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The purpose of this paper is to propose and develop PA2200-based composite powder containing 0-15 Wt.% magnesium oxide before directly using it in selective laser sintering (SLS) machine to produce end-use products for low-volume production in the engineering applications with keen focus to meet the functional requirements which rely on material properties.

The methodology reported emphasises PA2200-based composite powder containing 0-15 Wt.% magnesium oxide development for SLS process which starts with preparation and characterisation of composite material, thermal and rheological study of composite material to decide optimum process parameters for SLS process machine to get optimal part properties. Further, to verify composite material properties, a conventional casting methodology is used. The composition of composite materials those possessing good properties are further selected for processing in SLS process under optimal processing parameters.

The process parameters of SLS machine are material-dependent. The effect of temperature in X-ray diffraction profile is negligible in the case of magnesium oxide reinforced PA2200 composite material. The cyclic heating of material increases melting point temperature, this grounds to modify part bed temperature of material every time before processing on SLS machine to uphold build part properties, as well as material. With the rise in temperature, the Melt flow index and rheological property of materials change. The magnesium oxide reinforced PA2200 composite material has high thermal stability than pure PA2200 material. By the addition of small quantity of magnesium oxide, most of the mechanical property and flammability property improves while elongation at break (percentage) decreases significantly.

The proposed PA2200-based composite powder containing 0-15 Wt.% magnesium oxide material development system and casting metrology to verify developed material properties will be very useful to develop new composite material for SLS process with use of less material. The developed methodology has proven, especially in the case where non-experts or student need to develop composite material for SLS process according to the property requirement of applications.

Unlike earlier composite material development methodology, the projected methodology of polymer-based composite material and confirmation of material properties instead of commencing SLS process provides straight forward means for SLS process composite materials development with less use of the material and period of time.

The purpose of this paper is to propose and evaluate the selection of materials for the selective laser sintering (SLS) process, which is used for low-volume production in the engineering (e.g. light weight machines, architectural modelling, high performance application, manufacturing of fuel cell, etc.), medical and many others (e.g. art and hobbies, etc.) with a keen focus on meeting customer requirements.

The work starts with understanding the optimal process parameters, an appropriate consolidation mechanism to control microstructure, and selection of appropriate materials satisfying the property requirement for specific application area that leads to optimization of materials.

Fabricating the parts using optimal process parameters, appropriate consolidation mechanism and selecting the appropriate material considering the property requirement of applications can improve part characteristics, increase acceptability, sustainability, life cycle and reliability of the SLS-fabricated parts.

The newly proposed material selection system based on properties requirement of applications has been proven, especially in cases where non-experts or student need to select SLS process materials according to the property requirement of applications. The selection of materials based on property requirement of application may be used by practitioners from not only the engineering field, medical field and many others like art and hobbies but also academics who wish to select materials of SLS process for different applications.

The purpose of this paper is to develop a multi-item economic production quantity (EPQ) strategy under grey environment and space constraint. Since the “demand” cannot be predicted with certainty, it is assumed that data behave under grey environment and compare the proposed inventory model with other studies using crisp or fuzzy environments.

This paper is to optimise the cycle time and total cost of the multi-item EPQ inventory model. For this purpose, the Lagrangian coefficient is used to solve the constrained optimisation problem. The grey relational analysis approach and grey data are applied in developing the EPQ inventory model.

The results are compared with the analysis using crisp and fuzzy data. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The results of the study demonstrate that crisp data outperform the other two data in all scales problems in terms of cycle time and cost; grey data perform better in all scales problems than fuzzy data.

The contribution of this research is the use of grey data in developing the EPQ inventory model with space constraint.

Frugal innovation focuses on the core functionalities with the highest stakeholder benefits and directly targets user requirements. It has been widely adopted in developing countries, and extensively researched from both consumer and sustainable perspectives. However, few studies on frugal innovation consider “quality”, a seminal business management concept. This study focuses on this gap and uses a quality lens to understand frugal innovation.

