01948nas a2200241   4500000000100000008004100001653003700042653002900079653004100108653002100149653001700170100001600187700001500203700002600218700001200244700001600256245014000272856007200412300001100484490000800495520118900503022001401692       2026                            d10aConstruction progress monitoring10aPercentage of completion10aConstruction activity identification10aDepth estimation10aBridge piers1 aYuyang Wang1 aElton Chen1 aMirosław Skibniewski1 aZhe Wen1 aZehao Jiang00aAutomated monitoring of percentage of completion and activity-level progress in bridge pier construction using unmanned aerial vehicles  uhttps://www.sciencedirect.com/science/article/pii/S0926580526002815  a1070400 v1883 aEffective construction progress monitoring (CPM) is essential for successful engineering projects. However, given the large number of components, wide spans, extended construction cycles, and section-by-section pouring involved in pier group construction, existing approaches struggle to quantify progress effectively. To overcome this, this paper proposes an unmanned-aerial-vehicle-based approach to evaluate both percentage of completion (POC) and construction activity at reduced cost. A depth estimation model tailored for large-scale construction scenes (LSC-Depth) is developed to address inaccuracies in weak-texture regions and those with absent structural boundaries. Construction progress is quantified by computing bridge pier height through geometric mapping. Simultaneously, construction activities are inferred from the spatial and logical relationships among site elements. The proposed approach is validated through application to an actual pier construction project. It achieves accuracies of 0.95 for POC and 0.85 for activity-level CPM. Future research shall focus on improving POC accuracy and refining activity-level granularity to enhance managerial efficiency.  a0926-580500470nas a2200145   4500000000100000008004100001100001600042700001500058700002600073700001200099700001600111245014000127856004900267490000800316       2026                            d1 aYuyang Wang1 aElton Chen1 aMirosław Skibniewski1 aZhe Wen1 aZehao Jiang00aAutomated Monitoring of Percentage of Completion and Activity-Level Progress in Bridge Pier Construction Using Unmanned Aerial Vehicles  uhttps://doi.org/10.1016/j.autcon.2026.1070400 v18800453nas a2200157   4500000000100000008004100001100001200042700001000054700001700064700001400081700002600095700002100121245010100142856004600243490000600289       2026                            d1 aFei Tao1 aLi Yi1 aShuaiming Su1 aRay Zhong1 aMirosław Skibniewski1 aIoannis Brilakis00aDigital Twin Empowers Urban Digitalization: Driving Intelligent and Sustainable City Development  uhttps://doi.org/10.1016/j.dte.2026.1000970 v800528nas a2200181   4500000000100000008004100001100001200042700001000054700001700064700001400081700002600095700002100121245010100142856007200243300001100315490000600326022001400332       2026                            d1 aFei Tao1 aLi Yi1 aShuaiming Su1 aRay Zhong1 aMirosław Skibniewski1 aIoannis Brilakis00aDigital twin empowers urban digitalization: Driving intelligent and sustainable city development  uhttps://www.sciencedirect.com/science/article/pii/S2950550X26000105  a1000970 v8  a2950-550X00464nas a2200145   4500000000100000008004100001100001800042700001800060700001200078700002600090245013500116856005000251300001000301490000700311       2026                            d1 aReza Hosseini1 aTuba Kocaturk1 aHeng Li1 aMirosław Skibniewski00aEmbracing Digital Transformation to Combat Climate Change: Insights into Organizational Change Management in the Built Environment  uhttps://doi.org/10.1080/09613218.2025.2594337  a1–30 v5400490nas a2200157   4500000000100000008004100001260001400042100001800056700001800074700001200092700002600104245013500130856005000265300001000315490000700325       2026                            d  bRoutledge1 aReza Hosseini1 aTuba Kocaturk1 aHeng Li1 aMirosław Skibniewski00aEmbracing digital transformation to combat climate change: insights into organizational change management in the built environment  uhttps://doi.org/10.1080/09613218.2025.2594337  a1–30 v5400594nas a2200193   4500000000100000008004100001260001200042100001800054700001900072700001300091700001500104700002000119700001900139700002600158245012500184856007000309300001400379490000700393       2026                            d  c05/20261 aYong-Mei Ding1 aYing-Tao Zheng1 aFeng Liu1 aYung Tsang1 aSheng-Hua Xiong1 aZhen-Song Chen1 aMirosław Skibniewski00aESG, open innovation, and firm performance in construction firms: exploring the mediating role of digital transformation  uhttps://journals.vilniustech.lt/index.php/JCEM/article/view/26552  a513–5330 v3200544nas a2200181   4500000000100000008004100001100001800042700001900060700001300079700001500092700002000107700001900127700002600146245012500172856004400297300001400341490000700355       2026                            d1 aYong-Mei Ding1 aYing-Tao Zheng1 aFeng Liu1 aYung Tsang1 aSheng-Hua Xiong1 aZhen-Song Chen1 aMirosław Skibniewski00aESG, Open Innovation, and Firm Performance in Construction Firms: Exploring the Mediating Role of Digital Transformation  uhttps://doi.org/10.3846/jcem.2026.26552  a513–5330 v3201976nas a2200133   4500000000100000008004100001653010900042100001500151700001700166700001100183700002600194245009000220520153200310       2026                            d10aHuman–robot collaboration; Construction robots; Psychophysiological signals; Human–robot interaction1 aSaika Wong1 aZhentao Chen1 aMi Pan1 aMirosław Skibniewski00aExploring psychophysiological methods for human–robot collaboration in construction3 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.00488nas a2200157   4500000000100000008004100001100001800042700001800060700001100078700001800089700001100107700002600118245012900144856004900273490000800322       2026                            d1 aLingxiao Wang1 aJingfeng Yuan1 aShu Su1 aHongxing Ding1 aYu Bai1 aMirosław Skibniewski00aFusing Enhanced YOLO and Knowledge Graph-Based Large Language Models for Automatic Risk Perception in Tower Crane Operations  uhttps://doi.org/10.1016/j.autcon.2026.1068230 v18301912nas a2200253   4500000000100000008004100001653001600042653002000058653000900078653002000087653002500107100001800132700001800150700001100168700001800179700001100197700002600208245012900234856007200363300001100435490000800446520119000454022001401644       2026                            d10aTower crane10aRisk perception10aYOLO10aKnowledge graph10alarge language model1 aLingxiao Wang1 aJingfeng Yuan1 aShu Su1 aHongxing Ding1 aYu Bai1 aMirosław Skibniewski00aFusing enhanced YOLO and knowledge graph-based large language models for automatic risk perception in tower crane operations  uhttps://www.sciencedirect.com/science/article/pii/S0926580526000646  a1068230 v1833 aTower crane operations in construction are inherently hazardous due to complex and dynamic site environments. Enhancing operators' perceptual and cognitive capabilities is essential for ensuring safety and improving situational awareness. This paper presents an integrated framework that combines an improved YOLOv8 model with a Knowledge Graph (KG)-enhanced large language model to achieve proactive and intelligent safety management. The improved YOLOv8 incorporates attention-based optimization to improve detection accuracy for small targets in tower crane perspectives. A domain-specific safety KG is constructed to represent critical entities, relationships, and operational contexts, and is aligned with a fine-tuned GPT model, enabling semantic reasoning and context-aware hazard interpretation. The integrated system links visual perception with structured knowledge reasoning to provide real-time and interpretable safety feedback. This approach enhances the perception, understanding, and decision-making capabilities of tower crane operators, transforming safety management from reactive monitoring to proactive and intelligent control in complex construction environments.  a0926-580501482nas a2200133   4500000000100000008004100001100001700042700001600059700001600075700001700091700002600108245013000134520108400264       2026                            d1 aZhenzhao Xia1 aBotao Zhong1 aShuai Zhang1 aTonghui Zhao1 aMirosław Skibniewski00aGraph-driven embedding reinforcement and traceable LLM agent for reliable element alignment in construction report generation3 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.02064nas a2200181   4500000000100000008004100001653002400042653001600066653001900082653000800101100001800109700001500127700001600142700001500158700002600173245010600199520157700305       2026                            d10aSemantic enrichment10aMEP systems10aGraph matching10aBIM1 aZhuohao Zhang1 aWeiya Chen1 aJianhua Cai1 aHanbin Luo1 aMirosław Skibniewski00aHierarchical system decomposition and semantic enrichment of BIM for lifecycle support of MEP systems3 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.02457nas a2200265   4500000000100000008004100001653004800042653002800090653004900118653003200167653004000199100001400239700001700253700001700270700001600287700001200303700001300315700002600328245011900354856007200473300001200545490000700557520161300564022001402177       2026                            d10aSynchronous excavation and segment assembly10aShield attitude control10aBidirectional long short-term memory network10aKolmogorov–Arnold network10aMulti-objective grey wolf optimizer1 aLulu Wang1 aJiliang Wang1 aYongsheng Li1 aLimao Zhang1 aHui Luo1 aXin Zhao1 aMirosław Skibniewski00aIntelligent attitude control of tunnel boring machine in synchronous operations of excavation and segment assembly  uhttps://www.sciencedirect.com/science/article/pii/S2467967426000279  a137-1560 v283 aThis study introduces a shield attitude control method aimed at improving the accuracy and stability of tunnel boring machine (TBM) in synchronous excavation and segment assembly (S-TBM) along the design tunnel axis. The proposed hybrid deep learning model integrates bidirectional long short-term memory (BiLSTM) and Kolmogorov–Arnold network (KAN) cells to accurately predict S-TBM attitude. This model is further combined with the multi-objective grey wolf optimizer (MOGWO) method for determining the optimal proportional-integral-derivative (PID) parameters, thereby minimizing attitude deviations. The experimental results indicate that: (1) The S-TBM reduces the construction time per single lining ring to 39 min, which is 34 min faster than the conventional TBM. (2) The improved BiLSTM model can effectively estimate shield attitude, with an RMSE of 1.030, an MAE of 0.695, and an R2 score of 0.998. (3) The proposed multi-objective optimization (MOO) framework is able to reliably control S-TBM attitude, achieving an overall improvement percentage of 25.66%. (4) Compared to other methods, the proposed approach enhances R2 score by 0.03 and the overall improvement percentage by 5.72%. The novelty of this research lies in the development of an intelligent control framework for shield attitude under the synchronous excavation and segment assembly construction mode, which achieves reliable prediction and precise regulation of S-TBM attitude by synergistically coupling a nonlinear attitude response model based on an improved BiLSTM with an MOGWO-driven PID parameter optimization strategy.  