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Abstract Improvement of building energy performance is crucial in achieving energy conservation goals. Previous studies have indicated that effective collaboration among stakeholders can help to address the building energy performance gap. However, only a few studies have examined the effects of underlying collaboration between designers and contractors. To fill this research gap, this study proposes an evolutionary game model to investigate the underlying logic of the collaboration by analyzing the dynamic behaviors of designers and contractors. First, the main possible drivers and barriers of the collaboration between designers and contractors were identified through a literature review and an expert interview. Second, a Nash equilibrium model was utilized to analyze the decision of designers and contractors under different scenarios. The results show that the best means to promote the collaboration is "reducing collaboration costs", followed by "increasing the collaboration benefits" and "decreasing the loss caused by a lack of collaboration". Based on the parameter discussion of the evolutionary game model, five solutions were proposed for the effective collaboration between designers and contractors. This study helps to clarify the dynamic collaboration decision process of designers and contractors, who are considered players with bounded rationality. The proposed evolutionary game model provides a theoretical basis for quantitative research on the collaboration between designers and contractors. This study could help researchers to consider the dynamics of collaboration among stakeholders in building projects, and it could also help practitioners to select proper strategies for improved collaboration. Graphical abstract Image 10481961 [ABSTRACT FROM AUTHOR]

The construction industry in Hong Kong has been exposed to serious housing production issues such as insufficient manpower, safety, environmental concerns and inefficient housing supply. Prefabrication housing production has shown as efficient construction model which enables to overcome these issues and it is applied in construction industry in Hong Kong. In this paper, hybrid modeling techniques that combine system dynamics and discrete event simulation are used to analyze the interrelationships of schedule risks within the six-day cycle assembly of prefabrication housing production. Moreover, a hybrid dynamic model is developed to simulate and evaluate the impact of schedule risks on the schedule performance of the six-day cycle assembly of PHP via the Anylogic software package. The resulting model is validated by data which is collected from a PHP project in Hong Kong. Based on the simulation results, the first most influential level contains five schedule risks, namely, inefficient verification of precast components because of ambiguous labels, misplacement on the storage site because of carelessness, owner crane breakdown and maintenance, slow quality inspection procedures, and inefficient design data transition that cause average schedule delays of more than 300 min. The second most influential level includes delay of the delivery of precast element to site, design information gap between designer and manufacturer, installation error of precast elements, and logistics information inconsistency because of human errors, with average schedule delays less than 300 min and greater than 200 min. Design change, low information interoperability between different enterprise resource planning systems, and inefficiency of design approval belong to the third level that imposes the least influence on the schedule delay of the assembly. This research contributes to the current knowledge of the management of prefabrication construction by developing an effective model that offers an in-depth understanding of how schedule performance of PHP is dynamically influenced by interrelationships of various risk variables. Also, it provides an experimental platform for simulating and analyzing schedule risks that significantly affect the schedule performance of the six-day cycle assembly of prefabrication housing production. Such critical schedule risks could be identified and managed prior to the implement of prefabrication housing production projects. Compared with traditional techniques, the hybrid dynamic model simultaneously considers macro and micro levels, thereby enabling project managers to gain a deeper insight into schedule management and acquire a multidimensional understanding of schedule delay. [ABSTRACT FROM AUTHOR]

