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Blockchain has the potential to facilitate a paradigm shift in the construction industry toward effectiveness, transparency and collaboration. However, there is currently a paucity of empirical evidence from real-world construction projects. This study aims to systematically review blockchain adoption barriers, investigate critical ones and propose corresponding solutions.

An integrated method was adopted in this research based on the technology–organization–environment (TOE) theory and fuzzy decision-making trial and evaluation laboratory (DEMATEL) approach. Blockchain adoption barriers were first presented using the TOE framework. Then, key barriers were identified based on the importance and causality analysis in the fuzzy DEMATEL. Several suggestions were proposed to facilitate blockchain diffusion from the standpoints of the government, the industry and construction organizations.

The results highlighted seven key barriers. Specifically, the construction industry is more concerned with environmental barriers, such as policy uncertainties (E2) and technology maturity (E3), while most technical barriers are causal factors, such as “interoperability (T4)” and “smart contracts' security (T2)”.

This study contributes to a better understanding of the problem associated with blockchain implementation and provides policymakers with recommendations.

Identified TOE barriers lay the groundwork for theoretical observations to comprehend the blockchain adoption problem. This research also applied the fuzzy method to blockchain adoption barrier analysis, which can reduce the uncertainty and subjectivity in expert evaluations with a small sample.

The purpose of this paper is to clarify the effect of compressive stress on cavitation-erosion corrosion behavior of 304 stainless steel.

Compressive stresses of 60 MPa and 120 MPa were applied to 304 stainless steel through a self-designed loading device, and cavitation erosion-corrosion tests were performed using an ultrasonically vibratory apparatus. Scanning electron microscope and X-ray diffraction were used to analyze the microstructure evolution, and corrosion behavior was studied by electrochemical analysis.

The cavitation weight loss of 304 stainless steel decreased with the compressive stress. After cavitation corroded for 8 h, the weight loss for the specimen with 120 MPa compressive stress was 5.11 mg/cm², which was reduced by 56.7% from that of the specimen without loading stress (11.79 mg/cm²). The reason can be attributed to that compressive stress promoted the deformation-induced martensitic transformation during the cavitation process, which could not only provide a cushioning effect by absorbing cavitation impact energy but also improve the hardness of 304 stainless steel.

Compressive stress was found to restrain the cavitation damage on 304 stainless steel, and the corresponding mechanism was proposed.

The purpose of this paper is to improve the corrosion resistance of stainless-steel bipolar plate by magnetron sputtering.

TiC/amorphous carbon composite film was deposited by magnetron sputter at four different temperature of 25°C, 200°C, 300°C and 400°C. The morphology, composition and structure of the film were characterized by scanning electron microscopy, atomic force microscopy and X-ray photoelectron spectroscopy. And its corrosion behavior was analyzed through electrochemical impedance spectroscopy, potentiodynamic and potentiostatic polarization tests.

A compact TiC/amorphous carbon film was prepared by magnetron sputtering on 316L stainless steel, and the particles of the film were refined with the increase in sputtering temperature. High temperature promoted the formation of TiC and C–C sp² hybrid carbon, but excessively high temperature caused the oxidation of Ti and a significant decrease in sp² hybrid carbon. The corrosion resistance of the film increased with the temperature, and the corrosion current density polarization at 0.86 V and 1.8 V for TiC/a–C film prepared at 400 °C is only 1.2% and 43.2% of stainless steel, respectively.

The corrosion resistance of amorphous carbon films was improved by the doping of Ti carbide, and the appropriate sputtering temperature was obtained.

Nickel-aluminum bronze (NAB) has been widely used in ship propellers. It is always subjected to local micro-plastic deformation in service environments. This paper aims to study the influence of plastic deformation on the mechanical strength and corrosion resistance of NAB in 3.5 Wt.% NaCl solution.

Scanning electron microscope and X-ray diffraction were used to analyze the microstructure of NAB alloy with different plastic deformations. Mechanical properties of the sample were measured by tensile experiment, and corrosion behavior was studied by electrochemical measurements and the long-term immersion corrosion test.

Results showed that the plastic deformation caused lattice distortion but did not change the microstructure of NAB alloy. Microhardness and yield strength of NAB were significantly improved with the increase of deformation. The lattice distortion accelerated the formation of corrosion product film, which made the deformed alloy show a more positive open-circuit potential and an increased Rp. However, during the long-term immersion corrosion, the corrosion resistance of NAB alloys deteriorated with the increase of plastic deformation. This is because larger plastic deformation brought about higher internal stress in corrosion product film, which resulted in the premature peeling of the film and the loss of its protective effect on the alloy substrate.

