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Completing Right-of-Way (ROW) acquisition process on schedule is critical to avoid delays and cost overruns on transportation projects. However, transportation agencies face challenges in accurately forecasting ROW acquisition timelines in the early stage of projects due to complex nature of acquisition process and limited design information. There is a need of improving accuracy of estimating ROW acquisition duration during the early phase of project development and quantitatively identifying risk factors affecting the duration.

The quantitative research methodology used to develop the forecasting model includes an ensemble algorithm based on decision tree and adaptive boosting techniques. A dataset of Georgia Department of Transportation projects held from 2010 to 2019 is utilized to demonstrate building the forecasting model. Furthermore, sensitivity analysis is performed to identify critical drivers of ROW acquisition durations.

The forecasting model developed in this research achieves a high accuracy to predict ROW durations by explaining 74% of the variance in ROW acquisition durations using project features, which is outperforming single regression tree, multiple linear regression and support vector machine. Moreover, number of parcels, average cost estimation per parcel, length of projects, number of condemnations, number of relocations and type of work are found to be influential factors as drivers of ROW acquisition duration.

This research contributes to the state of knowledge in estimating ROW acquisition timeline through (1) developing a novel machine learning model to accurately estimate ROW acquisition timelines, and (2) identifying drivers (i.e. risk factors) of ROW acquisition durations. The findings of this research will provide transportation agencies with insights on how to improve practices in scheduling ROW acquisition process.

The emergence of networks within education has been driven by a number of factors, including: the complex nature of the issues facing education, which are typically too great for single schools to tackle by themselves; changes to educational governance structures, which involve the hollowing out of the middle tier and the introduction of new approaches with an individualized focus; in addition is the increased emphasis on education systems that are “self-improving and school-led”. Within this context, the realization of teacher and school improvement actively emerges from establishing cultures of enquiry and learning, both within and across schools. Since not every teacher in a school can collaboratively learn with every other teacher in a network, the most efficient formation of networks will comprise small numbers of teachers learning on behalf of others.

Within this context, Professional Learning Networks (PLNs) are defined as any group who engage in collaborative learning with others outside of their everyday community of practice; with the ultimate aim of PLN activity being to improve outcomes for children. Research suggests that the use of PLNs can be effective in supporting school improvement. In addition, PLNs are an effective way to enable schools to collaborate to improve educational provision in disadvantaged areas. Nonetheless harnessing the benefits of PLNs is not without challenge. In response, this paper explores the notion of PLNs in detail; it also sheds light on the key factors and conditions that need to be present if PLNs are to lead to sustained improvements in teaching and learning. In particular, the paper explores the role of school leaders in creating meaningful two-way links between PLNs and their schools, in order to ensure that both teachers and students benefit from the collaborative learning activity that PLNs foster. The paper concludes by suggesting possible future research in this area.

Earned value management systems (EVMS), also called integrated project and program management systems, have been greatly examined in the literature, which has typically focused on their technical aspects rather than social. This study aims to hypothesize that improving both the technical maturity of EVMS and the social environment elements of EVMS applications together will significantly impact project performance outcomes. For the first time, empirical evidence supports a strong relationship between EVMS maturity and environment.

Data was collected from 35 projects through four workshops, attended by 31 industry practitioners with an average of 19 years of EVMS experience. These experts, representing 23 organizations, provided over 2,800 data points on sociotechnical integration and performance outcomes, covering projects totaling $21.8 billion. Statistical analyses were performed to derive findings on the impact of technical maturity and social environment on project success.

The results show statistically significant differences in cost growth, compliance, meeting project objectives and business drivers and customer satisfaction, between projects with high EVMS maturity and environment and projects with poor EVMS maturity and environment. Moreover, the technical and social dimensions were found to be significantly correlated.

