This study assesses the water resources and environmental challenges of Lagos mega city, Nigeria, in the context of climate change. Being a commercial hub, the Lagos population has grown rapidly causing an insurmountable water and environmental crisis. In this study, a combined field observation, sample analysis, and interviews were used to assess water challenges. Observed climate, general circulation model (GCM) projections and groundwater data were used to assess water challenges due to climate change. The study revealed that unavailability of sufficient water supply provision in Lagos has overwhelmingly compelled the population to depend on groundwater, which has eventually caused groundwater overdraft. Salt water intrusion and subsidence has occurred due to groundwater overexploitation. High concentrations of heavy metals were observed in wells around a landfill. Climate projections showed a decrease in rainfall of up to 140 mm and an increase in temperature of up to 8 °C. Groundwater storage is projected to decrease after the mid-century due to climate change. Sea level rise will continue until the end of the century. As the water and environmental challenges of Lagos are broad and the changing characteristics of the climate are expected to intensify these as projected, tackling these challenges requires a holistic approach from an integrated water resources management perspective.
Motivation is one of the factors that influence productivity. Project management plays a vital role in the success of projects in Qatar construction industry (QCI). It relies profoundly on the team’s active participation and effective performance. Hence it is important to assess the impact of motivation and demotivation on performance. The main objective of this paper is to identify the key factors that cause motivation and de-motivation in QCI. Literature review, surveys with experts and semi-structured interviews were conducted to identify these factors. Using these factors to conduct specific motivational programs will help improve productivity in QCI. Research on motivational factors impacting productivity has not been conducted in Qatar before, so this work will provide insight on how to deal with productivity issues that QCI faces ahead of a major world event that Qatar will host in 2022.
PurposeThis study reviews the extent of application of artificial intelligence (AI) tools in the construction industry.Design/methodology/approachA thorough literature review (based on 165 articles) was conducted using Elsevier's Scopus due to its simplicity and as it encapsulates an extensive variety of databases to identify the literature related to the scope of the present study.FindingsThe following items were extracted: type of AI tools used, the major purpose of application, the geographical location where the study was conducted and the distribution of studies in terms of the journals they are published by. Based on the review results, the disciplines the AI tools have been used for were classified into eight major areas, such as geotechnical engineering, project management, energy, hydrology, environment and transportation, while construction materials and structural engineering. ANN has been a widely used tool, while the researchers have also used other AI tools, which shows efforts of exploring other tools for better modelling abilities. There is also clear evidence of that studies are now growing from applying a single AI tool to applying hybrid ones to create a comparison and showcase which tool provides a better result in an apple-to-apple scenario.Practical implicationsThe findings can be used, not only by the researchers interested in the application of AI tools in construction, but also by the industry practitioners, who are keen to further understand and explore the applications of AI tools in the field.Originality/valueThere are no studies to date which serves as the center point to learn about the different AI tools available and their level of application in different fields of AEC. The study sheds light on various studies, which have used AI in hybrid/evolutionary systems to develop effective and accurate predictive models, to offer researchers and model developers more tools to choose from.
PurposeVietnam's construction technology (CT) adoption is low when compared to other countries with similar gross domestic product (GDP) per capita resulting in lesser productivity. The research objectives are: (1) To undertake an extensive literature review on CT adoption challenges; (2) To investigate CT adoption challenges unique to Vietnam's construction sector; and (3) To propose data-driven solutions for a greater rate of CT adoption.Design/methodology/approachA two-stage descriptive survey method was adopted in alignment with the research aim and objectives. Based on the literature review of 215 articles, a questionnaire was designed and administered to experienced construction managers (CM) to identify whether CT has been adopted, barriers to adoption, drivers, and the most popular CT tools. Descriptive statistics were used to summarize the characteristics of interest in the empirical dataset and SPSS-based inferential statistics to estimate the means, frequency counts, variance and test hypotheses that informed the drawing of conclusions concerning the research objectives.FindingsThe popular CT tools identified were Autodesk, Microsoft Office and Primavera. The most influential CT adoption barriers: (1) Unknow`n impact on productivity, (2) Late implementation of software in construction projects, (3) Lack of understanding of importance and needs in the construction industry (4) Lack of funds during budget planning for technological advances and implementation (5) Lack of experts required for technological change, and insufficient skills in the industry.Practical implicationsIt is expected that the findings could inform data-driven regulatory and practice reforms targeted at increasing greater uptake of CT in Vietnam with potential for replication in countries facing similar adoption challenges.Originality/valueThe findings are intended to support data-driven regulatory and practice improvements aimed at improving CT adoption in Vietnam, with the possibility for replication in other countries facing comparable problems.
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