a2467-967400527nas a2200181   4500000000100000008004100001100001400042700001700056700001700073700001600090700001200106700001300118700002600131245011900157856004800276300001400324490000700338       2026                            d1 aLulu Wang1 aJiliang Wang1 aYongsheng Li1 aLimao Zhang1 aHui Luo1 aXin Zhao1 aMirosław Skibniewski00aIntelligent Attitude Control of Tunnel Boring Machine in Synchronous Operations of Excavation and Segment Assembly  uhttps://doi.org/10.1016/j.undsp.2025.12.005  a137–1560 v2800542nas a2200193   4500000000100000008004100001100001900042700001300061700001300074700001200087700001600099700002300115700001900138700002600157245009600183856004600279300001600325490000700341       2026                            d1 aZhen-Song Chen1 aHan Wang1 aZheng Ma1 aYi Yang1 aZhengze Zhu1 aFrancisco Chiclana1 aWitold Pedrycz1 aMirosław Skibniewski00aMultiobjective Optimization-Based Subjective Probability Distribution Aggregation: A Survey  uhttps://doi.org/10.1109/TSMC.2026.3685096  a4162–41800 v5600522nas a2200169   4500000000100000008004100001100001500042700001600057700002000073700001300093700001900106700002400125700002600149245012000175856004900295490000800344       2026                            d1 aDawei Wang1 aJingwei Guo1 aYongxiang Zhang1 aTao Feng1 aZhen-Song Chen1 aMaxwell Antwi-Afari1 aMirosław Skibniewski00aOptimizing Electric Vehicle Charging-Swapping Schemes to Enhance Utilization of Solar Energy Generation on Highways  uhttps://doi.org/10.1016/j.renene.2026.1258890 v27002234nas a2200265   4500000000100000008004100001653003100042653002200073653002900095653001200124653002300136100001500159700001600174700002000190700001300210700001900223700002400242700002600266245012000292856007200412300001100484490000800495520145100503022001401954       2026                            d10aIntegrated decision-making10aElectric vehicles10aCharging-swapping scheme10aHighway10aTime-space network1 aDawei Wang1 aJingwei Guo1 aYongxiang Zhang1 aTao Feng1 aZhen-Song Chen1 aMaxwell Antwi-Afari1 aMirosław Skibniewski00aOptimizing electric vehicle charging-swapping schemes to enhance utilization of solar energy generation on highways  uhttps://www.sciencedirect.com/science/article/pii/S0960148126007159  a1258890 v2703 aThe utilization of solar energy resources for replenishing electricity in electric vehicles is increasingly recognized as a critical component of low-carbon highway initiatives. Currently, the predominant methods for electric vehicle power replenishment are charging and battery swapping. However, the inherent differences between these methods, along with the uneven spatiotemporal distribution of solar energy resources, present significant challenges in optimizing solar energy utilization. This paper proposes an innovative approach to optimizing charging and swapping schemes of electric vehicles to enhance the efficient consumption of solar energy generated along highways. In detail, the proposed model integrates the concept of the time-space network for both charging-type and swapping-type electric vehicles, effectively illustrating the interactions between transportation and energy systems. Moreover, we develop a framework to schedule two types of electric vehicles while managing the charging process for depleted batteries at battery charging-swapping stations. The goal is to maximize the highway manager’s benefits while satisfying full-charged battery demands for swapping-type electric vehicles. Our case study illustrates that the proposed approach significantly enhances solar energy utilization and lowers grid electricity consumption, providing a more sustainable and economical operational solution for green highways.  a0960-148102571nas a2200229   4500000000100000008004100001653002600042653002600068653002800094653002400122653002500146100001900171700002600190700001500216700001500231245012700246856007200373300001100445490000700456520186400463022001402327       2026                            d10aTree defect detection10aSingle-device sensing10aNon-destructive testing10aAcoustic excitation10aMotion magnification1 aYishuang Zhang1 aMirosław Skibniewski1 aCheuk Chow1 aDenvid Lau00aSingle-device on-site inspection system for non-destructive internal defect detection in trees near constructed facilities  uhttps://www.sciencedirect.com/science/article/pii/S2590123026027556  a1117320 v323 aStructural failures caused by internal defects in trees pose major safety, operational, and financial risks to nearby buildings, transport corridors, and other constructed infrastructure. Routine inspection of internal or subsurface defects across widely distributed tree structures remains challenging due to the limitations of conventional non-destructive testing (NDT) methods, such as bulky equipment and poor field adaptability. To enable low-cost and field-adaptable detection of internal tree defects, this study proposes a single-device inspection system that uses a standard mobile phone for acoustic excitation and vibration sensing, evaluated through experiments on cedar specimens with prefabricated internal defects. Surface vibration responses exhibit strong correlation with internal structural characteristics, with indicative consistency between theoretical intrinsic frequencies and video-derived response characteristics. The results show that detection sensitivity is influenced by excitation frequency and decreases for smaller or deeper defects due to amplitude attenuation. Resonance-tuned excitation significantly amplifies vibration responses up to fourfold, enabling detection of subsurface defects with a minimum detectable size of approximately 1 mm under controlled conditions. Repeated experimental observations demonstrate consistent sensitivity to defect presence and size. Based on these characteristics, a defect-sensitive framework is developed to support structural condition assessment. These findings contribute to the advancement of portable NDT techniques for natural civil materials and support broader applications in infrastructure monitoring. The proposed approach offers potential for further investigation under more complex field conditions, with implications for improved robustness and practical applicability.  a2590-123000434nas a2200133   4500000000100000008004100001100001900042700002600061700001500087700001500102245012700117856004900244490000700293       2026                            d1 aYishuang Zhang1 aMirosław Skibniewski1 aCheuk Chow1 aDenvid Lau00aSingle-Device On-Site Inspection System for Non-Destructive Internal Defect Detection in Trees Near Constructed Facilities  uhttps://doi.org/10.1016/j.rineng.2026.1117320 v3200634nas a2200181   4500000000100000008004100001100001200042700001500054700001500069700001500084700002300099700002200122700002600144245021200170856004700382300001600429490000700445       2026                            d1 aHao Liu1 aXuhui Cong1 aLiang Wang1 aYuxuan Gao1 aJonas Šaparauskas1 aRobert Dankiewicz1 aMirosław Skibniewski00aSpatial Network Characteristics and Drivers of the Collaborative Development of the Arterial and Venous Industries in "Zero Waste City": Based on 31 Provinces (Autonomous Regions and Municipalities) in China  uhttps://doi.org/10.1007/s10163-026-02649-6  a3754–37730 v2802107nas a2200217   4500000000100000008004100001260001200042100001200054700001500066700001500081700001500096700002300111700002200134700002600156245021600182856004700398300001600445490000700461520140700468020001401875       2026                            d  c07/20261 aHao Liu1 aXuhui Cong1 aLiang Wang1 aYuxuan Gao1 aJonas Šaparauskas1 aRobert Dankiewicz1 aMirosław Skibniewski00aSpatial network characteristics and drivers of the collaborative development of the arterial and venous industries in “Zero Waste City”: Based on 31 provinces (autonomous regions and municipalities) in China  uhttps://doi.org/10.1007/s10163-026-02649-6  a3754-3773, 0 v283 aThe requirements of solid waste reduction, recycling, and harmlessness in the construction of “Zero Waste City” have introduced higher standards for the development of the arterial and venous industries. This study takes 31 provincial regions in China as the research objects. The coupling coordination degree model is used to quantify the collaborative development level of the venous and arterial industries in “Zero Waste City” from 2014 to 2023, and the process’s temporal and spatial evolution is examined. By applying the modified gravity model, social network analysis, and quadratic assignment procedure, this study examines the characteristics and drivers of the spatial network. The research shows that the collaborative development level of the arterial and venous industries in China’s provincial “Zero Waste City” exhibits a steady growing tendency over time and a stable downward trend from east to west in space. The frequency of connections in the spatial network demonstrates a declining trend of divergence from the east to the outside. Beijing, Shanghai, Zhejiang, Guangdong, and other regions are the central hubs in the network. Geographical proximity, economic difference, industrial structure difference, and public environmental attention difference facilitate the establishment of the spatial network, while government support difference inhibits its formation.  