A new perspective to evaluate the antecedent path of adoption of digital technologies in major projects of construction industry: A case study in China

The adoption of digital technologies is key to the digital transformation of the construction industry. However, the current adoption of digital technologies is limited. This study uses China as a case, combines the DOI and TOE theories to identify impact factors of the adoption of digital technologies in major projects. The configuration analysis is complemented with fuzzy-set qualitative comparative analysis. As a result, the study constructs the “TOE-D Technology Adoption Antecedent Framework”, including 11 antecedents, and identifies three distinct configurations types, namely: “Needs-Resource-Collaboration”; “Resource” under high competitive pressure; and “Resource” under low competitive pressure. Comparing the configurations horizontally, the core or edge characteristics of factor in configurations are analyzed. The results can help major projects in the construction industry to ascertain a combination of elements, which promote the adoption of digital technologies so that project practitioners can make targeted and precise adjustments to enable digital transformation of the construction industry

Duration and cost variability of construction activities: an empirical study

The unique nature of construction projects can mean that construction activities often suffer from duration and cost variability. Because this variability is unplanned, it can present a problem when attempting to complete a project on time and on budget. Various factors causing this variability have been identified in the literature, but they predominantly refer to the nature and/or context of the whole project rather than specific activities. In this paper, the order of magnitude of and correlation between activity duration and cost variability is analyzed in 101 construction projects with over 5,000 activities. To do this, the first four moments (mean, standard deviation, skewness, and kurtosis) of actual versus planned duration and cost (log) ratios are analyzed by project, phase of execution, and activity type. Results suggest that, contrary to common wisdom, construction activities do not end late on average. Instead, the large variability in the activity duration is the major factor causing significant project delays and cost overruns. The values of average activity duration and cost variability gathered in this study will also serve as a reference for construction managers to improve future construction planning and project simulation studies with more realistic data

Environmental Regulation and Green Productivity of the Construction Industry in China

There are few studies analyzing whether different types of environmental regulation have differential impacts on the efficiency of the construction industry. Using 2012-2016 panel data from 30 provinces in China, the green total factor productivity (GTFP) of the construction industry is measured with a global Malmquist Luenberger productivity index based on the epsilon measure (EBM-GML) model. Thereafter, a panel Tobit regression model is proposed to explore the relationship between three types of environmental regulation and the GTFP of the construction industry. The results show that: (1) from 2012 to 2016, the GTFP of the Chinese construction industry grew slowly at an average annual rate of 0.14%; (2) both one-phase lagged command-and-control and current phase market-based environmental regulation had a positive linear relationship with GTFP. One-phase lagged voluntary environmental regulation on the other hand, had an inverted U-shaped relationship with GTFP; (3) the three types of environmental regulation can be combined to establish a suitable environmental regulation system. The findings of this study provide guidance for the sustainable development of the construction industry by combining the actions of different types of environmental regulation

Influence of agglomeration and selection effects on the Chinese construction industry

The determination of whether market size can influence industrial agglomeration or selection is an important topic in economic development. To analyse the differential economic development of the construction industry under different market sizes, this research analyses the employment density of China’s provinces and their Total factor productivity (TFP). It also analyses whether the difference in the provinces’ productivity are explained by their agglomeration and selection effects. First, a DEA-Malmquist model is used to calculate the TFP of each construction industry sub-sector. Then, a nested model is used to measure the influence of the selection and the agglomeration effects on the TFP at different market sizes of the construction industry. Results evidence that there are significant differences in the construction productivity at different sub-sectors in different regions of China. These differences are mainly the consequence of the agglomeration effect, rather than the selection effect. Findings of this study suggest that the Chinese construction industry should optimise its structure in different provinces to achieve a balanced growth at different market sizes

Evaluating the impact of highway construction projects on landscape ecological risks in high altitude plateaus

In China and other countries, many highway projects are built in extensive and high-altitude flat areas called plateaus. However, research on how the materialisation of these projects produce a series of ecological risks in the landscape is very limited. In this research, a landscape ecological risk analysis model for high-altitude plateaus is proposed. This model is based on the pattern of land uses of the surrounding area. Our study includes buffer analysis, spatial analysis, and geostatistical analysis. We apply the model to the Qumei to Gangba highway, a highway section located in the southeast city of Shigatse at the Chinese Tibet autonomous region. Through global and local spatial autocorrelation analysis, the spatial clustering distribution of ecological risks is also explored. Overall, our study reveals the spatial heterogeneity of ecological risks and how to better mitigate them. According to a comparison of the risk changes in two stages (before and after the highway construction), the impact of highway construction on the ecological environment can be comprehensively quantified. This research will be of interest to construction practitioners seeking to minimize the impact of highway construction projects on the ecological environment. It will also inform future empirical studies in the area of environmental engineering with potential affection to the landscape in high-altitude plateaus

