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Various approaches have emerged to assist practitioners in making more informed decisions in highway construction projects. However, industry practitioners are still using subjective ways to make decisions. Also, researchers have developed tools and techniques with similar objectives. Lack of information on what has been developed might lead to those issues. Therefore, this paper aims to review trends of evolution, pinpoint strengths and gaps in the literature and identifies potential future directions for decision-making research in highway construction projects.

A systematic review was conducted on published articles on decision-making in highway construction projects using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) technique.

The analysis of 101 articles revealed that existing decision-making research in highway construction projects targets improvements in four areas: feasibility, conceptual, detailed scope and detailed design. The four areas consist of sixteen subthemes that are detailed in this study. In addition, most research involved developing decision support tools and systems as well as decision-making models, techniques and frameworks. Lastly, several research areas have emerged, such as adding more decision criteria including those with uncertainties, expanding existing decision-making models into decision support systems, benchmarking decision criteria between different sample populations and exploring inter-and intra-relationships between decision criteria.

This paper provides an overview of existing research on decision-making in highway construction projects. Also, it reveals research gaps in the body of knowledge to point out directions for future research. Finally, industry practitioners can use the findings to develop strategies for effective decision-making processes.

Soil is an essential component of road construction and is used in the form of subgrade materials. It ensures the stability and durability of the road under adverse conditions; being one of the important parameters, poor judgment of the engineering properties of soil can lead to pavement failure. Geopathic stress (GS) is a subtle energy in the form of harmful electromagnetic radiation. This study aims to investigate the effect of GS on soil and concrete.

A total of 23 soil samples from stress zones and nonstress zones were tested for different engineering properties like water content, liquid limit, plastic limit, specific gravity and California bearing ratio. Two concrete panels were placed on GS zones, and their quality was monitored through nondestructive testing for a period of one year.

The result shows that the engineering properties of soil and pavement thickness are increasing in stress zones as compared with nonstress zones. For concrete panels, as time passes, the quality of the concrete gets reduced, which hints toward the detrimental effect of GS.

This research is a systematic, scientific, reliable study which evaluated subgrade characteristics thus determining the detrimental impact of the GS on soil and pavement thickness. On a concluding note, this study provides a detailed insight into the performance of the road segment when subjected to GS. Through this investigation, it is recommended that GS should be considered in the design of roads.

To proactively draw efficient maintenance plans, road agencies should be able to forecast main road distress parameters, such as cracking, rutting, deflection and International Roughness Index (IRI). Nonetheless, the behavior of those parameters throughout pavement life cycles is associated with high uncertainty, resulting from various interrelated factors that fluctuate over time. This study aims to propose the use of dynamic Bayesian belief networks for the development of time-series prediction models to probabilistically forecast road distress parameters.

While Bayesian belief network (BBN) has the merit of capturing uncertainty associated with variables in a domain, dynamic BBNs, in particular, are deemed ideal for forecasting road distress over time due to its Markovian and invariant transition probability properties. Four dynamic BBN models are developed to represent rutting, deflection, cracking and IRI, using pavement data collected from 32 major road sections in the United Arab Emirates between 2013 and 2019. Those models are based on several factors affecting pavement deterioration, which are classified into three categories traffic factors, environmental factors and road-specific factors.

The four developed performance prediction models achieved an overall precision and reliability rate of over 80%.

The proposed approach provides flexibility to illustrate road conditions under various scenarios, which is beneficial for pavement maintainers in obtaining a realistic representation of expected future road conditions, where maintenance efforts could be prioritized and optimized.

Sustainable development goals (SDGs) are gaining significant importance in the current environment. Many businesses are keen to adopt SDGs to get a competitive edge. There are certain challenges in realigning the present working scenario for sustainable development, which is a primary concern for society. Various firms are adopting sustainable engineering (SE) practices to tackle such issues. Artificial intelligence (AI) is an emerging technology that can help the ineffective adoption of sustainable practices in an uncertain environment. In this regard, there is a need to review the current research practices in the field of SE in AI. The purpose of the present study is to comprehensive review the research trend in the field of SE in AI.

This work presents a review of AI applications in SE for decision-making in an uncertain environment. SCOPUS database was considered for shortlisting the articles. Specific keywords on AI, SE and decision-making were given, and a total of 127 articles were shortlisted after implying inclusion and exclusion criteria.

Bibliometric study and network analyses were performed to analyse the current research trends and to see the research collaboration between researchers and countries. Emerging research themes were identified by using structural topic modelling (STM) and were discussed further.