Tensile plastic deformations were found to cause a decline in the corrosion resistance of NAB. And the mechanism was clarified from the evolution of corrosion products during the corrosion process.

Blockchain technology (BCT) is considered a promising tool to improve the productivity of construction project management. Existing research has studied its potential costs and benefits for the construction industry. However, the potential costs and benefits of BCT failed to be compared as actual costs and benefits of specific applications for stakeholders. To fill this gap, this study seeks to analyze the cost-effectiveness of BCT-based applications in construction project management.

This study is conducted with a customized systematic literature review based on transaction cost theory to enable qualitative comparison. With a deliberately designed structure confining extraneous variables, the costs and benefits of BCT-based applications are identified and compared. The inherent dependent relations of processes and the evolution relations of functions are identified. The cost-effectiveness of blockchain adoption is then analyzed.

Seven functions and six challenges are identified within five processes. The result suggests all identified functions are cost-effective except for manual instruction (coding smart contracts manually). The smart contracts require explicit definition and logic to be effective. However, the construction projects essentially require the institution to be flexible due to unpredictability. The adoption of smart contracts and corresponding additional requirements can increase the transaction cost of bounded rationality.

As manual instruction is fundamental to realize other functions, and its advanced substitute relies on its broad adoption, its cost-effectiveness must be improved for applications to be acceptable to stakeholders. The establishment of a universal smart contract model and a universal, legitimate and efficient database structure are recommended to minimize the cost and maximize the effect of applications.

This study contributes to the knowledge by providing a comprehensive analysis of BCT adoption’s cost-effectiveness in construction project management. The adopted review structure can be extended to analyze the qualitative benefits and challenges of management automation in the early stages.

The information used for supervision by regulatory departments in public-private partnership (PPP) projects is primarily transmitted and processed by the PPP implementation department, which negatively impacts the information quality, leading to information asymmetry and undermining the overall effectiveness of supervision. This study aims to explore how to use blockchain to anchor the information used for supervision in PPP projects to the original information, to strengthen the oversight.

This paper adopts the principles of design science research (DSR) to design a conceptual framework that systematically organizes information along the information dissemination chain, ensuring the reliable anchoring of original information. Two-stage interviews involving experts from academia and industry are conducted, serving as formative and summative evaluations to guide the design.

The framework establishes a weak-centralized information organizing mode, including the design of governance community and on-chain and off-chain governance mechanisms. Feedback from experts is collected via interviews and the designed framework is thought to improve information used for supervision. Constructive suggestions are also collected and analyzed for further development.

This paper provides a novel example exploring the inspirations blockchain can bring to project governance, like exercising caution regarding the disorderly expansion of public sector authority in addressing information disadvantages and how to leverage blockchain to achieve this. Technical details conveyed by the framework deepen understanding of how blockchain benefits and the challenges faced in successful implementation for practitioners and policymakers. The targeted evaluation serves as rigorous validation, guiding experts to provide reliable feedback and richer insights by offering them a more cognitively convenient scenario.

Connected and autonomous mobility may be an imminent game-changing reality, still in its embryonic form, that is set to disrupt a century-long ‘driver-centric’ status quo and recalibrate transport in unprecedented and possibly entirely unexpected ways. Autonomous vehicles (AVs) may have among others, a major impact on sustainability which in an era where concerns about the urgency and magnitude of climate change threats are voiced more and louder than ever before, needs to be a positive one for helping societies to enjoy liveable futures. This might not be an easy task to accomplish, however. This chapter, using a thematically organised narrative review approach, tries to give a well-rounded answer on whether driverless technology can yield sustainability benefits (or not) by looking at all three spheres of sustainability referring to environmental, economic and social implications. Agendas like motor traffic, air pollution, energy consumption, employment dynamics, inclusion, cybersecurity and privacy are all explored, and a conclusion is derived highlighting the need to package automation with connectivity, alternative fuelling and multimodality and building it around public transport (and to a lesser extent sharing service) provision. The road to make driverless transport genuinely sustainable is ‘bumpy’ and ‘uphill’ and requires the development of an appetite not for technology excellence per se, but rather for travel behaviour change. Achieving this needs serious strategic and coordinated multi-stakeholder efforts in terms of pro-active policy reform, user (and transport provider) education and training initiatives, infrastructure investment, business plan development, and living lab experimentation.

