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This paper aims to estimate the bearing capacity of a surface strip and circular footings lying on layered sand using numerical limit analysis.

Lower and upper bound limit analysis, as well as finite elements and second-order conic programming (SOCP), are used in this analysis. The yield criterion of Mohr-Coulomb is used to model soil behavior. Using this technique, stringent lower and upper bounds on ultimate bearing capacity can be achieved by assuming an associated flow law.

The obtained results indicate that the exact collapse load is typically being bracketed to within 6% about a mean of both the bounds. The obtained results are compared with the existing literature wherever applicable.

To the best of the authors’ knowledge, no study has used lower and upper bound limit analysis, as well as finite elements and SOCP, to estimate the bearing capacity of a surface strip and circular footings lying on layered sand.

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.

The use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.

After an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.

The focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.

The country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.

The present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.

The quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.

This paper aims to quantify the trend of variables used for building a theoretical model with the help of analysing bibliometrics data of inventory management (IM) and Total Quality Management (TQM) practices and their effects on firm performance.

Scopus' research database and the Web of Science (WoS) (including Elsevier, Emerald Group Publishing, Taylor and Francis, Wiley, IEEE, Informs and SAGE) were used to find relevant articles. The articles, review papers and conference proceedings were screened from 1993 to 2021. The articles were analysed to explain the different types of IM practices, TQM practices and their effect on the firm's performance. Thematic analysis was done using a bibliometric package of “R” (Biblioshiny) and VOSviewer to identify the key trends, approaches and research agenda.

The research covered 28 years of publications and summarised 497 articles, review papers and conference papers. Researchers concluded that IM highly correlates with the inventory turnover ratio and has no relation to firm performance. Further, TQM positively affects firm performance, but integrating IM and TQM will be a research scope for future study as none of the researchers previously covered this.

Due to the systematic literature review (SLR) and Bibliometric review, the study is limited to the Scopus and WoS (including Elsevier, Emerald Group Publishing, Taylor and Francis, Wiley, IEEE, Informs and SAGE) databases.

Being the research on a bibliometric and systematic review, relating IM practices with TQM practices would be the novelty of this paper.

The study examined a wide range of proactive supply chain practices to demonstrate a cross-linkage among them and to understand their effects on both practitioners of previous decision-making models, frameworks, strategies and policies. Here, six supply chain practices are empirically evaluated based on 28 constructs to investigate a comprehensive model and confirm the connections for achieving performance and competence. The study presents a conceptual model and examines the influence of many crucial factors, i.e. supply chain collaboration, knowledge, information sharing, green human resources (GHR) management and lean-green (LG) practices on supply chain performance.

Structural equation modeling (SEM) examines the conceptual model and allied relationship. A sample of 175 respondents' data was collected to test the hypothesized relations. A resource based view (RBV) was adopted, and the questionnaires-based survey was conducted on the Indian supply chain professionals to explore the effect of LG and green human resource management (GHRM) practices on supply chain performance.

The study presented five constructs for supply chain capabilities (SCCA), five constructs for supply chain collaboration and integration (SCIN), four constructs for supply chain knowledge and information sharing (SCKI), five constructs for GHR, five constructs for LG practices (LGPR) and four constructs for lean-green SCM (LG-SCM) firm performance to be utilized for validation by the specific industry, company size and operational boundaries for attaining sustainability. The outcome emphasizes that SCCA positively influence GHRM, LG practices and LG supply chain firm performance. However, LG practices do not influence LG-SCM firm performance, particularly in India.

The study exploited multiple practices in a conceptual model to provide a widespread understanding of decision-making to assist in developing a holistic approach based on different practices for attaining organizational sustainability. The study stimulates the cross-pollination of ideas between many supply chain practices to better understand SCCA, SCIN, SCKI, GHRM and LG-SCM under a single roof for retaining organization performance.

This study aims to investigate the mediating role of “Big Data Analytics” played between “Project Performance” and nine factors including top management, project knowledge management focus on sustainability, green purchasing, environmental technologies, social responsibility, project operational capabilities, project complexity, collaboration and explorative learning, and project success.

A sample of 321 responses from 106 Indian manufacturing small and medium-scaled enterprises (SMEs) was collected. Data were analyzed using empirical analysis through structural equation modeling.

The result shows that project knowledge management, green purchasing and project operational capabilities require the mediating support of big data analytics. The adoption of big data analytics has a positive influence on project performance in the manufacturing sector.

This study is useful to SMEs managers, practitioners and government policymakers to develop an understanding of big data analytics, eliminate challenges in the adoption of big data, and formulate strategies to handle projects efficiently in SMEs in the context of Indian manufacturing.

For the first time, big data for manufacturing firms handing innovative projects was discussed in the Indian SME context.

Today, proficient practices are required to stimulate along various boundaries of the supply chain (SC) to exploit manufacturing resources economically, effectually and gracefully for retaining operational excellence. Accordingly, varieties of paramount practices, i.e. Lean, Agile, Resilient and Green practices, are integrated in present study with the objective to develop a Decision Support Framework (DSF) to select robust supplier under the extent of Lean-Agile-Resilient-Green (LARG) practices for a manufacturing firm. The framework is developed and validated in the Indian automotive sector, where the primary data is collected based on perceptions of the respondents working in an automotive company.

LARG metrics can ponder ecological balance, customer satisfaction, associations, effectiveness and sustainability and thus, the study consolidated LARG practices in one umbrella to develop a DSF. The analytical approach under DSF is developed by the integration AHP, DEMATEL, ANP, Extended MOORA and SAW techniques in present study to evaluate a robust supplier under the aegis of LARG practices in SC. DSF is developed by scrutinizing and categorizing LARG characteristics, where the selected LARG characteristics are handled by fuzzy sets theory to deal with the impreciseness and uncertainty in decision making.