Research propositions corresponding to each research theme were presented for future research directions. Finally, the implications of the study were discussed.

This work presents a systematic review of articles in the field of AI applications in SE with the help of bibliometric study, network analyses and STM.

To extend the reuse method and rate of straw biomass, this paper investigated the effect of lignin synthetic phenolic resin (LPF) on the rheological properties of asphalt binder.

Four LPFs with 25%, 50%, 75% and 100% substitution rates were prepared by replacing phenol with lignin in synthetic resins and using it as a modifier to prepare a bio-asphalt binder. Temperature sweep tests were conducted to evaluate aging resistance and temperature sensitivity of the bio-asphalt binder. The rutting resistance of the bio-asphalt binder was evaluated by frequency sweeps and multiple stress creep recovery (MSCR) test. Linear amplitude sweep (LAS) tests were conducted to evaluate the fatigue resistance of the bio-asphalt binder. A master curve was constructed to further analyze the rheological properties of the bio-asphalt binder at different frequencies. The low-temperature cracking resistance of the binder was evaluated by G-R parameters, critical temperatures and ΔTc. Fourier transform infrared spectroscopy (FTIR) was performed to investigate the changes in the functional groups of the binder before and after aging.

The results indicated that adding LPF could improve the high-temperature rutting resistance, fatigue resistance, aging resistance of asphalt and the binders are less affected by temperature. Additionally, LPF slightly prohibited the low-temperature performance of the asphalt binder, which, however, was significantly lower than the base asphalt degradation during aging. Compared with base asphalt binders, the bio-asphalt binder showed no new absorption peaks generated after adding LPF, identifying that the improved asphalt binder performance by LPF was a mainly physical modification.

The main objective of this paper is to further improve the substitution rate (i.e. the mass substitution ratio of lignin to phenol) of lignin and broaden the application of biomass resins, thus realizing resource sustainability.

There are various methods to assess the failure of a road construction project that does not meet quality and performance standards. This study aims to evaluate the factors affecting the quality management of road construction projects in Indonesia by identifying the critical challenges in implementing quality management processes and examining the countermeasures to address these problems.

In this research, the quality management processes in Indonesian road construction projects are evaluated using a mixed quantitative and qualitative approach. Quantitative data obtained from two rounds of Delphi questionnaire surveys as the primary data source, and focus group interviews as the qualitative data are used to achieve the aims of this study.

It is found that from as early as in the preconstruction stage of a project, the availability of quality standards and documentation is problematic when implementing quality management processes. The critical factor of the quality control activities of a project and the quality management roles and responsibilities of the stakeholders during road construction is the project team. This constraint deals with the interaction of the competency, commitment, and mutual cooperation among the main stakeholders to ensure that quality management processes are implemented. This implementation is a part of controlling the road pavement materials, supervising the project activities according to a specified standard, and reporting the project performance. The findings of this study add parameters relating to quality management and quality processes in a road construction project area.

This study is the first to evaluate the quality management processes in the construction of Indonesian road projects. The investigation identifies and evaluates the causes of the persistence of poor road quality. All revealed constraints are substantial factors that hinder the implementation of quality management processes when delivering quality road products. This study addresses the key influencing factors and scenarios related to quality management during road construction projects in Indonesia and other developing countries as practical examples and provides case-based insights for construction practitioners and civil engineering academics in developed countries.

The implementation of smart maintenance (SM) has greatly benefited facility managers, construction project managers and other stakeholders within the built environment. Unfortunately, its actualization for stakeholders in the built environment in the fourth industrial revolution (4IR) era remains a challenge. To reduce the challenge, this study aims at conducting a bibliometric analysis to unearth the critical success factors supporting SM implementation. The future direction and practice of SM in the construction industry were also explored.

A bibliometric approach was adopted for reviewing articles extracted from the Scopus database. Keywords such as (“smart maintenance“) OR (“intelligent maintenance”) OR (“technological maintenance”) OR (“automated maintenance”) OR (“computerized maintenance”) were used to extract articles from the Scopus database. The studies were restricted between 2006 and 2021 to capture the 4IR era. The initial extracted papers were 1,048; however, 288 papers were selected and analysed using VOSviewer software.

The findings revealed that the critical success factors supporting the implementation of SM in the 4IR era are collaboration, digital twin design, energy management system and decentralized data management system. Regarding the future practice of SM in the 4IR era, it was also revealed that SM is possible to evolve into maintenance 4.0. This will support the autonomous maintenance of infrastructures in the built environment.