The building energy performance gap is a critical obstacle to emissions reduction and energy conservation. Previous research mainly focused on identifying the factors contributing to the building energy performance gap (BEPG). Such studies have tended toward an inward-looking perspective that treats impact factors in isolation from one another. In reality, most factors are interrelated and associated with energy-related stakeholders. To address this research gap, this research developed a social network analysis model to investigate the underlying network of stakeholder-related influencing factors. According to nodal degree, status centrality, betweenness centrality, and brokerage roles, 21 factors and 14 links that substantially influence other factors directly or indirectly are identified. Six challenges, including "Challenges to knowledge and experience," "Challenges in determining who is responsible for BEPG among stakeholders," "Cost challenges," "Poor quality challenges," "Challenges to building operation management," and "Information integrity challenges," are further identified. Moreover, six strategies that are useful in controlling and eliminating influencing factors and interactions are proposed. The results show that, after the proposed strategies were conducted, the density and cohesion of the network are reduced by 48.28% and 11.62%, respectively, and the top ten betweenness centrality values for the nodes and links are reduced by at least 30%. This research is expected to aid not only researchers in better understanding the intricate interrelationships among the factors influencing BEPG but also practitioners in effectively controlling the influencing factors of BEPG. [Display omitted] • Influencing factors are situated closely in a dense network. • Factors related to designers and contractors considerably affect the network. • Communication helps to bridge the gap between diverse stakeholder groups. • Poor communication substantially affects adjacent factors. [ABSTRACT FROM AUTHOR]

Diesel vehicles for road freight are primary contributors to PM 2.5 and NO X emissions in numerous cities. Shenzhen, which is a megacity in China, has made efforts to promote the transition to green transport by implementing license plate restrictions. Nevertheless, it is still unclear whether the restrictions have greatly improved urban air quality. An effective framework for accurately estimating and visualising the effect of restriction policy on a large scale is still lacking. Therefore, this study aims to develop a novel method to visualise and evaluate the effect of license plate restriction policy by bridging diesel truck's license plate recognition data to emission inventories. The results reveal that the impact of the peak restriction on air quality was limited if it only affected nonlocal diesel vehicles. While the promotion of eco-friendly vehicles could reduce PM 2.5 and NO X emissions. The findings could provide references for other cities or countries to estimate air pollution from diesel vehicles and recognise high emission zones at a large scale and thus create effective policies and initiatives. • The environmental effect of license plate restriction on nonlocal diesel vehicles is limited. • Urban unrestricted roads in city centres have low emissions reduction potential. • The highest emissions factor was generally located at intersections and connectors. • The replacement of 30% local LDTs and buses with eco-friendly trucks can reduce 12.4% of PM 2.5 [ABSTRACT FROM AUTHOR]

Energy-related stakeholders play a critical role in energy-saving and emission reduction. However, most previous studies focused on only a few stakeholders (e.g., occupant, designer and owner). Therefore, there is a lack of systematic analysis of energy-related stakeholders. Improving building energy efficiency requires the collaboration of all stakeholders in the building lifecycle. This study applies a two-mode social network model to investigate the stakeholders' power over the impact issues of building energy efficiency. Results show that all issues can be addressed by at least two stakeholders, thereby indicating the potential of collaboration in building energy management. Designers, manufacturers, commissioning agents and researchers are the most influential stakeholders with the highest degree centrality, betweenness centrality and eigenvector centrality. Insufficient knowledge and experience, lack of information integrity and unclear responsibility are the most influential impact issues. With the density of interaction being 1.000, nine core stakeholders (i.e. owner, designer, contractor, subcontractor, supervisor, manufacturer, commissioning agent, energy manager and researcher) and four core issues (i.e. unclear responsibility, poor collaboration and communication, insufficient knowledge and experience, and lack of information integrity) have intensive relationships. The core stakeholders account for 75% of the total stakeholders, whereas the core issues account for 25% of the total issues. Moreover, five strategies that are useful in promoting collaboration are proposed and validated. After the proposed strategies are implemented, the density of the collaboration network increased from 1.242 to 2.652. This study is not only expected to help researchers in understanding the complex interrelationships between stakeholders and issues but also practitioners in promoting effective collaboration strategies. • Twelve energy-related stakeholder groups are identified. • Sixteen issues that contribute to building energy performance gap are identified. • All issues can be addressed by at least two stakeholder groups. • Seventy-five percent of stakeholders are identified in the core position. • Twenty-five percent of issues are identified in the core position. [ABSTRACT FROM AUTHOR]