Key contributions include a novel and tested performance-driven framework to support integrated project management using EVMS. The adoption of this detailed assessment framework by government and industry is driving a paradigm shift in project management of some of the largest and most complex projects in the U.S.; specifically transitioning from a project assessment based upon a binary approach for EVMS technical maturity (i.e. compliant/noncompliant to standards) to a wide-ranging scale (i.e. 0–1,000) across two dimensions.

This paper aims to examine the static compression characteristics of cell topologies in body-centered cubic with vertical struts (BCCZ) and face-centered cubic with vertical struts (FCCZ) along with novel BCCZZ and FCCZZ lattice structures.

The newly developed structures were obtained by adding extra interior vertical struts into the BCCZ and FCCZ configurations. The samples, composed of the AlSi10Mg alloy, were fabricated using the selective laser melting (SLM) additive manufacturing technique. The specific compressive strength and failure behavior of the manufactured lattice structures were investigated, and comparative analysis among them was done.

The results revealed that the specific strength of BCCZZ and FCCZZ samples with 0.5 mm strut diameter exhibited approximately a 23% and 18% increase, respectively, compared with the BCCZ and FCCZ samples with identical strut diameters. Moreover, finite element analysis was carried out to simulate the compressive response of the lattice structures, which could be used to predict their strength and collapse mode. The findings showed that while the local buckling of lattice cells is the major failure mode, the samples subsequently collapsed along a diagonal shear band.

An original and systematic investigation was conducted to explore the compression properties of newly fabricated lattice structures using SLM. The results revealed that the novel FCCZZ and BCCZZ structures were found to possess significant potential for load-bearing applications.

Managing differences is a difficult undertaking, especially considering the difficulties arising from the unconscious functions of our brains. Organisations should strive to counteract the potentially harmful effects of unconscious bias by implementing policies that support bias-aware management and decision-making. Although it is obvious that bias cannot be completely eliminated, there is enough data, as discussed in this work, to demonstrate that unconscious bias and stereotypes can be addressed and decreased with mindfulness-based interventions (MBIs) to some extent. Mindfulness involves the process of bringing non-judgemental awareness to experience by striving for full attention in the present moment. In this context, including mindfulness practises into training programmes for equality, diversity, and inclusion may serve as an accelerator for recognising hidden biases, reducing stereotypes, eliminating discrimination, and encouraging cognitive changes. This chapter explains the ways in which MBIs can be used to promote cognitive changes and comprehend the automatic and unconscious nature of emotions and thoughts in order to remove barriers between all differences in the workplace.

The purpose of this paper is to compare the influence of relative density (RD) and strain rates on failure mechanism and specific energy absorption (SEA) of polyamide lattices ranging from bending to stretch-dominated structures using selective laser sintering (SLS).

Three bending and two stretch-dominated unit cells were selected based on the Maxwell stability criterion. Lattices were designed with three RD and fabricated by SLS technique using PA12 material. Quasi-static compression tests with three strain rates were carried out using Taguchi's L9 experiments. The lattice compressive behaviour was verified with the Gibson–Ashby analytical model.

It has been observed that RD and strain rates played a vital role in lattice compressive properties by controlling failure mechanisms, resulting in distinct post-yielding responses as fluctuating and stable hardening in the plateau region. Analysis of variance (ANOVA) displayed the significant impact of RD and emphasised dissimilar influences of strain rate that vary to cell topology. Bending-dominated lattices showed better compressive properties than stretch-dominated lattices. The interesting observation is that stretch-dominated lattices with over-stiff topology exhibited less compressive properties contrary to the Maxwell stability criterion, whereas strain rate has less influence on the SEA of face-centered and body-centered cubic unit cells with vertical and horizontal struts (FBCCXYZ).

This comparative study is expected to provide new prospects for designing end-user parts that undergo various impact conditions like automotive bumpers and evolving techniques like hybrid and functionally graded lattices.

To the best of the authors' knowledge, this is the first work that relates the strain rate with compressive properties and also highlights the lattice behaviour transformation from ductile to brittle while the increase of RD and strain rate analytically using the Gibson–Ashby analytical model.

