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This study embarks on a comprehensive investigation into the intricate relationship between consumer trust in e-commerce platforms and the adoption of Green Supply Chain Management (GSCM). It delves into a multifaceted analysis of how these dynamics influence the landscape of online shopping, with a specific focus on four critical dimensions: the efficiency of online purchasing processes, the fulfillment of product delivery commitments, the convenience associated with e-platform utilization, and the safeguarding of consumers' personal information.

This research employs sophisticated Structural Equation Modeling (SEM) techniques, facilitated by SPSS and SmartPLS software, to meticulously analyze the amassed data and subject the formulated hypotheses to rigorous testing. The empirical foundation of this study draws from a sample of 377 randomly selected online shoppers, providing a robust basis for its insights.

At its core, this research is squarely focused on unraveling the dynamics of consumer trust within e-commerce platforms and highlighting the pivotal role played by GSCM in making online shopping more ecologically responsible and sustainable. Of paramount importance is the novel dimension introduced by this study the integration of trust in e-commerce platforms, GSCM practices, and the multifarious dimensions of online shopping all within a unified conceptual framework. Trust on e-commerce platforms leads to GSCM. GSCM determines online shopping satisfaction, i.e. efficiency, fulfillment, convenience, and privacy. Finally, GSCM mediates between trust on e-commerce platforms and online shopping satisfaction.

This holistic approach represents a ground-breaking contribution to the existing body of literature. It presents a fresh perspective on the intricate interactions that define the contemporary e-commerce landscape.

This initial research integrates trust in e-commerce platforms, GSCM, and online shopping in a single framework through UTAUT2.

Lean manufacturing (LM) concepts have been widely adopted in diverse industrial sectors. However, no literature review focusing on case studies describing LM implementation is available. Case studies represent the actual implementation and provide secondary data for further analysis. This study aims to review the same to understand the pathways of LM implementation. In addition, it aims to analyse other related review questions, such as how implementing LM impacts manufacturing capabilities and the maturity level of manufacturing organisations that implemented LM, to name a few.

A literature review of case studies that discuss the implementation of LM during the last decade (from 2010 to 2020) is carried out. These studies were synthesised, and content analyses were performed to reveal critical insights.

The implementation pattern of LM significantly varies across manufacturing organisations. The findings show simultaneous improvement in manufacturing capabilities. Towards the end of the last decade, organisations implemented LM with radio frequency identification, e-kanban, simulation, etc.

Reviewing the case studies documenting LM implementation to comprehend the various nuances is a novel attempt. Furthermore, potential future research directions are identified for advancing the research in the domain of LM.