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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.

The public distribution system (PDS) is an Indian food security system established to manage the distribution of food grains at affordable prices. As a result of the population explosion, the long-established PDS system finds it challenging to maintain operational efficiency, quality, trust and transparency. This paper explores the possibility of leveraging blockchain technology to overcome these operational hurdles.

Through a literature review and expert interactions, the present research identifies critical success factors in terms of enablers and barriers that influence the adoption of blockchain technology in PDS. Furthermore, we propose two independent interpretive structural models (ISM) and MICMAC to characterize these attributes.

The research identifies 15 distinct enablers and ten barriers that influence the diffusion of the latest technology in the sector at focus. The analyses disclose the interrelationships/dependencies among these enablers and between barriers, along with their individual driving power and dependence power.

The research showcases the importance of automating the system and illustrates how the features of blockchain technology can assist in augmenting stakeholder satisfaction levels. However, poor or nonexistent government regulations and patronage are found to be the major impediments to adoption. The research also delineates the cost implications of this barrier through its interrelationships with other barriers.

Interesting inferences are drawn from the models that offer actionable insights for the industry, government and technologists for improving PDS performance. Such interventions will ensure national food security through enhanced trust and transparency, which can further improve efficiency and effectiveness.

Foreign direct investment in the real estate (FDIRE) sector is required to bridge the gap between investment needed and domestic funds. Further, foreign direct investment is gaining importance because other sources of raising finance such as External Commercial Borrowing and foreign currency convertible bonds have been banned in the Indian real estate sector. Therefore, the objective of the study is to explore the determinants attracting foreign direct investment in real estate and to assess the impact of those variables on foreign direct investments in real estate.

Johansen cointegration test, vector error correction model along with variance decomposition and impulse response function are employed to understand the nexus of the relationship between various macroeconomic variables and foreign direct investment in real estate.

The results indicate that infrastructure, GDP and tourism act as drivers of foreign direct investment in real estate. However, interest rates act as a barrier.

This article aimed at exploring factors attracting FDIRE along with estimating the impact of identified variables on FDI in real estate. Unlike other studies, this study considers FDI in real estate instead of foreign real estate investments.

The purpose of this study was to see the impact of increased out-of-pocket expenditure oh health care exerting budget pressure on households, which leads to change in dietary consumption.

It was a hospital-based cross-sectional study comprising 414 patients with a chronic or major illness attending a large tertiary care public hospital at Delhi, India. Each patient represented a household with total number of family members of 2,550 in the study. Questionnaire was used to gather data on factors responsible for changes in consumption of 12 major food items.

Moderate decrease in food consumption of a household after major illness is associated with: rural residence (p < 0.001), decrease in savings (p < 0.001), more number of household items sold (p < 0.001), education of the children affected (p < 0.001), upper socio-economic status (SES) (p < 0.001) and children started working after illness in family (p = 0.043). In addition to decrease in food items, there was also deterioration in quality of food preparation. More than 80% of the families did not change the intake of cereals (rice and wheat), pulses and sugar. Food items that were decreased by most families were fruits, followed by milk and its products, vegetables, meat and egg, oils and ghee.

This study is a subset of other two studies previously published. The authors had not been able to cover this aspect fully in those two studies but understood the importance of impact of expenditure on illness on food consumption. The authors studied change in food consumption pattern (not amount) in subjects after illness. The impact of weather changes in food consumption on the impacted nutritional status of family has not been studied. The authors only collected cross-sectional, observational data and recall bias cannot be completely ruled out and corrected. With such data, only associations could be concluded, not causality. The illness condition of a household was measured by presence of chronic disease and inpatient treatment. Such measures did not take into account the types of illness and number of episodes. Data of this study cannot capture whether food intake of family prior to illness was sufficient/in excess/deficient. The Kuppuswamy scale, mostly used in urban and peri-urban settings, was also used for rural subjects in the study, which might have resulted in impaired capture of rural SES. The authors did not assess whether families were allocated food grains by schemes like public distribution system, which might have resulted in biased decrease in food consumption. Questionnaire used was not validated.

This study demonstrates the various factors that act as barriers to proper food consumption, including non-financial factors. The policy of user fee in government is hitting poorer section, and equity and access to health are compromised. Health expenditure should be increased by public sector policies to implement uniform healthcare. There is need for more studies to identify measures that could be put in place when designing policies and interventions for the uniform distribution of benefits.

The policy of user fee in government is hitting poorer section, and equity and access to health are compromised. Health expenditure should be increased by public-sector policies to implement uniform healthcare.

Major or chronic illness affects money acquisition and priorities of expenditure, resulting in deterioration in quality of food consumption and by a household.

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.

Two-level support with Level 1 consisting of a set of beams and Level 2 consisting of a tree-like structure is an efficient support structure for extrusion-based additive manufacturing (EBAM). However, the literature for finding a slim two-level support is rare. The purpose of this paper is to design a lightweight two-level support structure for EBAM.

To efficiently solve the problem, the lightweight design problem is split into two subproblems: finding a slim Level 1 support and a slim Level 2 support. To solve these two subproblems, this paper develops three efficient metaheuristic algorithms, i.e. genetic algorithm (GA), genetic programming (GP) and particle swarm optimization (PSO). They are problem-independent and are powerful in global search. For the first subproblem, considering the path direction is a critical factor influencing the layout of Level 1 support, this paper solves it by splitting the overhang region into a set of subregions, and determining the path direction (vertical or horizontal) in each subregion using GA. For the second subproblem, a hybrid of two metaheuristic algorithms is proposed: the GP manipulates the topologies of the tree support, while the PSO optimizes the position of nodes and the diameter of tree branches. In particular, each chromosome is encoded as a single virtual tree for GP to make it easy to manipulate Crossover and Mutation. Furthermore, a local strategy of geometric search is designed to help the hybrid algorithm reach a better result.

Simulation results show that the proposed method is preferred over the existing method: it saves the materials of the two-level support up to 26.34%, the materials of the Level 1 support up to 6.62% and the materials of the Level 2 support up to 37.93%. The proposed local strategy of geometric search can further improve the hybrid algorithm, saving up to 17.88% of Level 2 support materials.

The proposed approach for sliming Level 1 support requires the overhanging region to be a rectilinear polygon and the path direction in a subregion to be vertical or horizontal. This limitation limits the further material savings of the Level 1 support. In future research, the proposed approach can be extended to handle an arbitrary overhang region, each with several choices of path directions.

The details of how to integrate the proposed algorithm into the open-source program CuraEngine 4.13.0 is presented. This is helpful for the designers and manufacturers to practice on their own 3D printers.

The path planning of the overhang is a critical factor influencing the distribution of supporting points and will thus influence the shape of the support structure. Different from existing approaches that use single path directions, the proposed method optimizes the volume of the support structure by planning hybrid paths of the overhangs.