Energy conservation in the building sector is a major target worldwide, and individual's energy conservation behavior is considered a critical means to meet energy conservation goals. Although individual's energy conservation behavior has been explored, its formation mechanism in the workplace remains unclear. This study aims to investigate the effect of the determinants of energy conservation behavior in the workplace based on the extended theory of planned behavior model. The novelty of this study is that it extends the theory of planned behavior with the consideration of actual behavior controls. This study is also one of the first studies to identify the effect of user experience on energy saving behavior. Questionnaire survey was used for data collection, and structural equation modeling was applied to develop the structural model. Results show that individual's comfort is the most critical impact factor, followed by user experience and supervision. Intention has a limited effect on energy saving behavior. Moreover, three strategies were proposed to promote energy conservation behavior in the workplace from the perspectives of design, supervision, and punishment. These findings will not only help researchers in conducting further in-depth research on the mechanism of individual's energy conservation behavior but also practitioners in proposing other effective strategies to promote energy conservation behavior. Image 1 • An extended theory of planned behavior model was presented. • The effect of actual behavior control was identified and discussed. • Occupant comfort and user experience were found to have great impact. • Three effective strategies were proposed to promote energy conservation behavior. [ABSTRACT FROM AUTHOR]

The gap between the designed and measured building energy consumption is one of the biggest obstacles to the realization of energy conservation goal. The factor analysis method has been typically used in previous studies to explore the individual factors affecting building energy performance gap, while few studies examined the complex interrelationships among the influencing factors. In this research, the interpretive structural modelling approach was developed and applied to identify the key factors and explore the interrelationships among the factors affecting building energy performance gap. This paper first identified 47 factors by reviewing 276 relevant articles. Sixteen representative factors were further identified by interviewing 12 interviewees with 7–25 years' practical experience on building energy management. Second, a six-level hierarchical structure was developed based on interpretive structural modelling to illustrate the intricate interrelationships among the representative factors. Third, "Matrice d'Impacts croises-multipication applique a classement" was applied to demonstrate the driving force and dependence power of the representative factors. Four clusters of factors were identified, namely dependent factors, driving factors, autonomous factors and linkage factors. Fifth and finally, 10 strategies were proposed to address these factors and their interrelationships. The findings of this research will help not only researchers in understanding the factors and their hierarchical structures affecting BEPG but also policymakers and practitioners in understanding the priority of allocating limited resources to address these factors and issues. • Sixteen representative factors affecting building energy performance are identified. • Hierarchical structure of the representative factors is developed. • Ten strategies are proposed to improve building energy performance. • Interpretive Structural Modelling method is developed and applied. [ABSTRACT FROM AUTHOR]

Occupant characteristics are critical factors that have a significant impact on electricity consumption in residential buildings, which have attracted increasing attention in the research field of building energy. This study analyses the influencing of occupant characteristic-related factors on electricity consumption in residential buildings with the consideration of different targets of electricity consumption, particularly by developing a statistical model based on a large data set published by the US Department of Energy. Results show that ECRB can be substantially affected by occupant characteristic-related factors, including 'age of householders', 'household size', 'income', 'education level', 'type of occupancy' and 'length of residency'. They could explain 10.70% of the variance in electricity consumption. In which, type of occupancy' has the largest impact, followed by 'education level', 'length of residency', 'household size' and 'income'. It is also found that there are differences between some occupant characteristics corresponding to different occupant behaviors. Additionally, this study conducted an in-depth analysis of the relationship between occupant behaviour (including the use of energy star appliances, frequency appliances used, energy audit and insulation adding) and occupant characteristic-related factors. The analysis method serves as an effective tool for quantitatively evaluating the effect of various occupant characteristics in occupant behaviour modelling and building energy simulation, offering valuable references for practitioners, such that the appropriate strategies for electricity consumption saving can be selected in advanced. • Critical factors influencing electricity consumption in the point of occupant characteristic view. • Analyse the influencing mechanism of occupant characteristics on electricity consumption. • An effective tool for quantitatively evaluating the effect of various occupant characteristics. [ABSTRACT FROM AUTHOR]