The use of a single database contributed to the limitation of the findings from this study.

Despite the limitations, the findings of this study contributed to practice and research by providing stakeholders in the built environment with the direction of SM practice.

Stakeholders in the built environment have clamoured to implement SM in the 4IR era. This study provided the critical success factors for adopting SM, guaranteeing the 4IR era. It also provides the research trends and direction of SM practice.

From a technological determinist perspective, machine learning (ML) may significantly contribute towards sustainable development. The purpose of this study is to synthesize prior literature on the role of ML in promoting sustainability and to encourage future inquiries.

This study conducts a systematic review of 110 papers that demonstrate the utilization of ML in the context of sustainable development.

ML techniques may play a vital role in enabling sustainable development by leveraging data to uncover patterns and facilitate the prediction of various variables, thereby aiding in decision-making processes. Through the synthesis of findings from prior research, it is evident that ML may help in achieving many of the United Nations’ sustainable development goals.

This study represents one of the initial investigations that conducted a comprehensive examination of the literature concerning ML’s contribution to sustainability. The analysis revealed that the research domain is still in its early stages, indicating a need for further exploration.

The purpose of this paper is to examine the use of phragmites australis ash (PAA) in cementitious systems to achieve sustainable construction.

In this paper, the properties of mortar containing PAA as partial cement replacement are determined. The PAA is produced through slow burning in a closed system to minimize the CO₂ emission. A total of four mortar mixes are prepared with PAA replacement levels ranging from 0% to 30% by weight. The water to binder and the proportions of binder to sand are 0.55 and 1:3 by weight, respectively. The properties tested are density, compressive strength, flexural strength, ultrasonic pulse velocity, water absorption by total immersion and capillary rise. Testing is conducted at 1, 7, 28 and 90 days.

While there is a decrease in strength as the amount of PAA increases, there is strong indication of pozzolanic reaction in the presence of PAA. This is in agreement with the results reported by Salvo et al. (2015), where they found noticeable pozzolanic activities in the presence of straw ash, which is rich in SiO₂ and relatively high K₂O content. At 90 days of curing, there is a decrease of 5% in compressive strength at 10% PAA replacement. However, at 20% and 30% replacement, the reduction in compressive strength is 23% and 32%, respectively. The trend in flexural strength and ultrasonic pulse velocity is similar to that in compressive strength. The water absorption by total immersion and capillary rise tends to increase with increasing amounts of PAA in the mix. There seems to be a linear relationship between water absorption and compressive strength at each curing age.

The Phragmites australis plant used in this investigation is obtained from one location and this present a limitation as the type of soil may change the properties. Also one method of slow burning is used. Different burning methods may alter the composition of the PAA.

This outcome of this research will contribute towards sustainable development as it will make use of the waste generated, reduce the amount of energy-intensive cement used in construction and help generate local employment in the area where the Phragmites australis plant grows.

To the best knowledge of the authors, the ash from the Phragmites australis plant has not been used in cementitious system and this research can be considered original as it examines the properties of mortar containing PAA. Also, the process of burning in a closed system using this material.

The ultra-thin white topping (UTW) is a cement concrete overlay of the thickness of 50–100 mm on bituminous concrete pavements with surface failures. This is a long-lasting solution without having short-term failures. This paper aims to design an ultra-thin cement concrete overlay using a developed critical stress model with sustainable concrete materials for low-volume roads.

In this research paper, a parametric study was conducted using the ultra-thin concrete overlay finite element model developed with ANSYS software, considering the significant parameters affecting the performance and development. The non-linear regression equation was formed using a damped least-squares method to predict critical stress due to the corner load of 51 kN.

The parametric study results indicate that with a greater elastic modulus of bituminous concrete, granular layer along with 100 mm thickness of concrete layer reduces the critical corner stress, interface shear stress in a significant way responsible for debonding of concrete overlay, elastic strains in the pavement further the concrete overlay can bear infinite load repetitions. From validation, it is understood that the non-linear regression equation developed is acceptable with similar research work done.

From the semi-scale experimental study, it is observed that the quaternary blended sustainable concrete overlay having a high modulus of rupture of 6.34 MPa is competent with conventional cement concrete overlay in terms of failure load. So, concrete overlay with sustainable materials of 100 mm thickness and higher elastic modulus of the layers can perform in a sustainable way meeting the environmental and long-term performance requirements.