AbstractApplication studies on wireless sensor networks (WSN) are actively conducted in the construction industry. However, there are several technical limitations including signal interference caused by the characteristics of wireless sensors, reliability degradation in wireless communication and uncertainty of configuring a network topology. This may lead to a decline in reliability and performance of real-time data acquisition methods. Thus, the paper developed a model capable of predicting reliability performance of wireless signals applied to civil infrastructures. The measured and predicted values of wireless signals are compared and analyzed through a field experiment carried out in an actual bridge to verify the prediction model suggested herein. As a result of the analysis, the prediction model demonstrated a variation up to 8.4% compared with actual measurements, proving the high accuracy of the prediction model. Furthermore, the reception rate at short distances within a 5 m radius is at least 90%, showing a highly reliable reception capacity. When this is applied to monitoring systems in the construction sector, it is believed that performance and reliability of such system can be secured.
01896nas a2200181 4500000000100000000000100001008004100002100001600043700001500059700001600074700002600090700001300116245006400129856005200193300001200245490000700257520145000264 2016 d 1 aLimao Zhang 1 aXianguo Wu 1 aLieyun Ding 1 aMirosław Skibniewski 1 aYujie Lu 00 aBim-Based Risk Identification System in tunnel construction uhttp://dx.doi.org/10.3846/13923730.2015.1023348 a529-539 0 v22 3 aAbstractThis paper presents an innovative approach of integrating Building Information Modeling (BIM) and expert systems to address deficiencies in traditional safety risk identification process in tunnel construction. A BIM-based Risk Identification Expert System (B-RIES) composed of three main built-in subsystems: BIM extraction, knowledge base management, and risk identification subsystems, is proposed. The engineering parameter information related to risk factors is first extracted from BIM of a specific project where the Industry Foundation Classes (IFC) standard plays a bridge role between the BIM data and tunnel construction safety risks. An integrated knowledge base, consisting of fact base, rule base and case base, is then established to systematize the fragmented explicit and tacit knowledge. Finally, a hybrid inference approach, with case-based reasoning and rule-based reasoning combined, is developed to improve the flexibility and comprehensiveness of the system reasoning capacity. B-RIES is used to overcome low-efficiency in traditional information extraction, reduce the dependence on domain experts, and facilitate knowledge sharing and communication among dispersed clients and domain experts. The identification of a safety hazard regarding the water gushing in one metro station of China is presented in a case study. The results demonstrate the feasibility of B-RIES and its application effectiveness.
00408nas a2200157 4500000000100000000000100001008004100002260001200043100001200055700001400067700002600081245011000107300001200217490000700229022001400236 2017 d c04/2017 1 aQ.Q. Ju 1 aJ.Y. Ding 1 aMirosław Skibniewski 00 aOptimization strategies to eliminate interface conflicts in complex study chains of construction projects a712-726 0 v23 a1392-3730 00398nas a2200145 4500000000100000000000100001008004100002260001200043100001000055700002600065245013200091300000900223490000600232022001400238 2017 d c11/2017 1 aY Han 1 aMirosław Skibniewski 00 aA Market Equilibrium Supply Chain Model for Supporting Self-Manufacturing or Outsourcin Decisions in Prefabricated Construction a1-18 0 v9 a2071-1050 00397nas a2200169 4500000000100000000000100001008004100002260001200043100001200055700001100067700000900078700002600087245008200113300001000195490000800205022001400213 2017 d c08/2017 1 aL Zhang 1 aL Ding 1 aX Wu 1 aMirosław Skibniewski 00 aAn improved Dempster–Shafer approach to construction safety risk perception a30-46 0 v132 a0950-7051 00446nas a2200181 4500000000100000000000100001008004100002260001200043100001100055700001200066700002600078700001100104700001300115245010300128300001200231490000700243022001400250 2017 d c10/2017 1 aC Zhou 1 aLY Ding 1 aMirosław Skibniewski 1 aHB Luo 1 aSN Jiang 00 aCharacterizing time series of near-miss accidents in metro construction via complex network theory a145-158 0 v98 a0925-7535 00409nas a2200169 4500000000100000000000100001008004100002260001200043100001400055700001300069700001000082700002600092245008600118300001400204490000700218022001400225 2017 d c05/2017 1 aL.M Zhang 1 aY. Huang 1 aX. Wu 1 aMirosław Skibniewski 00 aRisk-based estimate for operational safety in complex projects under uncertainty, a108–120 0 v54 a1568-4946 00433nas a2200169 4500000000100000000000100001008004100002260001200043100001200055700001300067700001000080700002600090245011800116300000900234490000600243022001400249 2017 d c03/2017 1 aJ. Yuan 1 aX. Zheng 1 aJ You 1 aMirosław Skibniewski 00 aIdentifying Critical Factors Influencing the Rents of Public Rental Housing Delivery by PPPs: The Case of Nanjing a1-22 0 v9 a2071-1050 00457nas a2200181 4500000000100000000000100001008004100002260001200043100001300055700001000068700001300078700002600091700001300117245011200130300001200242490000700254022001400261 2015 d c02/2015 1 aLM Zhang 1 aXG Wu 1 aQQ. Chen 1 aMirosław Skibniewski 1 aJB Zhong 00 aDeveloping a cloud model based risk assessment methodology for tunnel- induced damage to existing pipelines a513-526 0 v29 a1436-3240 00459nas a2200181 4500000000100000000000100001008004100002260001200043100001300055700001000068700002600078700001200104700001200116245011600128300001200244490000700256022001400263 2015 d c05/2015 1 aLM Zhang 1 aXG Wu 1 aMirosław Skibniewski 1 aWL Fang 1 aQL Deng 00 aConservation of historical buildings in tunneling environments: Case study of Wuhan Metro construction in China a310-322 0 v82 a0950-0618 00414nas a2200169 4500000000100000000000100001008004100002260001200043100001200055700001000067700001300077700002600090245009500116300001200211490000700223022001400230 2015 d c12/2015 1 aLI Ding 1 aXG Wu 1 aLM Zhang 1 aMirosław Skibniewski 00 aHow to protect historical buildings against tunnel-induced damage: A case study in China. a904-911 0 v16 a1296-2074 00406nas a2200181 4500000000100000000000100001008004100002260001200043100001000055700000900065700001200074700002600086700001200112245006900124300001000193490000700203022001400210 2015 d c05/2015 1 aXG Wu 1 aQ Lu 1 aL Zhang 1 aMirosław Skibniewski 1 aYH Wang 00 aProspective safety performance evaluation on construction sites a58-72 0 v78 a0001-4575 00438nas a2200193 4500000000100000000000100001008004100002260001200043100001000055700001200065700001300077700001200090700002600102700001300128245007000141300001200211490000700223022001400230 2015 d c08/2015 1 aXG Wu 1 aYH Wang 1 aLM Zhang 1 aLY Ding 1 aMirosław Skibniewski 1 aJB Zhong 00 aA Dynamic Decision Approach for Risk Analysis in Complex Projects a591-601 0 v79 a0921-0296 02140nas a2200217 4500000000100000000000100001008004100002100001500043700001300058700002000071700001400091700001600105700002600121700001600147245009700163856007100260300001100331490000800342520155800350022001401908 2019 d 1 aCheng Zhou 1 aRui Chen 1 aShuangnan Jiang 1 aYing Zhou 1 aLieyun Ding 1 aMirosław Skibniewski 1 aXinggui Lin 00 aHuman dynamics in near-miss accidents resulting from unsafe behavior of construction workers uhttp://www.sciencedirect.com/science/article/pii/S037843711930888X a121495 0 v530 3 aNear misses, as a common result of unsafe behavior and/or unsafe conditions, are precursors of accidents in the construction industry. Given the complexity of near misses, seeking regularities in time series of near misses is almost impossible. We present a human dynamics model based on near-miss data to reveal common dynamic features of near-miss accidents that result from unsafe behavior of construction workers. To validate the model, we conducted an empirical case study based on unsafe behavior related to near misses from a database in the Early Warning System for Safety Risk Management in Wuhan Metro Construction, created by the Huazhong University of Science and Technology. Heavy-tailed distribution and approximate power-law distribution are observed in the inter-event time series of near misses, rather than being randomly distributed in time in current models. The strong burst and weak memory phenomena were observed in the whole, annual, and categorized inter-event time distributions of near misses. Moreover, the results showed a non-trivial, monotonous increase of the power-law exponent with the activity of different construction site in near misses, thus indicating that heterogeneity and complexity exist in general. We defined a new safety performance metric that is more reliable than the number of near misses and validated this performance metric by using expert assessment results of metro construction sites. Furthermore, we proposed further research prospects on human dynamics in construction safety behavior.
a0378-4371 02551nas a2200181 4500000000100000000000100001008004100002100001500043700001600058700002600074700001300100245011100113856007100224300001100295490000700306520204200313022001402355 2019 d 1 aShiyao Cai 1 aZhiliang Ma 1 aMirosław Skibniewski 1 aSong Bao 00 aConstruction automation and robotics for high-rise buildings over the past decades: A comprehensive review uhttp://www.sciencedirect.com/science/article/pii/S1474034619305622 a100989 0 v42 3 aAutomation and robotics technology is expected to improve the productivity of the construction industry as well as to solve problems such as labor shortage and safety risks, especially for high-rise buildings. Substantial research efforts have been devoted to the field over the past decades, while the application rate at the construction sites is still limited. Although various reviews have summarized the research topics and future trends in this field, few research efforts have been made on a consideration of both academic research and practical application in the industry. Focusing on high-rise building construction, this study explores the development of both academic research and practical application of automation and robotics based on literature and market review. Scientometric and critical literature reviews were conducted to identify and analyze the development of key research areas based on academic publications from the 1980s to present. In the meantime, the development of basic technologies was summarized. The market review surveyed on existing products and developers of construction automation and robotics. By comparing the results of the literature review and market review, four development patterns of academic research and product application were identified, i.e., simultaneous development led by the same party, development at a similar pace with the two sides taking the lead in different aspects, academic research providing basic technologies for product development, and available technologies in academic research with no products found. Then three gaps in this field, i.e., the gap between academic research and products, the gap between products and application, and the gap between the construction industry and the robotics industry, were discussed with corresponding suggestions to narrow the gaps, followed by an outlook for future directions. This study contributes to the knowledge body by identifying and analyzing the key research areas and the development gaps systematically.
