For the last two decades, Ready-Made Garment (RMG) Industry has been the life-blood of the economy of Bangladesh. This sector accounted for about 80% of the total export earnings of the country. In the recent years, it has been observed that the workers have came down in the street and making insurgence on their demand and tried to destruct public properties. As a result, companies are losing working-hours and production targets. It also hampers export earnings and the image of the country to the international markets. In this connection, this study tried to find out the factors behind the unrest in the ready-made garment industry of Bangladesh and identifies some measures to improve the situation. In this study, 244 workers were interviewed from the different garment factories located in Savar and Gazipur district of Bangladesh. Data were analyzed with factor analysis, regression model, and by using other suitable statistical tools. The results show that the main causes of labor unrest include lack of minimum facility and safety at work, sub-standard living conditions, deferred payment of wages and benefits, international conspiracy and coercive role of the law enforcing agency, too much dependency on buyers, pressures from the workers and local terrorists, use of workers by others and rumors, un-fulfillment of education demands of their children, distorted minded workers, political instability of the country, too much workload, lack of promotion opportunity, insufficient wages to survive etc. If the policy makers of Bangladesh consider these causes and make policies to overcome the problems the labor unrest in garment sector may be minimized.
Background During COVID-19 lockdown worldwide, classroom education continues remotely through online. The question remains, comparing with the face-to-face education, does online education has a similar satisfaction level among the students? There are only a few studies that examine the perceived service quality of online education. Objective The study aims to analyze the factors of perceived service quality of online education during a pandemic. Research Design A structured questionnaire elicits information from 147 students from different study backgrounds of various universities worldwide. The fuzzy-set qualitative comparative analysis (fsQCA) is used for data analysis and model design. Research constructs evaluation for reliability and internal consistency are subsequently performed. A snowball random sampling method is applied for data collection. Results Findings from the fsQCA analysis identify four core factors that underpin student satisfaction through positive perceived service quality of online education. Alternative paths are determined based on gender, students’ current education status, and their loyalty toward online education. We also introduce two topologies of perceived quality regarding online education and student satisfaction. Originality Because of the primary nature of the data, this is firsthand experience gathered from different universities around the world who have willingly or unwillingly experienced online learning during the pandemic. The fsQCA technique for examining perceived service quality of online education. Conclusions The findings contain a number of contributions, illustrating different topologies of the student from different backgrounds and their intention, satisfaction and loyalty towards e-learning, and identifying causal factors that influence willingness to recommend online education.
The outcome-based learning for graduate employability in higher education has been an important research topic among the policymakers, academicians, and researchers over the years. Yet, no bibliometric review on this topic has been published. This study, for the first time, examines bibliometric analysis on this topic examining current research trend and future research agenda. The bibliometrix package in R software and VOSviewer software are used for visualization and interpretation of results. A content analysis is performed to manually examine the bibliometric results.
PurposeData envelopment analysis (DEA) calculates the efficiency of a business unit if all the inputs are creating outputs within a “black box.” Under traditional DEA, the detailed process of that business unit is ignored. However, a network DEA can explain the black box structure and provide efficiency results for sub-sections within any business process. This study aims to propose a network DEA model that explains a bank's total operation.Design/methodology/approachEarlier studies have focused only on bank efficiency ignoring this breakdown. This study departs from them by using a slack-based two-stage network DEA under a novel banking business perspective.FindingsThe results reveal that network DEA provides better benchmarking insights than the traditional DEA. As such, better benchmarking can guide both the banking industry managers and policy makers in Bangladesh.Originality/valueThe major contribution of this study includes dividing a bank's total operation efficiency into two sub-operations: “core operations – collecting deposits and giving loans” and “additional operations – fees, commissions and other services.”
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