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The purpose of this study was to investigate the likely causes of failure of some sections of road pavements in Ajaokuta, Northcentral Nigeria. This was achieved through a geotechnical assessment of subgrade soils in affected areas.

The methods entailed field and laboratory methods and statistical analysis. Subgrade soil samples were retrieved from a depth of 1,000 mm beneath the failed portions using a hang auger. The soils were analyzed for natural moisture content (NMC), Atterberg limit (liquid limit, plastic limit and linear shrinkage), grain size distribution, compaction and California bearing ratio (CBR), respectively.

The results of the geotechnical tests ranged from NMC (12.5%–19.4%), sand (84%–98%), fines (2%–16%), LL (16.0%–32.2%), PL (17%–27.5%), LS (2.7%–6.4%), PI (2.5%–18.4%), maximum dry density (1756 kg/m2–1961 kg/m2), optimum moisture content (13.2%–20.2%), unsoaked CBR (15.5%–30.5%) and soaked CBR (8%–22%), respectively. Pearson’s correlation coefficient performed on the variables showed that some parameters exhibited a strong positive correlation with r2 > 0.5.

Funding was the main limitation.

Comparing the results with Nigerian standards for road construction, and the AASHTO classification scheme, the subgrade soils are competent and possess excellent to good properties. The soils also exhibited very low plasticity, a high percentage of sand, high CBR and low NMC, which implies that it has the strength required for road pavement subgrades. The likely causes of the failures are, therefore, due to the use of poor construction materials, technical incompetence and poor compaction of sub-base materials, respectively.

The China’s Belt and Road Initiative (BRI, hereafter) has reenergized the Silk Road concept, with most literature focusing on the political and economic effects of the BRI. While certain aspects of the Digital Silk Road (DSR), digital component of BRI, have been researched, much less focus has been placed on the technological development, tech transfer and information diffusion aspects of the BRI. The aim of this study is to investigate the opportunities, issues and critiques that have arisen as a result of the Belt and Road Initiative’s implications on innovation, knowledge transfer and dissemination.

Research in its nature is descriptive. Literature reviews are a significant part of the development of a field. Therefore, secondary sources were considered.

The literature and the study have highlighted several opportunities, problems and criticism that decision-makers and the relevant agencies and institutions should take into account when deciding how to move forward with BRI and its digital component DSR.

This paper contributes to the research literature on BRI and its subset DSR’s impacts on innovation, knowledge transfer and information diffusion. In fact, the DSR’s primary aim is to strengthen international cooperation in the digital economy. Furthermore, digital platforms now play a significant role in global trade, emphasizing the necessity of DSR.

Road transport is an important sector of the economy, however, its negative impacts on the environment, human health and sustainability of potential economic growth are significant. Transport externalities tend to be neglected within the market process. The damage generated through significant externalities of road transport in Czechia was identified, based on unique data processing, to reach almost 3.5 billion € annually. This chapter presents an overview of internalization taxes and fees, their current rates and generated receipts. If excise duty is disregarded as fundamentally unsuitable for the internalization of externalities, then the receipts from other applied taxes and fees, particularly the road tax, seem to be insufficient. Although economic growth is encouraged, its form is not sustainable in view of the rising phase of the Kuznets curve and the related irreversible environmental impacts.

The purpose of this study is to investigate the influence of institutional dynamics on road accidents and whether this relationship is moderated by information and communication technology (ICT).

The study adopted a quantitative approach with 133 respondents. Research hypotheses were tested in AMOS version 21. In addition, moderated regression analysis was used to test the moderating role of ICT on the relationship between institutional dynamics and road accidents.

The results show that vehicle maintenance, policy enforcement, safety culture, driver training and driver management positively influence road accidents. Moreover, the study established that ICT moderates the relationship between institutional dynamics and road accidents.

The results of this study serve as a practical guideline for policymakers in the road haulage sector. Managers may gain insights on how to design effective interventions to reduce road accidents.

This research contributes to the existing body of knowledge by exploring previously unexplored moderating paths in the relationship between institutional dynamics and road accidents. By highlighting the moderating role of ICT, the study sheds new light on the institutional dynamics that influence road accidents in the context of road haulage companies.

Road freight transportation companies need to take advantage of information and communication technologies to develop capabilities. This study proposes a framework to guide road freight transportation companies to achieve data visibility in their operations by developing such capabilities. By proposing this framework, this research contributes to literature and practice, highlighting the capabilities and the respective supporting technologies for improved data visibility in road freight transportation.

A mixed-method approach is used to develop the framework, considering three methodological steps. In phase 1, the capabilities are identified in the literature and validated by experts. In phase 2, an empirical assessment of cause–effect relationships between capabilities is performed using a multiple case study and DEMATEL. Lastly, in phase 3, an analysis of the cause model and significant associations is conducted to enable the development of the framework. In addition, the proposed framework was validated by the experts interviewed.

The results provide a framework that explains the link between the technology-enabled data visibility capabilities in road freight transportation operations. In addition, a pathway was established that road freight transportation companies could follow to achieve data visibility in their operations by developing such capabilities.

This work develops the first framework that provides a path for data visibility in road freight transportation operations from adopting certain technologies. The insights are compelling for researchers and practitioners to optimize the decision-making process for adopting technologies and developing capabilities related to data visibility.

The purpose of this paper is to investigate the vehicle-based sensor effect and pavement temperature on road condition assessment, as well as to compute a threshold value for the classification of pavement conditions.