a1474-0346 00448nas a2200157 4500000000100000000000100001008004100002100001500043700001500058700001000073700001500083700002600098245014500124300001400269490000700283 2020 d 1 aLiang Wang 1 aPing Zhang 1 aLi Ma 1 aXuhui Cong 1 aMirosław Skibniewski 00 aDeveloping a corporate social responsibility framework for sustainable construction using partial least squares structural equation modeling a186–212 0 v26 02459nas a2200169 4500000000100000000000100001008004100002100001400043700001500057700002600072245010000098856007100198300001200269490000700281520198700288022001402275 2019 d 1 aKaiman Li 1 aHanbin Luo 1 aMirosław Skibniewski 00 aA non-centralized adaptive method for dynamic planning of construction components storage areas uhttp://www.sciencedirect.com/science/article/pii/S1474034617305633 a80 - 94 0 v39 3 aRehandling of construction components, such as pipes, structural steel elements, and curtain walls, may increase the handling cost and reduce the construction efficiency, which is a critical issue for storage area plans of a project. Moreover, on some construction sites where space is limited, there are not adequate storage areas for centralized stacking of components and frequent changes in spatial state. Existing studies have investigated site layout planning for temporary facilities including arranging a storage area for the same type of material, which still have limitations in solving the above problems. This study proposes a novel and flexible arrangement method for incoming components in limited site space. This method is non-centralized and adaptive to the dynamic change of the actual component requirements based on construction activities and the real-time storage area availability. Therefore, a construction components storage areas planning (CCSAP) model is developed for dynamic allocation of construction components storage areas. Building information modeling (BIM) can be used to generate the material requirements planning before construction according to the actual construction activities. Real-time spatial recognition is a critical step for dynamic allocation of construction components storage areas because no such research has been done. This paper firstly presents an imaging technology with a low-rank matrix to identify on-site unoccupied locations automatically in real time. In addition, genetic algorithms (GA) consider two types of decision variables: actual components supply and real-time space availability. Finally, a dynamic visualization platform is built for planning construction components storage areas. An implementation example is demonstrated to validate principles and this model and shows a 21.9% reduction in the handling cost and a 19.4% increase in the construction efficiency compared with conventional methods.
a1474-0346 00339nas a2200145 4500000000100000000000100001008004100002100001500043700001400058700002600072700001100098700001700109245005800126490000900184 2019 d 1 aNuman Khan 1 aAhmad Ali 1 aMirosław Skibniewski 1 aDo Lee 1 aChansik Park 00 aExcavation Safety Modeling Approach Using BIM and VPL 0 v2019 00373nas a2200133 4500000000100000000000100001008004100002100001900043700001800062700001500080700002600095245010900121490000900230 2019 d 1 aChuanjun Zheng 1 aJingfeng Yuan 1 aLingzhi Li 1 aMirosław Skibniewski 00 aProcess-Based Identification of Critical Factors for Residual Value Risk in China's Highway PPP Projects 0 v2019 00392nas a2200145 4500000000100000000000100001008004100002100001800043700001500061700001600076700002600092245010600118300001400224490000800238 2019 d 1 aJingfeng Yuan 1 aLingzhi Li 1 aEndong Wang 1 aMirosław Skibniewski 00 aExamining sustainability indicators of space management in elderly Facilities—a case study in China a144–159 0 v208 00369nas a2200157 4500000000100000000000100001008004100002100001200043700001600055700001500071700001500086700002600101245006200127300001400189490000800203 2019 d 1 aYue Pan 1 aLimao Zhang 1 aXianguo Wu 1 aWenwei Qin 1 aMirosław Skibniewski 00 aModeling face reliability in tunneling: A copula approach a272–286 0 v109 00418nas a2200157 4500000000100000000000100001008004100002100001600043700001600059700002000075700002600095700002000121245009800141300001300239490000800252 2019 d 1 aShengyu Guo 1 aLieyun Ding 1 aYongcheng Zhang 1 aMirosław Skibniewski 1 aKongzheng Liang 00 aHybrid recommendation approach for behavior modification in the Chinese construction industry a04019035 0 v145 00422nas a2200157 4500000000100000000000100001008004100002100001800043700001100061700001100072700001400083700002600097245012000123300001400243490000700257 2019 d 1 aJingfeng Yuan 1 aWei Li 1 aBo Xia 1 aYuan Chen 1 aMirosław Skibniewski 00 aOperation performance measurement of public rental housing delivery by PPPS with fuzzy-AHP comprehensive evaluation a328–353 0 v23 00387nas a2200145 4500000000100000000000100001008004100002100001500043700001600058700001400074700002600088245010800114300001200222490000700234 2019 d 1 aCheng Zhou 1 aLieyun Ding 1 aYing Zhou 1 aMirosław Skibniewski 00 aVisibility graph analysis on time series of shield tunneling parameters based on complex network theory a10–24 0 v89 00382nas a2200121 4500000000100000000000100001008004100002100001800043700001400061700001600075700002600091245014300117 2019 d 1 aJingfeng Yuan 1 aLei Zhang 1 aYongtao Tan 1 aMirosław Skibniewski 00 aEvaluating the regional social sustainability contribution of public-private partnerships in China: The development of an indicator system 00420nas a2200145 4500000000100000000000100001008004100002100001800043700001500061700001400076700002600090245013500116300001600251490000700267 2019 d 1 aJingfeng Yuan 1 aWenying Ji 1 aJiyue Guo 1 aMirosław Skibniewski 00 aSimulation-based dynamic adjustments of prices and subsidies for transportation PPP projects based on stakeholders’ satisfaction a2309–2345 0 v46 00374nas a2200145 4500000000100000000000100001008004100002100001600043700001500059700001400074700002600088245009400114300001300208490000700221 2019 d 1 aLimao Zhang 1 aXianguo Wu 1 aWenli Liu 1 aMirosław Skibniewski 00 aOptimal Strategy to Mitigate Tunnel-Induced Settlement in Soft Soils: Simulation Approach a04019058 0 v33 00394nas a2200157 4500000000100000000000100001008004100002100001200043700001600055700001500071700001700086700002600103245008500129300001400214490000800228 2019 d 1 aYue Pan 1 aLimao Zhang 1 aXianguo Wu 1 aKainan Zhang 1 aMirosław Skibniewski 00 aStructural health monitoring and assessment using wavelet packet energy spectrum a652–665 0 v120 02014nas a2200157 4500000000100000000000100001008004100002260000900043100001200052700001600064700002600080245007800106856006300184490000700247520160200254 2020 d c2020 1 aYue Pan 1 aLimao Zhang 1 aMirosław Skibniewski 00 aClustering of designers based on building information modeling event logs uhttps://onlinelibrary.wiley.com/doi/abs/10.1111/mice.12551 0 v35 3 aA network-enabled event log mining approach is proposed for a deep understanding of the Building Information Modeling (BIM)-based collaborative design work. It proposes a novel algorithm termed node2vec-GMM combining a graph embedding algorithm named node2vec and a clustering method named Gaussian mixture model (GMM) to cluster designers within a network into several subgroups, and then makes cluster analysis. Its superiority lies in the efficient feature learning ability to preserve network structure and the powerful clustering ability to tackle uncertainty and visualize results, which can directly return the cluster embedding. As a case study, a directional network with 68 nodes (designers) and 436 ties (design task transmissions) is constructed based on retrieved data from 4GB real BIM event logs. The node2vec learns and projects the network feature representation into a 128-dimensional vector, which is learned by GMM to discover three possible clusters owning 15, 26, and 27 closely linked designers. Analysis of each cluster is performed from node importance measurement and link prediction to identify information spreading and designers’ roles within clusters. Our new algorithm node2vec-GMM is proven to better improve clustering quality than other state-of-the-art methods by at least 6.0% Adjusted Rand Index and 13.4% Adjusted Mutual Information. Overall, the designer clustering process provides managers with data-driven support in both monitoring the whole course of the BIM-based design and making reliable decisions to increase collaboration opportunities.
02477nas a2200193 4500000000100000000000100001008004100002100001900043700001500062700001900077700001800096700002600114245010300140856007100243300001100314490000700325520193700332022001402269 2020 d 1 aZhen-Song Chen 1 aXuan Zhang 1 aWitold Pedrycz 1 aXian-Jia Wang 1 aMirosław Skibniewski 00 aBid evaluation in civil construction under uncertainty: A two-stage LSP-ELECTRE III-based approach uhttp://www.sciencedirect.com/science/article/pii/S0952197620302025 a103835 0 v94 3 aIncreasing growth and development of building industry and civil engineering motivates enterprises to advance bid evaluation process in an effort to ameliorate building quality and diminish construction cost. The selection of qualified construction contractor has been generally formulated and addressed as a multi-attribute group decision-making problem. However, few existing studies have taken the reasoning logic pattern in human cognition process and the compensatory among attributes into account. Therefore, a two-stage logic scoring of preference-ELECTRE III-based approach is established for the management and manipulation of bidder selection. In a bid to facilitate expert evaluation articulation, alternative-attribute assessments in this approach take the form of generalized comparative linguistic expressions, which are subsequently converted into possibility-distribution-based hesitant fuzzy linguistic term set via the similarity measure-based generation approach to enhance information quality and reliability. Then, nonlinear optimization-based direction rules are introduced to advance the automatic minimum-distance-based consensus reaching model and based on which, the individual semantic-embedded assessments are algorithmically adjusted to reach acceptable consensus. Furthermore, the expert and attribute importance degrees are extracted from both semantic and formal logic aspects, and the modified individual assessments are gathered by integrating the two-stage logic scoring of preference aggregation structure and the ELECTRE III method. The present approach provides a solution to bid evaluation problems considering the reasoning logic pattern in human cognition process and the compensatory among attributes. A practical case study and a comparative analysis are performed to demonstrate the feasibility and effectiveness of the established multi-attribute group decision-making approach.
a0952-1976 00361nas a2200133 4500000000100000000000100001008004100002100001200043700002600055700001600081700001400097700001900111245009700130 2020 d 1 aHui Liu 1 aMirosław Skibniewski 1 aQianqian Ju 1 aJunjie Li 1 aHongbing Jiang 00 aBIM-enabled construction innovation through collaboration: a mixed-methods systematic review 01848nas a2200157 4500000000100000000000100001008004100002100001700043700001800060700001300078700002600091700001400117245011300131300001100244520143500255 2020 d 1 aXiaer Xiahou 1 aJingfeng Yuan 1 aHong Xie 1 aMirosław Skibniewski 1 aQiming Li 00 aExploring driving factors of smart city development under the physical-human society-cyber (PHC) space model a1–11 3 aThe concept of Smart City (SC) with its ambitious scheme has successfully attracted the interests of different stakeholders (i.e., government, information and communication technologies vendors, as well as researchers). While great efforts have been concentrating on the interpretation and the implementation of the ‘smartness’, the incentives for SC development are ignored. Understanding the incentives would clarify the goals of SC development and thereby boost its development efficiency. By exploring existing researches and cases of Nanjing, China, 15 factors were identified using a proposed physical-human society-cyber (P-H-C) space model. A structured questionnaire survey was conducted among different stakeholders in Nanjing to investigate their attitudes towards these factors. In factor analysis, these factors are grouped into three dimensions: technology push, government pull, and user-driven. Results show that currently SC development is mainly pushed by the technical progress and innovations. Meanwhile, government plays a significant role in pulling SC development especially at the initial stage. In addition, requirements to enhance the experience of end-users including government, companies, citizens etc. are critical for SC development. This paper provides insight on the incentives of SC development, research findings could be used as guidelines for the SC development in cities worldwide.
