Earned value management (EVM) is a project management approach that can enhance the probability of project success. It is applied widely across different industry sectors (e.g., energy, aerospace, construction, defense, and manufacturing), generally through the use of an earned value management system (EVMS). A holistic and up-to-date literature review on EVM and EVMS does not exist. A literature review can provide a comprehensive perspective on the topic, identifying and summarizing the existing body of knowledge, as a foundation to advance the state of practice of EVM/EVMS. Therefore, the objective of this paper is to investigate the EVM/EVMS state of the art by critically reviewing academic and industry publications, with a specific focus on the maturity of EVMS and the environment surrounding its implementation. By performing a systematic literature review, the authors identified 600 publications since the inception of the EVM concept in 1962, and then narrowed down this list to 160 relevant publications from the last decade for closer review. The findings include the discovery of eight emergent themes. Of these themes, "forecasting/prediction" constitutes the largest portion of the recent literature, followed by "application of EVMS." One interesting finding is that EVMS maturity, although being a critical topic, is only discussed in one publication. Publications focused on EVM/EVMS have increased in the last decade and significant differences were found between academia and industry literature in terms of the limitations and extensions of EVM/EVMS, EVMS environment, and compliance. A key finding is that designing a reliable EVMS should combine both technical and social aspects of implementation. This forward-looking paper provides a state-of-the-art review while highlighting gaps in the existing EVM/EVMS body of knowledge and introducing new perspectives to support EVMS research and application.

Generative design is the alteration of an object's shape to optimize its function. Currently, the scope of generative design is limited in the structural civil engineering field. Structural design still follows conventional methods compatible with conventional construction processes. These processes restrict the flexibility in design resulting in structural elements having excess materials to satisfy critical structural capacity requirements. This introduces additional costs and higher environmental impacts. New tools, such as concrete and steel 3D printers, are emerging to enable more complex geometries in construction allowing higher flexibility in design options. Inspired by the above, this paper aims at developing a design engine that provides optimal design solutions to reinforced concrete beams with sufficient structural capacities while using less materials and resources. Based on ACI code design guidelines, a cantilever beam was structurally analyzed to relate geometry parameters to structural capacity. Optimization was achieved by minimizing the depth and the steel reinforcement ratio at each segment along its length. Hence, concrete and steel at each location would take their optimal quantities. This results in lighter and more economic structures conforming to the structural capacities required by the codes. The engine is based on three objective functions that solve for the minimum values of beam depth and reinforcement at each section which optimize cost and CO2 emissions individually or simultaneously. MATLAB was used to design the optimized beam and to calculate the percentage decrease in cost and CO2 emissions between the optimized and conventional beam. A significant reduction ranging between 40% and 52% of cost and between 39% and 51% of CO2 emissions per beam is achieved. If the design engine developed was utilized in parallel with the 3D printing construction method, structures with optimized quantities, materials, and shapes would be developed. Thus, minimizing drastic effects on the environment and achieving reduced costs.

The sustainability movement is increasingly impacting the construction industry, which has been quick to adopt innovative methods to deliver sustainable facilities. The literature shows that energy consumption in the building sector is increasing at a rate comparable to those of industrial and transportation sectors, and that buildings are responsible for close to 40 percent of energy use and 74 percent of electricity retail sales. Numerous studies also show that this sector has high potential for energy savings and pollution reduction. There is an opportunity for stakeholders of the architecture, engineering, and construction industry to increase their revenues in delivering green buildings. Accordingly, this study presents quantitative analyses of green contractors’ market performance in terms of topline revenue. More than a decade’s worth of business data was used to perform statistical analyses to gauge and discover the green building construction revenue growth over the past decade, uncover trends and develop a forecasting model for the next decade. Results indicate that there is an average 3.7 percent growth in green building revenue on a yearly basis, and that green building revenue constitutes about 35 percent of the total revenue for the top 100 green building contractors, with an expected increase of $3 billion every year. Such findings give researchers a retrospective look at the green contractors’ market performance to investigate the underlying reasons for such significant growth, while also providing practitioners with a forecasted growth rate informing their decision to grow their green building business.

Methods to collect data in construction engineering and management (CEM) research are evolving, informed by recent technological advancements. One such method is research charrettes that allow effective interactions and knowledge sharing between expert industry practitioners and academic researchers, all colocated in a single venue, enabling rich data collection and live communication. A pivot point in technological evolution occurred with the COVID-19 pandemic, forcing a global shift to remote work. Hence, planned in-person research charrettes had to shift to remote sessions, relying on virtual conferencing platforms and online data collection mechanisms. Technology-enabled charrettes have allowed the authors to collect significantly richer data sets and ensure a more diverse representation of participants, while saving tremendous amounts of time. With the continuing emergence of technological applications, the world might not go back to functioning fully in person. The authors believe remote research charrettes (RRCs) will still be used in a post-COVID-19 world because of their superior performance. This paper builds on a previous publication that described traditional research charrettes as a method to enhance CEM research a decade ago; it offers a significantly updated and improved RRC method based on the knowledge gained from transitioning a dozen in-person charrettes into RRCs. It also presents performance comparisons between RRCs and traditional charrettes by quantifying metrics indicating how RRCs are more time-efficient and cost-saving, harness more participants from more diverse locations, and enable the collection of richer data sets and four times more industry comments and expert feedback. This paper also provides guidance on the integration of technology with traditional research charrettes, hence contributing to the CEM body of knowledge.