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The study aims to identify the key advantages/enablers and disadvantages/barriers of augmented reality (AR) implementation in education through existing reviews. It also examines whether these factors differ across educational domains.

This study conducted a systematic review of reviews to synthesize evidence on the barriers and enablers influencing AR adoption in education. Searches were performed across five databases, with 27 reviews meeting the inclusion criteria. Data extraction and quality assessment were completed. Content analysis was conducted using the AR adoption factor model and consolidated framework for implementation research.

The findings reveal several enablers such as pedagogical benefits, skill development and engagement. Equally, multiple barriers were identified, including high costs, technical issues, curriculum design challenges and negative attitudes. Interestingly, duality emerged, whereby some factors served as both barriers and enablers depending on the educational context.

This review contributes a novel synthesis of the complex individual, organizational and technological factors influencing AR adoption in education across diverse domains. The identification of duality factors provides nuanced understanding of the multifaceted dynamics shaping AR integration over time. The findings can assist educators in tailoring context-sensitive AR implementation strategies to maximize benefits and minimize drawbacks. Further research should explore duality factors and their interrelationships in AR adoption.

The purpose of this study is to see if market timing predicts the first reporting of earnings performance after the issue, i.e. the issue-year earnings performance. Furthermore, this study examines the behaviour of financial and non-financial issuers’ performance in the light of varied market timings.

This study focuses on 785 NSE-listed initial public offerings that took place between April 2010 and December 2021. This study evaluates market timing by using moving averages. Using multiple regression analysis, the research further investigates the impact of market timing on issue-year earnings performance for financial and non-financial issuers on the basis of an interaction (moderation) effect.

This study finds that there is a significant presence of market timing in India, which predicts issue-year earnings performance. This study also demonstrates that hot market issuers’ performance is heavily influenced by market timing for non-financial issuers only. However, financial companies are not influenced by market timing.

The findings of this study will assist the potential investors, analysts and stakeholders about performance of public issuers in India. Lower earnings performance for hot market non-financial issuers implies that the issuers’ market performance may not be supported by earnings figures. A market performance that is not synchronous with earnings will not last long. The findings of this study hold implications to the regulators as well to keep an eye on issuers’ earnings performance alongside the stock performance. Apart from that, the observations in context of financial and non-financial issuers provide insight about the variation in performance of public issues on the basis of background.

To the best of the authors’ knowledge, this is the only study to examine earnings performance in the context of market timing in India. This study holds significance in terms of methodology for anticipating the presence of market timing and the study of interaction effects. Moreover, it is one of the few studies that has focused on comparing financial and non-financial issuers around the world.

Lean Manufacturing Systems (LMS) gained popularity among manufacturers globally. However, their efficacy in developing and least-developed countries remained noticeably understudied. Motivated by this research gap, the researchers of this study designed a quantitative study with a structured survey technique to investigate its context-specific impact on the apparel industry of a developing country. Hence, this study aimed to examine the relationship between LMS and elimination of waste (EOW) and operational performance (OP) and comprehend how the EOW mediates the relationship between an LMS and OP within the apparel industry of a developing economy.

The researchers collected data from 227 garment companies in Bangladesh. These organization-level data were then analyzed using the structural equation modeling approach with AMOS 20.0 software to examine the direct and indirect effects among EOW, LMS and OP.

The findings of this study suggest that EOW has a direct and significant effect on OP. This research also revealed that EOW has a partial mediating effect on the relationship between LMS and OP.

This research focused on a single industry administering self-reported data and cross-sectional design, limiting generalizability and causal inference.

LMS and directing efforts towards EOW can significantly improve the operational performance of apparel companies by reducing lead times and costs, improving quality and increasing productivity.

These findings can provide useful insight to managers, practitioners and future researchers to understand the relationship between EOW, LMS and OP to optimize their production processes and improve OP in the apparel industry.