management like lean enablers, agile enablers and leagile enablers. It proposes modeling the enablers to find the most appropriate strategy or methodology for determining the lean enabled SC agility.

The paper proposed the fuzzy SWARA-WASPAS methodology for determining the role of lean in enabling the SC agility. Also in continuation the AHP methodology is applied to find the priority weightage and ranking of leagile enablers, and a comparative analysis is done to select the best approach among the above two methodologies so that it would be beneficial for all the stakeholders.

The paper provides the investigation and identification of 28 lean enablers, 11 agile factors which are highly responsible to affect any SC specially focusing of automobile sector. Apart from above 9 leagile enablers were also identified in the paper. Finally, the comparative analysis has been done in the results obtained by two methodologies – AHP & fuzzy SWARA-WASPAS – to determine the lean enabled SC agility, and also to which strategy should be adopted by the organizations as per the customized requirement of their SC.

The research limitation is that in future, there may be more number of lean, agile and leagile enablers which may be explored by different researchers in their findings, which may vary the output result accordingly. Though the research implications focus on having an advantage and impact on all aspects whether it is social, economic or commercial, there is a possibility of exploration of new and better decision-making tools and approaches in future. Also, the researchers are encouraged to test the proposed propositions further by taking case study of any automobile manufacturing organizations for the validation of the results.

The paper includes implications for the development of a powerful interrelationships between lean enablers, agile enablers and leagile enablers, which will help organization and the managers to take decisions regarding selection of best strategy appropriate to them to enhance their SC. This will also help new researchers of the field to take help of the research findings for exploring new and better optimization tools and techniques in future.

The findings of the research work will definitely help society, as the successful implementation of the lean, agile or leagile strategies in their SC system will leads to an increase in their efficiency and productivity, which will ultimately results in huge advantage to all the stakeholders directly or indirectly connected with the organization. The productivity dynamics cycle will also improve which will lead to more benefits to all in the market and achieving higher living index with better living standards.

This paper fulfills an identified need to study the various enablers of lean, agile and leagile SC, as well as their interrelationships. Also there is a need to understand the importance and effect of lean in enabling the SC agility.

Blockchain technology (BCT) can play a vital role in manufacturing industries by providing visibility and real-time transparency. With BCT adoption, manufacturers can achieve higher productivity, better quality, flexibility and cost-effectiveness. The current study aims to prioritize the performance metrics and ranking of enablers that may influence the adoption of BCT in manufacturing industries through a hybrid framework.

Through an extensive literature review, 4 major criteria with 26 enablers were identified. Pythagorean fuzzy analytical hierarchy process (AHP) method was used to compute the weights of the enablers and the Pythagorean fuzzy combined compromise solution (Co-Co-So) method was used to prioritize the 17-performance metrics. Sensitivity analysis was then carried out to check the robustness of the developed framework.

According to the results, data security enablers were the most significant among the major criteria, followed by technology-oriented enablers, sustainability and human resources and quality-related enablers. Further, the ranking of performance metrics shows that data hacking complaints per year, data storage capacity and number of advanced technologies available for BCT are the top three important performance metrics. Framework robustness was confirmed by sensitivity analysis.

The developed framework will contribute to understanding and simplifying the BCT implementation process in manufacturing industries to a significant level. Practitioners and managers may use the developed framework to facilitate BCT adoption and evaluate the performance of the manufacturing system.

This study can be considered as the first attempt to the best of the author’s knowledge as no such hybrid framework combining enablers and performance indicators was developed earlier.

The objectives of this study are as follows: RO1: to determine the key enablers that encourage the adoption of sustainable practices; RO2: to create a structural relationship model between the enablers that have been discovered and RO3: to use dependence and driving power to classify and analyse these factors.

In total, 11 variables were extracted through systematic literature review and experts opinion, and a group interview with more than 15 experts who have an experience of more than 10 years in academics was conducted. Generally odd in numbers, they presented each pair of variables and took their opinion. Using “Interpretative Structural Modelling” and “Cross-Impact Multiplication Applied to Classification” (ISM MICMAC) analysis, a model describing the structural relationship between these factors has been formulated to know the conceptual framework.

The study shows that the digital payment and waste treatment as the linkage or mediating variables. Top management commitment (TMC), regulatory framework and transparency are the drivers or independent variables. Green logistics, sustainable packaging and production are the dependent variables. Further, the resulting hierarchy and contextual linkages among variables shed light on key dimensions for decision-making. Green logistics, sustainable packaging and production are interconnected, playing a significant role, in the framework and influenced by the lower level variables. Transparency should be given due consideration to ensure sustainable competitive advantage.

(1) Owing to a lack of time and resources, the researchers have been able to explore only limited variables; more factors or enablers can be taken in future for further research. (2) Money constraint is also there. (3) One major limitation is that this research includes opinion from different experts which are dynamic in nature and keep on changing from time to time. (4) Primary research can also be done with the help of different software like partial least squares and structural equation modelling (PLS-SEM), covariance-based structural equation modelling (CB-SEM) and Statistical Package for the Social Sciences (SPSS) by taking same variables or merging new variables with the given variables of this paper. (5) With the help of this paper, the author tried to give an overview of some important enablers which are helpful in sustainability. Given a time in future, more research can be done by taking different sectors or a specific sector.