Although the literature is clear on what comprises effective project stakeholder management, communication between key stakeholders and project managers is often ineffective. Research is silent on stakeholders' insufficient knowledge of project management terminology, which is a barrier for such effective communication. This paper aims to identify the project management concepts that key stakeholders should understand to improve effective communication.

This paper employs a three-step research design. In the first step, based on threshold concept theory, the authors identify the key project management concepts through interviews with 20 project management practitioners, trainers and trainees. In the second step, the authors confirm the findings from the first step and identify effective approaches to enhance project stakeholders' communication through seven additional interviews with project stakeholders. In the third step, the authors construct a functional model of the research findings by employing a system-level modeling tool.

This research identifies five project management threshold concepts (TC) that are challenging for project stakeholders to understand (1) project benefits, (2) the iron triangle, (3) the critical path, (4) uncertainty and (5) project leadership. Following these knowledge barriers, the paper proposes unique approaches to develop effective project stakeholder communication.

This paper advances project stakeholder management research by identifying knowledge barriers and providing project managers with more effective approaches to better engage with their stakeholders.

To better understand the impact of choosing a carbon data provider for the estimated portfolio emissions across four asset classes. This is important, as prior literature has suggested that Environmental, Social and Governance scores across providers have low correlation.

The authors compare carbon data from four data providers for developed and emerging equity markets and investment grade and high-yield corporate bond markets.

Data on scope 1 and scope 2 is similar across the four data providers, but for scope 3 differences can be substantial. Carbon emissions data has become more consistent across providers over time.

The authors examine the impact of different carbon data providers at the asset class level. Portfolios that invest only in a subset of the asset class may be affected differently. Because “true” carbon emissions are not known, the authors cannot investigate which provider has the most accurate carbon data.

The impact of choosing a carbon data provider is limited for scope 1 and scope 2 data for equity markets. Differences are larger for corporate bonds and scope 3 emissions.

The authors compare carbon accounting metrics on scopes 1, 2 and 3 of corporate greenhouse gas emissions carbon data from multiple providers for developed and emerging equity and investment grade and high yield investment portfolios. Moreover, the authors show the impact of filling missing data points, which is especially relevant for corporate bond markets, where data coverage tends to be lower.

This chapter aims to shed light on the hidden benefits and losses of US-China trade within the framework of unequal exchange theory. After presenting the evolutions of the trade balance between China and the United States, we propose two methods for measuring the unequal exchange between them: one considers the labor content directly incorporated into the exchange; the other focuses on the international values with input-output tables. This allows to present a synthesis of sectoral analyses. Our results show a significant unequal exchange in US-China trade over 1995–2014, the United States being actually the main beneficiary of this trade. Both methods exhibit the inequality in exchange tending to decrease over time; China's disadvantage has been gradually reducing from the 2000s. We finally suggest that the relative decline in the hegemonic status of the United States in this bilateral unequal relationship could help explain its decision to launch its trade war with China.

Over the last three decades, construction projects have increasingly been delivered through alternative delivery methods. As a result, many owners have a range of delivery methods to choose from and aim to use the right one for each of their projects. Researchers have developed several tools and decision-support processes to facilitate this selection procedure. The purpose of this study is to review and discuss differences and common themes across selection tools developed by academic researchers and project owners.

The study reviews prominent selection processes and tools used for infrastructure projects by conducting an in-depth literature review and using the content analysis method to elicit findings on the methodologies and criteria presented in the literature.

This study presents three principal findings. First, findings show three common themes emerge within the selection criteria—characteristics, goals and risks. Second, while academic studies most commonly suggest employing multi-attribute analysis, this study reveals that, in practice, selection tools most frequently employ a staged or gated evaluation based on the type of criteria and their importance to the decision. Finally, this review further highlights the importance of institutional context in decision-making.

This work contributes to the body of knowledge by providing guidance to practitioners and opening new directions for researchers around the way selection criteria are categorized in the relevant literature and the institutional context considerations when structuring or evaluating a selection process or tool.