This study examines the role of industry competition, market capitalization, and debt levels in the relationship between profitability and firm value (FV). The sample included companies listed on the Indonesia Stock Exchange (IDX) in the manufacturing sector in 2017–2019. This study provides empirical evidence that the high level of industrial competition (IC), low level of market capitalization (market value of equity, MVE), and high levels of debt (debt-to-assets ratio, DAR) weaken the effect of profitability as measured by return on assets (ROA) on FV as measured by Tobin’s Q. Profitability is not even related to FV for firms facing high industry competition. In addition, profitability only has a marginal positive relationship with FV for firms with relatively small market capitalizations. These findings suggest that the relationship between profitability and FV is not monotonous but is influenced by the level of industry competence, market capitalization, and debt.

Learning from safety accidents and sharing safety knowledge has become an important part of accident prevention and improving construction safety management. Considering the difficulty of reusing unstructured data in the construction industry, the knowledge in it is difficult to be used directly for safety analysis. The purpose of this paper is to explore the construction of construction safety knowledge representation model and safety accident graph through deep learning methods, extract construction safety knowledge entities through BERT-BiLSTM-CRF model and propose a data management model of data–knowledge–services.

The ontology model of knowledge representation of construction safety accidents is constructed by integrating entity relation and logic evolution. Then, the database of safety incidents in the architecture, engineering and construction (AEC) industry is established based on the collected construction safety incident reports and related dispute cases. The construction method of construction safety accident knowledge graph is studied, and the precision of BERT-BiLSTM-CRF algorithm in information extraction is verified through comparative experiments. Finally, a safety accident report is used as an example to construct the AEC domain construction safety accident knowledge graph (AEC-KG), which provides visual query knowledge service and verifies the operability of knowledge management.

The experimental results show that the combined BERT-BiLSTM-CRF algorithm has a precision of 84.52%, a recall of 92.35%, and an F1 value of 88.26% in named entity recognition from the AEC domain database. The construction safety knowledge representation model and safety incident knowledge graph realize knowledge visualization.

The proposed framework provides a new knowledge management approach to improve the safety management of practitioners and also enriches the application scenarios of knowledge graph. On the one hand, it innovatively proposes a data application method and knowledge management method of safety accident report that integrates entity relationship and matter evolution logic. On the other hand, the legal adjudication dimension is innovatively added to the knowledge graph in the construction safety field as the basis for the postincident disposal measures of safety accidents, which provides reference for safety managers' decision-making in all aspects.

Evaluating project success within the construction industry presents challenges due to the unique characteristics of the sector, the complexity of projects, and the involvement of diverse stakeholders. Conducting a bibliometric analysis, this paper aims to unravel the major research themes and methodologies utilised by researchers in studying the critical success criteria for construction projects, as well as extracting these success criteria.

The researchers systematically searched and screened 95 papers from Scopus and Web of Science (WoS) databases. This study conducted research focus parallelship network (RFPN) analysis and keywords co-occurrence network (KCON) analysis using BibExcel and Gephi to cluster the papers, illuminate the relationships among keywords within each cluster, and identify the primary research directions.

Using the RFPN analysis, this study classified the papers into three distinct clusters: infrastructure and public projects success, risk and knowledge management, and contractors and procurement management. Statistical techniques such as structural equation modelling (SEM) and multi-criteria decision-making methods such as analytic hierarchy process (AHP) have been used to analyse project success in the construction industry.

Considering the intensified demand for streamlined digital interactions and the increasing emphasis on sustainability and safety performance, construction companies are recommended to allocate greater investments toward the automation and digitisation of their products and processes. Prioritising modular construction and embracing transformative technologies alongside data science is crucial for enabling well-informed decision-making, and enhancing project success.

This study contributes to the existing body of knowledge by conducting a quantitative and systematic evaluation of the literature on project success criteria in the construction industry and uncovering key research areas. It addresses the pressing need to understand the complexities of construction projects amidst evolving industry dynamics and emerging disruptions. Moreover, by highlighting the implications of digital innovations and modular construction, this study urges deeper exploration into their impact on project performance and stakeholder satisfaction. This research sets a comprehensive framework for investigating the interplay between project complexity, technological advancements, and sustainable practices in the construction sector, paving the way for strategic advancements in the field.