Construction is a major contributor to pollution in the natural environment. Among all construction pollutants, construction dust is the most significant pollutant that endangers human health. To expand the limited scope of studies on construction dust exposure, this study investigates current dust control practices in the construction industry in Hong Kong through dust monitoring data compilation. The database constructed and compiled by this study is larger than any other previous dust-related datasets in the construction industry in Hong Kong. A total of 837 samples are collected from 33 construction sites and 16 contractors, among which 783 valid samples are analyzed. Descriptive statistics are reported in terms of "construction process", "trade", "tools", "data source type", and "dust control measure". Overall geometric mean for personal exposures are 0.314 (geometric standard deviations: 3.929) mg/m3 for respirable dust and 0.003 (geometric standard deviations: 5.105) mg/m3 for quartz concentration. It is found that the top three dust respirable exposures are from cement mixing, concrete breaking, and manual demolition, whereas grinding and rock breaking are recorded the two highest processes in terms of quartz exposure. Analytical results indicate that respiratory protection commonly used on construction sites is often inadequate for exposures encountered. Data variability within task and tool is large, with high exposures reported for a broad spectrum of tools. This study attains a large dataset to represent as many dust production construction activities as possible, determining the most influential factors for predicting dust exposure and evaluating the effectiveness of current dust control practices. This knowledge should, in turn, lead to enhanced practices of dust control in Hong Kong and highlight areas that need improvements. Image 1 [ABSTRACT FROM AUTHOR]

Every country is dealing with its own housing problems; however, none compares with Hong Kong where housing has always been a major concern as a result of low supply over the past decades. Against the constraints in delivering sufficient houses, prefabrication as a sustainable solution for housing has been increasingly advocated for its potential merits of better quality, construction safety and cleaner built environment. However, schedule delay caused by various risks affected the prefabrication housing production (PHP) in Hong Kong. This problem can be further worsened when the manufacturing sector of PHP has entirely moved to offshore areas in the Pearl River Delta region. This study applies system dynamics to recognize and investigate the potential effect of various risks on the scheduling of prefabrication housing construction projects through the employment of Vensim software package. The simulation results show that schedule risks, namely low information interoperability between different enterprise resource planning systems (LIIBDERPS), logistics information inconsistency due to human errors probability (LIIHEP), Delay of delivery of precast element to site (DDPES), and Design information gap between designer and manufacturer (DIGDM) significantly contribute to the schedule delay in PHP. However, schedule is more sensitive toward LIIBDERPS than for the other three risks, indicating that LIIBDERPS should be monitored and given priority. The system dynamic model serves as an effective tool for quantitatively evaluating the effect of various risks on the schedule of PHP, offering valuable references for managers though comparing simulation results under different risk scenarios, so that potential risks that might lead to schedule delay could be identified and handled in advance. [ABSTRACT FROM AUTHOR]

Metro, as a convenient transportation, has many potential environmental risks during operation that pose a great threat to users, resulting in metro microenvironmental health vulnerability (MMHV). While prior research has focused on metro construction and safety management, some investigations have also addressed isolated metro microenvironment factors, such as air quality and noise, ignoring the underlying causes of health risks. Therefore, this research aims to reveal driving factors contributing to MMHV and assess the risk of MMHV from the coupling perspective. 14 Driving factors related to personnel, facility, environment, and management were firstly identified, along with their coupling relationships. Then, a risk coupling simulation model of the identified driving factors has been devised, which integrates a cloud theory-based coupling degree model framework and system dynamics principles to represent the interconnected risks posed by these factors. Finally, the constructed model is applied practically to discern the developmental trajectory of coupled risks emanating from the driving factors influencing MMHV. And the key factors at different periods were determined by adjusting coupling coefficients, so as to propose targeted strategies. Findings in this research offer valuable guidance for the implementation of diversified and precisely tailored measures to address MMHV at various stages of metro operation. This, in turn, contributes to the mitigation of health risks and ensures the sustained and healthy operation and management of metro. • 14 driving factors that trigger metro microenvironmental health vulnerability was identified. • Coupling relationship and coupling degree between MMHV driving factors was revealed. • A risk coupling simulation model to predict MMHV risk level and identify key factors was constructed. [ABSTRACT FROM AUTHOR]