a1611-822700484nas a2200145   4500000000100000008004100001100001200042700001400054700001400068700001800082700002600100245015400126856005000280490000800330       2026                            d1 aHui Liu1 aXuan Chen1 aYouwen Hu1 aBaoquan Cheng1 aMirosław Skibniewski00aSystematic Integration and Quantitative Benchmarking of Digital Technologies Empowering Low Carbon Building: A Three-Dimensional Analytical Framework  uhttps://doi.org/10.1016/j.enbuild.2026.1174900 v36102652nas a2200253   4500000000100000008004100001653002300042653002400065653003300089653002900122653003200151653002500183100001200208700001400220700001400234700001800248700002600266245015400292856007200446300001100518490000800529520184700537022001402384       2026                            d10aDigital technology10aLow carbon building10aRenewable energy integration10aCarbon cost optimization10aThree-dimensional framework10aEmpowering mechanism1 aHui Liu1 aXuan Chen1 aYouwen Hu1 aBaoquan Cheng1 aMirosław Skibniewski00aSystematic integration and quantitative benchmarking of digital technologies empowering low carbon building: a three-dimensional analytical framework  uhttps://www.sciencedirect.com/science/article/pii/S0378778826005505  a1174900 v3613 aBuilding with low carbon emissions (low carbon building, LCB) is crucial for the construction industry’s green transition. With digital technologies (DTs) playing an increasingly pivotal role in decarbonizing the construction sector, this study explores how DTs empower LCB to reduce global CO2 emissions. To objectively identify the core gaps of existing research, this study first conducts a preliminary scoping review of 1476 peer-reviewed articles, adopting a two-step inductive approach to reveal three dominant knowledge gaps: (1) stage-agnostic analytical bias, (2) qualitative mechanism limitation, and (3) disconnected renewable energy integration. Guided by these empirically validated gaps, a three-dimensional conceptual framework (LCB solutions-digital functions-building life-cycle stages) was developed, followed by a mixed-methods systematic review (bibliometric analysis and qualitative content coding) of 73 core peer-reviewed articles. The results indicate that: (1) Artificial Intelligence (AI) and Building Information Modeling (BIM) stand as the two dominant DTs driving LCB; (2) six core quantified empowering mechanisms are identified, with tangible benefits including a 15%-20% reduction in unnecessary electricity consumption (Internet of Things-based systems) and 18% carbon emission reduction (BIM-Life cycle assessment integration); (3) the proposed framework realizes stage-specific DT-LCB matching while integrating renewable energy synergy and carbon cost optimization. Findings provide stage-specific technical benchmarks for practitioners, targeted incentives for policymakers, and practice-driven research and development guidance for technology developers, advancing beyond fragmented DT applications to systematic, quantified, renewable energy-integrated empowerment that bridges theory–practice gaps.  a0378-778802466nas a2200157   4500000000100000008004100001100001500042700001700057700001400074700001700088700001600105700001800121700002600139245008600165520205700251       2025                            d1 aXudong Fan1 aYishuo Jiang1 aRay Zhong1 aFabio Duarte1 aWaishan Qiu1 aJürgen Hackl1 aMirosław Skibniewski00aAdvancements and potential pitfalls for smart cities and sentient infrastructures3 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 stewardship01762nas a2200121   4500000000100000008004100001100002000042700001800062700001800080700002600098245007400124520144200198       2025                            d1 aATaha Demirbağ1 aHande Aladağ1 aZeynep Işık1 aMirosław Skibniewski00aCircular Economy-Based Decision-Making Model for Contractor Selection3 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.02442nas a2200133   4500000000100000008004100001100001600042700001600058700002600074700001300100700001300113245012600126520205600252       2025                            d1 aHongyu Chen1 aQiping Shen1 aMirosław Skibniewski1 aYuan Cao1 aYang Liu00aDynamic prediction and optimization of tunneling parameters with high reliability based on a hybrid intelligent algorithm3 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.01485nas a2200157   4500000000100000008004100001100001500042700001500057700001700072700001400089700001800103700002600121700001800147245009800165520106400263       2025                            d1 aYashuai Li1 aWubin Wang1 aJichang Zhao1 aYang Yang1 aZhaohui Zhang1 aMirosław Skibniewski1 aJingfeng Yuan00aEstimating demolition waste from residential interior photos: A Large Language Model solution3 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.01469nas a2200145   4500000000100000008004100001100002000042700001600062700001900078700001400097700001900111700002600130245008800156520107900244       2025                            d1 aSheng-Hua Xiong1 aXi-Hang Wei1 aZhen-Song Chen1 aHao Zhang1 aWitold Pedrycz1 aMirosław Skibniewski00aIdentifying causes of aviation safety events using wW2V-tCNN with data augmentation3 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 events01552nas a2200109   4500000000100000008004100001100001400042700001600056700002600072245011400098520123000212       2025                            d1 aQiong Liu1 aLimao Zhang1 aMirosław Skibniewski00aNetwork extension planning towards resilient urban critical infrastructures using deep reinforcement learning3 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.00542nas a2200157   4500000000100000008004100001100001500042700001500057700001500072700001900087700001200106700002200118700002500140700002600165245019300191       2025                            d1 aBocong Liu1 aXuhui Cong1 aLiang Wang1 aShenghui Zhang1 aHao Liu1 aJonas Saparauskas1 aLeonas Ustinovichius1 aMirosław Skibniewski00aSpatial-temporal evolution and influencing factors of the coupling coordination degree between new infrastructure construction and high-quality development in urban agglomerations in China02170nas a2200133   4500000000100000008004100001100001200042700001600054700001600070700002600086700001800112245014700130520175900277       2025                            d1 aHui Liu1 aHanyu Zheng1 aQianqian Ju1 aMirosław Skibniewski1 aMengmeng Wang00aTemporal-Spatial Evolution of BIM-Based Collaborative Innovation Network: Evidence from Patents in China\textquoterights Construction Industry3 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.02123nas a2200157   4500000000100000008004100001100001400042700001800056700001600074700001600090700001500106700001300121700002600134245011200160520169300272       2025                            d1 aLei Zhang1 aJingfeng Yuan1 aXianfei Yin1 aTiantian Gu1 aYinghao Lu1 aPing Liu1 aMirosław Skibniewski00aThe emotional equation: how psychosocial support boosts safety practices in the context of construction 5.03 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 ecosystems01657nas a2200133   4500000000100000008004100001100001900042700001200061700001300073700001600086700002600102245014400128520125100272       2025                            d1 aZhen-Song Chen1 aYue Tan1 aZheng Ma1 aZhengze Zhu1 aMirosław Skibniewski00aUnlocking the potential of quantum computing in prefabricated construction supply chains: Current trends, challenges, and future directions3 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.00390nas a2200121   4500000000100000008004100001100002400042700001800066700001400084700002600098245010000124856004400224       2024                            d1 aSvetlana Besklubova1 aMuhammad Raza1 aRay Zhong1 aMirosław Skibniewski00a3D Printing vs. Traditional Construction: Cost Comparisons from Design to Waste Disposal Stages  uhttps://doi.org/10.22260/isarc2024/016100464nas a2200145   4500000000100000008004100001100002400042700001800066700001400084700002500098700002600123245007700149856007800226022001400304       2024                            d1 aSvetlana Besklubova1 aNikola Spicek1 aRay Zhong1 aEkaterina Kravchenko1 aMirosław Skibniewski00aA framework for the acceptance of 3D printing technology in construction  uhttps://gigvvy.com/journals/ijase/articles/21/4/ijase-202409-21-4-001.pdf  a1727-239400553nas a2200157   4500000000100000008004100001100001500042700001500057700001300072700001900085700002600104700001900130245014500149856008700294022001400381       2024                            d1 aQiurui Liu1 aYanfang Ma1 aLin Chen1 aWitold Pedrycz1 aMirosław Skibniewski1 aZhen-Song Chen00aArtificial intelligence for production, operations and logistics management in modular construction industry: A systematic literature review  uhttps://api.elsevier.com/content/article/PII:S156625352400201X?httpAccept=text/xml  a1566-253500555nas a2200157   4500000000100000008004100001100001500042700001900057700001900076700001800095700001900113700002600132245015200158856007300310022001400383       2024                            d1 aQiang Yang1 aZhen-Song Chen1 aJiang-Hong Zhu1 aLuis Martinez1 aWitold Pedrycz1 aMirosław Skibniewski00aConcept Design Evaluation of Sustainable Product–Service Systems: A QFD–TOPSIS Integrated Framework with Basic Uncertain Linguistic Information  uhttps://link.springer.com/content/pdf/10.1007/s10726-023-09870-w.pdf  a0926-264400563nas a2200169   4500000000100000008004100001100001700042700001700059700001700076700001400093700001600107700002600123700002100149700001700170245011900187856008700306       2024                            d1 aYishuo Jiang1 aShuaiming Su1 aShuxuan Zhao1 aRay Zhong1 aWaishan Qiu1 aMirosław Skibniewski1 aIoannis Brilakis1 aGeorge Huang00aDigital twin-enabled synchronized construction management: A roadmap from construction 4.0 towards future prospect  uhttps://api.elsevier.com/content/article/PII:S2666165924001935?httpAccept=text/xml00431nas a2200133   4500000000100000008004100001100001500042700001200057700001100069700002600080245010700106856007000213022001400283       2024                            d1 aLiang Wang1 aYue Cao1 aJun Hu1 aMirosław Skibniewski00aDoes digital economy development benefit low-carbon transition: evidence based on urban carbon lock-in  uhttps://www.tandfonline.com/doi/pdf/10.1080/09640568.2024.2390573  a0964-056802282nas a2200157   4500000000100000008004100001260001200042100001900054700001900073700001600092700001900108700002600127245012500153490000800278520183800286       2024                            d  c03/20241 aZhen-Song Chen1 aChong-Ze Liang1 aYa-Qiang Xu1 aWitold Pedrycz1 aMirosław Skibniewski00aDynamic collective opinion generation framework for digital transformation barrier analysis in the construction industry0 v1033 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.00501nas a2200145   4500000000100000008004100001100001500042700001600057700001300073700001500086700002600101245012700127856008700254022001400341       2024                            d1 aJiaqi Wang1 aLimao Zhang1 aHui Yang1 aHuabei