Findings are helpful for policymakers about effective strategies for promoting sustainability. They provide evidence-based insights into the potential impact of policy interventions and help shape the development of environmental regulations and initiatives. Sustainability is a global issue. Thus, this research paper contributes to international discussions and collaborations on environmental conservation and sustainable development goals (SDGs). They may influence diplomatic efforts to address transnational environmental challenges. Companies can use research findings to improve their sustainability practices and develop environmentally friendly products and services. Understanding sustainability enablers can help businesses reduce their ecological footprint while remaining economically viable. Research on sustainability enablers often involves exploring new technologies and innovations. Practical implications include the development and adoption of renewable energy sources, waste reduction techniques and sustainable agricultural practices. Sustainable communities rely on a range of enablers, from renewable energy infrastructure to local governance structures. Research informs community development efforts by identifying best practices and effective strategies for building resilient, environmentally friendly neighbourhood.

This research paper contributes to raising awareness about sustainability issues among the public. It also provides insights into the importance of sustainable practices and their impacts on society. Sustainability enablers can influence individual and collective behaviour, and they may encourage people to adopt more sustainable lifestyles and consumption habits. Sustainability research often addresses issues of equity and social justice. Understanding the enablers of sustainability can help identify strategies to ensure that sustainable practices benefit all segments of society, including marginalized communities.

This research paper endeavour to identify key sustainability development enablers (SDEs) by consolidating numerous factors within a single study. While several research papers have explored various sustainability enablers separately, no previous study has delved into their interactions. Furthermore, there is a dearth of research on classifying enablers based on the fuzzy MICMAC analysis. The ISM-based model presented here serves as a valuable resource for both practitioners and academics, aiding in their comprehension of the framework of relationships.

India’s rapid economic growth has triggered a significant transformation in its logistics sector, fueled by comprehensive reforms and digital initiatives outlined in the National Logistics Policy. Smart warehouses, equipped with cutting-edge technologies such as IoT, AI and automation, have taken center stage in this evolution. They play a pivotal role in India’s digital journey, revolutionizing supply chains, reducing costs and boosting productivity. This AI-driven transformation, in alignment with the “Digital India” campaign, positions India as a global logistics leader poised for success in the industry 4.0 era. In this context, this study highlights the significance of smart warehouses and their enablers in the broader context of supply chain and logistics.

This paper utilized the ISM technique to suggest a multi-tiered model for smart warehouse ecosystem enablers in India. Enablers are also graphically categorized by their influence and dependence via MICMAC analysis.

The study not only identifies the 17 key enablers fostering a viable ecosystem for smart warehouses in India but also categorizes them as linkage, autonomous, dependent and independent enablers.

This research provides valuable insights for practitioners aiming to enhance technological infrastructure, reduce costs, minimize wastage and enhance productivity. Moreover, it addresses critical academic and research gaps contributing to the advancement of knowledge in this domain, thus paving the way forward for more research and learning in the field of smart warehouses.

The qualitative modeling is done by collecting experts' opinions using the ISM technique solicits substantial value to this research.

Strategic integration of enablers and the realization of drone delivery benefits emerge as essential strategies for business organizations to enhance operational efficiency and stay competitive in last-mile logistics. This paper aims to explore the benefits of drone-based last-mile delivery in the Indian logistic sector by providing a framework for ranking drone delivery benefits (DDBs) due to the adoption of its enablers.

This study proposes a novel hybrid framework applied in the Indian logistic sector by integrating a sentence boundary extraction algorithm for extracting benefits from literature, a spherical fuzzy analytical hierarchy process (SF-AHP) for evaluating primary enablers, unsupervised fuzzy C-means clustering (FCM) for clustering benefits and a spherical combined compromised solution (SF-CoCoSo) for ranking benefits with respect to primary enablers.

The results reveal that technological and infrastructure enablers (TIE), government and legislation enablers (GLE) and operational and service quality enablers (OSE) are the most significant enablers for drone implementation in logistics. Top-ranked benefits increase the efficiency of last-mile delivery (DDB10), foster supply chain management and logistic sustainability (DDB16) and increase delivery access to rural area and vulnerable people (DDB17).

This research assists scholars, entrepreneurs and policymakers in the sustainable deployment of drone delivery in the logistics sector. This study facilitates the use of drones in delivery services and provides a foundation for all stakeholders in logistics.

The assessments involve considering judgment from a highly knowledgeable and experienced group in India, characterized by a large volume of inputs and a high level of expertise.

Agile new product development (ANPD) attracts researchers and practitioners by its ability to rapidly reconfigure products and related processes to meet the needs of emerging markets. To increase ANPD adoption, this study aims to identify ANPD enablers (ANPDEs) and create a structural framework that practitioners can use as a quick reference.