01956nas a2200193 4500000000100000000000100001008004100002260000800043100001400051700001800065700001600083700002600099245010000125856004600225300000900271490000700280520146100287022001401748 2020 d coct 1 aXijun Yao 1 aHsi-Hsien Wei 1 aIgal Shohet 1 aMirosław Skibniewski 00 aAssessment of Terrorism Risk to Critical Infrastructures: The Case of a Power-Supply Substation uhttps://www.mdpi.com/2076-3417/10/20/7162 a7162 0 v10 3 aThis paper presents a novel approach for estimating the vulnerability level of critical infrastructure confronting potential terrorist threats and assessing the usefulness of various protection strategies for critical infrastructure (CI). A methodology, utilizing a combination of topological network analysis and game theory, is presented to evaluate the effectiveness of protection strategies for certain components in the infrastructure under various attack scenarios. This paper focuses on protective strategies that are based on different attack scenarios as well as on the connectivity of the critical infrastructure components. The methodology proposed allows optimization of protection strategies in terms of investment in critical infrastructure protection in order to reduce expenditures on local infrastructure protection or on a single critical infrastructure for small projects. A case study of a power-supply substation is included to validate the analytical framework. The results indicate that the framework is highly applicable to other types of critical infrastructures facing similar threats. The results suggest that when only terrorist attacks are considered, improving the robustness of CI has a much higher effectiveness and efficiency than improving CI redundancy. The research methodology in this paper can be applied to a wide range of critical infrastructures and systems that may be at risk from manmade extreme events.
a2076-3417 00431nas a2200169 4500000000100000000000100001008004100002100001400043700001800057700001300075700001300088700001400101700002600115245009900141300001400240490000700254 2020 d 1 aLei Zhang 1 aJingfeng Yuan 1 aNini Xia 1 aYan Ning 1 aJunwei Ma 1 aMirosław Skibniewski 00 aMeasuring value-added-oriented BIM climate in construction projects: dimensions and indicators a800–818 0 v26 01615nam a2200181 4500000000100000000000100001008004100002260001300043100001600056700001200072700001500084700002600099245007100125300001200196490000800208520119500216020002201411 2021 d bSpringer 1 aLimao Zhang 1 aYue Pan 1 aXianguo Wu 1 aMirosław Skibniewski 00 aArtificial Intelligence in Construction Engineering and Management aXI, 263 0 v163 3 aThis book highlights the latest technologies and applications of Artificial Intelligence (AI) in the domain of construction engineering and management. The construction industry worldwide has been a late bloomer to adopting digital technology, where construction projects are predominantly managed with a heavy reliance on the knowledge and experience of construction professionals. AI works by combining large amounts of data with fast, iterative processing, and intelligent algorithms (e.g., neural networks, process mining, and deep learning), allowing the computer to learn automatically from patterns or features in the data. It provides a wide range of solutions to address many challenging construction problems, such as knowledge discovery, risk estimates, root cause analysis, damage assessment and prediction, and defect detection. A tremendous transformation has taken place in the past years with the emerging applications of AI. This enables industrial participants to operate projects more efficiently and safely, not only increasing the automation and productivity in construction but also enhancing the competitiveness globally.
In the past decades, the rapid urbanisation has driven the prosperity of building industry, which, however, has led to the consumption of enormous amounts of energy and resources and the continued deterioration of the environment owing to its unsustainable development. These outcomes impact seriously the ecosystems and human health. In order to promote the sustainable performance of building sector, the widely adoption of sustainable building materials has been considered as one of the most promising ways toward this endeavor. This paper aims at addressing the problem of sustainable building material selection (SBMS) under uncertain context by developing an integrated multi-criteria large-group decision-making framework. In the proposed framework, the assessment information is characterised in the form of Improved Basic Uncertain Linguistic Information (IBULI), which incorporates reliable degrees of decision experts that can accurately quantify subjective assessment information provided under uncertainty. The weights of assessment criteria for SBMS are determined by the Quality Function Deployment-based method that is capable of accommodating the influences of multiple stakeholders and the fields of conflicts amongst them. Subsequently, the assessment information given by a large-group of decision experts are aggregated by IBULI-aggregation operators guided by an IBULI-based correlation- and consensus-driven clustering method, which achieves the classification of large-scale decision experts and the satisfied consensus level simultaneously. The selection of sustainable building materials is eventually accomplished by the IBULI-based Technique for Order Preference by Similarity to Ideal Solution method. Finally, an illustrative example accompanied by sensitivity and comparative analyses is performed to verify the rationality and feasibility of the proposed model.
00470nas a2200157 4500000000100000000000100001008004100002100001400043700001700057700001900074700002600093700001900119700001800138700001900156245013700175 2021 d 1 aAli Khoso 1 aAminah Yusof 1 aZhen-Song Chen 1 aMirosław Skibniewski 1 aKwai-Sang Chin 1 aShabir Khahro 1 aSamiullah Sohu 00 aComprehensive analysis of state-of-the-art contractor selection models in construction environment-A critical review and future call 00313nas a2200121 4500000000100000000000100001008004100002100002400043700002600067700001800093245007200111490000800183 2021 d 1 aSvetlana Besklubova 1 aMirosław Skibniewski 1 aXueqing Zhang 00 aFactors Affecting 3D Printing Technology Adaptation in Construction 0 v147 00273nas a2200097 4500000000100000000000100001008004100002100001200043700002600055245009400081 2021 d 1 aMing Hu 1 aMirosław Skibniewski 00 aA Review of Building Construction Cost Research: Current Status, Gaps and Green Buildings 00451nas a2200157 4500000000100000000000100001008004100002100001500043700001000058700001500068700002300083700002300106700002600129245013000155490000800285 2021 d 1 aXuhui Cong 1 aLi Ma 1 aLiang Wang 1 aJonas Šaparauskas 1 aJarosław Górecki 1 aMirosław Skibniewski 00 aThe early warning system for determining the “not in My Back Yard” of heavy pollution projects based on public perception 0 v282 00405nas a2200133 4500000000100000000000100001008004100002100001800043700001500061700002600076700001700102245014500119490000700264 2021 d 1 aMuhammad Khan 1 aNuman Khan 1 aMirosław Skibniewski 1 aChansik Park 00 aEnvironmental Particulate Matter (PM) Exposure Assessment of Construction Activities Using Low-Cost PM Sensor and Latin Hypercubic Technique 0 v13 00364nas a2200133 4500000000100000000000100001008004100002100001900043700001800062700001600080700002600096245010100122490000700223 2021 d 1 aHan-Tang Huang 1 aH Ping Tserng 1 aRuei-Yu Hou 1 aMirosław Skibniewski 00 aWireless Sensor Network-Based Monitoring of Bridge Pile Foundations for Detecting Scouring Depth 0 v29 02021nas a2200145 4500000000100000000000100001008004100002100001100043700001300054700001300067700002600080245011900106490000700225520164300232 2022 d 1 aY. Pan 1 aL. Zhang 1 aJ. Unwin 1 aMirosław Skibniewski 00 aDiscovering spatial-temporal patterns via complex networks in investigating COVID-19 pandemic in the United States 0 v77 3 aA novel approach combining time series analysis and complex network theory is proposed to deeply explore characteristics of the COVID-19 pandemic in some parts of the United States (US). It merges as a new way to provide a systematic view and complementary information of COVID-19 progression in the US, enabling evidence-based responses towards pandemic intervention and prevention. To begin with, the Principal Component Analysis (PCA) varimax is adopted to fuse observed time-series data about the pandemic evolution in each state across the US. Then, relationships between the pandemic progress of two individual states are measured by different synchrony metrics, which can then be mapped into networks under unique topological characteristics. Lastly, the hidden knowledge in the established networks can be revealed from different perspectives by network structure measurement, community detection, and online random forest, which helps to inform data-driven decisions for battling the pandemic. It has been found that states gathered in the same community by diffusion entropy reducer (DER) are prone to be geographically close and share a similar pattern and tendency of COVID-19 evolution. Social factors regarding the political party, Gross Domestic Product (GDP), and population density are possible to be significantly associated with the two detected communities within a constructed network. Moreover, the cluster-specific predictor based on online random forest and sliding window is proven useful in dynamically capturing and predicting the epidemiological trends for each community, which can reach the highest.
00434nas a2200169 4500000000100000000000100001008004100002260000800043100001200051700001600063700001200079700001300091700002600104700001600130245010900146490000900255 2022 d cjan 1 aHui Liu 1 aQianqian Ju 1 aNa Zhao 1 aHujun Li 1 aMirosław Skibniewski 1 aHanliang Fu 00 aValue Proposition for Enabling Construction Project Innovation by Applying Building Information Modeling 0 v2022 01829nas a2200205 4500000000100000000000100001008004100002260001500043100001300058700001800071700001900089700001600108700001800124700002000142700001600162700002600178245006400204520134100268022001401609 2023 d c01/08/2023 1 aYang Liu 1 aXian-Jia Wang 1 aZhen-Song Chen 1 aYifei Zhang 1 aShenghao Zhao 1 aMuhammet Devici 1 aLeSheng Jin 1 aMirosław Skibniewski 00 aEvaluating Digital Health Services Quality via Social Media 3 aGiven the widespread demand for digital health services, a systematic study on the quality of digital health services is essential. Based on the current situation of tertiary hospitals in central China providing digital health services via social media, we used the Cronbach and Bayesian Best and Worst methods to evaluate the quality of hospital digital health services and conduct an empirical study of several hospitals. Based on the results of the empirical study, we propose a path for constructing a digital health service platform, suggesting that hospitals focus on building business function services of social media and accelerate the development of Internet hospitals. Hospitals should also improve the operation and maintenance of social media, optimize the intelligence of online guidance, and simplify the design logic of function menus. In terms of content information services, hospitals need to design targeted content according to the characteristics of different social media, improve content quality, and ensure the appropriate proportion of various types of information. With such measures, hospitals can guide users to use social media through business function services and retain users through content information services to increase the influence of hospitals and the quality of social health welfare.
a0018-9391 00397nas a2200133 4500000000100000000000100001008004100002100002400043700001700067700001900084700002600103245012500129490000900254 2018 d 1 aPrzemysław Sekuła 1 aZachary Laan 1 aKaveh Sadabadi 1 aMirosław Skibniewski 00 aPredicting work zone collision probabilities via clustering: application in optimal deployment of highway response teams 0 v2018 01523nas a2200181 4500000000100000000000100001008004100002260001200043100002000055700002000075700002000095700002200115700002600137245009200163856007700255490001200332520099700344 2023 d c10/2023 1 aBartosz Wójcik 1 aMateusz Żarski 1 aKamil Książek 1 aJaroslaw Miszczak 1 aMirosław Skibniewski 00 aA deep learning method for hard-hat-wearing detection based on head center localization uhttps://journals.pan.pl/dlibra/publication/147340/edition/128931/content 0 v71 (EA) 3 aIn recent years, a lot of attention is paid to deep learning methods in the context of vision-based construction site safety systems. However, there is still more to be done to establish the relationship between supervised construction workers and their essential personal protective equipment, like hard hats. A deep learning method combining object detection, head center localization, and simple rule-based reasoning is proposed in this article. In tests, this solution surpassed the previous methods based on the relative bounding box position of different instances and direct detection of hard hat wearers and non-wearers. Achieving MS COCO style overall AP of 67.5% compared to 66.4% and 66.3% achieved by the approaches mentioned above, with class-specific AP for hard hat non-wearers of 64.1% compared to 63.0% and 60.3%. The results show that using deep learning methods with a humanly interpretable rule-based algorithm is better suited for detecting hard hat non-wearers.