Liu1 aMirosław Skibniewski00aDynamic reliability analysis of Aerial Building Machine under extreme wind loads using improved QBDC-based active learning  uhttps://api.elsevier.com/content/article/PII:S0951832024000024?httpAccept=text/xml  a0951-832000469nas a2200133   4500000000100000008004100001100002000042700001100062700002600073700001900099245011600118856008700234022001400321       2024                            d1 aJian-Peng Chang1 aYan Su1 aMirosław Skibniewski1 aZhen-Song Chen00aEvaluating potential quality of e-commerce order fulfillment service: A collective intelligence-driven approach  uhttps://api.elsevier.com/content/article/PII:S0020025524003384?httpAccept=text/xml  a0020-025500446nas a2200145   4500000000100000008004100001100001800042700001400060700001700074700001400091700002600105245007200131856008300203022001400286       2024                            d1 aYuanxin Zhang1 aLiujun Xu1 aXiaolong Xue1 aZeyu Wang1 aMirosław Skibniewski00aFormation and dynamics of prefabricated building innovation network  uhttps://www.emerald.com/insight/content/doi/10.1108/ECAM-10-2023-1073/full/xml  a0969-998800530nas a2200157   4500000000100000008004100001100001900042700001800061700001800079700002600097700001500123700002000138245011700158856008300275022001400358       2024                            d1 aZhen-Song Chen1 aZhuo-Ran Wang1 aXian-Jia Wang1 aMirosław Skibniewski1 aBrij Gupta1 aMuhammet Deveci00aLeveraging Probabilistic Optimization for Digital Transformation Maturity Evaluation of Construction Enterprises  uhttp://xplorestaging.ieee.org/ielx7/17/10339242/10518098.pdf?arnumber=10518098  a0018-939101680nas a2200157   4500000000100000008004100001260001200042100001900054700001700073700001600090700001900106700002600125245010200151490000700253520126200260       2024                            d  c01/20241 aZhen-Song Chen1 aKou-Dan Chen1 aYa-Qiang Xu1 aWitold Pedrycz1 aMirosław Skibniewski00aMultiobjective optimization-based decision support for building digital twin maturity measurement0 v593 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.01677nas a2200169   4500000000100000008004100001260001200042100001900054700001800073700002000091700001700111700001900128700002600147245014600173490000800319520118000327       2024                            d  c02/20241 aZhen-Song Chen1 aZhuo-Ran Wang1 aMuhammet Deveci1 aWeiping Ding1 aWitold Pedrycz1 aMirosław Skibniewski00aOptimization-based probabilistic decision support for assessing building information modelling (BIM) maturity considering multiple objectives0 v1023 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.01792nas a2200157   4500000000100000008004100001260001200042100002000054700001800074700001200092700002600104700001900130245009600149490000800245520138100253       2024                            d  c04.20241 aSheng-Hua Xiong1 aZhi-Peng Wang1 aGang Li1 aMirosław Skibniewski1 aZhen-Song Chen00aPrediction of airport runway settlement using an integrated SBAS-InSAR and BP-EnKF approach0 v6653 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%.00463nas a2200145   4500000000100000008004100001100001200042700001300054700001900067700001800086700002600104245008600130856008700216022001400303       2024                            d1 aPeng He1 aQi Shang1 aZhen-Song Chen1 aAbbas Mardani1 aMirosław Skibniewski00aShort video channel strategy for restaurants in the platform service supply chain  uhttps://api.elsevier.com/content/article/PII:S0969698924000511?httpAccept=text/xml  a0969-698900581nas a2200169   4500000000100000008004100001100001700042700001700059700001100076700002000087700002000107700002600127700001900153245015200172856007300324022001400397       2024                            d1 aZhu-Jun Wang1 aYangyang Sun1 aQin Su1 aMuhammet Deveci1 aKannan Govindan1 aMirosław Skibniewski1 aZhen-Song Chen00aSmart Contract Application in Resisting Extreme Weather Risks for the Prefabricated Construction Supply Chain: Prototype Exploration and Assessment  uhttps://link.springer.com/content/pdf/10.1007/s10726-024-09877-x.pdf  a0926-264400501nas a2200145   4500000000100000008004100001100001900042700001900061700001800080700002000098700002600118245011000144856008700254022001400341       2024                            d1 aTong-Yuan Wang1 aZhen-Song Chen1 aXian-Jia Wang1 aKannan Govindan1 aMirosław Skibniewski00aStrategic information sharing in the dual-channel closed loop supply chain with nonlinear production cost  uhttps://api.elsevier.com/content/article/PII:S0020025523015293?httpAccept=text/xml  a0020-025500528nas a2200157   4500000000100000008004100001100001900042700001300061700001600074700001600090700001700106700002600123245012000149856008700269022001400356       2024                            d1 aZhen-Song Chen1 aYan Wang1 aYa-Qiang Xu1 aZhengze Zhu1 aYue-Hua Chen1 aMirosław Skibniewski00aTowards social-welfare and confidence optimizing approach to examining barriers for digital transformation in SMCEs  uhttps://api.elsevier.com/content/article/PII:S0020025524002251?httpAccept=text/xml  a0020-025501501nas a2200169   4500000000100000008004100001260001200042100002000054700002000074700002000094700002200114700002600136245009200162856007700254490001200331520098800343       2023                            d  c10/20231 aBartosz Wójcik1 aMateusz Żarski1 aKamil Książek1 aJaroslaw Miszczak1 aMirosław Skibniewski00aA deep learning method for hard-hat-wearing detection based on head center localization  uhttps://journals.pan.pl/dlibra/publication/147340/edition/128931/content0 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.01559nas a2200145   4500000000100000008004100001260001200042100001900054700001900073700001200092700002000104700002600124245009500150520116800245       2023                            d  c02/20231 aTong-Yuan Wang1 aZhen-Song Chen1 aPeng He1 aKannan Govindan1 aMirosław Skibniewski00aAlliance strategy in an online retailing supply chain: Motivation, choice, and equilibrium3 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.02266nas a2200181   4500000000100000008004100001260001200042100002000054700001900074700001700093700001600110700001900126700001800145700002600163245014300189490001000332520174200342       2023                            d  c02/20231 aJian-Peng Chang1 aZhen-Song Chen1 aZhu-Jun Wang1 aLeSheng Jin1 aWitold Pedrycz1 aLuis Martinez1 aMirosław Skibniewski00aAssessing Spatial Synergy Between Integrated Urban Rail Transit System and Urban Form: A BULI-Based MCLSGA Model With the Wisdom of Crowds0 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.02480nas a2200193   4500000000100000008004100001260001200042100001500054700001300069700001700082700001200099700001200111700001900123700001300142700002600155245013500181490000800316520196200324       2023                            d  c06/20231 aXianguo Wu1 aYuan Cao1 aWeicheng Liu1 aYabo He1 aGang Xu1 aZhen-Song Chen1 aYang Liu1 aMirosław Skibniewski00aBIM-driven building greenness evaluation system: An integrated perspective drawn from model data and collective experts' judgments0 v4063 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.01854nas a2200169   4500000000100000008004100001260001200042100001900054700001500073700001800088700001700106700002000123700002600143245011700169490000800286520139000294       2023                            d  c11/20231 aZhen-Song Chen1 aJing-Yi Lu1 aJiang-Tao Wen1 aXianjia Wang1 aMuhammet Deveci1 aMirosław Skibniewski00aBIM-enabled decision optimization analysis for architectural glass material selection considering sustainability0 v6473 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.02492nas a2200169   4500000000100000008004100001260001200042100001700054700001900071700001100090700001200101700002000113700002600133245010200159490000900261520205200270       2023                            d  c12/20231 aZhu-Jun Wang1 aZhen-Song Chen1 aQin Su1 aLu Xiao1 aKannan Govindan1 aMirosław Skibniewski00aBlockchain adoption in sustainable supply chains for Industry 5.0: A multistakeholder perspective0 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.02252nas a2200193   4500000000100000008004100001260001200042100001500054700001500069700001300084700001400097700001500111700002300126700002300149700002600172245017500198490001200373520167300385       2023                            d  c10/20231 aXuhui Cong1 aZhipeng Qi1 aSai Wang1 aPeikun Su1 aLiang Wang1 aJonas Šaparauskas1 aJarosław Górecki1 aMirosław Skibniewski00aEcological Welfare Performance Evaluation and Spatial–Temporal Difference Evolution of Blue Economic Zones: A Case Study of the Blue Economic Zone of Shandong Peninsula0 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.01903nas a2200169   4500000000100000008004100001260001200042100001600054700001500070700001400085700001900099700001700118700002600135245007900161490001000240520148300250       2023                            d  c05/20231 aOmar Daboun1 aNur Abidin1 aAli Khoso1 aZhen-Song Chen1 aAminah Yusof1 aMirosław Skibniewski00aEffect of relationship management on construction project success delivery0 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.00546nas a2200157   4500000000100000008004100001100001700042700001900059700001100078700001900089700001900108700002600127245014800153856007300301022001400374       2023                            d1 aZhu-Jun Wang1 aZhen-Song Chen1 aQin Su1 aKwai-Sang Chin1 aWitold Pedrycz1 aMirosław Skibniewski00aEnhancing the sustainability and robustness of critical material supply in electrical vehicle market: an AI-powered supplier selection approach  uhttps://link.springer.com/content/pdf/10.1007/s10479-023-05698-4.pdf  a0254-533001777nas a2200181   4500000000100000008004100001260001200042100001300054700001700067700001900084700001600103700001800119700002000137700001600157700002600173245006400199520133200263       2023                            d  c07/20231 aYang Liu1 aXianjia Wang1 aZhen-Song Chen1 aYifei Zhang1 aShenghao Zhao1 aMuhammet Deveci1 aLeSheng Jin1 aMirosław Skibniewski00aEvaluating Digital Health Services Quality via Social Media3 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.01807nas a2200193   4500000000100000008004100001260001500042100001300057700001800070700001900088700001600107700001800123700002000141700001600161700002600177245006400203520133200267022001401599       2023                            d  c01/08/20231 aYang Liu1 aXian-Jia Wang1 aZhen-Song Chen1 aYifei Zhang1 aShenghao Zhao1 aMuhammet Devici1 aLeSheng Jin1 aMirosław Skibniewski00aEvaluating Digital Health Services Quality via Social Media3 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.  