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The paper identifies and explores the perspectives of middle school educators regarding the benefits and challenges of an ongoing, emerging school–university partnership. Over five years, professors at one comprehensive, Midwestern university, formed a partnership with a local middle school. While progress has been made to develop the partnership, the authors recognized a lack of shared governance (Essential 7). In particular, they were unsure the partnership was mutually beneficial. The authors interviewed teachers, the principal, assistant principals, guidance counselors, the instructional coach and the youth service center director to gain their perspectives on the partnership.

The authors used an intrinsic, evaluative case study to examine educators perceptions of the benefits and challenges of the partnership (Guba & Lincoln, 1981; Patton, 2002). This approach was used because within this bounded system the authors have an interest in obtaining information to help improve the program and partnership.

Results suggest the partnership was beneficial in a number of ways including hiring of and offering fresh ideas to teachers. Educators also felt there were many benefits for university candidates. Challenges included scheduling, technology access and candidate disposition. Implications are discussed.

Inherent within the research methodology, researchers’ inclusion in the data collection process may affect participants responses.

Researchers discuss the implications of this work, including the role of hiring candidates and clear articulation of a mission for the partnership.

This work adds to research on school site stakeholders’ perspectives on the value of school–university partnerships and includes teachers and the schools’ entire leadership team.

In repetitive projects, repetition offers more possibilities for activity scheduling at the sub-activity level. However, existing resource-constrained repetitive scheduling problem (RCRSP) models assume that there is only one sequence in performing the sub-activities of each activity, resulting in an inefficient resource allocation. This paper proposes a novel repetitive scheduling model for solving RCRSP with soft logic.

In this paper, a constraint programming model is developed to solve the RCRSP using soft logic, aiming at the possible relationship between parallel execution, orderly execution or partial parallel and partial orderly execution of different sub activities of the same activity in repetitive projects. The proposed model integrated crew assignment strategies and allowed continuous or fragmented execution.

When solving RCRSP, it is necessary to take soft logic into account. If managers only consider the fixed logic between sub-activities, they are likely to develop a delayed schedule. The practicality and effectiveness of the model were verified by a housing project based on eight different scenarios. The results showed that the constraint programming model outperformed its equivalent mathematical model in terms of solving speed and solution quality.

Available studies assume a fixed logic between sub-activities of the same activity in repetitive projects. However, there is no fixed construction sequence between sub-activities for some projects, e.g. hotel renovation projects. Therefore, this paper considers the soft logic relationship between sub-activities and investigates how to make the objective optimal without violating the resource availability constraint.

The target of this research is to develop a mathematical model which combines the Resource-Constrained Multi-Project Scheduling Problem (RCMPSP) and the Multi-Skilled Resource-Constrained Project Scheduling Problem (MSRCPSP). Due to the importance of resource management, the proposed formulation comprises resource leveling considerations as well. The model aims to simultaneously optimize: (1) the total time to accomplish all projects and (2) the total deviation of resource consumptions from the uniform utilization levels.

The K-Means (KM) and Fuzzy C-Means (FCM) clustering methods have been separately applied to discover the clusters of activities which have the most similar resource demands. The discovered clusters are given to the scheduling process as priori knowledge. Consequently, the execution times of the activities with the most common resource requests will not overlap. The intricacy of the problem led us to incorporate the KM and FCM techniques into a meta-heuristic called the Bi-objective Symbiosis Organisms Search (BSOS) algorithm so that the real-life samples of this problem could be solved. Therefore, two clustering-based algorithms, namely, the BSOS-KM and BSOS-FCM have been developed.

Comparisons between the BSOS-KM, BSOS-FCM and the BSOS method without any clustering approach show that the clustering techniques could enhance the optimization process. Another hybrid clustering-based methodology called the NSGA-II-SPE has been added to the comparisons to evaluate the developed resource leveling framework.

The practical importance of the model and the clustering-based algorithms have been demonstrated in planning several construction projects, where multiple water supply systems are concurrently constructed.

Reviewing the literature revealed that there was a need for a hybrid formulation that embraces the characteristics of the RCMPSP and MSRCPSP with resource leveling considerations. Moreover, the application of clustering algorithms as resource leveling techniques was not studied sufficiently in the literature.

Compressing the schedule by using overlapping activities is a commonly adopted approach for accelerating projects. However, this approach might channel a variety of risks into the construction processes. Risks imply waste; still, evaluating the effects of using overlapping activities on schedule quality has been a looming gap in construction research. Therefore, this paper aims to study the quality of overlapping in terms of emerging waste and to demarcate the boundaries of the overlapping envelope.