02304nas a2200169 4500000000100000000000100001008004100002260001200043100001900055700001900074700001600093700001900109700002600128245012500154490000800279520184700287 2024 d c03/2024 1 aZhen-Song Chen 1 aChong-Ze Liang 1 aYa-Qiang Xu 1 aWitold Pedrycz 1 aMirosław Skibniewski 00 aDynamic collective opinion generation framework for digital transformation barrier analysis in the construction industry 0 v103 3 aThe absence of a reliable, dynamic evaluation system has impeded early-stage industrial research progress, particularly in the digital transformation of the construction industry. Moreover, existing research studies rarely explore the impact of digitalt transformation barriers considering the interplays among them. This paper aims to introduce an innovative framework to generate dynamic collective opinions for barrier analysis in such context. The proposed dynamic collective opinion generation framework comprises three key components: Collective Opinion Generation, Prediction with Expert Advice (PEA), and Social Network Analysis. Its goal is to provide dependable decision support when subjective evaluation data from experts is available. Initially, a bi-objective optimization model generates the initial barrier weight vector. The PEA incorporates a loss function to measure the deviation between aggregated probablity density function and actual observed data, updating the weight vector over time. Next, an influence network covering all barriers is established. Node significance is evaluated through metrics like degree centrality, closeness centrality, and eigenvector centrality. The gravity model based on three metrics is used to determine interrelationships among barriers, resulting in a weight vector capturing these interplays. The two weight vectors are combined with Nash equilibrium, yielding the ultimate weight vector for barriers. The effectiveness of the proposed dynamic collective opinion generation framework is showcased through a case study on China Construction Third Bureau. Results indicate that talent structure notably influences construction companies' digital transformation. Additionally, market structure and strategic position significantly impact digital transformation in this industry.
02667nas a2200181 4500000000100000000000100001008004100002260001200043100001900055700001800074700002000092700001700112700001900129700002600148245014600174490000800320520215700328 2024 d c02/2024 1 aZhen-Song Chen 1 aZhuo-Ran Wang 1 aMuhammet Deveci 1 aWeiping Ding 1 aWitold Pedrycz 1 aMirosław Skibniewski 00 aOptimization-based probabilistic decision support for assessing building information modelling (BIM) maturity considering multiple objectives 0 v102 3 aThe phase of operation and maintenance (O&M) is the most time-consuming and cost-intensive stage in the project life cycle. However, the potential benefits of Building Information Modeling (BIM) in this phase have not been fully explored, unlike in the design and construction phases. This is particularly evident in the absence of a comprehensive assessment of its application capabilities. In light of this setting, we develop a BIM maturity assessment model (BIM MAM) for the project’s O&M phase. The proposed model comprises of an assessment indicator system that facilitates experts in providing individual assessment results, and a collective opinion aggregation method in a probabilistic context based on a multi-objective optimization model that is employed to generate the ultimate collective assessment results. The established multi-objective optimization model for BIM MAM incorporates the influence of human behavior factors on the final results by introducing the fairness concern utility level as an objective. Finally, we take Wuhan Jiangxia Sewage Treatment Plant as a practical case to illustrate the effectiveness and feasibility of the proposed BIM MAM.
02077nas a2200169 4500000000100000000000100001008004100002260001200043100001900055700001700074700001600091700001900107700002600126245010200152490000700254520164600261 2024 d c01/2024 1 aZhen-Song Chen 1 aKou-Dan Chen 1 aYa-Qiang Xu 1 aWitold Pedrycz 1 aMirosław Skibniewski 00 aMultiobjective optimization-based decision support for building digital twin maturity measurement 0 v59 3 aThe digital twin (DT) represents a powerful tool for advancing construction industry to provide a cyber–physical integration that enables real-time monitoring of assets and activities and facilitates decision-making. Due to the inherent characteristics of the construction industry and the diverse possibilities with DT, proliferation of building digital twin (BDT) necessitates a comprehensive comprehension of its evolution and the creation of roadmaps. This paper aims to contribute to the formalization and standardization of BDT. It designs a novel assessment framework for the overall maturity measurement of existing BDT projects. The developed BDT maturity model incorporates a collective opinion generation paradigm based on a fairness-aware multiobjective optimization model to provide an expert-based evaluation system for evaluating the maturity of BDT projects. The effectiveness and feasibility of the proposed framework have been validated through a case study of an experimental BDT initiative. This paper establishes a generalizable framework for BDT maturity assessment that can offer insights into BDT maturity standards to construction practitioners to create effective strategies for the diffusion, development, and maturation of BDT.
02313nas a2200205 4500000000100000000000100001008004100002260001200043100001900055700001300074700001600087700001700103700002000120700002000140700001800160700002600178245013600204490000600340520176100346 2023 d c12/2023 1 aZhen-Song Chen 1 aJia Zhou 1 aChen-Ye Zhu 1 aZhu-Jun Wang 1 aSheng-Hua Xiong 1 aRosa Rodríguez 1 aLuis Martinez 1 aMirosław Skibniewski 00 aPrioritizing real estate enterprises based on credit risk assessment: an integrated multi-criteria group decision support framework 0 v9 3 aCredit risk assessment involves conducting a fair review and evaluation of an assessed subject’s solvency and creditworthiness. In the context of real estate enterprises, credit risk assessment provides a basis for banks and other financial institutions to choose suitable investment objects. Additionally, it encourages real estate enterprises to abide by market norms and provide reliable information for the standardized management of the real estate industry. However, Chinese real estate companies are hesitant to disclose their actual operating data due to privacy concerns, making subjective evaluation approaches inevitable, occupying important roles in accomplishing Chinese real estate enterprise credit risk assessment tasks. To improve the normative and reliability of credit risk assessment for Chinese real estate enterprises, this study proposes an integrated multi-criteria group decision-making approach. First, a credit risk assessment index for Chinese real estate enterprises is established. Then, the proposed framework combines proportional hesitant fuzzy linguistic term sets and preference ranking organization method for enrichment evaluation II methods. This approach is suitable for processing large amounts of data with high uncertainty, which is often the case in credit risk assessment tasks of Chinese real estate enterprises involving massive subjective evaluation information. Finally, the proposed model is validated through a case study accompanied by sensitivity and comparative analyses to verify its rationality and feasibility. This study contributes to the research on credit assessment for Chinese real estate enterprises and provides a revised paradigm for real estate enterprise credit risk assessment.
01595nas a2200193 4500000000100000000000100001008004100002260001200043100001600055700001300071700002600084700001500110700001500125700002300140700001400163245008000177490000800257520113600265 2023 d c11/2023 1 aHuanbao Liu 1 aZihan Li 1 aMirosław Skibniewski 1 aLiang Wang 1 aXuhui Cong 1 aJarosław Górecki 1 aWenyu Jin 00 aMolding quality control with nonlinear forming method in 3D cement printing 0 v235 3 a3D cement printing is an emerging technology that can construct building elements without formwork, which has broad application prospects in the field of constructing non-linear and complex building structures. However, the high-quality printing and molding of nonlinear structure has become one of the bottleneck technologies restricting the development of 3D building printing. In this paper, variable radian 3D printing nozzle is firstly developed to verify the controllability of extruded concrete material based on self-developed 3D building printer. Then, variable radian forming theory is presented and used to evaluate the mechanism material fracture and accumulation, and improve the molding quality of nonlinear structure. Finally, simulation analysis and experiments are designed to explore the controllable mechanism of variable radian molding and verify the consistency between the experimental results and the theoretical analysis. The research results can promote the application of 3D printing in the construction industry, and provide support for the utilization of building resources and green buildings.
01984nas a2200169 4500000000100000000000100001008004100002260001200043100001200055700001900067700001200086700001800098700002600116245012600142490000800268520153800276 2023 d c11/2023 1 aLu Xiao 1 aZhen-Song Chen 1 aRui Hou 1 aAbbas Mardani 1 aMirosław Skibniewski 00 aGreenness-based subsidy and dual credit policy to promote new energy vehicles considering consumers' low-carbon awareness 0 v185 3 aConsidering a market consisting of a new energy vehicle (NEV) manufacturer, a fuel vehicle (FV) manufacturer, the government, and consumers with low-carbon awareness, this paper constructs NEV-FV competitive models to study the effect of greenness-based subsidy policy and dual credit policy on prices, quantities, profits, consumer surplus and social welfare. Under the greenness-based subsidy policy, the government provides subsidies based on NEVs’ carbon emission reduction to consumers. Under the dual credit policy, the FV manufacturer has to purchase NEV credits from the NEV manufacturer before starting to manufacture. The government’s optimal subsidy strategy and the two manufacturers’ pricing and production strategies of two kinds of vehicles are studied. The impact of consumers’ low-carbon awareness, NEVs’ carbon emission reduction, unit production cost, and unit cost gap between two kinds of vehicles with respect to equilibrium decisions are analyzed. The results show that both the greenness-based subsidy policy and dual credit policy can improve NEVs’ market share when the manufacturing cost gap is relatively low, and enhance the NEV firm’s competitiveness when the investment cost of greenness-enhancement is relatively low. The subsidy policy can improve social welfare, whereas the dual credit policy is harmful to social welfare. In terms of promoting the sales and profits of NEVs, both the subsidy policy and dual credit policy can play a positive role under different conditions.
02638nas a2200181 4500000000100000000000100001008004100002260001200043100001900055700001500074700001800089700001700107700002000124700002600144245011700170490000800287520216100295 2023 d c11/2023 1 aZhen-Song Chen 1 aJing-Yi Lu 1 aJiang-Tao Wen 1 aXianjia Wang 1 aMuhammet Deveci 1 aMirosław Skibniewski 00 aBIM-enabled decision optimization analysis for architectural glass material selection considering sustainability 0 v647 3 aThe careful consideration and choice of Sustainable Architectural Glass Material (SAGM) is a crucial step towards reducing energy consumption and enhancing the overall sustainability of buildings. However, the current techniques employed for selecting architectural glass material do not take into account the aspect of sustainability in the ultimate adoption of material solutions, as perceived by the stakeholders. This study aims to develop a comprehensive evaluation criteria system and introduce a group decision support framework that utilizes Building Information Modeling technology to facilitate the selection of SAGM in large-scale projects, in accordance with the demands of various stakeholders. The proposed framework is utilized to address a selection problem related to SAGM faced by a large construction corporation in Wuhan. The findings indicate that the criteria of daylighting and thermal insulation performance hold significant importance, with insulating glass being a subtype of SAGM exhibiting superior performance. Ultimately, the proposed model is subjected to sensitivity and comparative analyses to validate its advantages over several existing methodologies. The proposed model in this study offers practitioners an optimized methodology for the selection of SAGM, while also providing a framework for the selection of other sustainable building materials.