a0018-939101962nas a2200157   4500000000100000008004100001260001200042100001200054700001900066700001200085700001800097700002600115245012600141490000800267520152900275       2023                            d  c11/20231 aLu Xiao1 aZhen-Song Chen1 aRui Hou1 aAbbas Mardani1 aMirosław Skibniewski00aGreenness-based subsidy and dual credit policy to promote new energy vehicles considering consumers' low-carbon awareness0 v1853 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.02482nas a2200157   4500000000100000008004100001260001200042100001700054700001500071700001300086700001600099700002600115245017900141490000800320520199600328       2023                            d  c11/20231 aZongbao Feng1 aWeiya Chen1 aYang Liu1 aHongyu Chen1 aMirosław Skibniewski00aLong-term equilibrium relationship analysis and energy-saving measures of metro energy consumption and its influencing factors based on cointegration theory and an ARDL model0 v2633 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.02003nas a2200193   4500000000100000008004100001260001200042100001500054700001400069700001500083700001300098700001500111700002300126700002300149700002600172245015400198490001000352520144700362       2023                            d  c10/20231 aXuhui Cong1 aPeikun Su1 aLiang Wang1 aSai Wang1 aZhipeng Qi1 aJonas Šaparauskas1 aJarosław Górecki1 aMirosław Skibniewski00aMeasuring the Construction Efficiency of Zero-Waste City Clusters Based on an Undesirable Super-Efficiency Model and Kernel Density Estimation Method0 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.01573nas a2200181   4500000000100000008004100001260001200042100001600054700001300070700002600083700001500109700001500124700002300139700001400162245008000176490000800256520112700264       2023                            d  c11/20231 aHuanbao Liu1 aZihan Li1 aMirosław Skibniewski1 aLiang Wang1 aXuhui Cong1 aJarosław Górecki1 aWenyu Jin00aMolding quality control with nonlinear forming method in 3D cement printing0 v2353 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.02405nas a2200169   4500000000100000008004100001260001200042100001900054700001600073700001700089700002300106700002700129700002600156245009000182490001000272520195300282       2023                            d  c09/20231 aZhen-Song Chen1 aZhengze Zhu1 aXianjia Wang1 aFrancisco Chiclana1 aEnrique Herrera-Viedma1 aMirosław Skibniewski00aMultiobjective Optimization-Based Collective Opinion Generation With Fairness Concern0 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.01870nas a2200157   4500000000100000008004100001260001200042100001500054700001300069700001500082700001500097700002600112245011300138490001000251520145100261       2023                            d  c04/20231 aXuhui Cong1 aSai Wang1 aLiang Wang1 aZhipeng Qi1 aMirosław Skibniewski00aNew smart city clusters’ construction level evaluation under economic circles: the case of Shandong, China0 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.01918nas a2200169   4500000000100000008004100001260001200042100002000054700001600074700001900090700002000109700002300129700002600152245011800178490000800296520144400304       2023                            d  c03/20231 aSheng-Hua Xiong1 aChen-Ye Zhu1 aZhen-Song Chen1 aMuhammet Deveci1 aFrancisco Chiclana1 aMirosław Skibniewski00aOn extended power geometric operator for proportional hesitant fuzzy linguistic large-scale group decision-making0 v6323 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.02002nas a2200157   4500000000100000008004100001260001200042100001300054700001200067700002600079700001300105700001500118245014700133490000800280520155600288       2023                            d  c05/20231 aPing Xie1 aKe Chen1 aMirosław Skibniewski1 aJun Wang1 aHanbin Luo00aParametric geological model update and probabilistic analysis of shield tunnel excavation: A borehole-based conditional random fields approach0 v1573 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.02291nas a2200193   4500000000100000008004100001260001200042100001900054700001300073700001600086700001700102700002000119700002000139700001800159700002600177245013600203490000600339520175200345       2023                            d  c12/20231 aZhen-Song Chen1 aJia Zhou1 aChen-Ye Zhu1 aZhu-Jun Wang1 aSheng-Hua Xiong1 aRosa Rodríguez1 aLuis Martinez1 aMirosław Skibniewski00aPrioritizing real estate enterprises based on credit risk assessment: an integrated multi-criteria group decision support framework0 v93 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.03279nas a2200169   4500000000100000008004100001260001200042100002000054700001900074700001700093700001800110700001900128700002600147245015100173490000800324520277700332       2023                            d  c01/20231 aJian-Peng Chang1 aZhen-Song Chen1 aXianjia Wang1 aLuis Martinez1 aWitold Pedrycz1 aMirosław Skibniewski00aRequirement-driven sustainable supplier selection: Creating an integrated perspective with stakeholders' interests and the wisdom of expert crowds0 v1753 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.01805nas a2200193   4500000000100000008004100001260001200042100001600054700001300070700001700083700001300100700001400113700002600127700001900153700001300172245007100185490000800256520134700264       2023                            d  c06/20231 aHongyu Chen1 aXinyi Li1 aZongbao Feng1 aLei Wang1 aYawei Qin1 aMirosław Skibniewski1 aZhen-Song Chen1 aYang Liu00aShield attitude prediction based on Bayesian-LGBM machine learning0 v6323 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.00346nas a2200109   4500000000100000008004100001100001900042700002600061245008200087856005300169022001400222       2022                            d1 aSaurabh Jethva1 aMirosław Skibniewski00aAgile project management for design-build construction projects: a case study  uhttp://dx.doi.org/10.6703/ijase.202203_19(1).001  a1727-239400523nas a2200157   4500000000100000008004100001100001500042700001300057700001500070700002300085700002300108700002600131245014600157856004800303022001400351       2022                            d1 aXuhui Cong1 aSai Wang1 aLiang Wang1 aJonas Šaparauskas1 aJarosław Górecki1 aMirosław Skibniewski00aAllocation Efficiency Measurement and Spatio-Temporal Differences Analysis of Digital Infrastructure: The Case of China’s Shandong Province  uhttps://www.mdpi.com/2079-8954/10/6/205/pdf  a2079-895400529nas a2200157   4500000000100000008004100001100001900042700001700061700002000078700001600098700001900114700002600133245011100159856008700270022001400357       2022                            d1 aZhen-Song Chen1 aLi-Ping Yang1 aRosa Rodríguez1 aZhengze Zhu1 aWitold Pedrycz1 aMirosław Skibniewski00aBIM-aided large-scale group decision support: Optimization of the retrofit strategy for existing buildings  uhttps://api.elsevier.com/content/article/PII:S1568494622008390?httpAccept=text/xml  a1568-494601999nas a2200133   4500000000100000008004100001100001100042700001300053700001300066700002600079245011900105490000700224520163400231       2022                            d1 aY. Pan1 aL. Zhang1 aJ. Unwin1 aMirosław Skibniewski00aDiscovering spatial-temporal patterns via complex networks in investigating COVID-19 pandemic in the United States0 v773 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.00444nas a2200133   4500000000100000008004100001100001200042700001900054700002000073700002600093245009600119856008100215022001400296       2022                            d1 aLu Xiao1 aZhen-Song Chen1 aKannan Govindan1 aMirosław Skibniewski00aEffects of Online Consumer Reviews on a Dual-Channel Closed-Loop Supply Chain With Trade-In  uhttp://xplorestaging.ieee.org/ielx7/17/4429834/09770409.pdf?arnumber=9770409  a0018-939100554nas a2200157   4500000000100000008004100001100001900042700001500061700002000076700001900096700001800115700002600133245014200159856008100301022001400382       2022                            d1 aZhen-Song Chen1 aXuan Zhang1 aRosa Rodríguez1 aWitold Pedrycz1 aLuis Martinez1 aMirosław Skibniewski00aExpertise-Structure and Risk-Appetite-Integrated Two-Tiered Collective Opinion Generation Framework for Large-Scale Group Decision Making  uhttp://xplorestaging.ieee.org/ielx7/91/9967417/09786680.pdf?arnumber=9786680  a1063-670600572nas a2200157   4500000000100000008004100001100001500042700001900057700001900076700001900095700001800114700002600132245015500158856008700313022001400400       2022                            d1 aQiang Yang1 aZhen-Song Chen1 aCatherine Chan1 aWitold Pedrycz1 aLuis Martinez1 aMirosław Skibniewski00aLarge-scale group decision-making for prioritizing engineering characteristics in quality function deployment under comparative linguistic environment  uhttps://api.elsevier.com/content/article/PII:S1568494622005178?httpAccept=text/xml  a1568-494600406nas a2200109   4500000000100000008004100001100001200042700002600054245013200080856007000212022001400282       2022                            d1 aMing Hu1 aMirosław Skibniewski00aThe impact of the design team characteristics on the sustainable building construction cost: structural equation model analysis  uhttps://www.tandfonline.com/doi/pdf/10.1080/17452007.2022.2068497  a1745-200700421nas a2200157   4500000000100000008004100001260000800042100001200050700001600062700001200078700001300090700002600103700001600129245010900145490000900254       2022                            d  cjan1 aHui Liu1 aQianqian Ju1 aNa Zhao1 aHujun Li1 aMirosław Skibniewski1 aHanliang Fu00aValue Proposition for Enabling Construction Project Innovation by Applying Building Information Modeling0 v202200260nas a2200085   4500000000100000008004100001100001200042700002600054245009400080       2021                            d1 aMing Hu1 aMirosław Skibniewski00aA Review of Building Construction Cost Research: Current Status, Gaps and Green Buildings01556nam a2200169   4500000000100000008004100001260001300042100001600055700001200071700001500083700002600098245007100124300001200195490000800207520114900215020002201364       2021                            d  bSpringer1 aLimao Zhang1 aYue Pan1 aXianguo Wu1 aMirosław Skibniewski00aArtificial Intelligence in Construction Engineering and Management  aXI, 2630 v1633 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.  