Medium and low-temperature solar thermal power generation, integrating parabolic trough collectors with transcritical carbon dioxide (CO 2)-based mixture power cycles, is explored for enhanced solar energy utilization and improved efficiency. This study assesses the feasibility of parabolic trough concentrated solar power plants utilizing transcritical CO 2 -based mixtures, considering energy output, efficiency, economics, and environmental (4E) aspects. Seven candidate organic working fluids (R32, R134a, R152a, R1234yf, R161, R290, and R1270) are evaluated within a two-layer decision-making framework based on multi-objective optimization. Results indicate a significant performance improvement with an increased mass fraction of the organic working fluid. Particularly, systems employing CO 2 /R32 or CO 2 /R161 demonstrate superior overall performance compared to those with other CO 2 -based mixtures. Under the base case (at a hot tank temperature of 350 °C), the CO 2 /R32 (0.3/0.7 wt%) system achieves the maximum energy output (355.22 kW), while the CO 2 /R161 (0.3/0.7 wt%) system attains the highest efficiency with the lowest levelized cost of electricity and CO 2 emissions (9.78%, 0.576 $/kW·h, and 0.0328 kg/kW·h, respectively). Exergy analysis emphasizes the predominant role of the solar collector in exergy destruction (approximately 70%), with the CO 2 /R161 (0.3/0.7 wt%) system yielding the highest exergy efficiency (14.96%). Across a hot tank temperature range of 250–350 °C and an organic fluid mass fraction of 0.3–0.7, the working fluids are generally ranked as CO 2 /R161, CO 2 /R32, CO 2 /R152a, CO 2 /R1270, CO 2 /R134a, CO 2 /R290, and CO 2 /R1234yf in terms of the 4E aspects via a multi-objective optimization decision-making framework. • Multi-objective optimization results are determined using the TOPSIS method. • CO 2 -based mixtures are selected based on the 4 E aspects. • Strategies for fluid selection are provided for the hot tank temperatures and mixture compositions. • Exergy analysis quantitatively reveals the exergy destruction distribution of system components. [ABSTRACT FROM AUTHOR]

The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) was recently proposed by the Chinese government for socioeconomic–political–environmental development. As one of the most important parts for the development of the GBA, the transportation sector has become a nonnegligible consumer of energy and source of emission. Therefore, vehicle energy consumption and related emissions in the GBA must be evaluated. However, an effective framework for accurately estimating the real-time transportation performance, vehicle energy consumption and emission in large urban areas is still lacking. This study aims to develop a novel method for examining the regional integration and the spatial connection that affect vehicle emission via crowdsourced traffic data and an emission model. The novelty of this study is that it explores the acquisition of large-scale and real-time data as well as the calculation of corresponding energy consumption and environmental impact. Based on the analysis of transportation in GBA, it is found that the vehicle energy consumption and emission on the expressway are nearly half as that on the other urban roads. Moreover, a significant difference exists in vehicle energy consumption and emission between passenger cars and medium-duty trucks. Regarding transportation performance, vehicle energy consumption and emissions, they are closely related to departure time. It is also found that most of the adjacent cities tend to have high vehicle energy consumption and emission. The contribution of the Hong Kong–Zhuhai–Macao Bridge to transportation from Hong Kong, Macao and Zhuhai is different. Hong Kong benefits most from the bridge in terms of traffic energy efficiency. This study would be valuable to both researchers and practitioners. It helps researchers apply a large dataset in replicating real-world travel, energy consumption and emission pattern at a large scale. Policymakers and practitioners would benefit from developing effective strategies for the sustainable development of the GBA. • The vehicle energy consumption and emission on expressway are nearly half as that on the other urban roads. • The change rate of the NOx emission for medium-duty truck has an opposite trend with that for passenger car. • Vehicle energy consumption and emissions are closely related to departure time. • Most of the adjacent cities tend to have high vehicle energy consumption and emission. • Hong Kong benefits most from the Hong Kong–Zhuhai–Macao Bridge regarding traffic energy efficiency. [ABSTRACT FROM AUTHOR]