02887nas a2200205 4500000000100000000000100001008004100002260001200043100001500055700001500070700001300085700001400098700001500112700002300127700002300150700002600173245017500199490001200374520229500386 2023 d c10/2023 1 aXuhui Cong 1 aZhipeng Qi 1 aSai Wang 1 aPeikun Su 1 aLiang Wang 1 aJonas Šaparauskas 1 aJarosław Górecki 1 aMirosław Skibniewski 00 aEcological Welfare Performance Evaluation and Spatial–Temporal Difference Evolution of Blue Economic Zones: A Case Study of the Blue Economic Zone of Shandong Peninsula 0 v12 (10) 3 aEcological security (ES) is an important element in the construction of an ecological civilization and plays a vital role in ensuring the sustainable development of social economies. Further, ES is an important measure of regional sustainable development. Based on ecosystem theory, this study constructs a comprehensive evaluation framework using the driving force-pressure-state-impact-response (DPSIR) and slacks-based measure of data envelopment analysis (SBM-DEA) models. Taking the Three Gorges Reservoir Area as an example, the study develops an ES evaluation system and realizes a transformation from “efficiency” to “quality”.Gray correlation theory and spatial autocorrelation and are adopted to analyze the ecosystem's spatial–temporal evolution and driving factors. The results demonstrate that the overall level of ES in the Three Gorges Reservoir Area from 2010 to 2020 was good; however, the spatial distribution of ES revealed an unbalanced state. The influence of each subsystem on the result of the ES evaluation is state > response > impact > driving force > pressure. The spatial correlation analysis of ES in the Three Gorges Reservoir area exhibited a positive autocorrelation, and the agglomeration effect was significant; on this basis, the key factors affecting ES were identified. The ratio of environmental protection investment, sewage treatment rate, green coverage rate of built-up areas, proportion of primary industry in GDP, and proportion of tertiary industry in GDP had notable effects on the ES of the study area. The research contributes to the theory of ES and provides guidance for ecologically sustainable development.
02529nas a2200181 4500000000100000000000100001008004100002260001200043100001700055700001900072700001100091700001200102700002000114700002600134245010200160490000900262520207600271 2023 d c12/2023 1 aZhu-Jun Wang 1 aZhen-Song Chen 1 aQin Su 1 aLu Xiao 1 aKannan Govindan 1 aMirosław Skibniewski 00 aBlockchain adoption in sustainable supply chains for Industry 5.0: A multistakeholder perspective 0 v8(4) 3 aIndustry 5.0 has introduced a novel interpretation of sustainable supply chains (SSCs) that emphasizes the importance of building a transparent and trustworthy network that can be continuously monitored and controlled through stakeholder collaboration as well as the use of advanced, intelligent machinery. The ultimate goal of SSCs is to meet specific economic, social, and environmental standards. The implementation of blockchain technology can significantly improve the reliability, efficiency, and security of the information exchanged among stakeholders in SSCs. However, these stakeholders inevitably possess varying informational advantages and exhibit divergent perspectives regarding the adoption of blockchain technology. This paper thus aims to examine the impediments to the adoption of blockchain technology in the context of SSCs with the goal of promoting blockchain adoption. To achieve this objective, this study analyzes the barriers to blockchain adoption from the perspectives of various stakeholders in SSCs and constructs a barrier severity assessment model that utilizes group decision-making methods to integrate all stakeholders’ attitudes. This study employs the PEEST (political, economic, environmental, social, and technological) framework to identify 27 barriers to the adoption of blockchain technology. Subsequently, an expertise-based group decision-making approach is used to quantify the prominence of various barriers according to various types of stakeholders. The results indicate that the five most intense barriers are storage constraints, insufficient economic incentives, high integration costs, a lack of functional appeal, and ambiguity regarding data disclosure and public data management regulations. This research makes novel theoretical and practical contributions, as it takes an empirical and all-encompassing approach to identifying obstacles to the adoption of blockchain technology and provides valuable insights for policymakers and practitioners to reference in overcoming these obstacles.
02025nas a2200205 4500000000100000000000100001008004100002260001200043100001500055700001400070700001500084700001300099700001500112700002300127700002300150700002600173245015400199490001000353520145600363 2023 d c10/2023 1 aXuhui Cong 1 aPeikun Su 1 aLiang Wang 1 aSai Wang 1 aZhipeng Qi 1 aJonas Šaparauskas 1 aJarosław Górecki 1 aMirosław Skibniewski 00 aMeasuring the Construction Efficiency of Zero-Waste City Clusters Based on an Undesirable Super-Efficiency Model and Kernel Density Estimation Method 0 v11(9) 3 aThe global total amount of generated solid waste is currently on a rapid growth trend. China, as the largest developing country, promulgated its Pilot Work Plan for the Construction of Zero-Waste Cities led by the new development concept in 2018 after recognizing the inadequacy and urgency of solid waste management, and the lack of valuable experience and benchmark cities for the construction of zero-waste cities. This study uses the undesirable super-efficiency model and kernel density estimation method to measure the efficiency of zero-waste city construction in 16 prefecture-level cities in Shandong Province and analyze their spatial and temporal differences. Three major problems were found, namely, low regional coordination, the rigid policies of some local governments, and the unbalanced development of scale efficiency and pure technical efficiency. Results show that the zero-waste city construction efficiency as a whole shows a declining and then fluctuating growth trend, and that low-scale efficiency is the main reason behind the decrease in construction efficiency. Suggestions are then provided considering three aspects: improving regional synergy; improving government quality and capacity, and strengthening government supervision and revitalizing the market; and introducing social capital for environmental pollution treatment. These suggestions ultimately help improve the level of zero-waste city construction.
02427nas a2200181 4500000000100000000000100001008004100002260001200043100001900055700001600074700001700090700002300107700002700130700002600157245009000183490001000273520196200283 2023 d c09/2023 1 aZhen-Song Chen 1 aZhengze Zhu 1 aXianjia Wang 1 aFrancisco Chiclana 1 aEnrique Herrera-Viedma 1 aMirosław Skibniewski 00 aMultiobjective Optimization-Based Collective Opinion Generation With Fairness Concern 0 v59(9) 3 aThe generation of collective opinion based on probability distribution function (PDF) aggregation is gradually becoming a critical approach for tackling immense and delicate assessment and evaluation tasks in decision analysis. However, the existing collective opinion generation approaches fail to model the behavioral characteristics associated with individuals, and thus, cannot reflect the fairness concerns among them when they consciously or unconsciously incorporate their judgments on the fairness level of distribution into the formulations of individual opinions. In this study, we propose a multi-objective optimization-driven collective opinion generation approach that generalizes the bi-objective optimization-based PDF aggregation paradigm. In doing so, we adapt the notion of fairness concern utility function to characterize the influence of fairness inclusion and take its maximization as an additional objective, together with the criteria of consensus and confidence levels, to achieve in generating collective opinion. The formulation of fairness concern is then transformed into the congregation of individual fairness concern utilities in the use of aggregation functions. We regard the generalized extended Bonferroni mean as an elaborated framework for aggregating individual fairness concern utilities. In such way, we establish the concept of Bonferroni mean-type collective fairness concern utility to empower multi-objective optimization-driven collective opinion generation approach with the capacity of modeling different structures associated with the expert group with fairness concern. The application of the proposed fairness-aware framework in the maturity assessment of building information modelling demonstrates the effectiveness and efficiency of multi-objective optimization-driven approach for generating collective opinion when accomplishing complicated assessment and evaluation tasks with data scarcity.
02502nas a2200205 4500000000100000000000100001008004100002260001200043100001500055700001300070700001700083700001200100700001200112700001900124700001300143700002600156245013500182490000800317520197100325 2023 d c06/2023 1 aXianguo Wu 1 aYuan Cao 1 aWeicheng Liu 1 aYabo He 1 aGang Xu 1 aZhen-Song Chen 1 aYang Liu 1 aMirosław Skibniewski 00 aBIM-driven building greenness evaluation system: An integrated perspective drawn from model data and collective experts' judgments 0 v406 3 aTraditional buildings will lead to a series of problems such as high energy consumption, high pollution, and serious waste of resources and environmental damage. It is of great significance to construct a green building evaluation system based on the physical building framework to achieve energy saving and consumption reduction and to fit the sustainable development. In this study, a building greenness evaluation system combining BIM data model and prior knowledge of experts is constructed and the applicability of the method has been verified. IFC information is expressed and transmitted in terms of components, materials, equipment, environmental quality impact, etc., and BIM based building performance design data information conversion and greenness evaluation process is constructed; Based on the comparison and summary of the existing green building evaluation systems at home and abroad, the evaluation model of building greenness is determined; Based on the ideas and steps of establishing the index system proposed in the research, the index system of building greenness evaluation is established from the aspects of environmental quality (Q) and building load (L) on the basis of questionnaire, prior knowledge of experts and other methods; Combined with the mathematical model of greenness evaluation, the paper analyzes the indexes of different levels, determines the structural calculation methods of different indexes, and carries on the quantitative classification of the overall greenness evaluation. Finally, taking a citizen's house as an engineering case, the paper makes an empirical analysis on the greenness evaluation of green buildings. The results show that the green degree of the building is excellent(class A), which is consistent with the project positioning, and provides the basis for the efficient and accurate evaluation of green building. † Xianguo Wu and Yuan Cao and Weicheng Liu contributed equally to the work.
01940nas a2200181 4500000000100000000000100001008004100002260001200043100002000055700001600075700001900091700002000110700002300130700002600153245011800179490000800297520145300305 2023 d c03/2023 1 aSheng-Hua Xiong 1 aChen-Ye Zhu 1 aZhen-Song Chen 1 aMuhammet Deveci 1 aFrancisco Chiclana 1 aMirosław Skibniewski 00 aOn extended power geometric operator for proportional hesitant fuzzy linguistic large-scale group decision-making 0 v632 3 aThe unduly low or high data are commonly regarded as outliers in the classical power geometric operator. However, in many cases, these types of data may be significantly important to the aggregated results. This study aims at expanding the practical application scope of the power geometric operator and then utilizing it to develop a proportional hesitant fuzzy linguistic large-scale group decision-making (LSGDM) model. The extended power geometric (EPG) operator is first introduced, in which these outliers can be distinguished as sufficiently important or "false/biased" data in accordance with the decision-making context. Several useful properties and application characteristics of the EPG operator are highlighted. Subsequently, the proportional hesitant fuzzy linguistic normalized Manhattan distance is proposed, which is a basic concept for the construction of the proportional hesitant fuzzy linguistic extended power geometry (PHFLEPG) operator. Combined with the clustering model for decision-makers, a PHFLEPG-operator-based consensus-reaching approach is provided to simplify and rationalize the decision-making process. Furthermore, the comprehensive LSGDM result is derived by utilizing the PHFLEPG operator. Eventually, a case study on regulatory capacity evaluation for the Civil Aviation Safety Regulatory Authority of China is performed to validate the feasibility and effectiveness of the established LSGDM method.
01827nas a2200205 4500000000100000000000100001008004100002260001200043100001600055700001300071700001700084700001300101700001400114700002600128700001900154700001300173245007100186490000800257520135600265 2023 d c06/2023 1 aHongyu Chen 1 aXinyi Li 1 aZongbao Feng 1 aLei Wang 1 aYawei Qin 1 aMirosław Skibniewski 1 aZhen-Song Chen 1 aYang Liu 00 aShield attitude prediction based on Bayesian-LGBM machine learning 0 v632 3 aEffective shield attitude control is essential for the quality and safety of shield construction. The traditional shield attitude control method is manual control based on a driver's experience, which has the defects of hysteresis and poor reliability. This research proposes an intelligent method to predict the shield attitude based on a Bayesian-light gradient boosting machine (LGBM) model. The constructed model includes 29 parameters that impact the shield attitude and 6 parameters that represent the shield attitude. The developed the Bayesian-LGBM model can predict the shield attitude and support shield attitude control by adjusting construction parameters and conducting iterative prediction. Guiyang rail transit line 3 is selected as a case study to verify the effectiveness of the proposed method. The results indicate: (1) The developed the Bayesian-LGBM model is able to effectively predict the shield attitude; (2) The importance ranking can clarify the key construction parameters that should be controlled; (3) The proposed method enables support the effective shield attitude control by continuously adjusting the shield construction parameters. the proposed attitude guidance control method based on the Bayesian-LGBM can be used to provide a reference for actual shield attitude applications and other similar problems.