This study adopts a mixed methodology. The Delphi focus group method is first applied to identify two cases of frugal innovation in the construction industry and a cross-case analysis done. Then, the analytic hierarchy process (AHP) is used to examine eight product quality dimensions to draw the final conclusions.

From Garvin’s concept of quality, frugal innovation focuses on performance and conformance. Furthermore, it prioritises a value-based approach the most.

This study examines frugal innovation from quality perspective. This opens up a new line of research which contributes to both streams. The study is based on construction which is a limitation of the study.

A quality-based frugal innovation understanding can be helpful in the conceptualisation, implementation and acceptance of the frugal innovation business model. It can provide clarity on the innovation's value proposition and also help in operationalisation of the business model.

Frugal encourages social entrepreneurs and understanding of the concept from quality perspective shall facilitate the operationalisation will become easier for them.

To the author’s knowledge, this is the first study at the interface of frugal innovation and quality management. Furthermore, the use of AHP to prioritise equality approaches and dimensions is an original contribution.

The purpose of this study is to identify and prioritize capabilities and practices to ensure a resilient supply chain during an unexpected disruption. In addition, this study ranks maturity factors that influence the main capabilities identified.

This paper is conducted in three stages. First, capabilities and practices are extracted through a literature review. Second, capabilities and practices are ranked using the analytical hierarchical process method. Third, a gray technique for order preference by similarity to ideal solution method is used to rank maturity factors influencing capabilities.

The findings indicate that responsiveness, readiness, flexibility and adaptability are the most important capabilities for supply chain resilience. Also, commitment and communication are the highest maturity factors influencing resilience capabilities.

The findings provide a hierarchical vision of capabilities and practices for industries to increase resilience. Limitations of the paper are related to capabilities, practices and number of experts consulted.

This paper highlights the importance of high-maturity practices in resilience capability adoption. The findings of this study will encourage decisions-makers to increase maturity practices to build resilience against disruption.

The paper reveals that developing powerful capabilities, good practices and a high level of maturity improve supply chain resilience.

Introduction: This study investigates the COVID-19 pandemic’s effects on the sustainability of the supply chain. It investigates how modern supply networks and procedures were equipped for such a catastrophe, and the pandemic’s effects on the environment, highlighting the significance of studying resilience and sustainability concurrently.

Purpose: The study acknowledges the importance of environmental sustainability for businesses and the need to examine trends in organisational, customer, policy, and distribution networks.

Need for the Study: The COVID-19 pandemic has significantly impacted supply chains. This study aims to provide insight into the long-term repercussions of the crisis and the importance of incorporating environmental considerations.

Methodology: The study uses a mixed-methods approach to evaluate the effects of the COVID-19 pandemic on supply networks and environmental sustainability indices. Data from industry reports, governmental publications, polls, and qualitative research techniques have been gathered.

Findings: The results of this study advance our understanding of how to preserve supply chains in the wake of the COVID-19 pandemic. It highlights the need for enhanced resilience and sustainability measures, expose the flaws and weaknesses of contemporary supply networks, and uncover developing patterns and tactics in customer behaviour, policy frameworks, distribution networks, and supply chain management.

Practical Implications: The COVID-19 pandemic has provided businesses, decision makers, and researchers with guidance on handling its potential and challenges – increasing the supply chain’s resistance to future interruptions, incorporating environmentally friendly practises, developing policies to support resilient and sustainable supply chains, adapting to changing consumer tastes, increasing effectiveness, and minimising the environmental impact of distribution networks.

This hypothetical case study aims to revisit the classical model given by Henri Fayol whereby he put forward a set of 14 principles to guide managers in decision-making across organizations. The case study showcases the dilemma in which the top manager of an automobile company finds himself when some of the very basic principles – on which the whole discipline of management is founded – are ignored. It will also serve as an aid for faculty members in B-Schools to teach students the significance of basic management principles postulated many years back which stand relevant even in contemporary times.

