Joseph R. Feinberg and Yasmine Bey
A primary goal of the Collaboration and Resources for Encouraging and Supporting Transformations in Education (CREST-Ed) program was to increase the number of highly qualified…
Abstract
Purpose
A primary goal of the Collaboration and Resources for Encouraging and Supporting Transformations in Education (CREST-Ed) program was to increase the number of highly qualified, minoritized teachers committed to teaching in minority-serving, high-need school districts. This study's purpose was to evaluate the CREST-Ed program's impact on teacher residency outcomes using multiple sources of program evaluation data collected during the five-year grant.
Design/methodology/approach
This study of a federal Teacher Quality Partnership (TQP) grant at Georgia State University (GSU), a minority-serving institution (MSI) and research university, shows teacher residency programs can improve the diverse teacher pipeline. The grant, CREST-Ed, provided professional development schools (PDS) support for four urban and 23 rural school districts through partnerships with GSU, Albany State University (ASU) and Columbus State University (CSU).
Findings
The study findings suggest that teacher preparation grants can be leveraged to recruit traditionally minoritized teachers of color to increase the diverse teacher pipeline and strengthen PDS partnerships.
Originality/value
Both urban and rural PDSs could benefit from teacher residency programs like the CREST-Ed model that catered to the unique needs of each school and partnership district.
Details
Keywords
Muhammad Imran Qureshi, Mehwish Iftikhar, Yasmine Muhammad Javaid Iqbal, Chaudry Bilal Ahmad Khan and Jia Liu
Despite the growing interest in closed-loop manufacturing, there is a lack of comprehensive frameworks that integrate product development, production processes, people and…
Abstract
Purpose
Despite the growing interest in closed-loop manufacturing, there is a lack of comprehensive frameworks that integrate product development, production processes, people and policies (4Ps) to optimize sustainable manufacturing performance. This study investigates the influence of the four Ps of closed-loop manufacturing systems (product development, production processes, people and policies) on sustainable manufacturing performance (SMP).
Design/methodology/approach
To investigate the influence of the four Ps on SMP, a hybrid analytical model was employed, combining structural equation modeling (SEM) with artificial neural networks (ANN). Data were collected through a structured survey administered to 353 manufacturing firms in Malaysia. SEM was used to assess the relationships between the variables, while ANN was employed to capture nonlinear relationships and improve prediction accuracy.
Findings
The research findings demonstrate that product development practices, including eco-design, life cycle assessment and resource planning, exert the most significant influence on SMP. Furthermore, implementing green and lean manufacturing techniques, energy modeling and material utilization/toxicity planning significantly enhances sustainability outcomes. While the social setting (employee motivation, turnover and work–life quality) does not directly impact SMP, it plays a pivotal role in facilitating the implementation of internal environmental policies. Moreover, environmental management practices, both mandatory and voluntary, serve as intermediaries between the four Ps and SMP within closed-loop manufacturing systems.
Practical implications
The findings offer valuable insights for policymakers, industry leaders and manufacturing organizations. By prioritizing product development, implementing green and lean manufacturing practices and fostering a positive social setting, organizations can significantly enhance their sustainable performance. Additionally, the study highlights the importance of effective environmental management practices in mediating the relationship between other factors and SMP.
Originality/value
This study contributes to the literature by providing a comprehensive framework for understanding the factors that drive sustainable manufacturing performance. The hybrid SEM-ANN model offers a robust and innovative approach to analyzing the complex relationships between the four Ps and SMP.