03199nas a2200169 4500000000100000000000100001008004100002260001200043100001300055700001200068700002600080700001300106700001500119245014700134490000800281520274000289 2023 d c05/2023 1 aPing Xie 1 aKe Chen 1 aMirosław Skibniewski 1 aJun Wang 1 aHanbin Luo 00 aParametric geological model update and probabilistic analysis of shield tunnel excavation: A borehole-based conditional random fields approach 0 v157 3 aShield tunnel construction has faced considerable challenges due to the uncertain geological conditions in real scenarios. The borehole data obtained from geological investigations are often too limited to effectively evaluate uncertainties at nonsampled points. Moreover, the existing probabilistic safety assessment (PSA) frameworks that consider the uncertainties of soil properties have encountered limitations in engineering practice due to the complexity of conditional random field (CRF) theory and the operability of numerical modeling. Based on the digitization of the underground infrastructure, this study implements the object-oriented parametric modeling (PM) to address these limitations. A PM-CRF engine is first developed to automate the process of parametric geological modeling using CRFs. Then, a PM-CRF-PSA interoperability framework is proposed to automatically generate a PSA model for comprehensive safety assessment considering the uncertainties of soil properties. Finally, a case study is conducted with the proposed framework to assess the whole process of parametric modeling from CRF characterization to PSA. The results of this study highlight the clear advantages of this framework compared to traditional deterministic safety assessment (DSA) methods in terms of characterization of the uncertainty of soil properties and the efficiency of PSA modeling. Thus, the proposed framework enables the efficient and comprehensive exploration of shield tunnel design schemes by considering the uncertainties of soil properties.
01892nas a2200169 4500000000100000000000100001008004100002260001200043100001500055700001300070700001500083700001500098700002600113245011300139490001000252520146000262 2023 d c04/2023 1 aXuhui Cong 1 aSai Wang 1 aLiang Wang 1 aZhipeng Qi 1 aMirosław Skibniewski 00 aNew smart city clusters’ construction level evaluation under economic circles: the case of Shandong, China 0 v29(3) 3 aChina’s Shandong Province plans to create a new smart city cluster that is developmentfocused, demand-led, people-oriented, and data-driven. This entails the scientific assessment of construction levels, analysis of potential hurdles, and formulation of upgraded strategies. However, existing research has mainly focused on measuring single or multiple traditional smart cities, therein overlooking the construction level of new smart city clusters. Thus, this study takes the new smart city clusters in Shandong Province and uses both entropy method and the Moran index to analyze the construction level and spatial differences in the four dimensions of social livelihood, economic production, innovation-driven development, and safeguard measures. Results show that the construction level of the provincial capital economic circle is uneven and has polarization issues. Meanwhile, the construction level of Jiaodong economic circle is relatively good, although the economic driving capacity needs further improvement. The low urbanization rate of the Lunan economic circle occupies a gathering zone with low construction levels, making the construction of digital villages necessary. Targeted suggestions in improving the radiationdriven capacity of core cities, improving digital infrastructure, and developing smart industries are then forwarded to promote the establishment of new smart city clusters and achieve top-notch economic growth.
01925nas a2200181 4500000000100000000000100001008004100002260001200043100001600055700001500071700001400086700001900100700001700119700002600136245007900162490001000241520149200251 2023 d c05/2023 1 aOmar Daboun 1 aNur Abidin 1 aAli Khoso 1 aZhen-Song Chen 1 aAminah Yusof 1 aMirosław Skibniewski 00 aEffect of relationship management on construction project success delivery 0 v29(5) 3 aThe dynamic, challenging, and complex nature of the construction projects environment often cause adversarial culture, disputed claims, and deteriorating relationships between project participants. This paper aims to study the correlation between Relationship Management (RM) and construction project success and to develop a framework that includes practical actions, tools, and strategies for managing relationships in construction projects. Literature review and interviews were used to explore and validate the RM’s relevant associated traits. Subsequently, a piloted questionnaire was used to collect the data from 264 construction experts and assess the effect of RM on the overall project success. The data were analyzed using Partial-Least Squares Structural Equation Modeling (PLS-SEM), where the structural and measurement models of the higher and lower order constructed were assessed. The study findings categorized the RM-associated traits into three main pillars: Contractual Measures, Team Interactions, and Top Management Actions. The findings also confirmed that RM has a significant positive effect on the overall success of construction projects. In addition, this paper proposed an integrated framework for managing relationships in construction projects, allowing construction firms to monitor the relationships in their projects and identify key areas for strengthening the relationships throughout their projects to foster their projects' success rates.
01581nas a2200157 4500000000100000000000100001008004100002260001200043100001900055700001900074700001200093700002000105700002600125245009500151520117700246 2023 d c02/2023 1 aTong-Yuan Wang 1 aZhen-Song Chen 1 aPeng He 1 aKannan Govindan 1 aMirosław Skibniewski 00 aAlliance strategy in an online retailing supply chain: Motivation, choice, and equilibrium 3 aIn this paper, we investigate the alliance strategy in an Online Retailing Supply Chain (ORSC). Three alliance models in addition to one no alliance model are built and examined. The no alliance model as a benchmark is developed to characterize the alliance motivation for each supply chain member. Afterwards, we identify the optimal alliance strategy and the final alliance equilibrium. The results show that the manufacturer always has motivations to form an alliance with each of other two members, while the retailer and the platform may form an alliance only when the agency rate is relatively low. Moreover, under certain conditions, all supply chain members could achieve a win-win-win result in the manufacturer-retailer and manufacturer-platform alliance models, but fall into a lose-lose-lose situation in the retailer-platform alliance model. Additionally, it is interesting that a higher agency rate makes the retailer more profitable when the platform and manufacturer enter into an alliance. Finally, we find that each of the three alliance models may be the final equilibrium, which is largely dependent on channel competition and the agency rate.
02288nas a2200193 4500000000100000000000100001008004100002260001200043100002000055700001900075700001700094700001600111700001900127700001800146700002600164245014300190490001000333520175100343 2023 d c02/2023 1 aJian-Peng Chang 1 aZhen-Song Chen 1 aZhu-Jun Wang 1 aLeSheng Jin 1 aWitold Pedrycz 1 aLuis Martinez 1 aMirosław Skibniewski 00 aAssessing Spatial Synergy Between Integrated Urban Rail Transit System and Urban Form: A BULI-Based MCLSGA Model With the Wisdom of Crowds 0 v31(2) 3 aSpatially synergizing the urban rail transit (URT) network integrated with its feeder transit system and the urban form plays an important role in improving the effectiveness of URT in mitigating traffic congestion, reducing air pollution, optimizing urban spatial structure, etc. This article mainly focuses on assessing the spatial synergy between the two parts by specifying the assessment criteria that can effectively characterize the spatial synergic mechanism between the two parts and developing a novel multicriteria large-scale group assessment (MCLSGA) model, in which basic uncertain linguistic information (BULI), as an extended form of fuzzy linguistic approach, is used to model and process the subjective assessment information (Assess-Inf) elicited by experts. In order to alleviate the computing complexity, an agglomerative hierarchical clustering algorithm is introduced to cluster the Assess-Inf given by a huge number of experts as per the organizers’ expected discrimination level on reliability-related Assess-Inf. A method for weighting the clusters is then proposed to control the roles played by the items of the Assess-Inf, representing each cluster and having different reliability levels in their fusing process to tap into wisdom of crowds (WOC) while accommodating the organizers’ trust level in the reliability-related Assess-Inf given by experts. Afterward, the best–worst method is extended to the BULI-based large-scale group assessment context with the aim of accurately weighting the criteria by drawing on WOC. Finally, a case study on assessing the spatial synergy between Chongqing’s integrated URT system and urban form is conducted to validate the validity of the proposed MCLSGA model.
02504nas a2200169 4500000000100000000000100001008004100002260001200043100001700055700001500072700001300087700001600100700002600116245017900142490000800321520200500329 2023 d c11/2023 1 aZongbao Feng 1 aWeiya Chen 1 aYang Liu 1 aHongyu Chen 1 aMirosław Skibniewski 00 aLong-term equilibrium relationship analysis and energy-saving measures of metro energy consumption and its influencing factors based on cointegration theory and an ARDL model 0 v263 3 aThe energy consumption of metros has widely been concerned with respect to their economy and environmental protection. To analyze the complex dynamic relationship between metro energy consumption and its influencing factors and provide a reference for metro energy conservation control, this paper uses the monthly energy consumption, passenger flow and operating distance statistical data for Wuhan Metro Line 2 from 2018 to 2019. First, metro energy consumption and its influencing factors are qualitatively analyzed and identified. Then, based on cointegration theory and an autoregressive distributed lag (ARDL) model, a correlation hypothesis between metro energy consumption and its influencing factors is constructed, and a method for analyzing the influencing factors of metro energy consumption is proposed. The total energy consumption of a metro (TEC), train traction energy consumption (TTEC), environmental control energy consumption (ECEC), station lighting energy consumption (SLEC), station equipment energy consumption (SEEC) and the operating distance (OD) and passenger flow (PF) variables are analyzed. Using cointegration and an impulse response function, the dynamic relationships between the various energy consumption factors and operating distance and passenger flow are evaluated. The results show that there are substantial differences in the effects of OD and PF and their degree of influence on metro energy consumption. (1) OD affects mainly TTEC and TEC. The degree of influence of OD on TTEC reaches 97.8%, and the degree of influence of OD on TEC reaches 65.9%. (2) PF affects mainly ECEC and SEEC, and the degrees of influence of PF on ECEC and SEEC are 32.2% and 41.3%, respectively. (3) Considering that OD is the key factor affecting TTEC and TEC, train marshaling schemes, train running intervals and train stopping scheme optimization countermeasures are proposed, which can provide decision support for metro energy consumption management and control.
01799nas a2200193 4500000000100000000000100001008004100002260001200043100001300055700001700068700001900085700001600104700001800120700002000138700001600158700002600174245006400200520134100264 2023 d c07/2023 1 aYang Liu 1 aXianjia Wang 1 aZhen-Song Chen 1 aYifei Zhang 1 aShenghao Zhao 1 aMuhammet Deveci 1 aLeSheng Jin 1 aMirosław Skibniewski 00 aEvaluating Digital Health Services Quality via Social Media 3 aGiven the widespread demand for digital health services, a systematic study on the quality of digital health services is essential. Based on the current situation of tertiary hospitals in central China providing digital health services via social media, we used the Cronbach and Bayesian Best and Worst methods to evaluate the quality of hospital digital health services and conduct an empirical study of several hospitals. Based on the results of the empirical study, we propose a path for constructing a digital health service platform, suggesting that hospitals focus on building business function services of social media and accelerate the development of Internet hospitals. Hospitals should also improve the operation and maintenance of social media, optimize the intelligence of online guidance, and simplify the design logic of function menus. In terms of content information services, hospitals need to design targeted content according to the characteristics of different social media, improve content quality, and ensure the appropriate proportion of various types of information. With such measures, hospitals can guide users to use social media through business function services and retain users through content information services to increase the influence of hospitals and the quality of social health welfare.
