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The purpose of the paper is to contribute to an understanding of the relational work carried out in mentoring programmes and the implications for learning capabilities in future practices.

This study is based on field research of a mentoring programme bringing together senior and newly graduated workers in a large Swedish health care organisation. In total, 54 qualitative interviews with mentors, mentees, HR, managers and union representatives are included.

The findings point to the role of trust and a psychological sense of community in the socialisation work that goes on in relationships between the mentor and the mentee. This in turn leads to increased social capital in the form of learning and retaining workers. The conditions for being vulnerable and asking questions, as well as daring to be independent, are an essential and decisive part of constructing bonding within the professional group and bridging out to other professions and parts of the organisation.

The practical contribution from this study is the workplace conditions that are central to organising mentoring programmes, with implications for learning capabilities in future practices.

With its theoretical focus on social capital, the study shows the importance of relationships for learning and retaining both newly graduated and experienced employees in a context of high employee turnover. It is central to achieving strong and mutually beneficial relationships through continual and trustful interaction between actors. By using the concepts of social capital, socialisation agents and psychological sense of community, this study contributes to an understanding of mentoring and workplace learning.

This research uses a multifaceted approach to develop an MPA/MPP curriculum to support a data science track within the existing MPA/MPP programs by identifying the core and elective areas needed.

The approach includes (1) identifying a suitable structure for MPA/MPP programs which can allow the program to develop its capacity to train students with the data science and general public administration skills to solve public policy problems and leave explicit space for local experimentation and modification; (2) defining bridging modules and required modules for the MPA/MPP programs; and (3) developing of data science track thought to make suggestions for the inclusion of suitable data science modules into the data science track and benchmarking the data science modules suggested with the best practices developed by other professional bodies. The authors review 46 NASPAA-accredited MPA/MPP programs from 40 (or 22.7%) schools to identify the suitable required modules and some potential data science and analytics courses that MPA/MPP programs currently provide as electives.

The proposal includes a three-course (six–nine credits, not counted in the program but as prerequisites) bridging module, a nine-course (27 credits) required module and a five-course (15 credits) data science track/concentration.

This work can provide a starting point for the public administration education community to develop graduate programs focusing on data science to cater to the needs of both public managers and society at large.

Retirement is a preparation for transitioning from one role to another and transitioning to a new stage of life. The deepening aging of the population encourages the policymakers to start the Bridge Employment plan when the society faces the unprecedented challenges of decreasing labor supply, heavier burdens of retirement and slow economic growth. The purpose of this study, the decision model for Bridge Employment has been developed by systematically reviewing the research literature.

A bibliometric analysis was conducted to cover publications on Bridge Employment for Return to Work published from 1994 to 2023, including a total of 1,936 publications collected from the Web of Science and Scopus. The patterns and trends in terms of sources of publications, intellectual structure and major topics were analyzed.

After carefully examining the results of the selected studies, three categories of individual (micro level), organizational (medium level) and contextual (macro level) factors were identified as effective factors on bridge employment and model development. Each of the mentioned factors, along with the legal, financial, managerial, educational-administrative and consulting requirements, form the basis for the development of the model and decision framework for Paul’s employment.

This model can be a basis as a framework for bridge recruitment planning so that organizations can once again use their skills–knowledge–expertise in different jobs and even training younger people.

This qualitative study aims to provide insights and reflections of how the pandemic affected the identity and a sense of self of students, who completed undergraduate leadership learning academic program.

Interviews.

Findings of this study showed three major themes throughout the interviews. During the COVID-19 pandemic, participants identified experiences with self-reflection, building community and navigating issues of social justice.

These findings highlight how leadership learning enabled certain participants to navigate and seek to resolve these problems and how their leadership learning aided their own self-discovery.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

This research paper set out to explore how an Indonesian organization addressed hiring and training challenges while contributing to society through a Vocational and Education Training (VET) program. The VET intervention, “Project VALERIE,” reduced costs, provided jobs for graduates, and addressed local youth unemployment. Embracing a strategic CSR approach aligned with organizational and societal goals, creating shared value for every stakeholder. Fostering collaborative industry-education partnerships in this way bridged skill gaps and created a reliable talent pipeline. It’s a great example of a strategic win-win approach that other HR teams can replicate.

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

The application of reinforcing old bridges by adding external prestressed steel bundles is becoming more and more widespread. However, the long-term safety performance test of the strengthening method is rarely carried out. In this paper, the bearing capacity of a 420 m prestressed concrete (PC) continuous girder bridge after five years of strengthening is analyzed.

The bridge model of the bridge structure and strengthening scheme is established by the finite element software of the bridge. The theoretical load-bearing capacity of the bridge under the latest standard load grade is obtained by finite element analysis. The actual bearing capacity of the bridge is obtained by field test. Through the comparative analysis of theory and practice, the health state of the bridge after five years of reinforced operation is judged. The damage to the overall stiffness and external prestressing of the bridge is also analyzed.

The results of deflection and strain show that the stiffness and strength of the secondary side span and the middle span decrease slightly, and the maximum reduction of bearing capacity is 4.5%. The static stiffness of the whole bridge decreases as a result of cracks, and the maximum decrease is 21%. In the past five years, the relaxation loss of the external prestressing of the bridge is 3.31–3.97%, which is the main reason for the decrease in bearing capacity.

Through the joint analysis of the bridge stiffness and the loss of external prestressing, the strengthening condition of the bridge after five years of operation is effectively analyzed. The strengthening effect of the external prestressed steel beam strengthening method is analyzed, which can provide a reference for similar bridge strengthening.