a978-981-16-2842-900457nas a2200145   4500000000100000008004100001100001400042700001700056700001900073700002600092700001900118700001800137700001900155245013700174       2021                            d1 aAli Khoso1 aAminah Yusof1 aZhen-Song Chen1 aMirosław Skibniewski1 aKwai-Sang Chin1 aShabir Khahro1 aSamiullah Sohu00aComprehensive analysis of state-of-the-art contractor selection models in construction environment-A critical review and future call00378nas a2200133   4500000000100000008004100001100001200042700001600054700001700070700001300087700002600100245011100126490000700237       2021                            d1 aYue Pan1 aLimao Zhang1 aZhenzhen Yan1 aMay Lwin1 aMirosław Skibniewski00aDiscovering optimal strategies for mitigating COVID-19 spread using machine learning: Experience from Asia0 v7500527nas a2200157   4500000000100000008004100001100001400042700001700056700001900073700001800092700002600110700001700136245013300153856006900286022001400355       2021                            d1 aAli Khoso1 aAminah Yusof1 aZhen-Song Chen1 aXian-Jia Wang1 aMirosław Skibniewski1 aNafees Memon00aEMBEDDED REMOTE GROUP ENVIRONMENT THROUGH MODIFICATION IN MACBETH – AN APPLICATION OF CONTRACTOR’S SELECTION IN CONSTRUCTION  uhttps://journals.vgtu.lt/index.php/JCEM/article/view/15763/10780  a1392-373000392nas a2200121   4500000000100000008004100001100001800042700001500060700002600075700001700101245014500118490000700263       2021                            d1 aMuhammad Khan1 aNuman Khan1 aMirosław Skibniewski1 aChansik Park00aEnvironmental Particulate Matter (PM) Exposure Assessment of Construction Activities Using Low-Cost PM Sensor and Latin Hypercubic Technique0 v1300300nas a2200109   4500000000100000008004100001100002400042700002600066700001800092245007200110490000800182       2021                            d1 aSvetlana Besklubova1 aMirosław Skibniewski1 aXueqing Zhang00aFactors Affecting 3D Printing Technology Adaptation in Construction0 v14700245nas a2200097   4500000000100000008004100001100001200042700002600054245006000080490000700140       2021                            d1 aMing Hu1 aMirosław Skibniewski00aGreen Building Construction Cost Surcharge: An Overview0 v2700606nas a2200157   4500000000100000008004100001100001900042700001600061700001900077700001900096700002000115700002600135245018600161856008700347022001400434       2021                            d1 aZhen-Song Chen1 aXiao-Lu Liu1 aKwai-Sang Chin1 aWitold Pedrycz1 aKwok-Leung Tsui1 aMirosław Skibniewski00aOnline-review analysis based large-scale group decision-making for determining passenger demands and evaluating passenger satisfaction: Case study of high-speed rail system in China  uhttps://api.elsevier.com/content/article/PII:S1566253520304164?httpAccept=text/xml  a1566-253500529nas a2200145   4500000000100000008004100001100002000042700001900062700002300081700001900104700002600123245015800149856006200307022001400369       2021                            d1 aSheng-Hua Xiong1 aZhen-Song Chen1 aFrancisco Chiclana1 aKwai-Sang Chin1 aMirosław Skibniewski00aProportional hesitant 2‐tuple linguistic distance measurements and extended VIKOR method: Case study of evaluation and selection of green airport plans  uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002/int.22714  a0884-817302402nas a2200181   4500000000100000008004100001100001900042700001700061700001900078700001200097700001900109700002000128700001900148700002600167245011200193490001600305520189900321       2021                            d1 aZhen-Song Chen1 aLan-Lan Yang1 aKwai-Sang Chin1 aYi Yang1 aWitold Pedrycz1 aJian-Peng Chang1 aLuis Martínez1 aMirosław Skibniewski00aSustainable building material selection: An integrated multi-criteria large group decision making framework0 v113, Part A3 aIn 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.00438nas a2200145   4500000000100000008004100001100001500042700001000057700001500067700002300082700002300105700002600128245013000154490000800284       2021                            d1 aXuhui Cong1 aLi Ma1 aLiang Wang1 aJonas Šaparauskas1 aJarosław Górecki1 aMirosław Skibniewski00aThe early warning system for determining the “not in My Back Yard” of heavy pollution projects based on public perception0 v28200351nas a2200121   4500000000100000008004100001100001900042700001800061700001600079700002600095245010100121490000700222       2021                            d1 aHan-Tang Huang1 aH Ping Tserng1 aRuei-Yu Hou1 aMirosław Skibniewski00aWireless Sensor Network-Based Monitoring of Bridge Pile Foundations for Detecting Scouring Depth0 v2901934nas a2200181   4500000000100000008004100001260000800042100001400050700001800064700001600082700002600098245010000124856004600224300000900270490000700279520145200286022001401738       2020                            d  coct1 aXijun Yao1 aHsi-Hsien Wei1 aIgal Shohet1 aMirosław Skibniewski00aAssessment of Terrorism Risk to Critical Infrastructures: The Case of a Power-Supply Substation  uhttps://www.mdpi.com/2076-3417/10/20/7162  a71620 v103 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.  a2076-341702455nas a2200181   4500000000100000008004100001100001900042700001500061700001900076700001800095700002600113245010300139856007100242300001100313490000700324520192800331022001402259       2020                            d1 aZhen-Song Chen1 aXuan Zhang1 aWitold Pedrycz1 aXian-Jia Wang1 aMirosław Skibniewski00aBid evaluation in civil construction under uncertainty: A two-stage LSP-ELECTRE III-based approach  uhttp://www.sciencedirect.com/science/article/pii/S0952197620302025  a1038350 v943 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.  a0952-197600348nas a2200121   4500000000100000008004100001100001200042700002600054700001600080700001400096700001900110245009700129       2020                            d1 aHui Liu1 aMirosław Skibniewski1 aQianqian Ju1 aJunjie Li1 aHongbing Jiang00aBIM-enabled construction innovation through collaboration: a mixed-methods systematic review01992nas a2200145   4500000000100000008004100001260000900042100001200051700001600063700002600079245007800105856006300183490000700246520159300253       2020                            d  c20201 aYue Pan1 aLimao Zhang1 aMirosław Skibniewski00aClustering of designers based on building information modeling event logs  uhttps://onlinelibrary.wiley.com/doi/abs/10.1111/mice.125510 v353 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.00435nas a2200145   4500000000100000008004100001100001500042700001500057700001000072700001500082700002600097245014500123300001400268490000700282       2020                            d1 aLiang Wang1 aPing Zhang1 aLi Ma1 aXuhui Cong1 aMirosław Skibniewski00aDeveloping a corporate social responsibility framework for sustainable construction using partial least squares structural equation modeling  a186–2120 v2601828nas a2200145   4500000000100000008004100001100001700042700001800059700001300077700002600090700001400116245011300130300001100243520142800254       2020                            d1 aXiaer Xiahou1 aJingfeng Yuan1 aHong Xie1 aMirosław Skibniewski1 aQiming Li00aExploring driving factors of smart city development under the physical-human society-cyber (PHC) space model  a1–113 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.00476nas a2200157   4500000000100000008004100001100001400042700001600056700002600072700001600098700001200114700001500126245008000141856008300221022001400304       2020                            d1 aTianyu Ma1 aZhuofu Wang1 aMirosław Skibniewski1 aJiyong Ding1 aGe Wang1 aQinghua He00aInvestigating stewardship behavior in megaprojects: An exploratory analysis  uhttps://www.emerald.com/insight/content/doi/10.1108/ECAM-07-2020-0479/full/xml  a0969-998800418nas a2200157   4500000000100000008004100001100001400042700001800056700001300074700001300087700001400100700002600114245009900140300001400239490000700253       2020                            d1 aLei Zhang1 aJingfeng Yuan1 aNini Xia1 aYan Ning1 aJunwei Ma1 aMirosław Skibniewski00aMeasuring value-added-oriented BIM climate in construction projects: dimensions and indicators  a800–8180 v2602437nas a2200157   4500000000100000008004100001100001400042700001500056700002600071245010000097856007100197300001200268490000700280520197800287022001402265       2019                            d1 aKaiman Li1 aHanbin Luo1 aMirosław Skibniewski00aA non-centralized adaptive method for dynamic planning of construction components storage areas  uhttp://www.sciencedirect.com/science/article/pii/S1474034617305633  a80 - 940 v393 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.  a1474-034602529nas a2200169   4500000000100000008004100001100001500042700001600057700002600073700001300099245011100112856007100223300001100294490000700305520203300312022001402345       2019                            d1 aShiyao Cai1 aZhiliang Ma1 aMirosław Skibniewski1 aSong Bao00aConstruction automation and robotics for high-rise buildings over the past decades: A comprehensive review  uhttp://www.sciencedirect.com/science/article/pii/S1474034619305622  a1009890 v423 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.  a1474-034600369nas a2200109   4500000000100000008004100001100001800042700001400060700001600074700002600090245014300116       2019                            d1 aJingfeng Yuan1 aLei Zhang1 aYongtao Tan1 aMirosław Skibniewski00aEvaluating the regional social sustainability contribution of public-private partnerships in China: The development of an indicator system00379nas a2200133   4500000000100000008004100001100001800042700001500060700001600075700002600091245010600117300001400223490000800237       2019                            d1 aJingfeng Yuan1 aLingzhi Li1 aEndong Wang1 aMirosław Skibniewski00aExamining sustainability indicators of space management in elderly Facilities—a case study in China  a144–1590 v20800326nas a2200133   4500000000100000008004100001100001500042700001400057700002600071700001100097700001700108245005800125490000900183       2019                            d1 aNuman Khan1 aAhmad Ali1 aMirosław Skibniewski1 aDo Lee1 aChansik Park00aExcavation Safety Modeling Approach Using BIM and VPL0 v201902118nas a2200205   4500000000100000008004100001100001500042700001300057700002000070700001400090700001600104700002600120700001600146245009700162856007100259300001100330490000800341520154900349022001401898       2019                            d1 aCheng Zhou1 aRui Chen1 aShuangnan Jiang1 aYing Zhou1 aLieyun Ding1 aMirosław Skibniewski1 aXinggui Lin00aHuman dynamics in near-miss accidents resulting from unsafe behavior of construction workers  uhttp://www.sciencedirect.com/science/article/pii/S037843711930888X  a1214950 v5303 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.  