03301nas a2200181 4500000000100000000000100001008004100002260001200043100002000055700001900075700001700094700001800111700001900129700002600148245015100174490000800325520278600333 2023 d c01/2023 1 aJian-Peng Chang 1 aZhen-Song Chen 1 aXianjia Wang 1 aLuis Martinez 1 aWitold Pedrycz 1 aMirosław Skibniewski 00 aRequirement-driven sustainable supplier selection: Creating an integrated perspective with stakeholders' interests and the wisdom of expert crowds 0 v175 3 aDriven by the pressure from various stakeholders to embrace sustainability and from the market to enhance competitiveness, more and more companies have been committed to conducting sustainable supplier selection (SSS). SSS is a requirement-driven multi-criteria decision-making (MCDM) problem and the existing pieces of literature have attempted to integrate quality function deployment (QFD) with various MCDM methods to model the problem. However, these models have not conducted SSS based on stakeholders’ satisfaction from alternatives and used the weights of criteria obtained from stakeholders’ preferences for requirements, which is used to model the compensation among satisfaction levels of different requirements, to guide the compensation among alternatives’ performances on different criteria. In order to address these deficiencies, this paper develops a novel generalized (QFD)-based MCDM structure for SSS, based on which we further design a QFD-based multi-stakeholders and multi-experts MCDM model considering stakeholders’ consensus of interest and wisdom of expert crowds. Firstly, multiple stakeholder groups with multiple participants in each one are asked to output their expectations and preferences for their own requirements; within each group, the algorithm for consensus reaching process (CRP) is designed to formulate the acceptable collective expectations, and the best-worst method (BWM) method integrated with an algorithm for consistency improving process (CIP) and an algorithm for CRP is developed to weight requirements. Secondly, multiple experts use basic uncertain linguistic information (BULI) to characterize performances of alternatives on criteria and the relationship between requirements and criteria, and a method of weighting individual judgments with the capability of drawing on the wisdom of crowds (WOC) while accommodating organizers’ trust level in reliability given by experts is used to facilitate formulating a collective judgment. Thirdly, for each alternative and each requirement of each stakeholder group, we can quantify the comprehensive performance of the alternative on the requirement with the help of QFD, based on which and the group’s expectation we can use the value function of prospect theory to quantify the group’s satisfaction of the requirement from the alternative; aggregating the weighted satisfaction levels of requirements gives rise to the comprehensive satisfaction level of each group from each alternative, and then the Maximin decision rule is introduced to rank alternatives because of its ability to accommodate the non-compensation among different stakeholder groups. Finally, a case study is conducted to investigate the validity and effectiveness of the proposed model.
01814nas a2200169 4500000000100000000000100001008004100002260001200043100002000055700001800075700001200093700002600105700001900131245009600150490000800246520139000254 2024 d c04.2024 1 aSheng-Hua Xiong 1 aZhi-Peng Wang 1 aGang Li 1 aMirosław Skibniewski 1 aZhen-Song Chen 00 aPrediction of airport runway settlement using an integrated SBAS-InSAR and BP-EnKF approach 0 v665 3 aThe prediction of surface settlement occupies a crucial role in achieving effective catastrophe prevention and mitigation, as well as facilitating the maintenance of airport runways. Given the challenges associated with the manual collection of settlement data and the suboptimal timeliness of the Back Propagation (BP) technique in neural networks, this study proposes an integrated prediction method that combines the Ensemble Kalman Filter (EnKF) with BP. This study focuses on the processing of Synthetic Aperture Radar (SAR) pictures obtained from the ascending orbit of the Sentinel-1A satellite. The Small Baseline Subset Interferometric synthetic aperture radar (SBAS-InSAR) technology is employed to derive the settlement time series on the runway of Kangding Airport. Moreover, three sites with high coherence within the primary settlement region are employed to assess the dependability of the model after the expansion of the data by cubic spline interpolation. The findings of the study indicate that both the BP-EnKF and BP models exhibit favorable outcomes in predicting airport runway settlement. However, following the alteration of data caused by external environmental influences, the BP-EnKF model has superior adaptability to variations in data. It has been shown that the BP-EnKF model exhibits a prediction accuracy that surpasses the BP model by 9.25%.
01983nas a2200133 4500000000100000008004100001653010900042100001500151700001700166700001100183700002600194245009000220520153900310 2026 d 10 aHuman–robot collaboration; Construction robots; Psychophysiological signals; Human–robot interaction 1 aSaika Wong 1 aZhentao Chen 1 aMi Pan 1 aMirosław Skibniewski 00 aExploring psychophysiological methods for human–robot collaboration in construction 3 aPsychophysiological methods present a promising approach to fostering enhanced mutual communication and collaboration between human workers and robots. Despite their potential, there is still limited understanding of how to effectively integrate psychophysiological methods to improve human–robot collaboration (HRC) in construction. This paper addresses this gap by critically reviewing the use of psychophysiological methods for HRC within construction environments, based on a concept-methodology-value philosophical framework. The review explores different interaction modalities of implementing psychophysiological measures to communicate or control robots in construction. The analysis reveals that measuring brain activity using electroencephalography is the most widely used psychophysiological method, while the majority of the works are still at the proof-of-concept stage in laboratory and virtual construction environments and lack empirical evidence. Four potential research directions are proposed: the fusion of multi-modal psychophysiological signals, enriching field experimental settings for better generalizability, leveraging advanced biocompatible or contactless technologies for effective signal detection in construction scenarios, and examining the practicality of psychophysiological methods to construction HRC. The findings should benefit subsequent exploration and practical applications of psychophysiological methods to enable the better implementation of robots and support HRC in construction.
01476nas a2200145 4500000000100000008004100001100002000042700001600062700001900078700001400097700001900111700002600130245008800156520108600244 2025 d 1 aSheng-Hua Xiong 1 aXi-Hang Wei 1 aZhen-Song Chen 1 aHao Zhang 1 aWitold Pedrycz 1 aMirosław Skibniewski 00 aIdentifying causes of aviation safety events using wW2V-tCNN with data augmentation 3 aIdentifying the causes of these safety events is crucial for safety agencies to create recommendations and for airlines to enhance procedures and mitigate hazards. This paper proposes a model to identify the causes of civil aviation safety events using a weighted Word2Vec-based Text-CNN (wW2V-tCNN) algorithm and data augmentation techniques. A corpus is built by matching narrative texts from investigation reports with cause labels from the Aviation Safety Network database. This corpus is transformed into Text-CNN inputs using a weighted sentence vector method based on word embeddings, considering word frequency and part-of-speech weighting. Additionally, a novel document balancing method is introduced for data augmentation. The proposed identification model achieves Macro-F1 and Macro-accuracy scores of 0.9803 and 0.9699, outperforming traditional methods and showing significant improvement over models like Doc2vec and SBERT. This model provides an accurate tool for safety agencies and airlines to analyze and effectively mitigate civil aviation safety events
01664nas a2200133 4500000000100000008004100001100001900042700001200061700001300073700001600086700002600102245014400128520125800272 2025 d 1 aZhen-Song Chen 1 aYue Tan 1 aZheng Ma 1 aZhengze Zhu 1 aMirosław Skibniewski 00 aUnlocking the potential of quantum computing in prefabricated construction supply chains: Current trends, challenges, and future directions 3 aThe intricate nature of prefabricated construction supply chain management (PCSCM) presents ongoing challenges in production scheduling, inventory control, and logistics coordination. Recent advances in quantum computing (QC) offer compelling approaches to address these multifaceted issues by enabling significantly faster and more precise optimization. This paper systematically reviews and synthesizes existing QC research in the supply chain context, particularly focusing on quantum algorithms that target the PCSCM lifecycle. Our analysis identifies three key domains: production, inventory, and transportation, in which QC can outperform classical methods, as evidenced by enhanced scheduling flexibility and cost minimization. However, our findings also highlight crucial bottlenecks, including quantum hardware limitations, organizational readiness gaps, and a lack of specialized interdisciplinary talent. We propose a framework of strategies to guide QC adoption, such as specialized algorithm development, collaborative research partnerships, and standardized data protocols. These insights offer promising future directions for leveraging QC to streamline operations and boost sustainability in the prefabricated construction sector.
02151nas a2200157 4500000000100000008004100001100001400042700001800056700001600074700001600090700001500106700001300121700002600134245011200160520172100272 2025 d 1 aLei Zhang 1 aJingfeng Yuan 1 aXianfei Yin 1 aTiantian Gu 1 aYinghao Lu 1 aPing Liu 1 aMirosław Skibniewski 00 aThe emotional equation: how psychosocial support boosts safety practices in the context of construction 5.0 3 aBackground: Construction 5.0, which emphasizes human-centric technologies and improved collaboration between humans and machines in intelligent construction ecosystems, introduces distinct safety management challenges that necessitate effective emotional resource allocation strategies. This study utilizes job demands-resources theory to investigate how emotional resources are allocated for safety management by examining the relationships among safety practice, psychosocial support, safety participation, and leadership safety behavior.
Methods: A face-to-face questionnaire survey was conducted with front-line construction workers involved in Construction 5.0 projects, yielding 118 valid responses. The data were analyzed using linear regression models and the bootstrap method.
Results: The findings reveal that: (1) psychosocial support positively influences both safety participation and safety practices; (2) safety participation enhances safety practices; (3) safety participation fully mediates the effect of psychosocial support on safety practices; and (4) leadership safety behavior positively moderates the relationship between safety participation and safety practices.
Conclusion: This study extends the job demands-resources framework by illustrating the flow of emotional resources in the context of Construction 5.0, thereby highlighting the principles of multi-level emotional resources in the relationship between emotion and safety. Practically, this framework allows for the evolution of human-centric safety measures in tandem with advanced technology-enabled work environments, while also maintaining psychosocial balance in intelligent construction ecosystems
02177nas a2200133 4500000000100000008004100001100001200042700001600054700001600070700002600086700001800112245014700130520176600277 2025 d 1 aHui Liu 1 aHanyu Zheng 1 aQianqian Ju 1 aMirosław Skibniewski 1 aMengmeng Wang 00 aTemporal-Spatial Evolution of BIM-Based Collaborative Innovation Network: Evidence from Patents in China\textquoterights Construction Industry 3 aNowadays, the efficiency and effectiveness of construction innovation is deemed urgent. Given the innovative potential of building information modeling (BIM), BIM-based collaborative innovation (BIM-CI) has been perceived as a promising approach to meet this requirement. However, the underlying mechanism that drives BIM-CI remains largely unexplored, which seriously hinders progress in designing and planning effective interventions to promote BIM-CI so as to accelerate the release of innovation capacity in the construction system. BIM-CI exhibits distinct network characteristics. Therefore, this study employed social network analysis to examine the temporal and spatial evolution process of the BIM-based collaborative innovation network (BIM-CIN) in China based on 1,677 BIM-CI-related patent data from 2011 to 2023. The results indicate that BIM-CIN has expanded across three phases, with its network structure becoming more decentralized and diversified. This shift provides innovators with enhanced collaboration opportunities, fostering a more dynamic and inclusive innovation process. Key innovators, such as the State Grid Corporation of China and China Construction First (Group) Company Limited, play a pivotal role in facilitating communication and strengthening collaboration within the BIM-CIN. Additionally, the spatial evolution analysis highlights that the increasing number of provinces participating signifies a positive trend toward more extensive collaboration and innovation within the BIM-CIN. The findings provide valuable references for relevant practitioners to better organize their managerial activities to promote the development of BIM-CI, thereby improving the efficiency and effectiveness of construction innovation.