Abstract Construction waste minimization in design stage can reduce construction waste from sources. Design unit is regarded as a key stakeholder in this stage and plays a critical role in reducing construction waste. However, the limited studies focused on factors affecting their willingness towards construction waste. To fill this research gap, this study explored the critical factors which affect design units' willingness towards construction waste minimization using exploratory sequential mixed method. Literature bibliometric and semi-structured interviews were initially conducted to identify influencing factors of the willingness of design units towards construction waste minimization. Questionnaire survey was used for data collection and Structural equation modeling was then used for analyzing factorial interactions. It is indicated that social and market environment exerts the greatest positive effects on design units' willingness towards construction waste minimization, followed by government supervision and minimization attitude of designers, while effect of project constraints seems minimal. Furthermore, enterprise internal culture indirectly affects design units' willingness towards construction waste minimization by influencing minimization attitude of designers. Moreover, strategies and suggestions were proposed from perspectives of society, government, design units, and clients, respectively. Findings of this empirical study provide theoretical reference for improving relevant standards and regulations regarding construction waste minimization design with establishing incentive mechanisms. Graphical abstract Standardized estimation of the final model and key path of affecting factors. Image 1 Highlights • Factors of design units' construction waste minimization willingness were examined. • Social and market environment was revealed as the most important critical factor. • Enterprise internal culture exerted no significant direct effect. • Strategies and suggestions were proposed from views of different stakeholders. [ABSTRACT FROM AUTHOR]

Abstract Effective energy saving and environmental protection are the global topics. Organic Rankine cycle (ORC) that efficiently converts the waste heat into electricity has drawn widespread attention. The sustainability assessment of ORC can explicitly reveal its contribution to mitigating the ecosystem degradation. Meanwhile, the ecological cumulative exergy consumption (ECEC) analysis is generally used to evaluate the sustainability of industrial activities. Therefore, we established the ORC-ECEC model based on the ecological life cycle assessment involving three fundamental aspects, the resource consumption, economic capital and the environmental impact. Particle swarm optimization algorithm was adopted to optimize the system parameters. The working fluid, R134a, is used in ORC to illustrate the features of proposed framework and conduct the comparison with coal-fired power generation system. Further, systems using working fluids of different hydrogen fluoride olefins (HFOs) are selected to investigate the effect of working fluid on ORC sustainability. The results showed that the economic capital exhibited the largest ECEC during the life-time of ORC, followed by environmental impact and resource consumption. The ECEC of system using R134a was about 1.89E+10 sej/kWh, which was much smaller than that of coal-fired power plant, 1.41E+12 sej/kWh. In addition, the ECEC analysis of systems using different HFOs indicated that ORC using R1336mzz as working fluid was significantly superior compared to systems using other working fluids from the point of view of the sustainable development. Highlights • Ecological cumulative exergy consumption method was applied to evaluate ORC. • Particle swarm optimization algorithm was adopted to calculate parameters of ORC. • Effect of resource capital and environmental impact for ORC were carried out. • The ECEC comparison of different HFOs for ORC was discussed. [ABSTRACT FROM AUTHOR]

