A Bibliometric Analysis of Neuroscience Tools Use in Construction Health and Safety Management.

Despite longstanding traditional construction health and safety management (CHSM) methods, the construction industry continues to face persistent challenges in this field. Neuroscience tools offer potential advantages in addressing these safety and health issues by providing objective data to indicate subjects' cognition and behavior. The application of neuroscience tools in the CHSM has received much attention in the construction research community, but comprehensive statistics on the application of neuroscience tools to CHSM is lacking to provide insights for the later scholars. Therefore, this study applied bibliometric analysis to examine the current state of neuroscience tools use in CHSM. The development phases; the most productive journals, regions, and institutions; influential scholars and articles; author collaboration; reference co-citation; and application domains of the tools were identified. It revealed four application domains: monitoring the safety status of construction workers, enhancing the construction hazard recognition ability, reducing work-related musculoskeletal disorders of construction workers, and integrating neuroscience tools with artificial intelligence techniques in enhancing occupational safety and health, where magnetoencephalography (EMG), electroencephalography (EEG), eye-tracking, and electrodermal activity (EDA) are four predominant neuroscience tools. It also shows a growing interest in integrating the neuroscience tools with artificial intelligence techniques to address the safety and health issues. In addition, future studies are suggested to facilitate the applications of these tools in construction workplaces by narrowing the gaps between experimental settings and real situations, enhancing the quality of data collected by neuroscience tools and performance of data processing algorithms, and overcoming user resistance in tools adoption.

Stakeholders' purchase intention of products with recycled content: a combination of SEM and BPNN approach.

The rapid urban renewal progress has generated a large amount of construction and demolition (C&D) waste in China. According to the concept of circular economy (CE), producing products with recycled content (PwRC) is an effective solution to achieve sustainable C&D waste management. However, the low market acceptance of PwRC affects stakeholders' purchase intention, which hinders the development of the PwRC industry. In order to clarify the stakeholders' purchase intention and investigate the influencing mechanism of stakeholders' purchase intention, a novel method which combines structural equation modeling (SEM) with a back-propagation neural network (BPNN) is proposed. The method makes full use of the causal analysis ability of SEM and the nonlinear characteristics of BPNN to simulate and to verify the path of product cues, perceived value, and behavioral intention of stakeholders. The results reveal that the brand and materials of PwRC can affect stakeholders' perceived value, and in turn, affect their purchase intention. Focus on the brand and materials of PwRC will help recycled product manufacturers and governments to promote stakeholders' purchase intention and the development of the C&D waste recycled products market.

Evaluating the effects of policies on building construction waste management: a hybrid dynamic approach.

The construction industry, as a vital pillar of a country's economy, generates a significant amount of construction waste, which places a tremendous burden on the environment and society. Although previous studies have explored the impact of policies on construction waste management, there is a lack of a simulation model that can be easily used, taking into account the dynamic nature, generality, and practicability of the model. To fill this gap, a hybrid dynamics model of construction waste management system is developed using agent-based modeling, system dynamics, perceived value, and experienced weighted attraction. Based on relevant data from the construction waste industry in Shenzhen, China, the effect of five policies on contractor strategy selection and overall evolution is tested. The results indicate that industry rectification policy and combination policy can effectively promote the resource treatment of construction waste and reduce illegal dumping, pollution to the environment of waste and treatment process, and waste treatment cost. The findings of this research will help not only researchers better analyze the effect of construction waste policies but also policymakers and practitioners in proposing effective construction waste management policies.

Determinants of contractor's construction and demolition waste recycling intention in China: Integrating theory of planned behavior and norm activation model.

The abundant generation of construction and demolition waste (CDW) poses a threat to the sustainable development in China and recycling plays a vital role in complying with circular economy zero-waste goal. In this study, we first investigate the determinants of contractor's intention to recycle CDW by establishing an integrative model of the theory of planned behavior (TPB) and the norm activation model (NAM) with rational and moral considerations. Based on the questionnaire data of 210 valid responses, structural equation modeling is employed to test the proposed hypotheses and analyze the integrative structural model. The results show that the integrative model with adequate reliability and validity fits the empirical data well and the explanation power is superior to that of initial TPB model and NAM model, demonstrating the appropriateness of merging TPB and NAM in the area of CDW recycling research. Moreover, it is found that personal norms are the most critical determinant enhancing the CDW recycling intention, followed by perceived behavioral control. Although subjective norms fail to directly affect the CDW recycling intention, they can significantly strengthen personal norms and perceived behavioral control. These findings provide useful insights for government to develop effective management strategies to motivate CDW recycling intention of contractors.