01559nas a2200109 4500000000100000008004100001100001400042700001600056700002600072245011400098520123700212 2025 d 1 aQiong Liu 1 aLimao Zhang 1 aMirosław Skibniewski 00 aNetwork extension planning towards resilient urban critical infrastructures using deep reinforcement learning 3 aAs cities continue to grow, expanding metro networks becomes essential for optimizing urban transportation efficiency. Therefore, scientific strategic planning of metro networks is indispensable. This study proposes a deep reinforcement learning (DRL) approach to discover the optimal planning strategy for metro network extension. The model integrates multi-source data into the reward function while customizing the state and action spaces to reflect the unique characteristics of metro networks. A policy network is developed using an Encoder-Decoder framework, with the parameters being updated by an Actor-Critic framework based on policy gradient. A comprehensive performance index is proposed to evaluate the vulnerability and service capacity of planned networks. The proposed method is validated through a case study on the Hangzhou metro system. The results demonstrate that the proposed DRL can result in optimal planned networks that outperform the actually implemented network with a maximum Performance Improvement Percentage of 19.87 \%. The DRL-based optimization framework proposed for metro network extension planning is anticipated to enhance adaptability towards urban development and increase resilience.
01492nas a2200157 4500000000100000008004100001100001500042700001500057700001700072700001400089700001800103700002600121700001800147245009800165520107100263 2025 d 1 aYashuai Li 1 aWubin Wang 1 aJichang Zhao 1 aYang Yang 1 aZhaohui Zhang 1 aMirosław Skibniewski 1 aJingfeng Yuan 00 aEstimating demolition waste from residential interior photos: A Large Language Model solution 3 aDemolition waste management is a critical challenge during the final stages of construction projects, particularly concerning fine-grained waste at the room level. This paper investigates the predictive potential of visual elements for demolition waste estimation, with an emphasis on interior room design. A framework integrating deep learning models with Large Language Model (LLM) is proposed to automatically classify interior design types and predict demolition waste. By utilizing both residential interior photos and floor plans, the framework can identify design types, segment walls, match rooms, and estimate demolition volumes at the room level. The results show high accuracy in design classification and waste prediction, surpassing traditional methods based on waste generation rates. The framework also provides valuable insights into specific waste materials, enhancing waste management at a detailed level. This research advances micro-level demolition waste prediction, promoting the broader application of LLMs in the construction industry.
02449nas a2200133 4500000000100000008004100001100001600042700001600058700002600074700001300100700001300113245012600126520206300252 2025 d 1 aHongyu Chen 1 aQiping Shen 1 aMirosław Skibniewski 1 aYuan Cao 1 aYang Liu 00 aDynamic prediction and optimization of tunneling parameters with high reliability based on a hybrid intelligent algorithm 3 aIn this paper, a hybrid intelligent framework comprising Bayesian optimization (BO), gradient boosting with categorical features (CatBoost) and the nondominated sorting genetic algorithm-III (NSGA-III) was proposed to support multiobjective optimization of shield construction parameters without large sample datasets, improve the shield performance, and ensure reliable and interpretable results. First, with the use of the specific tunneling energy, advancing speed and cutter wear as objective functions, a BO-CatBoost prediction model for shield construction parameters and various objectives was constructed, and the key influencing factors were identified via the SHapley Additive exPlanations (SHAP) method. Then, a BO-CatBoost-NSGA-III model was developed to obtain Pareto solutions under different scenarios involving the adjustment of the key influencing factors. Finally, adopting the Wuhan Metro as the background, the accuracy, stability, and generalizability of the constructed algorithm were verified. The results indicated that (1) the developed BO-CatBoost algorithm is superior to 9 other algorithms. The R2 values of the proposed approach were 0.976 and 0.901\textendash0.976 on the test set. (2) The developed BO-CatBoost-NSGA-III algorithm could be used to obtain Pareto solutions under different scenarios via the adjustment of the key influencing factors with the SHAP method, and the optimal solutions could facilitate improvements in the advancing speed, specific tunneling energy and cutter wear of 3.45 \%, 6.09 \%, and 0.52 \%, respectively, with an overall average reliability of 90.5 \%. (3) By comparing various prediction algorithms, optimization schemes of different objectives and geological conditions, the accuracy, stability, and generalizability of the constructed algorithm were verified. The developed BO-CatBoost-NSGA-III framework could enable dynamic adjustment of shield construction parameters for decision-making purposes in the event of conflicting shield construction objectives and exhibits generality.
01769nas a2200121 4500000000100000008004100001100002000042700001800062700001800080700002600098245007400124520144900198 2025 d 1 aATaha Demirbağ 1 aHande Aladağ 1 aZeynep Işık 1 aMirosław Skibniewski 00 aCircular Economy-Based Decision-Making Model for Contractor Selection 3 aIncreasing environmental pollution has reinforced the necessity of implementing circular economy (CE) as a sustainable approach to reducing resource consumption, waste generation, and carbon emissions. Despite the construction industry\textquoterights significant environmental impact in terms of global carbon emissions, water consumption, and biodiversity loss, only 12\% of its materials exhibit circular characteristics, necessitating improvements in terms of circularity in construction projects. This study develops a CE-based decision-making model for contractor selection, focusing on off-site construction (OSC), which offers greater circularity potential than conventional construction methods. The decision-making model, established through literature analysis and expert discussions, utilizes the fuzzy analytic hierarchy process (AHP) to evaluate CE criteria and employ the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to determine contractor suitability. The findings indicate that Material Circularity, Energy Circularity, and Product Circularity are the most influential criteria, with green procurement emerging as the highest-priority factor. The model was validated through a hypothetical case study involving four contractors experienced in sustainable construction. The results demonstrate the model\textquoterights capacity to produce sensitive outcomes in terms of decision-making.
02473nas a2200157 4500000000100000008004100001100001500042700001700057700001400074700001700088700001600105700001800121700002600139245008600165520206400251 2025 d 1 aXudong Fan 1 aYishuo Jiang 1 aRay Zhong 1 aFabio Duarte 1 aWaishan Qiu 1 aJürgen Hackl 1 aMirosław Skibniewski 00 aAdvancements and potential pitfalls for smart cities and sentient infrastructures 3 aAs urban areas struggle with increasing challenges related to population growth, climate change, the built environment, and public well-being, the concept of smart cities has emerged as a transformative solution. A smart city refers to the seamless integration of advanced information and communication technologies (ICT) with existing urban infrastructure to enhance efficiency, sustainability, and quality of life, thereby reshaping the future of urban living [2]. Originating in the early 2000s with a focus on \textquotedbllefttop-down\textquotedblright technology deployment [9], the practice has evolved owing to the rapid growth of digital infrastructure-such as broadband networks, smart sensors, and open data platforms, which has enabled cities to become dynamic environments that foster real-time decision-making and community participation [6]. Contemporary smart city initiatives increasingly recognize the importance of \textquotedblleftbottom-up\textquotedblright innovation, where residents actively contribute to the design and improvement of urban services [17]. This evolution reflects a shift towards emphasizing connectivity, citizen engagement, and a more human-centric approach to urban challenges. The collaborative, living-lab approach positions citizens as agents of change, making cities more adaptive and responsive to evolving needs. Despite these advancements, the development of smart cities still involves several challenges. Beyond technological deployments, ethical issues such as privacy, data security, and equitable access to technology are critical hurdles that must be addressed [1]. Moreover, the growing complexity of managing interconnected urban systems demands innovative governance frameworks that ensure interoperability while balancing technological progress with inclusiveness and sustainability. Ultimately, the success of smart cities will depend on the ability to create resilient, data-driven communities that empower their residents and prioritize both human well-being and environmental stewardship
00542nas a2200157 4500000000100000008004100001100001500042700001500057700001500072700001900087700001200106700002200118700002500140700002600165245019300191 2025 d 1 aBocong Liu 1 aXuhui Cong 1 aLiang Wang 1 aShenghui Zhang 1 aHao Liu 1 aJonas Saparauskas 1 aLeonas Ustinovichius 1 aMirosław Skibniewski 00 aSpatial-temporal evolution and influencing factors of the coupling coordination degree between new infrastructure construction and high-quality development in urban agglomerations in China 01489nas a2200133 4500000000100000008004100001100001700042700001600059700001600075700001700091700002600108245013000134520109100264 2026 d 1 aZhenzhao Xia 1 aBotao Zhong 1 aShuai Zhang 1 aTonghui Zhao 1 aMirosław Skibniewski 00 aGraph-driven embedding reinforcement and traceable LLM agent for reliable element alignment in construction report generation 3 aEngineering report generation from construction-site Internet of Things (IoT) data using large language models (LLMs) remains challenging due to hallucinations. Ensuring traceability and reliability in information retrieval and multi-step reasoning is essential within retrieval-augmented generation (RAG) for LLM. This paper formalizes the RAG-LLM pipeline and proposes a dual-stream enhancement combining knowledge graph (KG) construction with reinforcement learning (RL)-based retriever tuning. The graph-guided module extracts structured engineering elements, while RL improves semantic alignment and tokenization of critical terms. Leveraging this dual-stream RAG, a traceable reporting agent is developed, providing end-to-end traceability of retrieval and reasoning, along with inter-step similarity measures. When collaborating with existing on-site IoT systems, the agent can extend automated monitoring to decision-making support. This paper presents a reliable approach for construction report generation and advances human-AI collaboration in construction management.
02071nas a2200181 4500000000100000008004100001653002400042653001600066653001900082653000800101100001800109700001500127700001600142700001500158700002600173245010600199520158400305 2026 d 10 aSemantic enrichment 10 aMEP systems 10 aGraph matching 10 aBIM 1 aZhuohao Zhang 1 aWeiya Chen 1 aJianhua Cai 1 aHanbin Luo 1 aMirosław Skibniewski 00 aHierarchical system decomposition and semantic enrichment of BIM for lifecycle support of MEP systems 3 aThe effective lifecycle management of modular Mechanical, Electrical, and Plumbing (MEP) systems is often compromised by a significant data gap between the digital design in Building Information Modeling (BIM) and the as-built conditions of prefabricated components. This paper specifically addresses the challenge of defining and structuring functionally independent component groups, or \textquoterightblocks,\textquoteright within complex BIM models that lack explicit system-level semantics and suffer from disorganized data. To solve this, a framework was proposed for hierarchical MEP system decomposition and semantic enrichment and implemented through a hybrid topological-geometric matching method that first identifies all structurally identical component assemblies via a topological search and then verifies these candidates by comparing their morphological signatures. Experimental validation demonstrates the method\textquoterights high accuracy and scalability, achieving an F1-score of 0.98, near-linear time complexity, and above 99\% precision in large-scale applications, as verified by domain experts. This research provides a robust, bottom-up approach to automatically populate a structured system hierarchy, bridging the critical data gap between the design model and physical, prefabricated modules. By creating semantically enriched and well-structured models, this work establishes a foundational data layer that enables future advancements in automated quantity take-off, modular maintenance, and end-of-life management, such as component reuse.