a0378-437100405nas a2200145   4500000000100000008004100001100001600042700001600058700002000074700002600094700002000120245009800140300001300238490000800251       2019                            d1 aShengyu Guo1 aLieyun Ding1 aYongcheng Zhang1 aMirosław Skibniewski1 aKongzheng Liang00aHybrid recommendation approach for behavior modification in the Chinese construction industry  a040190350 v14500356nas a2200145   4500000000100000008004100001100001200042700001600054700001500070700001500085700002600100245006200126300001400188490000800202       2019                            d1 aYue Pan1 aLimao Zhang1 aXianguo Wu1 aWenwei Qin1 aMirosław Skibniewski00aModeling face reliability in tunneling: A copula approach  a272–2860 v10900409nas a2200145   4500000000100000008004100001100001800042700001100060700001100071700001400082700002600096245012000122300001400242490000700256       2019                            d1 aJingfeng Yuan1 aWei Li1 aBo Xia1 aYuan Chen1 aMirosław Skibniewski00aOperation performance measurement of public rental housing delivery by PPPS with fuzzy-AHP comprehensive evaluation  a328–3530 v2300361nas a2200133   4500000000100000008004100001100001600042700001500058700001400073700002600087245009400113300001300207490000700220       2019                            d1 aLimao Zhang1 aXianguo Wu1 aWenli Liu1 aMirosław Skibniewski00aOptimal Strategy to Mitigate Tunnel-Induced Settlement in Soft Soils: Simulation Approach  a040190580 v3300360nas a2200121   4500000000100000008004100001100001900042700001800061700001500079700002600094245010900120490000900229       2019                            d1 aChuanjun Zheng1 aJingfeng Yuan1 aLingzhi Li1 aMirosław Skibniewski00aProcess-Based Identification of Critical Factors for Residual Value Risk in China's Highway PPP Projects0 v201900407nas a2200133   4500000000100000008004100001100001800042700001500060700001400075700002600089245013500115300001600250490000700266       2019                            d1 aJingfeng Yuan1 aWenying Ji1 aJiyue Guo1 aMirosław Skibniewski00aSimulation-based dynamic adjustments of prices and subsidies for transportation PPP projects based on stakeholders’ satisfaction  a2309–23450 v4600381nas a2200145   4500000000100000008004100001100001200042700001600054700001500070700001700085700002600102245008500128300001400213490000800227       2019                            d1 aYue Pan1 aLimao Zhang1 aXianguo Wu1 aKainan Zhang1 aMirosław Skibniewski00aStructural health monitoring and assessment using wavelet packet energy spectrum  a652–6650 v12000374nas a2200133   4500000000100000008004100001100001500042700001600057700001400073700002600087245010800113300001200221490000700233       2019                            d1 aCheng Zhou1 aLieyun Ding1 aYing Zhou1 aMirosław Skibniewski00aVisibility graph analysis on time series of shield tunneling parameters based on complex network theory  a10–240 v8900303nas a2200085   4500000000100000008004100001100002600042245011000068856003900178       2018                            d1 aMirosław Skibniewski00aInfluence of Relational Norms on User Interests in PPP Projects: Mediating Effect of Project Performance.  uhttps://doi.org/10.3390/su1006202700384nas a2200121   4500000000100000008004100001100002400042700001700066700001900083700002600102245012500128490000900253       2018                            d1 aPrzemysław Sekuła1 aZachary Laan1 aKaveh Sadabadi1 aMirosław Skibniewski00aPredicting work zone collision probabilities via clustering: application in optimal deployment of highway response teams0 v201800385nas a2200133   4500000000100000008004100001260001200042100001000054700002600064245013200090300000900222490000600231022001400237       2017                            d  c11/20171 aY Han1 aMirosław Skibniewski00aA Market Equilibrium Supply Chain Model for Supporting Self-Manufacturing or Outsourcin Decisions in Prefabricated Construction  a1-180 v9  a2071-105000384nas a2200157   4500000000100000008004100001260001200042100001200054700001100066700000900077700002600086245008200112300001000194490000800204022001400212       2017                            d  c08/20171 aL Zhang1 aL Ding1 aX Wu1 aMirosław Skibniewski00aAn improved Dempster–Shafer approach to construction safety risk perception  a30-460 v132  a0950-705100433nas a2200169   4500000000100000008004100001260001200042100001100054700001200065700002600077700001100103700001300114245010300127300001200230490000700242022001400249       2017                            d  c10/20171 aC Zhou1 aLY Ding1 aMirosław Skibniewski1 aHB Luo1 aSN Jiang00aCharacterizing time series of near-miss accidents in metro construction via complex network theory  a145-1580 v98  a0925-753500420nas a2200157   4500000000100000008004100001260001200042100001200054700001300066700001000079700002600089245011800115300000900233490000600242022001400248       2017                            d  c03/20171 aJ. Yuan1 aX. Zheng1 aJ You1 aMirosław Skibniewski00aIdentifying Critical Factors Influencing the Rents of Public Rental Housing Delivery by PPPs: The Case of Nanjing  a1-220 v9  a2071-105000395nas a2200145   4500000000100000008004100001260001200042100001200054700001400066700002600080245011000106300001200216490000700228022001400235       2017                            d  c04/20171 aQ.Q. Ju1 aJ.Y. Ding1 aMirosław Skibniewski00aOptimization strategies to eliminate interface conflicts in complex study chains of construction projects  a712-7260 v23  a1392-373000396nas a2200157   4500000000100000008004100001260001200042100001400054700001300068700001000081700002600091245008600117300001400203490000700217022001400224       2017                            d  c05/20171 aL.M Zhang1 aY. Huang1 aX. Wu1 aMirosław Skibniewski00aRisk-based estimate for operational safety in complex projects under uncertainty,  a108–1200 v54  a1568-494601874nas a2200169   4500000000100000008004100001100001600042700001500058700001600073700002600089700001300115245006400128856005200192300001200244490000700256520144100263       2016                            d1 aLimao Zhang1 aXianguo Wu1 aLieyun Ding1 aMirosław Skibniewski1 aYujie Lu00aBim-Based Risk Identification System in tunnel construction  uhttp://dx.doi.org/10.3846/13923730.2015.1023348  a529-5390 v223 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.01665nas a2200145   4500000000100000008004100001100001700042700001700059700002600076245012200102856005100224300001200275490000700287520122500294       2016                            d1 aSun-Chan Bae1 aWon-Suk Jang1 aMirosław Skibniewski00aReliability performance of wireless sensor networks for civil infrastructure – Part II: prediction and verification  uhttp://dx.doi.org/10.3846/13923730.2014.948909  a243-2530 v223 aAbstractApplication 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.00484nas a2200169   4500000000100000008004100001100001600042700001500058700001400073700002600087700001400113245011100127856004100238300001400279490000700293022001400300       2016                            d1 aLimao Zhang1 aXianguo Wu1 aYawei Qin1 aMirosław Skibniewski1 aWenli Liu00aTowards a Fuzzy Bayesian Network Based Approach for Safety Risk Analysis of Tunnel-Induced Pipeline Damage  uhttp://dx.doi.org/10.1111/risa.12448  a278–3010 v36  a1539-692401749nas a2200181   4500000000100000008004100001100001500042700001500057700001600072700002600088700001600114700001700130245009600147300001400243490000800257520128800265022001401553       2015                            d1 aWu Xianguo1 aLiu Huitao1 aZhang Limao1 aMirosław Skibniewski1 aDeng Qianli1 aTeng Jiaying00aA dynamic Bayesian network based approach to safety decision support in tunnel construction  a157–1680 v1343 aThis paper presents a systemic decision approach with step-by-step procedures based on dynamic Bayesian network (DBN), aiming to provide guidelines for dynamic safety analysis of the tunnel-induced road surface damage over time. The proposed DBN-based approach can accurately illustrate the dynamic and updated feature of geological, design and mechanical variables as the construction progress evolves,in order to overcome deficenciesof traditional fault analysis method. Adopting the predictive, sensitivity and diagnostic analysis techniques in the DBN inference, this this approach is able to perform feed-forward, concurrent and back-forward control respectively on a quantitative basis, and provide real-time support before and after an accident. A case study in relating to dynamic safety analysis in the construction of Wuhan Yangtze Metro Tunel in China is used to verify the feasibility of the proposed approach, as well as its application potential. The relationships between the DBN-based and BN-based approaches are further discussed according to analysis results. The proposed aproach can be used as a decision tool to provide support for safety analysis in tunnel construction, and thus increase the likelihood of a successful project in a dynamic project environment.  a0951-832000425nas a2200181   4500000000100000008004100001260001200042100001000054700001200064700001300076700001200089700002600101700001300127245007000140300001200210490000700222022001400229       2015                            d  c08/20151 aXG Wu1 aYH Wang1 aLM Zhang1 aLY Ding1 aMirosław Skibniewski1 aJB Zhong00aA Dynamic Decision Approach for Risk Analysis in Complex Projects  a591-6010 v79  a0921-029600446nas a2200169   4500000000100000008004100001260001200042100001300054700001000067700002600077700001200103700001200115245011600127300001200243490000700255022001400262       2015                            d  c05/20151 aLM Zhang1 aXG Wu1 aMirosław Skibniewski1 aWL Fang1 aQL Deng00aConservation of historical buildings in tunneling environments: Case study of Wuhan Metro construction in China  a310-3220 v82  a0950-061800444nas a2200169   4500000000100000008004100001260001200042100001300054700001000067700001300077700002600090700001300116245011200129300001200241490000700253022001400260       2015                            d  c02/20151 aLM Zhang1 aXG Wu1 aQQ. Chen1 aMirosław Skibniewski1 aJB Zhong00aDeveloping a cloud model based risk assessment methodology for tunnel- induced damage to existing pipelines  a513-5260 v29  a1436-324001561nas a2200169   4500000000100000008004100001100001200042700001300054700001500067700002600082700001500108245011000123300001600233490000700249520112100256022001401377       2015                            d1 aX.G. Wu1 aZ. Jiang1 aL.M. Zhang1 aMirosław Skibniewski1 aJ.B. Zhong00aDynamic risk analysis for adjacent buildings in tunneling environments: a Bayesian network based approach  a1447–14610 v293 aThis paper presents a systemic Bayesian network (BN) based approach for dynamic risk analysis of adjacent buildings in tunneling environments, consisting of risk/hazard identification, BN learning and BN validation. Two validation indicators are proposed to evaluate the effectiveness of the established BN model, aiming to ensure that the model predictions are not significantly different from actual observations. In the dynamic risk analysis framework, the predictive, sensitivity and diagnostic techniques are used to conduct the feed-forward control in the pre-construction stage, intermediate control in the construction stage and back-forward control in the post-accident stage, respectively. A case regarding some existing buildings adjacent to construction of the Wuhan Yangtze metro tunnel in China is presented. The results demonstrate the feasibility of the proposed approach, as well as its application potential. The proposed approach can be used by practitioners in the industry as a decision support tool to provide guidelines on the conservation of adjacent buildings against tunnel-induced damages.  