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1 – 4 of 4Ankang Ji, Xiaolong Xue, Limao Zhang, Xiaowei Luo and Qingpeng Man
Crack detection of pavement is a critical task in the periodic survey. Efficient, effective and consistent tracking of the road conditions by identifying and locating crack…
Abstract
Purpose
Crack detection of pavement is a critical task in the periodic survey. Efficient, effective and consistent tracking of the road conditions by identifying and locating crack contributes to establishing an appropriate road maintenance and repair strategy from the promptly informed managers but still remaining a significant challenge. This research seeks to propose practical solutions for targeting the automatic crack detection from images with efficient productivity and cost-effectiveness, thereby improving the pavement performance.
Design/methodology/approach
This research applies a novel deep learning method named TransUnet for crack detection, which is structured based on Transformer, combined with convolutional neural networks as encoder by leveraging a global self-attention mechanism to better extract features for enhancing automatic identification. Afterward, the detected cracks are used to quantify morphological features from five indicators, such as length, mean width, maximum width, area and ratio. Those analyses can provide valuable information for engineers to assess the pavement condition with efficient productivity.
Findings
In the training process, the TransUnet is fed by a crack dataset generated by the data augmentation with a resolution of 224 × 224 pixels. Subsequently, a test set containing 80 new images is used for crack detection task based on the best selected TransUnet with a learning rate of 0.01 and a batch size of 1, achieving an accuracy of 0.8927, a precision of 0.8813, a recall of 0.8904, an F1-measure and dice of 0.8813, and a Mean Intersection over Union of 0.8082, respectively. Comparisons with several state-of-the-art methods indicate that the developed approach in this research outperforms with greater efficiency and higher reliability.
Originality/value
The developed approach combines TransUnet with an integrated quantification algorithm for crack detection and quantification, performing excellently in terms of comparisons and evaluation metrics, which can provide solutions with potentially serving as the basis for an automated, cost-effective pavement condition assessment scheme.
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Zhenzong Zhou, Chen Wei, Geoffrey Qiping Shen, Jin Xue, Yongyue Liu, Yaowu Wang and Qingpeng Man
This study explores citizens’ acceptance of prefabricated housing (PH) from the perspective of socio-demographic and psychological factors, aiming to reveal the formation of PH…
Abstract
Purpose
This study explores citizens’ acceptance of prefabricated housing (PH) from the perspective of socio-demographic and psychological factors, aiming to reveal the formation of PH acceptance and realize a sustainable development of PH.
Design/methodology/approach
This study proposed hypotheses drawing on procedural justice theory and uncertainty management theory. A survey of 245 respondents was conducted, and the collected data was analyzed in a stepwise multiple regression model. Then, the psychological influencing mechanism was demonstrated using a mediation model.
Findings
Results of the data analysis manifested that citizens’ acceptance of PH was influenced by socio-demographic and psychological factors, where psychological factors had more significant effects on acceptance than socio-demographic factors. The psychological mechanism was examined by verifying the mediating role of uncertainty between procedural justice and the acceptance of PH. Furthermore, a scientific strategy for developing PH was proposed based on this empirical study.
Originality/value
This study extends the knowledge of procedural justice theory by investigating people’s acceptance in the PH context. This study is also one of the first studies to unveil the psychological mechanism toward a high-cost product with invisible technological innovation. This study contributes to the literature by introducing uncertainty management theory to a controversial issue, examining and expanding its application in a complicated context. Moreover, results highlight the positive influence of fair processes on controversial issues.
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Kangning Liu, Bon-Gang Hwang, Jianyao Jia, Qingpeng Man and Shoujian Zhang
Informal learning networks are critical to response to calls for practitioners to reskill and upskill in off-site construction projects. With the transition to the coronavirus…
Abstract
Purpose
Informal learning networks are critical to response to calls for practitioners to reskill and upskill in off-site construction projects. With the transition to the coronavirus disease 2019 (COVID-19) pandemic, social media-enabled online knowledge communities play an increasingly important role in acquiring and disseminating off-site construction knowledge. Proximity has been identified as a key factor in facilitating interactive learning, yet which type of proximity is effective in promoting online and offline knowledge exchange remains unclear. This study takes a relational view to explore the proximity-related antecedents of online and offline learning networks in off-site construction projects, while also examining the subtle differences in the networks' structural patterns.
Design/methodology/approach
Five types of proximity (physical, organizational, social, cognitive and personal) between projects members are conceptualized in the theoretical model. Drawing on social foci theory and homophily theory, the research hypotheses are proposed. To test these hypotheses, empirical case studies were conducted on two off-site construction projects during the COVID-19 pandemic. Valid relational data provided by 99 and 145 project members were collected using semi-structured interviews and sociometric questionnaires. Subsequently, multivariate exponential random graph models were developed.
Findings
The results show a discrepancy arise in the structural patterns between online and offline learning networks. Offline learning is found to be more strongly influenced by proximity factors than online learning. Specifically, physical, organizational and social proximity are found to be significant predictors of offline knowledge exchange. Cognitive proximity has a negative relationship with offline knowledge exchange but is positively related to online knowledge exchange. Regarding personal proximity, the study found that the homophily effect of hierarchical status merely emerges in offline learning networks. Online knowledge communities amplify the receiver effect of tenure. Furthermore, there appears to be a complementary relationship between online and offline learning networks.
Originality/value
Proximity offers a novel relational perspective for understanding the formation of knowledge exchange connections. This study enriches the literature on informal learning within project teams by revealing how different types of proximity shape learning networks across different channels in off-site construction projects.
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Bao Ngoc Nguyen, Kerry London and Peng Zhang
This paper aims to report a comprehensive analysis of literature on stakeholder relationships towards identifying patterns of relationships within the off-site construction…
Abstract
Purpose
This paper aims to report a comprehensive analysis of literature on stakeholder relationships towards identifying patterns of relationships within the off-site construction context.
Design/methodology/approach
Key scholarly databases were accessed and after a filtering process, 74 relevant papers were retrieved for analysis. The papers were analysed using qualitative content analysis and scientometric techniques through the application of software Leximancer and VOSviewer.
Findings
Research synthesis methods used in the present study generate compatible results. Through text mining analysis, the key themes identified in the off-site construction stakeholder relationships literature included “collaboration”, “building information modelling”, “social network analysis”, supply chain. As a finding by scientometric analysis, collaboration, BIM, supply chain management, housing and social network analysis were the most frequently entered keywords context of off-site construction. Regarding authorship pattern, the whole network of collaboration was fragmented into multiple isolated clusters, implying that the authors had tendency to cooperate in small groups.
Practical implications
The paper can bring together an important area of research not previously studied in detail. It will primarily assist academics in the first instance; however, the research leads to important findings that will ultimately assist policymakers and practitioners better understand factors affecting stakeholder relationships and in particular network thinking and collaborative mind-sets.
Originality/value
The review contributes a needed systematic and theoretical foundation for future stakeholder relationship studies and practices in off-site construction sector. It provides the basis for future studies and is a seminal analysis of stakeholder management and off-site construction. The scientometric methodology offers scholars a different approach to analysing and visualising literature reviews.
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