Bridge deterioration is a critical risk to public safety, which mandates regular inspection and maintenance to ensure sustainable transport services. Many models have been developed to aid in understanding deterioration patterns and in planning maintenance actions and fund allocation. This study aims at developing a deep-learning model to predict the deterioration of concrete bridge decks.

Three long short-term memory (LSTM) models are formulated to predict the condition rating of bridge decks, namely vanilla LSTM (vLSTM), stacked LSTM (sLSTM), and convolutional neural networks combined with LSTM (CNN-LSTM). The models are developed by utilising the National Bridge Inventory (NBI) datasets spanning from 2001 to 2019 to predict the deck condition ratings in 2021.

Results reveal that all three models have accuracies of 90% and above, with mean squared errors (MSE) between 0.81 and 0.103. Moreover, CNN-LSTM has the best performance, achieving an accuracy of 93%, coefficient of correlation of 0.91, R2 value of 0.83, and MSE of 0.081.

The study used the NBI bridge inventory databases to develop the bridge deterioration models. Future studies can extend the model to other bridge databases and other applications in the construction industry.

This study provides a detailed and extensive data cleansing process to address the shortcomings in the NBI database. This research presents a framework for implementing artificial intelligence-based models to enhance maintenance planning and a guideline for utilising the NBI or other bridge inventory databases to develop accurate bridge deterioration models. Future studies can extend the model to other bridge databases and other applications in the construction industry.

This research aims to create a methodology that integrates optimization techniques into preliminary cost estimates and predicts the impacts of design alternatives of steel pedestrian bridges (SPBs). The cost estimation process uses two main parameters, but the main goal is to create a cost estimation model.

This study explores a flexible model design that uses computing capabilities for decision-making. Using cost optimization techniques, the model can select an optimal pedestrian bridge system based on multiple criteria that may change independently. This research focuses on four types of SPB systems prevalent in Egypt and worldwide. The study also suggests developing a computerized cost and weight optimization model that enables decision-makers to select the optimal system for SPBs in keeping up with the criteria established for that system.

In this paper, the authors developed an optimization model for cost estimates of SPBs. The model considers two main parameters: weight and cost. The main contribution of this study based on a parametric study is to propose an approach that enables structural engineers and designers to select the optimum system for SPBs.

The implications of this research from a practical perspective are that the study outlines a feasible approach to develop a computerized model that utilizes the capabilities of computing for quick cost optimization that enables decision-makers to select the optimal system for four common SPBs based on multiple criteria that may change independently and in concert with cost optimization during the preliminary design stage.

The model can choose an optimal system for SPBs based on multiple criteria that may change independently and in concert with cost optimization. The resulting optimization model can forecast the optimum cost of the SPBs for different structural spans and road spans based on local unit costs of materials cost of steel structures, fabrication, erection and painting works.

The authors developed a computerized model that uses spreadsheet software's capabilities for cost optimization, enabling decision-makers to select the optimal system for SPBs meeting the criteria established for such a system. Based on structural characteristics and material unit costs, this study shows that using the optimization model for estimating the total direct cost of SPB systems, the project cost can be accurately predicted based on the conceptual design status, and positive prediction outcomes are achieved.

Supplier codes of conduct are amongst the most widely used practices in sustainable procurement programs. While there are limitations and risks involved in using supplier codes of conduct (including the risk of greenwashing, a weak link to action and the inability of supplier to comply), there is only a modest amount of research on the topic, other than content analysis. We aim to contribute to research both lessons learned, over a two-decade period, about the implementation and use of a supplier code of conduct from a case study, as well as, to suggest further research that can support the industry and enrich insight into the effective adoption of supply codes of conduct.

Thanks to the support of our co-author from Bayer we are able to share lessons learned by the global procurement team of Bayer and use these as a basis for suggesting questions for further research. The approach of this paper centres on the adoption and implementation of the supplier code of conduct in an effort to complement existing research on supplier codes of conduct that is largely focused on code of conduct content, less on the implementation of codes of conduct. The collaboration with our co-author from Bayer enables direct access to experiences and managerial perspectives. By considering the two-decade journey towards more sustainable supply chain management at Bayer, we are able to achieve a longitudinal perspective on adoption and implementation aspects.

Bayer ensures personal and community engagement in its sustainable procurement program in order to drive action and improve decision making along the value chains. The company regularly updates its code of conduct to stay aligned with its maturity and complements the code of conduct with a continuous improvement focus, supported by both generic and industry-specific consortia. The company has not yet been able to establish direct visibility into the conduct of tier 2 and up suppliers.

This paper helps close a gap in the literature and provides input into industry efforts in one of the most widely used practices in sustainable procurement. We hope that the research questions that we developed based on the first 20+ years of Bayer’s learning journey towards sustainable procurement will inspire research that can impact industry efforts towards creating a more sustainable future.

This study aims to explore the influence of Mutqen programmes on university students’ personality and skills development. It evaluates the cognitive attitudes of university student participants in Mutqen training programmes. The research was analysed thematically, and this paper reports on the roles businesses and universities play in enhancing students’ personality and skills and the importance of knowledge acquisition to develop students’ career prospects.

Using a quantitative research approach, the study used a descriptive survey design. A total of 1,039 respondents based in Saudi Arabia participated voluntarily in the survey.

The results revealed a positive impact from Mutqen programmes on students’ personality and skills development. Moreover, the outcomes demonstrated that the Mutqen programmes promote knowledge acquisition, which enhances future career readiness by enabling students to positively develop their awareness of potential future career requirements.

The critical contribution of this paper is that it empirically evaluates the perceived impact of social corporate training programmes on students’ personality and skills development from the perspective of the students themselves.