This case study is based on a hypothetical scenario in the corporate world. Different incidents in a fictitious automobile manufacturing firm are presented and the corresponding principles given by Henri Fayol are inferred.

This case study highlights that decision-making gets complicated if fundamental principles of management are not complied with. The decision taken during each and every situation which has been discussed in this case study is contrary to the correct course of action as propounded by Fayol. Modern-day managers must acknowledge the relevance and importance of these principles for achieving success in business.

This case study underscores that even in this volatile business environment where most of the management practices are technology-driven, we cannot disregard the most elementary rules of management. The managers working at different levels in the organizational hierarchy may be guided to make the right decisions in situations similar to the ones described.

The purpose of this paper is to identify, analyze and classify (i.e. driving and dependence power) the government-supported health-care supply chain enablers (GHSCEs) in rural areas of India for enhancing availability and minimizing wastage of generic medicines.

A methodology is proposed using interpretive structural modeling (ISM) – fuzzy matriced impacts croises multiplication appliqueeaun classement (Fuzzy MICMAC) analysis to analyze the GHSCEs on the basis of inputs collected from various stakeholders about their driving and dependence power.

The performance measurement system, employee recognition and reward, technology adoption, training cell and inbuilt analytical tool for IT system were found to be the appropriate GHSCEs where efforts and resources should be put for enhancing availability and minimizing wastage.

The proposed approach provides a platform for the both researchers and academicians to understand the GHSCEs and their relationships. It also provides the direction to the government for optimally allocating the efforts and resources to enhance the current performance level of generic drug distribution.

Although many issues related to health-care supply chain have been widely researched and reported, no literature has been found for analysis of GHSCEs to choose the appropriate set of GHSCEs for supply chain performance improvement in general and developing country like India in specific.

This study initially aims to identify the barriers to the big data analytics (BDA) initiative and further evaluates the barriers for knowing their interrelations and priority in improving the performance of manufacturing firms.

A total of 15 barriers to BDA adoption were identified through literature review and expert opinions. Data were collected from three types of industries: automotive, machine tools and electronics manufacturers in India. The grey-decision-making trial and evaluation laboratory (DEMATEL) method was employed to explore the cause–effect relationship amongst barriers. Further, the barrier's influences were outranked and cross-validated through analytic network process (ANP).

The results showed that “lack of data storage facility”, “lack of IT infrastructure”, “lack of organisational strategy” and “uncertain about benefits and long terms usage” were most common barriers to adopt BDA practices in all three industries.

The findings of the study can assist service providers, industrial managers and government organisations in understanding the barriers and subsequently evaluating interrelationships and ranks of barriers in the successful adoption of BDA in a manufacturing organisation context.

The paper is one of the initial efforts in evaluating the barriers to BDA in improving the performance of manufacturing firms in India.

The purpose of this paper is to analyze the impact of the cost of microfinance intermediation on borrowers’ loan size. The identified transaction cost and credit risk factors tell about what a lender takes into accounts while screening and allocating loan amounts to the borrowers, where the lender has limited information about the client’s ability to repay.

The analysis is based on the primary data collected from a sample of 498 microfinance institutions (MFI) linked group clients covering two microfinance leading states of India.

Empirical findings suggest that the cost of microfinance intermediation has an impact on borrowers’ loan size. To reduce the cost, the MFIs lend big loans to clients having a high income, assets, land size, lower informal borrowings and having longer loan experiences. In MFI lending, the younger and less educated people are the ones who demand bigger loan amounts. The geographical distance of borrowers’ location from MFI offices, group size and interest rate are the other factors that influence the loan size.

The past empirical works seem to have not focused on how the cost of microfinance intermediation creates loan size variation among the borrowers in joint liability group lending. The endogeneity problem has not been resolved. The present article thus identifies the factors that influence the individual member loan size by using two-stage least squared regression to tackle the issue of endogeneity.