This study presents a method for assessing the consequences of implementing overlapping activities in a schedule on two types of waste namely waiting time and variation gap. A critical path method (CPM) network including eleven activities is modeled stochastically where the durations of individual activities are sampled as beta-distributions. Using program evaluation and review technique (PERT) assumptions to calculate the schedule dates, the network is simulated for various amounts of overlapping and the corresponding waste is quantified each time.

Results show that not only the returns on overlapping are diminishing after a certain overlap percentage, but also waste in the production system increases. Particularly, results reveal that compressing the schedule leads to a decrease in variation gaps, but at the same time, it leads to a larger increase in waiting times, which creates more waste.

The presented study shows through simulation how overlapping activities affects productivity by identifying wastes. It shows that despite the apparent gains, overlaps should be used with caution, and while considering the side-effects of increased waste which introduces a need for increased managerial awareness.

The purpose of this study is to develop an integrated model for the stochastic multiproject scheduling and material ordering problems, where some of the prominent features of offshore projects and their environmental-degrading effects have been embraced as well. The durations of activities are uncertain in this model. The developed formulation is tri-objective that seeks to minimize the expected time, total cost and CO₂ emission of all projects.

A new version of the multiobjective multiagent optimization (MOMAO) algorithm has been proposed to solve the amalgamated model. To empower the MOMAO, various procedures of this algorithm have been modified based on the multiattribute utility theory (MAUT) technique. Along with the MOMAO, this study has employed four other meta-heuristic methodologies to solve the model as well.

The outputs of the MOMAO have been put to test against four other optimizers in terms of convergence, diversity, uniformity and computation times. The results of the Mean Ideal Distance (MID) metric have revealed that the MOMAO has strongly prevailed its rival optimizers. In terms of diversity of the acquired solutions, the MOMAO has ranked the first among all employed optimizers since this algorithm has offered the best solutions in 56.66 and 63.33% of the test problems regarding the diversification metric and hyper-volume metrics. Regarding the uniformity of results, which is measured through the spacing metric (SP), the MOMAO has presented the best SP values in more than 96% of the test problems. The MOMAO has needed more computation times in comparison to its rivals.

A real case study comprising two concurrent offshore projects has been offered. The proposed formulation and the MOMAO have been implemented for this case study, and their effectiveness has been appraised.

Very few studies have focused on presenting an integrated formulation for the stochastic multiproject scheduling and material ordering problems. The model embraces some of the characteristics of the offshore projects which have not been adequately studied in the literature. Limited capacities of the offshore platforms and cargo vessels have been embedded in the proposed model. The offshore platforms have spatial limitations in storing the required materials. The vessels are also capacitated and they also have limited shipment capacities. Some of the required materials need to be transported from the base to the offshore platform via a fleet of cargo vessels. The workforces and equipment can become idle on the offshore platform due to material shortage. Various offshore-related costs have been integrated as a minimization objective function in the model. The cargo vessels release CO₂ detrimental emissions to the environment which are sought to be minimized in the developed formulation. To the best of the authors' knowledge, the MOMAO has not been sufficiently employed as a solution methodology for the stochastic multiproject scheduling and material ordering problems.

This study aims to explore the career transition process of women professionals when they return to the workplace after a break and re-integrate with their career aspirations.

This research used a qualitative approach with semi-structured interviews for data collection. All 20 women participants have returned to their careers after a break.

The data analysis reveals women’s career transition and re-integration process into the workplace after a career break. Supervisory support, work–life balance practices, role models, coworker support and career success emerged as factors enabling successful transition. The employing organisations’ diversity, equity and inclusion (DEI) hiring strategy emerged as an important mechanism for re-entry.

Although previous research has studied women professionals returning after a break, the “transition process” that enables re-entry is missing.

Staffing is one of the most influential human resource (HR) activities and is the primary method of hiring and retaining human resources. Among staffing’s several activities, recruitment and selection are one of the most crucial activities. It is possible to rehire former firm employees using the talent management strategy known as “boomerang recruitment”. The boomerang recruitment trend has tremendously grown because many employees who believe they are qualified for the position now wish to return to their old employers. According to data, boomerang employees can be 50% less expensive than conventional ways of hiring. The purpose of this study is to identify the generic critical factors that play a role in the boomerang hiring process based on the literature review. Next, the objective is to determine the relative weight of each of these factors, rank the candidates, and develop a decision-making model for boomerang recruitment.

This paper focuses on the grey-based multicriteria decision-making (MCDM) methodology for recruiting some of the best candidates out of a few who worked for the organization earlier. The grey theory yields adequate findings despite sparse data or significant factor variability. Like MCDM, the grey methods also incorporate experts' opinions for evaluation. Furthermore, sensitivity analysis is also done to show the robustness of the suggested methodology.

