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Weirui Xue

Bio: Weirui Xue is an academic researcher from Guangzhou University. The author has contributed to research in topics: Prefabrication & Business. The author has an hindex of 2, co-authored 4 publications receiving 38 citations.

Papers
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Journal ArticleDOI
TL;DR: An integrated approach based on the convolutional neural network DeepLabv3+ for crack detection, as well as a Crack quantification algorithm for crack quantification at the pixel level that could potentially serve as the basis of an automated, cost-effective pavement-condition assessment scheme for the operation and maintenance of pavement.

103 citations

Journal ArticleDOI
TL;DR: In this paper, a systematic review was conducted of policies related to prefabricated construction in China, which revealed a closely integrated policy network, the evolution of ambitious policy objectives, and the development of a combination of various policy instruments over different stages.

67 citations

Journal ArticleDOI
TL;DR: Wang et al. as discussed by the authors developed an evaluation system for technology innovation capability in prefabricated construction at the enterprise level and scientifically quantified all the evaluation indexes, including total input, technology output (TO), and project output.
Abstract: Purpose This study aims to evaluate enterprise technology innovation capability in prefabricated construction (PC) from an input-output perspective, using six integrated enterprises in China as cases. Design/methodology/approach An evaluation system for enterprise technology innovation capability in PC was constructed, including total input, technology output (TO) and project output. All the evaluation indexes were quantified, and the subject and object indexes weights were determined using the fuzzy cognitive map and information entropy, respectively. The final scores and ranks were evaluated through gray relational analysis (GRA) based on the combined weights. Findings It was found that enterprise technology innovation capability in PC was low in China, with its unbalanced development in different dimensions and the poorest performance in TO, currently. Originality/value This research has developed an evaluation system for technology innovation capability in PC at the enterprise level and scientifically quantified all the indexes, which is a breakthrough over existing studies. The GRA model based on the combined weights proposed in this study can be applied to other comparable fields and regions, with its easy operation.

4 citations

Journal ArticleDOI
TL;DR: Wang et al. as discussed by the authors explored BIM acceptance from the perspective of non-managerial users in the Chinese AECO industry, especially using the theories related to technology acceptance, and found that performance expectancy and task-technology fit significantly and positively influence behavioral intention to accept BIM, while the impacts from effort expectancy, social influence and facilitating conditions are not essential.
Abstract: PurposeConscious of the benefits building information modeling (BIM) has brought about to the architecture, engineering, construction and operations (AECO) industry, the Chinese government has been driving BIM adoption. Nonetheless, its acceptance and proliferation in China remain stagnant. Most relevant literature focuses on BIM diffusion at the industry and organizational levels, but the impact of non-managerial practitioners executing BIM or the traditional drafting approach in day-to-day work tends to be disregarded. This study aims to extend theoretical models pertaining to technology acceptance to understand non-managerial practitioners’ perceptions toward working with BIM in China.Design/methodology/approachA new BIM acceptance model was proposed based on previous technology acceptance theories. After a pilot study, a survey was conducted with 153 non-managerial practitioners in the Chinese AECO industry.FindingsAmong factors impacting non-managerial practitioners’ BIM acceptance in China, performance expectancy and task-technology fit significantly and positively influence behavioral intention to accept BIM, while the impacts from effort expectancy, social influence and facilitating conditions are not essential.Research limitations/implicationsManagement strategies, such as improving non-managerial staff’s benefits and sense of BIM usefulness, selecting suitable tools to match with the staff’s tasks and promoting a middle-out approach in parallel with top-down interventions, are proposed for Chinese AECO organizations to enhance BIM acceptance.Originality/valueFew studies have explored BIM acceptance from the perspective of non-managerial users in the Chinese AECO industry, especially using the theories related to technology acceptance. The BIM acceptance model developed in this study is different from those used in previous global studies in terms of influencing factors.

Cited by
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01 Jan 2011
TL;DR: In this article, the authors examined the reasons that construction project participants are motivated to pursue voluntary incentive goals through four Australian case studies and demonstrated the critical role played by project relationships and equitable contract conditions in promoting the effectiveness of financial incentives.
Abstract: Construction industry observers tout the use of financial incentives as promoters of motivation and commitment on projects. Yet, little empirical evidence exists concerning their effectiveness. What are the drivers of motivation on construction projects? The reasons that construction project participants are motivated to pursue voluntary incentive goals are examined through four Australian case studies. The results demonstrate the critical role played by project relationships and equitable contract conditions in promoting the effectiveness of financial incentives. In the context of a construction project, this study finds financial incentives to be less important to motivation and performance than relationship enhancement initiatives. This finding is unexpected and has implications for the design of project procurement strategies. These results suggest if project clients ignore the importance of relationship quality between participants, the impact of any financial incentive will be compromised.

101 citations

Journal ArticleDOI
Yishun Li1, Pengyu Che1, Chenglong Liu1, Difei Wu1, Yuchuan Du1 
TL;DR: A transfer learning pipeline is proposed to address this problem, which enables a distress detection model to be applied to other untrained scenarios and can reduce the demand for training data by at least 25% when the model is applied in a new scene.

72 citations

Journal ArticleDOI
TL;DR: This study proposes a real-time and cost-effective computer vision-based framework to inspect track components quickly and efficiently, and proposes the cutting-edge convolutional neural network, YOLOv4, improved trained, and evaluated based on the images in a public track components image database.

59 citations

Journal ArticleDOI
TL;DR: In this paper, an evolutionary game model was established on the basis of 16 variables influencing the strategy selection of game players for determining the effective incentive policies, and the interaction effect of the two players' behaviours was discussed.

47 citations

Journal ArticleDOI
TL;DR: Comparisons of two approaches for crack segmentation on grayscale images acquired from two experimental campaigns on stone masonry walls show that the deep learning method can better preserve the geometry of detected crack patterns and the prediction in terms of pixels belonging to a crack is finally more accurate than the threshold method.

46 citations