The Influence of Media in Purchasing Decisions for Recycled Construction and Demolition Waste Products: An Functional Near Infrared Spectroscopy Study.

The increasing hazards caused by construction and demolition (C&D) waste is an inevitable problem in the development of the construction industry. Many countries have successively launched many policies to encourage and guide the recycling of C&D waste, which has greatly improved the recycling rate of C&D waste. However, most of these policies only regulate contractors but do not promote C&D waste recycling products enough. It has led to an increase in the production of C&D waste recycling products while the acceptance in the market is generally low. Consumers believe that products made with "garbage" may have problems such as quality defects. In order to explore a measure that can mitigate this problem, this study uses functional near infrared spectroscopy (fNIRS) to investigate whether the influence of media can increase consumers' willingness to purchase products for recycling construction and demolition waste, and thus increase consumers' choice to purchase products for C&D recycling waste. This experiment consists of two phases. First, a pre-test experiment to obtain pre-intervention brain images characterizing consumers' original attitudes toward C&D recycling waste products through a functional near-infrared imaging brain technique and a questionnaire. Second, The post-test builds on the pre-test to investigate the effectiveness of the intervention. The activation mechanism of the consumer purchase decision is further investigated by fNIRS data. The behavioral results showed that the choice of recycled C&D waste products was significantly higher after the intervention. The fNIRS results further revealed the significantly higher activation of the dorsolateral prefrontal cortex (dlPFC), orbitofrontal cortex (OFC), and medial prefrontal cortex (mPFC) after the intervention. These findings suggest that consumers' purchase willingness is significantly improved after intervention, and their purchase behavior changed substantially. This study also demonstrates the great potential of fNIRS for interdisciplinary research in engineering management and neuroscience.

Cost-benefit analysis of demolition waste management via agent-based modelling: A case study in Shenzhen.

The economic instrument is an effective approach to encourage demolition contractors to conduct low-impact waste management. It is essential for project managers and decision-makers to better understand the cost-benefit of demolition waste (DW) management, to promote development of an effective waste management plan. This study explores the interactive dynamics and adaptive nature between stakeholders, where the cost-benefit of DW management is analysed through the agent-based modelling approach. Shenzhen, a leading city in China in the management of DW, was selected as the study area. It was revealed that if the traditional demolition method is adopted as the primary choice, the net benefit of demolition of buildings in the study case will reach -131.4 billion yuan, i.e. the cost will surpass the revenue. If the selective demolition method is widely used by demolition contractors, simulation results indicate that the net benefit will reach 33.3 billion yuan, an increase of 125.34%, compared to the situation in which the traditional demolition method is widely implemented. Based on the simulation, an optimal management framework for DW management stakeholders was constructed. The research results can provide a decision-making basis for the government and relevant departments to formulate DW management measures.

A text mining-based thematic model for analyzing construction and demolition waste management studies.

Over the years, numerous studies have been conducted to investigate construction and demolition waste (CDW) management problems. However, the massive amount of literature brings challenges to scholars because it is difficult and time-consuming to manually identify research emphasis from the literature. Therefore, a method that can informationize literature collection and automatically detect insights from the identified literature is worthy of exploration. This paper attempts to present a comprehensive thematic model by combining Latent Dirichlet Allocation, word2vec, and community detection algorithm on python to detect insights from CDW management literature. Based on the database of Web of Science, 641 articles published between 2000 and 2019 are retrieved and used as the sample for analysis. The comprehensive thematic results reveal a four-domain knowledge map in CDW management research, which covers (1) introducing current situation of CDW management, (2) quantifying CDW generation, (3) assessing CDW and by-products, and (4) facilitating waste diversion. Future research directions in CDW management research have also been discussed. The results prove that the comprehensive thematic model is useful in mining insights from CDW management literature.

Information system with multiple data layer approach to select the C&D waste landfilling infrastructure.

Landfilling is a critical method in managing massive generated C&D waste, and the appropriate selection of C&D waste landfill sites can reduce the impacts of landfilling. This study proposes an approach combined F-AHP and GIS to select suitable C&D waste landfills. The proposed model considers multiple factors from environmental, social and economic aspects. A case study of Shenzhen, China, is undertaken to showcase the implementation of the proposed model. It is found that about 25 million m2 of land has the potential to be used for C&D waste landfills in the study case, but the actual usable land is limited as some lands are too small for a landfill site. The study contributes to the waste management discipline as it provides an improved framework for selecting a landfill site. Besides, the landfill site selection procedure and results have practical implications for urban planning.