Seven (7) recruitment criteria for boomerang employees were identified and validated based on the opinions of industry experts. Using these recruitment criteria, three candidates emerged as the top three and created a pool out of six. In addition, this study finds that Criteria 1 (C1), the employee's past performance, is the most significant predictor among all other criteria in boomerang hiring.

Since the weights and ratings of attributes and alternatives in MCDM methods are primarily based on expert opinion, a significant difference in expert opinions (caused by differences in their knowledge and qualifications) may impact the values of the grey possibility degree. However, enough attention was taken while selecting the experts for this study regarding their expertise and subject experience.

The proposed method provides the groundwork for HR management. Managers confronted with recruiting employees who want to rejoin may use this model. According to experts, each attribute is not only generic but also crucial. In addition, because these factors apply to all sectors, they are industry-neutral.

To the best of the authors’ knowledge, this is the first study to apply a grey-based MCDM methodology to the boomerang recruitment model. This study also uses an example to explain the computational intricacies associated with such methods. The proposed system may be reproduced for boomerang recruiting in any sector because the framework is universal and replicable. Furthermore, the framework is expandable to include new criteria for different work.

Ores and minerals are extracted from the earth’s crust depending on the type of deposit. Iron ore mines come under massive deposit patterns and have their own mine development and life cycles. This study aims to depict the development and life cycle of large open-pit iron ore mines and the intertwined organizational design of the departments/sections operated within the industry.

Primary data were collected on the site by participant observation, in-depth interviews of the field staff and executives, and field notes. Secondary data were collected from the literature review to compare and cite similar or previous studies on each mining activity. Finally, interactions were conducted with academic experts and top field executives to validate the findings. An organizational ethnography methodology was employed to study and analyse four large-scale iron ore mines of India’s largest iron-producing state, Odisha, from January to April 2023.

Six stages were observed for development and life cycle, and the operations have been depicted in a schematic diagram for ease of understanding. The intertwined functioning of organizational set-up is also discovered.

The paper will benefit entrepreneurs, mining and geology students, new recruits, and professionals in allied services linked to large iron ore mines. It offers valuable insights for knowledge enhancement, operational manual preparation and further research endeavours.

Research indicates that inconsistent gender norm presentations are met with backlash, which is particularly damaging to women. With social media use in selection rising, it is important to understand if this remains consistent for job applicants on social media.

In two experiments, this study investigates hiring managers' reactions to job applicant (in)consistent gender norm-based communication on Facebook (n = 197) and YouTube (n = 203). Participants located in the United States were asked to review social media materials, reported perceptions of task and social attraction, and make hiring recommendations.

Inconsistent with work on backlash in face-to-face settings, results demonstrated that masculine communication styles on social media may be detrimental to job seekers, and this was more pronounced for male job seekers. Feminine presentation styles had more favorable results.

The findings challenge the long-held understanding that men have more leeway to behave in agentic ways in job seeking contexts. While this may remain true in face-to-face settings, these findings suggest that social media, lacking media richness, may be a context in which males experience backlash for agentic behavior.

The research offers a novel perspective investigating traditional gender expectations in the digital realm, paving the way for a more comprehensive understanding of gender in employment contexts. This study contributes to the growing body of research on online behavior and expands understanding of how hiring managers react to gender norms in the era of social media.

This paper aims to investigate the direct relationship between green human resource management (GHRM) practices and environmental performance (EP) in Palestinian universities, as well as the mediating role of management support (MS) and green organisational culture (GOC) in this relationship.

A quantitative approach was used in this study. The data were collected from 351 employees working in Palestinian universities through a questionnaire and analysed using partial least squares structural equation modelling.

The study finds that the implementation of GHRM practices positively enhances EP. The results further demonstrate that GHRM practices influence both MS and GOC. Furthermore, this study reveals that both MS and GOC play a significant role in mediating the relationship between GHRM and EP.

This study adds to the existing literature by providing a conceptual framework and empirical evidence of the correlation between GHRM, GOC, MS and EP, specifically in university settings. Educational institutions can use this study’s findings to foster a green culture and gain endorsement from top-level management. This approach promotes the adoption of eco-friendly practices and the development of environmental strategies that can influence EP.

This study contributes to the field by enhancing the understanding of the ability–motivation–opportunity theory in the context of Palestinian universities. Specifically, this study investigates how GHRM practices and GOC establish core competence for sustainable EP. Furthermore, the findings reveal a positive influence of GHRM practices on both GOC and MS. Finally, this study’s empirical evidence highlights the significance of GHRM practices in fostering GOC, MS and, ultimately, improving EP within universities.