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Many research findings demonstrate the benefits of lean manufacturing implementation. However, the impact of lean manufacturing on organizational performance in developing countries like Bangladesh remains unexplored. The purpose of this paper is to investigate the impact of lean manufacturing system (LMS) on the organizational performance of the apparel industry in Bangladesh.

Empirical data were collected from 227 apparel manufacturing firms using a close-ended structured questionnaire. The causal relationships between the independent and dependent variables are examined by structural equation modeling using AMOS 20.0 software.

The results reveal significant evidence that the implementation of LMS has a direct impact on organizational performance in terms of operational and business performance.

The findings of this study will create a substantial interest among the practitioners of the apparel industry to implement LMS. This study will also explore the opportunities to develop lean implementation framework and identify the benefits that will enhance the competitive advantages.

This paper explores the causal relationships and argues based on the empirical data in the context of the apparel industry in Bangladesh.

The purpose of this study is the development of an objective approach to prioritize and rank airfield pavement sections based on their condition and justify their funding requirements using a soft-computing technique.

The airfield pavement condition is evaluated by collecting data through field tests and visual surveys. The performance indicators are selected as deflection, structural index, subgrade modulus and pavement condition index, by taking the help of field experts. The condition of pavement sections is analyzed by obtaining scores for each sections using Buckley’s fuzzy analytic hierarchy process. The sections are finally ranked for performing their maintenance and repair activities.

The condition of pavements is represented using a single score that takes an account of cumulative impact of various parameters as well as any subjectivity associated with human perceptions.

The developed methodology is very useful for its practical implications, and it is explained using a case study of an international airport.

Decision-making for maintenance and repair practices is often based on subjective decisions and lacks a robust and judicious approach. Thus, obtaining sufficient budget for repair and maintenance becomes one of the primary challenges. This study adds a value to prevailing practices by developing an objective decision-making methodology. Additionally, the use of non-destructive testing techniques, which pose little or no necessity to destructive coring and boring, eases this task.

The purpose of this paper is to develop a numerical model for estimating the unknown boundary heat flux in a parallel plate channel for the case of a hydrodynamically and thermally developing laminar flow.

The conjugate gradient method (CGM) is used to solve the inverse problem. The momentum equations are solved using an in-house computational fluid dynamics (CFD) source code. The energy equations along with the adjoint and sensitivity equations are solved using the finite volume method.

The effects of number of measurements, distribution of measurements and functional form of unknown flux on the accuracy of estimations are investigated in this work. The prediction of boundary flux by the present algorithm is found to be quite reasonable.

It is noticed from the literature review that study of inverse problem with hydrodynamically developing flow has not received sufficient attention despite its practical importance. In the present work, a hydrodynamically and thermally developing flow between two parallel plates is considered and unknown transient boundary heat flux at the upper plate of a parallel plate channel is estimated using CGM.

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 paper is to investigate the relationship between total productive maintenance (TPM) practices and operational performance (OP) in soft drinks manufacturing industry, Ethiopia.

In this study acceptability and implementation of five TPM practices (i.e., dependent factors: autonomous maintenance (AUT); safety, health and environment (SHE); education and training (EDT); focused improvement; and planned maintenance (PLM)) in soft drinks manufacturing industry have been elaborated to ascertain the benefits accrued as a result of successful TPM practices (i.e., independent variables) on OP (i.e., dependent variables). A self-administered survey seven-point Likert scale questionnaire was used for primary data collection. By using simple random sampling technique a total of 100 useable responses resulted in a 66.66 per cent response rate. Descriptive (mean, standard deviation) and inferential statistics (factor analysis, correlation, simple and multiple regression analysis) analysis were performed using Statistical Package for Social Sciences (SPSS) software (version-28) to identify the relationship and effect of TPM practices on OP. Five hypotheses were developed and tested.

Results show that four of the TPM practices were positively and significantly correlated with OP. Aggregate TPM shows positive and significant correlation with OP. Four hypotheses results revealed that the AUT; SHE; EDT and PLM practices have positive and significant relationship with OP and significantly improve OP. The results also show that the TPM practices have positive and significant relationship with OP and significantly improve cost effectiveness, product quality, on-time delivery and volume flexibility.

The benefits gained by TPM practices in selected soft drinks manufacturing industry have been highlighted, that could be genuine source of motivation to other companies to go in for TPM program. This research contributes to the literature by examining the contingency of various TPM enabling factors in the context of the Ethiopian soft drinks manufacturing sector, and it, therefore, provides direction to increase the success rate of TPM implementation. Study offers academics and practitioners a better understanding of the relationship and effect of the TPM practices on the OPs. Thus, practitioners will be able to make better and more effective decisions about the implementation of TPM practices for better OP results.

The relationship between the five factors TPM practices and OP has not yet been studied or reported in the case of soft drink manufacturing industry. The questionnaire manner and items developed, factor considered in this study, sampling method, deeply statistical data analysis techniques used, soft drink manufacturing industry, developing country like Ethiopia make this study unique and revealed the gap identification in this area. The study has contributed to the TPM literature with a better understanding of the five TPM practices and their association with a soft drink manufacturing industry OP that will provide valuable knowledge to top-management of manufacturing companies, to refine their current TPM practices and subsequently improve OP.

The COVID-19 pandemic has disrupted the ‘real’ world and substantially impacted the virtual world and thus the Internet ecosystem. It has caused a significant exogenous shock that offers a wealth of natural experiments and produced new data about broadband, clouds, and the Internet in times of crisis. In this chapter, we characterise and evaluate the evolving impact of the global COVID-19 crisis on traffic patterns and loads and the impact of those on Internet performance from multiple perspectives. While we place a particular focus on deriving insights into how we can better respond to crises and better plan for the post-COVID-19 ‘new normal’, we analyse the impact on and the responses by different actors of the Internet ecosystem across different jurisdictions. With a focus on the USA and Europe, we examine the responses of both public and private actors, with the latter including content and cloud providers, content delivery networks, and Internet service providers (ISPs). This chapter makes two contributions: first, we derive lessons learned for a future post-COVID-19 world to inform non-networking spheres and policy-making; second, the insights gained assist the networking community in better planning for the future.

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.

This case describes the events following an incident of a rape in a taxi associated with Uber, by its driver. Uber was an application based taxi operator. The events raised several issues for government systems and processes, such as need for regulation of new formats of business like application based taxi services, integrated databases, checks against forgery and holistic approach towards women safety. The case also brings out how an e-commerce business raises regulatory concerns.