Design, manufacturing, storage, transportation, and on-site assembly are fundamental processes in prefabricated housing production (PHP) in Hong Kong. However, these processes are fragmented and entail various risks that adversely affect the schedule performance of PHP, thereby causing frequent delay problems in PHP projects and hindering the government from satisfying the high housing demands. Accordingly, many researchers have examined these schedule risks to resolve these delay problems. However, none of these studies developed an effective tool for managing schedule risks of PHP by envisaging the key characteristics of schedule risks and PHP. Most of previous research regarding to the management of prefabrication construction tends to consider risks from static and isolated perspectives, despite that these risks are coherently interrelated with each other and their influence varies throughout the whole PHP process. To fill the research gaps, a hybrid dynamic model is developed in this research to evaluate and simulate the impact of identified schedule risks on the schedule performance of PHP in view of underlying interrelationships and interactions, employing the hybrid system dynamics (SD) and discrete event simulation (DES) method. The resulting hybrid model is validated through a serial of model structure tests and model behavior tests, with the use of data collected from a PHP project in Hong Kong. This study offers an in-depth understanding of how schedule performance of PHP are dynamically influenced by interrelationships and interactions underlying various schedule risk variables. The developed model not only has the benefits of ease of modifying model structure to reflect real schedule situation of PHP project, performing various risk analyses and communicating with simulation results, but also is of value of providing an experiment platform for identifying and determining managerial and technical solutions proposed to minimize and mitigate the influence of corresponding schedule risks prior to implementation. [ABSTRACT FROM AUTHOR]

Various schedule risks beset prefabrication housing production (PHP) in Hong Kong throughout the prefabrication supply chain, from design, manufacturing, logistics, to on-site assembly. Previous research on the risks in prefabrication construction projects has mainly focused on the construction stage and has been confined to issues of completeness and accuracy without consideration of stakeholder-related risks and their cause-and-effect relationships. However, in reality, the supply chain is inseparable as precast components should be manufactured and transported to sites to fit in with the schedule of on-site assembly in seamless connection manner, and most risks are interrelated and associated with various stakeholders. This study applies social network analysis (SNA) to recognize and investigate the underlying network of stakeholder-associated risk factors in prefabrication housing construction projects. Critical risks and relationships that have important roles in structuring the entire network of PHP are identified and analyzed. BIM (Building Information Modeling)-centered strategies are proposed to facilitate stakeholder communication and mitigate critical schedule risks and interactions underlying the risk network. This study not only provides an effective method to analyze stakeholder-associated risk factors and to evaluate the effect of these risk factors from a network perspective, but also offers a new visual perspective in the promotion of the use of the Internet of things (IoT) and helps identify housing construction problems in Hong Kong. [ABSTRACT FROM AUTHOR]

Large-scale demolition waste was generated during urban renewal. How to accurately quantify the potential of recycling large amounts of demolition waste has been widely considered a prerequisite for effective waste management, as it contributes to numbers and scales of recycling enterprises being managed and planned in advance. However, there is limited research, if any, focusing on this niche area. This study aims to quantify the potential of recycling demolition waste amidst urban renewal by considering actual market situations and different waste types. Firstly, the whole recycling process of demolition waste was scrutinized by using the free-flow mapping technique. Models for quantifying recycling potential of non-inert and inert demolition waste were then established, respectively, based on economic value and the principle of mass conservation. Finally, a case study was conducted to verify the models by putting them into the context of Shenzhen, a young and vibrating city in China but subject to massive urban renewal pressure. Results show that the recycling process of demolition waste is mainly divided into offsite and onsite recycling, both including five stages, viz. , waste generation, on-site treatment, transportation, recycling, and product regeneration. In addition, different types of demolition waste have their respective recycling potential. The recycling potential of non-inert demolition waste is RMB 19,315.85 million yuan. In contrast, the recycling potential of inert demolition waste depends on types of recyclable products, with 18.41 million tons of recyclable bricks, 7.02 million tons of mortar, 28.36 million tons of aggregate, and 4.16 million tons of lightweight wallboard. Findings of this study improve the accuracy of the existing quantification methods. The research provides useful reference for the recycling industry to adjust production scale and arrange production sites to fully harness the waste recycling potential. • Recycling potential of different types of demolition waste is quantified. • Processes of offsite and onsite recycling are remapped based on free-flow mapping. • Quantitative models for non-inert and inert demolition waste are established. [ABSTRACT FROM AUTHOR]