Smart technologies are advancing, and smart cities can be made smarter by increasing the connectivity and interactions of humans, the environment, and smart devices. This paper discusses selective technologies that can potentially contribute to developing an intelligent environment and smarter cities. While the connectivity and efficiency of smart cities is important, the analysis of the impact of construction development and large projects in the city is crucial to decision and policy makers, before the project is approved. This raises the question of assessing the impact of a new infrastructure project on the community prior to its commencement—what type of technologies can potentially be used for creating a virtual representation of the city? How can a smart city be improved by utilizing these technologies? There are a wide range of technologies and applications available but understanding their function, interoperability, and compatibility with the community requires more discussion around system designs and architecture. These questions can be the basis of developing an agenda for further investigations. In particular, the need for advanced tools such as mobile scanners, Geospatial Artificial Intelligence, Unmanned Aerial Vehicles, Geospatial Augmented Reality apps, Light Detection, and Ranging in smart cities is discussed. In line with smart city technology development, this Special Issue includes eight accepted articles covering trending topics, which are briefly reviewed.

A simple neoclassical production function model is used to determine the incremental cost of each floor as building height increases. This analytic method provides an alternative to earlier studies using computer simulation and more cumbersome attempts at measuring the cost variation directly. By modelling construction costs analytically, it is possible to identify and assess the impacts of particular variables more explicitly. There are two main findings. First, cost variation with building height is not only affected by technology; building design, demand and institutional factors also play important roles. Secondly, the model may be used to estimate construction cost variation with building height from readily available data. In this sense it is an improvement over previous methods using simulated or direct cost measurement.Construction Cost, Building Height, Productivity,

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In the construction industry, knowledge management is usually associated with the management of organizational knowledge. Little is known in a systematic way about how knowledge is coherently managed at the industry level. This paper analyses the case of Singapore to illustrate how knowledge is managed at this level to correct for pervasive market failure in information generation and dissemination. It focuses on the policies and institutions that allow Singapore to continuously tap construction knowledge and achieve a high level of construction quality within a relatively short span of time.

This paper critically examines the changing relations between construction and economic development in selected less developed countries (LDCs) in the light of new development dynamics. Historically, the relationship was seen in Keynesian terms. By the 1980s, attention turned towards structuralist and political economy explanations amid a neoclassical revival towards structural adjustments and 'market friendly' reforms. Current explanations tend to focus on property rights and building institutional capabilities. The strengths and weaknesses of current explanations provide future directions for research.Construction And Economic Development, Structure, Political Economy, Institutions,

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China’s rapid urbanization has led to rising construction and demolition waste (C&DW) amid a quoted recycling rate of only about 10%. Previous studies on C&DW recycling in China have focused on lack of awareness, weak regulation, limited markets for recycled products, and immature recycling technology. This paper investigates the recycling rate of demolition waste (DW) through a case study of the demolition process in a highway project in Taixing, Jiangsu Province, and data collected through analyses of past documents, field observations, and interviews with key stakeholders to provide contrary evidence that the recycling rate is much higher than reported. The reason for the discrepancy is that the reported recycling rate did not include the efforts of a myriad of relocated residents, small construction businesses, informal recycling establishments, developers, and road construction contractors. Proper estimation of the DW recycling rate in China should consider these efforts, especially from the informal sector.