The study has identified 63 measures (15 for Lean, 15 for Agile, 14 for resilient and 19 for Green) to support the robust supplier selection process for manufacturing firms. The findings of study explicate “Internal communication agility”, “Interchangeability to personnel resources”, “Manufacturing flexibility”, “degree of online solution”, “Quickness to resource up-gradation”, “Manageability to demand and supply change”, “Overstocking inventory practices” as significant metrics in ranking order. Additionally, “Transparency to share information”, “Internal communication agility”, “Manufacturing Flexibility”, “Green product (outgoing)” are found as influential metrics under LARG practices respectively.

A technical DSF to utilize by the managers is developed, which is connected with knowledge-based theory and a case of an automobile manufacturing firm is presented to illustrate its implementation. The companies can utilize presented DSF to impose service excellence, societal performance, agility and green surroundings in SC for achieving sustainable outcomes to be welcomed by the legislations, society and rivals. The framework represents an important decision support tool to enable managers to overcome imprecise SC information sources.

The study presented a proficient platform to review the most significant LARG alternative in the SC. The study suggested a cluster of LARG metrics to support operational improvement in manufacturing firms for shifting gear toward sustainable SC practices. The present study embraces its existence in enrolling a high extent of collaboration amongst clients, project teams and LARG practices to virtually eradicate the likelihood of absolute project failure.

Blockchain, in general, diversifies supply chain management in record-keeping and maintains authenticity. In addition, traditional issues and challenges like overflow and information overload press down mysteriously whenever the blockchain steering wheel of the supply chain turns. Factually, the miracle and twists in supply chain resilience have not been incorporated under systematic review homogeneously. As a result, this study reviews the potential impact of blockchain on logistics and supply chain (LSC) efficiency. The methodology of this study provides a subjective assessment of the utility of blockchain-based LSC performance.

On the other hand, the review reveals new insights on its current acceptance and applications, with a particular emphasis on the Limit Redundancy Mechanism and Core Information-based Direct Comparison. Prospectively, the identified facts under the research paradigm and extensive literature survey will subsidize the practices of blockchain technology and possible areas of extension in supply chain resilience in luminous fashion in the future. After all, this study materializes new solid magnitudes, adaptability, and a realistic overview of blockchain-based LSC movements.

This paper aims to identify modern construction techniques for affordable housing, such as prefabrication and interlocking systems, that can save time and cost while also providing long-term sustainable benefits that are desperately needed in today's construction industry.

The need for housing is growing worldwide, but traditional construction cannot cater to the demand due to insufficient time. There should be some paradigm shift in the construction industry to supply housing to society. This paper presented a state-of-the-art review of modern construction techniques practiced worldwide and their advantages in affordable housing construction by conducting a systematic literature review and applying the backward snowball technique. The paper reviews modern prefabrication techniques and interlocking systems such as modular construction, formwork systems, light gauge steel/cold form steel construction and sandwich panel construction, which have been globally well practiced. It was understood from the overview that modular construction, including modular steel construction and precast concrete construction, could reduce time and costs efficiently. Further enhancement in the quality was also noticed. Besides, it was observed that light gauge steel construction is a modern phase of steel that eases construction execution efficiently. Modern formwork systems such as Mivan (Aluminium Formwork) have been reported for their minimum construction time, which leads to faster construction than traditional formwork. However, the cost is subjected to the repetitions of the formwork. An interlocking system is an innovative approach to construction that uses bricks made of sustainable materials such as earth that conserve time and cost.

The study finds that the prefabrication techniques and interlocking system have a lot of unique attributes that can enable the modern construction sector to flourish. The study summarizes modern construction techniques that can save time and cost, enhancing the sustainability of construction practices, which is the need of the Indian construction industry in particular.

This study is limited to identifying specific modern construction techniques for time and cost savings, lean concepts and sustainability which are being practiced worldwide.

Modern formwork systems such as Mivan (Aluminium Formwork) have been reported for their minimum construction time which leads to faster construction than traditional formwork.

The need for housing is growing rapidly all over the world, but traditional construction cannot cater to the need due to insufficient time. There should be some paradigm shift in the construction industry to supply housing to society.

This study is unique in identifying specific modern construction techniques for time and cost savings, lean concepts and sustainability which are being practiced worldwide.

This paper aims to study the relationship between servant leadership (SL), employee turnover intention (TI) and organizational identification (OI) in hospitals.

The study uses a quantitative approach to investigate the relationships between SL, OI and TI, using data collected from a sample of 266 front-facing employees in a private Indian hospital setup. Structural equation modeling is used to analyze the data and test the hypotheses.

The findings reveal that servant leadership has a positive relationship with organizational identification and negatively impacts turnover intentions of the front-facing employee. Further, the study also reveals, contrary to expectations, organizational identification has no significant mediating effect between servant leadership and turnover intentions.

This research is limited to front-facing employees in hospitals and the study may be extended to other industries in the service sector. Future studies may consider other mediating and moderating variables to fully understand the mechanism of impact of servant leadership on turnover intention. Multi-level studies can also be carried out.

With the ever-increasing expectations for better patient care, robust leadership models have required that address front-facing employee’s well-being, enabling their attention toward patients. This paper provides the impetus for the development and adoption of servant leadership specifically within hospitals and the service sector.

This study is one of the few studies that empirically examines servant leadership in the health-care domain. The study also contributes to the extant literature on servant leadership by empirically examining the mediation effect of organizational identification between SL and TI. To the authors’ best of knowledge, this study may be the first of its kind, providing evidence of servant leadership’s impact on turnover intention and organizational identification in hospitals using data from the Indian context.