Four sensors were placed on the vehicle’s control arms and one inside the vehicle to collect vibration acceleration data for analysis. The Analysis of Variance (ANOVA) tests were performed to diagnose the effect of the vehicle-based sensors’ placement in the field. To classify road conditions and identify pavement distress (point of interest), the probability distribution was applied based on the magnitude values of vibration data.

Results from ANOVA indicate that pavement sensing patterns from the sensors placed on the front control arms were statistically significant, and there is no difference between the sensors placed on the same side of the vehicle (e.g., left or right side). A reference threshold (i.e., 1.7 g) was computed from the distribution fitting method to classify road conditions and identify the road distress based on the magnitude values that combine all acceleration along three axes. In addition, the pavement temperature was found to be highly correlated with the sensing patterns, which is noteworthy for future projects.

The paper investigates the effect of pavement sensors’ placement in assessing road conditions, emphasizing the implications for future road condition assessment projects. A threshold value for classifying road conditions was proposed and applied in class assignments (I-17 highway projects).

Recently, the serviceability of the transportation infrastructure in urban areas has become crucial. Any impact of the hazardous conditions on the urban road network causes significant disruption to the functioning of the urban region, making the city’s resilience a point of concern. Thereby, the purpose of the study is to examine the city’s recovery capacity to absorb the impacts of adverse events like urban floods.

This study examines the road network resilience for an urban flood event for zones proposed by the Municipal Corporation to develop multiple central business districts. This study proposes a novel approach to measure the resilience of road networks in an urban region under floods caused due to heavy rainfall. A novel Road Network Resilience Index (RNRI) based on the serviceability of the road network during floods is proposed, estimated using Analytic Hierarchy Process - Multiple Criteria Evaluation (AHP-MCE) approaches by using the change in street centrality, impervious area and road network density. This study examines and analyses the resilience of road networks in two conditions: flood and nonflood conditions. Resilience was estimated for both the conditions at the city level and the decentralized zone level.

Based on RNRI values, this study identifies zones having a lower or higher resilience index. The central, southern and eastern zones have lower road network resilience and western and northern zones have high road network resilience.

The proposed methodology can be used to increase road network resilience within the city under flood conditions.

The previous literature on road network resilience concentrates on the physical properties of roads after flood events. This study demonstrates the use of nonstructural measures to improve the resilience of the road network by innovatively using the AHP-MCE approach and street centrality to measure the resilience of the road network.

This paper aims to clarify the resistance degree of group road logistics to flood disaster resilience. The paper measures the resilience of group road logistics by establishing network structure model. The purpose of this study is to improve the resilience of road log.

This paper adopts Delphi method to collect data, interviews mainly flood management experts and supply chain risk management experts, and then analyzes the data through the network structure model combined with interpretative structure model (ISM) and analytical network process (ANP).

The results show that flood frequency and drainage systems are the main factors affecting the resilience of road transport logistics in urban areas. These research results provide useful guidance for the effective planning and design of urban road construction and infrastructure.

However, the main factors affecting the resilience of road transport logistics are likely to change with the development of factors such as climate, economy and environment. Therefore, in future work, the authors' research will focus on the further application of this evaluation method.

The results show that the impact of flooding on the four dimensions of road logistics resilience varies. This shows that in deciding what intervention measures are to be taken to improve the resilience of the road network to flooding, various measures need to be considered.

This paper provides a more scientific analysis of the risk management ability of the road network in the face of floods. In addition, it also provides a useful reference for urban road planners.

This paper addresses a clear need to study how to build models to improve the resilience of road logistics in flood risk.

Delays in utility shifting during road construction have broad ramifications. These delays not only lengthen the project's timeline but also raise expenses and cause problems with resource allocation. Thus, this study investigates the influence of delay in utility shifting for extension of time claims in road construction projects (RCPs) in Sri Lanka.

The study used a quantitative approach with three rounds of Delphi surveys to gather empirical data. Further, the probability impact assessment was used to carefully analyse the data and appraise the information gathered.

The findings initially revealed 33 causes of delays in utility shifting for extension of time claims in RCPs in Sri Lanka. Ultimately, 11 severe causes were identified based on their high probability and impact, concluding with 45 strategies that were assigned to overcoming those most severe causes of delay.

This study will contribute to the industry and theory by providing solutions to handle utility-shifting delays with the linkage of preventing time extension claims for RCPs in Sri Lanka. Further, there is a dearth of literature in the research area, both locally and globally. Thus, the findings of this research will provide a benchmark for further detailed studies in other countries as well.

The current estimation practice in construction projects greatly needs upgrading, as there has been no improvement in the cost overrun issue over the past 70 years. The purpose of this research was to develop a new multiple regression analysis (MRA)-based model to forecast the final cost of road projects at the pre-design stage using data from 43 projects in New Zealand (NZ).

The research used the case study of 43 completed road projects in NZ. Document analysis was conducted to collect data, and statistical tests were used for model development and analysis.

Eight models were developed, and all models achieved the required F statistics and met the regression assumptions. The models’ mean absolute percentage error (MAPE) was between 21.25% and 22.77%. The model with the lowest MAPE comprised the road length and width, number of bridges, pavement area, cut and fill area, preliminary cost and cost indices change.

The model is based on road projects in NZ. However, it was designed to be able to adapt to other contexts. The findings suggest that the model can be used to improve traditional conceptual estimating methods. Past project data is often stored by the project team but rarely used for analysing and forecasting purposes. This research emphasises that past data can be effectively used to predict the project cost at the pre-design stage with limited information.

No research was conducted to adopt cost modelling techniques into the conceptual estimation practice in the NZ construction industry.