a1436-324000401nas a2200157   4500000000100000008004100001260001200042100001200054700001000066700001300076700002600089245009500115300001200210490000700222022001400229       2015                            d  c12/20151 aLI Ding1 aXG Wu1 aLM Zhang1 aMirosław Skibniewski00aHow to protect historical buildings against tunnel-induced damage: A case study in China.   a904-9110 v16  a1296-207401746nas a2200157   4500000000100000008004100001100001000042700001000052700002600062700001000088700001200098700001000110245013700120490000700257520132400264       2015                            d1 aY. Lu1 aY. Li1 aMirosław Skibniewski1 aZ. Wu1 aR. Wang1 aY. Le00aInformation and communication technology applications in architecture, engineering, and construction organizations: a 15 year review0 v313 aInformation and communication technology (ICT) has had enormous effects on the development of architecture, engineering, and construction (AEC) organizations in past decades. The effects have resonated in various disciplines, such as organizational efficiency, communication approach, and employee behavior. However, a comprehensive and in-depth review of the ICT applied in the AEC organization is missing from the current literature. To fill this gap, this paper presents an in-depth review of mainstream studies of ICT-supported AEC organizations published in last 15years (1998-2012). A total of 145 articles from 12 construction and IT-related journals are identified and have been thoroughly reviewed. This review is divided into four parts: (1)synthesis and general trend of existing literature; (2)lessons learned from ICT practical implementation; (3)enabling technologies of ICT applications; and (4)ICT-induced organizational outcomes. Throughout this paper the authors summarize and categorize developments to date, discuss the advances and limitations of the use of ICT, and propose key areas for future research. This review can become a foundation for the classification and integration of the state of the art in ICT research on behalf of AEC organizations. (C) 2014 American Society of Civil Engineers.00393nas a2200169   4500000000100000008004100001260001200042100001000054700000900064700001200073700002600085700001200111245006900123300001000192490000700202022001400209       2015                            d  c05/20151 aXG Wu1 aQ Lu1 aL Zhang1 aMirosław Skibniewski1 aYH Wang00aProspective safety  performance evaluation on construction sites  a58-720 v78  a0001-457500381nas a2200157   4500000000100000008004100001100001300042700002600055700001000081700001200091700001200103245007600115300001100191490000700202022001400209       2014                            d1 aL. Zhang1 aMirosław Skibniewski1 aX. Wu1 aY. Chen1 aQ. Deng00aA probabilistic approach for safety risk analysis in metro construction  a8–170 v63  a0925-753500378nas a2200157   4500000000100000008004100001100001300042700001000055700002600065700001300091700001000104245007200114300001200186490000800198022001400206       2014                            d1 aL. Zhang1 aX. Wu1 aMirosław Skibniewski1 aJ. Zhong1 aY. Lu00aBayesian-network-based safety risk analysis in construction project  a29–390 v131  a0951-832000438nas a2200157   4500000000100000008004100001100001000042700001000052700002600062700001000088700001200098700001000110245013900120490000700259022001400266       2014                            d1 aY. Lu1 aY. Li1 aMirosław Skibniewski1 aZ. Wu1 aR. Wang1 aY. Le00aInformation and communication technology applications in architecture, engineering, and construction organizations: A 15-years review.0 v31  a0742-597x00391nas a2200157   4500000000100000008004100001100001300042700001400055700002600069700001100095700001400106245008100120300001100201490000700212022001400219       2014                            d1 aS. Ghosh1 aB. Lauren1 aMirosław Skibniewski1 aN. Sam1 aK.J. Hoon00aOrganizational governance to integrate sustainability project: a case study.  a1–240 v20  a2029-491300402nas a2200157   4500000000100000008004100001100001200042700001300054700001000067700002600077700001500103245009400118300001100212490000700223022001400230       2014                            d1 aL. Ding1 aL. Zhang1 aX. Wu1 aMirosław Skibniewski1 aY. Qunzhou00aSafety management in tunnel construction: Case study of Wuhan metro construction in China  a8–150 v62  a0925-753502096nas a2200169   4500000000100000008004100001100001300042700001000055700001200065700002600077700001400103245011100117300001400228490000700242520166300249022001401912       2014                            d1 aL. Zhang1 aX. Wu1 aQ. Chen1 aMirosław Skibniewski1 aS.-C. Hsu00aTowards a safety management approach for adjacent buildings in tunneling environments: Case study in China  a222–2350 v753 aThis paper develops a systematic approach with detailed step-by-step procedures for safety management of existing buildings adjacent to tunneling excavation. The potential safety risk of a specific nearby building is assessed within four different risk levels, with the spatial neighbor relation (hazard parameter) and the building health condition (vulnerability component) taken into account. Compared with the traditional two-stage approach, a reasonable balance between the system safety and cost constrains is reached in the developed systematic approach, where the safety risk assessment is added in the first stage, and the assessed safety risk level acts as a decisive role in the depth of the subsequent two-stage numerical analyses. It is suggested that numerical simulation analyses should be employed in the situation where the existing building lies in a risk level of III (Medium risk) or IV (High risk). A case concerning the protection of a five-story framed building adjacent to a twin-tunnel in China is utilized to verify the applicability oh the proposed approach. The impact of both the tunnel excavation on the soil displacement and building foundation deformation is further analyzed in details. Results demonstrate the feasibility of the proposed approach, as well as its application potential. The proposed approach can be used by practitioners in the industry to provide guidelines on guaranteeing the system safety of adjacent buildings in tunneling environments. At the same time, the analysis cost can be greatly reduced, especially when a large number of existing buildings adjacent to tunneling excavation need to be protected.  a0360-132301309nas a2200205   4500000000100000008004100001100002600042700001700068700001300085700001500098700001400113700001400127700001500141700001400156245008000170300001200250490000600262520082100268022001401089       2014                            d1 aMirosław Skibniewski1 aH.-P. Tserng1 aS.-H. Ju1 aC.-W. Feng1 aC.-T. Lin1 aJ.-Y. Han1 aK.-W. Weng1 aS.-C. Hsu00aWeb-based real time bridge scour monitoring system for disaster management.  a17–250 v93 aNatural disasters such as typhoous, earthquakes, and especially floods, often cause severe damage in Taiwan. Although bridge engineering technology has matured, the lack of an integrated bridge management system under sever disasters remains a challenge for the government. This research aims to develop a web-based system that displays the real time bridge scour information through combining Global Positioning System an Wirelles Sensor Networks technologies for bridges. The system also provides early warming for bridge safety based on a developed genetic model for estimating scour depth a round the bridge piers. The bridge safety monitoring agency utilizes the system as a decision support tool make the maintenance plan for bridges under severe weather conditions to prevent the damages from bridge collapse.  a1822-427x00370nas a2200145   4500000000100000008004100001100001300042700001000055700001200065700002600077245008600103300001400189490000700203022001400210       2013                            d1 aL. Zhang1 aX. Wu1 aL. Ding1 aMirosław Skibniewski00aA novel model for risk assessment of adjacent buildings in tunneling environments  a185–1940 v65  a0360-132301593nas a2200169   4500000000100000008004100001260005600042100001300098700001000111700001200121700002600133700001300159700002600172245010500198300001400303520110600317       2013                            d  bSent Istvan University Ybl Miklos Faculty, Budapest1 aL. Zhang1 aX. Wu1 aL. Ding1 aMirosław Skibniewski1 aM. Hajdu1 aMirosław Skibniewski00aDecision support analysis for safety assurance in metro construction base on Fuzzy Bayesian Networks  a896–9093 aThis paper presents a novel and systemic decision support model based on Fuzzy Bayesian Networks (FBN) for safety assurance in metro construction. An expert confidence index is proposed for the fuzzification in probability assessment of basic risk factors, aiming to ensure the reliability of collected data during the expert investigation. A fuzzy-based decision approach, with the capacity of forward reasoning, sensitivity analysis and backward reasoning, is developed based on Bayesian inference. The safety assurance progress is extended to the entire life cycle of risk-prone events, including the pre-accident, during-construction continuous and post-accident control. A typical hazard concerning the tunnel leakage in the Wuhan Yangtze Metro Tunnel construction is presented in a case study. The results demonstrate the feasibility of the proposed method and its application potential. The proposed method can be used as a decision support tool to provide guidelines for safety assurance in metro construction, and thus increase the likelihood of a successful project in a complex environment.