Initially, a comprehensive literature review is conducted to identify ANPDEs, and a structural framework is developed in consultation with an expert panel using a hybrid robust best–worst method interpretive structural modeling (ISM). During the ISM process, the interactions between the ANPDEs are investigated. The ISM result is used as input for fuzzy Matrice d’Impacts croises-multiplication appliqúean classment means cross-impact matrix multiplication applied to classification (MICMAC) analysis to investigate enablers that are both strong drivers and highly dependent.

The study’s findings show that four ANPDEs are in the low-intensity cluster and thus are excluded during the structural frame development. ISM output shows that “Strong commitment to NPD/top management support,” “Availability of resources,” “Supplier commitment/capability” and “Systematic project planning” are the important ANPDEs. Based on their driving and dependence power, the clusters formed during the fuzzy MICMAC approach show that 16 ANPDEs appear in the dependent zone, one ANPDE in the linkage zone and 14 ANPDEs in the driving zone.

This research has intense functional consequences for researchers and practitioners within the industry. Industry professionals require a conservative focus on the established ANPDEs during ANPD adoption. Management has to carefully prepare a course of action to avoid any flop during ANPD adoption.

The framework established is a one-of-a-kind study that provides an integrated impression of important ANPDEs. The authors hope that the suggested structural framework will serve as a blueprint for scholars working in the ANPD domain and will aid in its adoption.

This study aims to analyze and understand mutual relationships between lean and agile enabling factors in the context of the construction domain and put forth the most driving and dependent enablers for a hybrid lean–agile system (HLAS).

A threefold research flow is adopted. First, the content analysis of literature stemmed from the identification of preliminary enablers (n = 26). Second, a questionnaire survey (n = 101) is administered to downsize enablers to ten using the relative importance index. Further, in the third phase, interpretive structural modeling (ISM) and the cross-impact matrix multiplication applied to classification analysis were performed amid the ten key enablers through pairwise interactions from subject matter experts (n = 19). Hierarchical representation of enablers has been presented, which facilitates a conceptual model for application in the construction industry.

The ISM model demonstrates a three leveled classification structure that showcases direct and transitive relationships among various enablers. “Use of project management tools” is the driving enabler, followed by “collaborative and common data platform working” and “institution of team training” are critical enablers to HLAS adoption.

A structured way of identification of interdependent among lean–agile is a vital unique contribution to this study. The results serve as a knowledge base for practical adoption of HLAS and may prove to be influential in developing a framework for easier adoption in developing countries.

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.

Although it is commonly agreed that prescriptive analytics can benefit organizations by enabling better decision-making, the deployment of prescriptive analytics tools can be challenging. Previous studies have primarily focused on methodological issues rather than the organizational deployment of analytics. However, successful deployment is key to achieving the intended benefits of prescriptive analytics tools. Therefore, this study aims to identify the enablers of successful deployment of prescriptive analytics.

The authors examine the enablers for the successful deployment of prescriptive analytics through five organizational case studies. To provide a comprehensive view of the deployment process, each case includes interviews with users, managers and top management.

The findings suggest the key enablers for successful analytics deployment are strong leadership and management support, sufficient resources, user participation in development and a common dialogue between users, managers and top management. However, contrary to the existing literature, the authors found little evidence of external pressures to develop and deploy analytics. Importantly, the success of deployment in each case was related to the similarity with which different actors within the organization viewed the deployment process. Furthermore, end users tended to highlight user participation, skills and training, whereas managers and top management placed greater emphasis on the importance of organizational changes.

The results will help practitioners ensure that key enablers are in place to increase the likelihood of the successful deployment of prescriptive analytics.

This study aims to investigate the most effective enablers and tools for inhabitants’ knowledge acquisition in public policymaking organizations.

Based on a literature review, the study summarized 51 individual, organizational, technological and inhabitant-related enablers of inhabitants’ knowledge acquisition, as well as 36 technological and social tools. The study assessed the effectiveness of these enablers and tools based on two rounds of a Delphi study targeting 31 policymakers in the Gulf Cooperation Council (GCC) countries. Kendall’s coefficient of concordance was assessed to determine consensus among participating policymakers.

The findings indicate that the most effective enablers were inhabitants’ willingness to get involved, information technology (IT) infrastructure, IT staff support and inhabitants’ trust in policymakers. Additionally, the study found that the most effective tools for inhabitants’ knowledge acquisition included meetings, interviews, social media and field visits.

Inhabitants’ knowledge acquisition is an important social and economic force that will drive change in any society by enabling the implementation of innovative ideas and practices. A review of the relevant research shows that despite the usability of inhabitants’ knowledge, the degree to which inhabitants’ knowledge acquisition is integrated into the public policymaking system remains unclear. This study of inhabitants’ knowledge acquisition from the policymaker perspective provides a better understanding of the inhabitants’ knowledge acquisition process in policymaking organizations.