Optical test of the DS1 prototype concentrating surface

This paper describes the optical test of the DS1 prototype concentrating surface carried out by CTAER. The DS1 is a parabolic Stirling dish developed under the framework of “SOLARDIS” project. The aim of this investigation was to characterize the DS1 prototype optical parameters. For this purpose the real and the theoretical flux distribution was calculated on a target placed at the focal length and a comparison between them reported about the value of some relevant parameters. The theoretical flux distribution was obtained by photogrammetry technique and ray tracing tools; the real flux distribution was measured by photographic flux mapping technique of lunar images. The results comparison showed that the dish surface had an average optical error of 2.5mrad (it includes errors due to deviation of surface normal vector and the effect of the specularity, but it does not include the sun shape error) and an estimated spillage value of 7%, for this geometry

Dynamic Quality Monitoring System to Assess the Quality of Asphalt Concrete Pavement

With the rapid development of new technologies, such as big data, the Internet of Things (IoT) and intelligent sensing, the traditional asphalt pavement construction quality evaluation method has been unable to meet the needs of road digital construction. At the same time, the development of such technologies enables a new management system for asphalt pavement construction. In this study, firstly, the dynamic quality monitoring system of asphalt concrete pavement is established by adopting the BeiDou Navigation Satellite System, intelligent sensing, the IoT and 5G technology. This allows key technical indicators to be collected and transmitted for the whole process of asphalt mixture, which includes the mixing plant, transport vehicle, paving and compaction. Secondly, combined with AHP and the entropy weight (EW) method, the index combination weight is calculated. The comprehensive index for the pavement digital construction quality index (PCQ) is proposed to reflect the impact of monitoring indicators on pavement quality. An expert decision-making model is formed by using the improved particle swarm optimization (PSO) algorithm coupled with radial basis function neural network (RBF). Finally, the digital monitoring index and pavement performance index are connected to establish a full-time and multi-dimensional digital construction quality evaluation model. This study is verified by a database created from the digital monitoring data of pavement construction collected from a highway construction project. The system proposed in this study can accurately reflect the quality of pavement digital construction and solve the lag problem existing in the feedback of construction site

Evaluating the impact of highway construction projects on landscape ecological risks in high altitude plateaus

[EN] In China and other countries, many highway projects are built in extensive and high-altitude flat areas called plateaus. However, research on how the materialisation of these projects produce a series of ecological risks in the landscape is very limited. In this research, a landscape ecological risk analysis model for high-altitude plateaus is proposed. This model is based on the pattern of land uses of the surrounding area. Our study includes buffer analysis, spatial analysis, and geostatistical analysis. We apply the model to the Qumei to Gangba highway, a highway section located in the southeast city of Shigatse at the Chinese Tibet autonomous region. Through global and local spatial autocorrelation analysis, the spatial clustering distribution of ecological risks is also explored. Overall, our study reveals the spatial heterogeneity of ecological risks and how to better mitigate them. According to a comparison of the risk changes in two stages (before and after the highway construction), the impact of highway construction on the ecological environment can be comprehensively quantified. This research will be of interest to construction practitioners seeking to minimize the impact of highway construction projects on the ecological environment. It will also inform future empirical studies in the area of environmental engineering with potential affection to the landscape in high-altitude plateaus.This research is supported by the Branch of China Road and Bridge Corporation (Cambodia) Technology Development Project (No.2020-zlkj-04); National Social Science Fund Projects (No.20BJY010); National Social Science Fund Post-financing Projects (No.19FJYB017); Sichuan-Tibet Railway Major Fundamental Science Problems Special Fund (No.71942006); Qinghai Natural Science Foundation (No. 2020-JY-736); List of Key Science and Technology Projects in China's Transportation Industry in 2018-International Science and Technology Cooperation Project (Nos. 2018-GH-006 and 2019-MS5-100); Emerging Engineering Education Research and Practice Project of Ministry of Education of China (No. E-GKRWJC20202914); Shaanxi Social Science Fund (No. 2017S004); Xi'an Construction Science and Technology Planning Project (Nos. SZJJ201915 and SZJJ201916); Shaanxi Province Higher Education Teaching Reform Project (No. 19BZ016); Fundamental Research for Funds for the Central Universities (Humanities and Social Sciences), Chang'an University (Nos. 300102239616, 300102281669 and 300102231641).Li, C.; Zhang, J.; Philbin, SP.; Yang, X.; Dong, Z.; Hong, J.; Ballesteros-Pérez, P. (2022). Evaluating the impact of highway construction projects on landscape ecological risks in high altitude plateaus. Scientific Reports. 12(1):1-16. https://doi.org/10.1038/s41598-022-08788-811612

