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The purpose of this study is to evaluate the impact of green human resource management (GHRM) practices on Indian companies of different sectors and to identify the most critical GHRM practices that can lead to a more sustainable and environmentally friendly workplace.

This study uses an integrated Analytic Hierarchy Process-Evaluation based on Distance from Average Solution approach to determine the importance of 32 GHRM practices classified into eight categories, as identified through literature review and expert consultation. This study also identifies the best sector for GHRM practices in India.

This study reveals that employee engagement is the most critical practice among all the GHRM practices identified. India’s Information Technology-Enabled Services sector benefited the most from GHRM practices, followed by the Insurance sector.

This study contributes to the literature on GHRM practices and their impact on organisations and sectors. The integrated Analytic Hierarchy Process-Evaluation based on Distance from Average Solution approach used in this study is innovative and can be helpful for Indian companies to prioritise and implement effective GHRM practices.

This study aims to enhance freight logistics by overcoming barriers and driving sustainable growth through an integrated approach. It focuses on the critical role of efficient freight logistics in sustaining economic growth and addresses the challenges hindering the sector’s efficiency.

The research employs the grey Delphi method for a comprehensive literature review and expert evaluation to identify significant barriers in India’s freight logistics sector. Subsequently, the grey decision-making trial and evaluation laboratory (DEMATEL) method establishes causal relationships among these barriers to provide insights into their interconnectedness.

The findings of the study highlight the importance of addressing these barriers through sustainable strategies and innovative solutions. The study recommends the adoption of green transportation technologies, collaborative efforts among stakeholders and the development of modern logistics facilities. By mitigating the adverse effects of logistics operations on the environment and society, these strategies aim to improve overall efficiency and competitiveness in the freight logistics sector.

This study is primarily based on feedback from ten seasoned experts; however, incorporating input from a broader range of experts would provide deeper insights and perspectives.

This study offers a comprehensive analysis of barriers and opportunities for sustainable growth in India’s freight logistics sector. The study contributes valuable evidence-based insights and practical recommendations, serving as a guide for policymakers, industry stakeholders and practitioners seeking to enhance the efficiency and competitiveness of the country’s freight logistics operations.

This study aims to address the inherent uncertainties within closed-loop supply chain (CLSC) networks through the application of a multi-objective approach, specifically focusing on the optimization of integrated production and transportation processes. The primary purpose is to enhance decision-making in supply chain management by formulating a robust multi-objective model.

In dealing with uncertainty, this study uses Pythagorean fuzzy numbers (PFNs) to effectively represent and quantify uncertainties associated with various parameters within the CLSC network. The proposed model is solved using Pythagorean hesitant fuzzy programming, presenting a comprehensive and innovative methodology designed explicitly for handling uncertainties inherent in CLSC contexts.

The research findings highlight the effectiveness and reliability of the proposed framework for addressing uncertainties within CLSC networks. Through a comparative analysis with other established approaches, the model demonstrates its robustness, showcasing its potential to make informed and resilient decisions in supply chain management.

This study successfully addressed uncertainty in CLSC networks, providing logistics managers with a robust decision-making framework. Emphasizing the importance of PFNs and Pythagorean hesitant fuzzy programming, the research offered practical insights for optimizing transportation routes and resource allocation. Future research could explore dynamic factors in CLSCs, integrate real-time data and leverage emerging technologies for more agile and sustainable supply chain management.

This research contributes significantly to the field by introducing a novel and comprehensive methodology for managing uncertainty in CLSC networks. The adoption of PFNs and Pythagorean hesitant fuzzy programming offers an original and valuable approach to addressing uncertainties, providing practitioners and decision-makers with insights to make informed and resilient decisions in supply chain management.

Educational data mining (EDM) discovers significant patterns from educational data and thus can help understand the relations between learners and their educational settings. However, most previous data mining techniques focus on prediction of learning performance of learners without integrating learning patterns identification techniques.

This study proposes a new framework for identifying learning patterns and predicting learning performance. Two modules, the learning patterns identification module and the deep learning prediction models (DNN), are integrated into this framework to identify the difference of learning performance and predicting learning performance from profiles of students.

Experimental results from survey data indicate that the proposed identifying learning patterns module could facilitate identifying valuable difference (change) patterns from student’s profiles. The proposed learning performance prediction module which adapts DNN also performs better than traditional machine techniques in prediction performance metrics.

To our best knowledge, the framework is the only educational system in the literature for identifying learning patterns and predicting learning performance.

India liberalized its economy in 1991, which resulted in intense global competition, quality-conscious and demanding customers. Additionally, significant technological advancements lead to enhancements in products and processes. These forced Indian organizations to adopt innovative business strategies in the past 30 years. Meanwhile, the Lean Six Sigma methodology has significantly grown with vast applicability during the past 30 years. Thus, the purpose of this study is to develop the learning on Lean Six Sigma methodology in the Indian context through investigation of literature.

A three-stage systematic literature review approach was adopted to investigate the literature during the present study. In total, 187 articles published in 62 journals/conference proceedings from 2005 to 2022 (18 years) were shortlisted. The first part of the article summarizes the significant milestones towards the quality journey in the Indian context, along with the evolution of the Lean Six Sigma methodology. The second part examines the shortlisted papers on Lean Six Sigma frameworks, their applicability in industrial sectors, performance metrics, outcomes realized, publication trends, authorship patterns and leading researchers from the Indian perspective.

Lean Six Sigma has emerged as a highly acclaimed and structured business improvement strategy worldwide. The Indian economy has seen remarkable growth in the past decade and is one of the fastest-growing economies in the 21st century. Lean Six Sigma implementation in India has significantly increased from 2014 onward. The study revealed that researchers have proposed several different frameworks for Lean Six Sigma implementation, the majority of which are conceptual. Furthermore, the balanced applicability of Lean Six Sigma in manufacturing and service sectors was observed with the highest implementation in the health-care sector. Additionally, the widely adopted tools, techniques along with performance metrics exploring case studies were reported along with a summary of eminent and leading researchers in the Indian context.

This study is confined to reviewed papers as per the research criteria with a significant focus on the Indian context and might have missed some papers due to the adopted papers selection strategy.

The present study is one of the initial attempts to investigate the literature published on Lean Six Sigma in the Indian context, including perspective on the Indian quality movement. Therefore, the present study will provide an understanding of Lean Six Sigma methodology in the Indian context to graduating students in engineering and management and entry-level executives. The analysis and findings on Lean Six Sigma frameworks, research approach, publications details, etc., will be helpful to potential research scholars and academia. Additionally, analysis of case studies on Lean Six Sigma implementation by Indian industries will assist the managers and professionals in decision making.