A Feasibility Study on HPMC-Improved Sulphoaluminate Cement for 3D Printing.

A novel 3D printing material based on hydroxypropyl methylcellulose (HPMC)-improved sulphoaluminate cement (SAC) for rapid 3D construction printing application is reported. The hydration heat, setting time, fluidity of paste and mortar, shape retainability, and compressive strength of extruded SAC mortar were investigated. HPMC dosage, water-to-cement (W/C) ratio, and sand-to-cement (S/C) ratio were studied as the experimental parameters. Hydration heat results reveal HPMC could delay the hydration of SAC. The initial and final setting time measured using Vicat needle would be shortened in the case of W/C ratio of 0.3 and 0.35 with HPMC dosage from 0.5% to 1.5%, W/C ratio of 0.40 with HPMC dosage of 0.5%, 0.75%, and 1.5%, and W/C ratio of 0.45 with HPMC dosage of 0.45, or be extended in the case of W/C ratio of 0.4 with HPMC dosage of 1.0% and W/C ratio of 0.45 with HPMC dosage from 0.75% to 1.5%. Fluidity measurement shows HPMC significantly improves the shape retainability. Furthermore, the addition of HPMC remarkably increased the compressive strength of extruded mortar. The results showed that HPMC could be used to prepare 3D printing SAC having satisfactory shape retainability, setting time and compressive strength.

Combining AHP-Entropy Approach with GIS for Construction Waste Landfill Selection-A Case Study of Shenzhen.

With the recent fast economy development and rapid urbanization, the huge generation of construction waste has become a threat to sustainable development in China. Though efforts have been made to promote reuse and recycling of construction waste, landfilling of waste remains the most commonly adapted approach for construction waste disposal. As the space for landfills is limited and because of the negative issues in terms of environmental and social aspects that may be caused, the appropriate site selection of landfills is crucial. With this background, this paper aims to establish a framework for facilitating landfill selection for construction waste. To begin with, a total of sixteen factors that may influence landfill site selection were identified from a literature review. Then, based on the combined analytic hierarchy process (AHP) and entropy method, the weights and the final comprehensive scores of the identified factors were calculated. According to the derived results, potential sites for landfills were divided into three levels, namely the most appropriate (0.38%), appropriate (17.58%), and inappropriate (82.04%). The proposed decision-making methods in this paper can provide a valuable reference for the selection of construction waste landfill sites.

A system dynamics-based environmental performance simulation of construction waste reduction management in China.

A huge amount of construction waste has been generated from increasingly higher number of construction activities than in the past, which has significant negative impacts on the environment if they are not properly managed. Therefore, effective construction waste management is of primary importance for future sustainable development. Based on the theory of planned behaviors, this paper develops a system dynamic model of construction waste reduction management at the construction phase to simulate the environmental benefits of construction waste reduction management. The application of the proposed model is shown using a case study in Shenzhen, China. Vensim is applied to simulate and analyze the model. The simulation results indicate that source reduction is an effective waste reduction measure which can reduce 27.05% of the total waste generation. Sorting behaviors are a premise for improving the construction waste recycling and reuse rates which account for 15.49% of the total waste generated. The environmental benefits of source reduction outweigh those of sorting behaviors. Therefore, to achieve better environmental performance of the construction waste reduction management, attention should be paid to source reduction such as low waste technologies and on-site management performance. In the meantime, sorting behaviors encouragement such as improving stakeholders' waste awareness, refining regulations, strengthening government supervision and controlling illegal dumping should be emphasized.

An empirical investigation of construction and demolition waste generation rates in Shenzhen city, South China.

The construction and demolition waste generation rates (C&D WGRs) is an important factor in decision-making and management of material waste in any construction site. The present study investigated WGRs by conducting on-site waste sorting and weighing in four ongoing construction projects in Shenzhen city of South China. The results revealed that WGRs ranged from 3.275 to 8.791 kg/m(2) and miscellaneous waste, timber for formwork and falsework, and concrete were the three largest components amongst the generated waste. Based on the WGRs derived from the research, the paper also discussed the main causes of waste in the construction industry and attempted to connect waste generation with specific construction practices. It was recommended that measures mainly including performing waste sorting at source, employing skilful workers, uploading and storing materials properly, promoting waste management capacity, replacing current timber formwork with metal formwork and launching an incentive reward program to encourage waste reduction could be potential solutions to reducing current WGRs in Shenzhen. Although these results were derived from a relatively small sample and so cannot justifiably be generalized, they do however add to the body of knowledge that is currently available for understanding the status of the art of C&D waste management in China.