Quick abnormal-bid-detection method for construction contract auctions

Noncompetitive bids have recently become a major concern in both public and private sector construction contract auctions. Consequently, several models have been developed to help identify bidders potentially involved in collusive practices. However, most of these models require complex calculations and extensive information that is difficult to obtain. The aim of this paper is to utilize recent developments for detecting abnormal bids in capped auctions (auctions with an upper bid limit set by the auctioner) and extend them to the more conventional uncapped auctions (where no such limits are set). To accomplish this, a new method is developed for estimating the values of bid distribution supports by using the solution to what has become known as the German Tank problem. The model is then demonstrated and tested on a sample of real construction bid data, and shown to detect cover bids with high accuracy. This paper contributes to an improved understanding of abnormal bid behavior as an aid to detecting and monitoring potential collusive bid practices

Dynamic Quality Monitoring System to Assess the Quality of Asphalt Concrete Pavement

[EN] With the rapid development of new technologies, such as big data, the Internet of Things (IoT) and intelligent sensing, the traditional asphalt pavement construction quality evaluation method has been unable to meet the needs of road digital construction. At the same time, the development of such technologies enables a new management system for asphalt pavement construction. In this study, firstly, the dynamic quality monitoring system of asphalt concrete pavement is established by adopting the BeiDou Navigation Satellite System, intelligent sensing, the IoT and 5G technology. This allows key technical indicators to be collected and transmitted for the whole process of asphalt mixture, which includes the mixing plant, transport vehicle, paving and compaction. Secondly, combined with AHP and the entropy weight (EW) method, the index combination weight is calculated. The comprehensive index for the pavement digital construction quality index (PCQ) is proposed to reflect the impact of monitoring indicators on pavement quality. An expert decision-making model is formed by using the improved particle swarm optimization (PSO) algorithm coupled with radial basis function neural network (RBF). Finally, the digital monitoring index and pavement performance index are connected to establish a full-time and multi-dimensional digital construction quality evaluation model. This study is verified by a database created from the digital monitoring data of pavement construction collected from a highway construction project. The system proposed in this study can accurately reflect the quality of pavement digital construction and solve the lag problem existing in the feedback of construction site.This research is supported by the Branch of China Road and Bridge Corporation (Cambodia) Technology Development Project(No.2020-zlkj-04); National Social Science Fund projects (No.20BJY010); National Social Science Fund Post-financing projects (No.19FJYB017); Sichuan-tibet Railway Major Fundamental Science Problems Special Fund (No.71942006); Qinghai Natural Science Foundation (No.2020-JY-736); List of Key Science and Technology Projects in China's Transportation Industry in 2018-International Science and Technology Cooperation Project (No.2018-GH-006 and No.2019-MS5-100); Emerging Engineering Education Research and Practice Project of Ministry of Education of China (No.E-GKRWJC20202914); Shaanxi Social Science Fund (No.2017S004); Xi'an Construction Science and Technology Planning Project (No.SZJJ201915 and No.SZJJ201916); Shaanxi Province Higher Education Teaching Reform Project (No.19BZ016); Fundamental Research for Funds for the Central Universities (Humanities and Social Sciences), Chang'an University (No.300102239616, No.300102281669 and No.300102231641).Ma, Z.; Zhang, J.; Philbin, SP.; Li, H.; Yang, J.; Feng, Y.; Ballesteros-Pérez, P.... (2021). Dynamic Quality Monitoring System to Assess the Quality of Asphalt Concrete Pavement. Buildings. 11(12):1-18. https://doi.org/10.3390/buildings11120577S118111