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The purpose of this paper is to synthesize and characterize a series of two-component aromatic waterborne polyurethane (2K-WPU) which is composed of non-ionic and anionic polyisocyanate aqueous dispersion and polyurethane polyol aqueous dispersion.

The polyisocyanate aqueous dispersion was synthesized through non-ionic and anionic hydrophilic modification procedures. The values of the hydrogen bonding index (HBI) and molecule structures of WPU were obtained by Fourier transform infrared (FTIR). The thermal, mechanical and water resistance properties of 2K-WPU films were investigated.

The appearance of non-ionic polyisocyanate aqueous dispersion and anionic polyisocyanate aqueous dispersion was colorless translucent pan blue and yellow opaque emulsions, respectively. FTIR not only showed that 2K-WPU was obtained from the polymerization of polyisocyanate component and polyhydroxy component by polymerization but also showed that the content of hydrogen bondings of anionic 2K-WPU (WPU 2) was higher than non-ionic 2K-WPU (WPU 1). The glass-transition temperature (Tg), storage modulus and water resistance of WPU 2 were higher than WPU1, whereas the thermal stability of WPU1 was better than WPU 2.

The investigation established a method to prepare a series of 2K-WPU which was composed of non-ionic or anionic polyisocyanate aqueous dispersion and polyurethane polyol aqueous dispersion. The prepared 2K-WPU film could be applied as substrate resin material in the field of waterborne coating.

The paper established a method to synthesize a series of 2K-WPU. The effect of HBI value and the molecule structure of soft segment on the thermal stability, mechanical and water resistance properties of 2K-WPU films were studied.

This research aims to develop an approach to assess the reliability of integrated construction supply chains via an integrated model of building information modelling (BIM) and the lean supply chain (LSC). It reflects the synergistic workflow between BIM and LSC as a novel approach to improve the reliability of construction projects.

This research evaluates the reliability of the BIM-LSC approach through a combination of entropy theory, set pair analysis (SPA), and Markov chains (EESM). An exploratory survey was conducted to collect data from 316 industry professionals experienced in BIM and LSC. Subsequently, multiple cycles of calculations were performed with indirect data inputs. Finally, a reliability evaluation index is established for the BIM-LSC approach and potential applications are identified.

The results show that the EESM model of BIM-LSC developed in this study can handle not only supply chain reliability evaluation at a given state but also the prediction of reliability in supply chain state transitions due to changing project conditions. This is particularly relevant to the current environment of the construction project, which is characterised by an increasing level of complexity in terms of labour, technology, and resource interactions.

Future research could consider the accuracy and validity of the proposed model in real-life scenarios with by considering both quantitative and qualitative data across the entire lifecycle of projects.

The research offers a model to evaluate the reliability of the BIM-LSC approach. The accuracy of BIM supply chain reliability analysis and prediction in an uncertain environment is improved.

The BIM-LSC reliability evaluation and prediction presented in this study provides a theoretical foundation to enhance understanding of the BIM-LSC in the construction project context.

Previous studies have highlighted that communication barrier was one of the major safety problems faced by ethnic minority (EM) workers. This study aims to model the predominant safety communication networks of EM crews and explore the relationships among safety communication networks, individual attributes, safety climate, near misses and injuries of EM crews.

Case studies were conducted with EM crews in the Hong Kong construction industry. Demographic attribute, network, safety climate and accidents data were collected through questionnaires and analyzed by a combination of social network analysis (SNA), cross-case comparison and nonparametric tests.

The results revealed that language proficiency, network density and level of reciprocity were contributing factors of distinguishing high and low safety performing EM crews. EM management received more safety information from EM workers than local management. The centrality of EM workers was significantly related to their age, the perceived priority of safety and language ability.

The research findings regarding the impact of safety communication network characteristics on the safety performance of EM crews provides insights to employers on how to cultivate effective safety communication patterns within EM crews that can lead to better safety performance. The connections between personal attributes and their positions in safety communication networks could help the employers identify the EM workers who are positioned on edges of networks and need more attention.

This study contributes to knowledge by enriching the limited research on analyzing safety communication of small construction crews using SNA and expanding the research object to EM construction crews in the literature, who are more vulnerable to construction accidents. This research also extends the existing body of knowledge from studies mainly carried out in Western culture to Eastern culture. Although safety communication has been regarded as important for EM workers, there is a lack of quantitative analysis on this at a crew level. The present study provides empirical research to reveal authentic safety communication networks and their connections with safety performance and personal attributes.

In China, external supervision on construction safety mainly comes from the government and supervision engineers (SEs). However, the construction safety supervisory mechanism (CSSM) contains some dilemmas affecting the improvement of safety performance, such as the declining impact of SEs, the increasing rent-seeking behaviors of contractor and excessive government interference. This study aims to depict and analyze the CSSM in China from an evolutionary game view. The objectives are to understand the supervision strategy and evolutionary behaviors of different stakeholders, propose suggestions for improving safety performance and help the key safety supervision stakeholders, especially the government, formulate a suitable safety supervision strategy.

This research uses tripartite dynamic evolutionary game theory to study the CSSM in China and solve the stable equilibrium solution using system dynamics.

This study has revealed the game relationship of construction safety supervision mechanisms in China and solved the stable equilibrium solution. The results prove that a supervision engineer (SE) plays a crucial role in the CSSM, and “supervision engineer useless” is an unreasonable assertion. For government supervision agency (GSA), excessive inspection and free-market regulation are neither wise strategies. GSA can reduce the inspection frequency when general contractors (GCs) input high safety investments and SEs implement responsible supervision. But keeping proper government supervision to avoid GC's unlawful behaviors and SE's rent-seeking is indispensable. In addition, excessive governmental supervision will weaken SE's role, so the government should transfer some supervision powers to SE.

This study focuses on the dynamic evolution process between GSA, GC and SE. This method is different from most research that neglected the dynamic characteristic of system and game solution stability. The research methods not only contribute to construction safety supervision policy-making in China but also help to improve supervision efficiency in other countries and other fields.

Prefabricated housing has become a boom industry across the world; however, the uptake of offsite construction (OSC) approaches in Australian low-rise buildings is rather low compared with high-rise buildings in other countries. This study aims to investigate and analyse the adoption of different levels of OSC approaches and the selection of different procurement options in Australian low-rise residential buildings.

The research objectives were pursued through a mixed research method. An empirical questionnaire survey was carried out with 35 professionals in the Australian building and construction industry. Semi-structured interviews were conducted with 20 interviewees and analysed using thematic analysis method in NVivo software.

The research results found that the most suitable OSC level for Australian low-rise buildings is components-based prefabrication and identified the barriers to OSC uptake for each OSC level. The study also showed that the best option of procuring prefabricated products is from Australian manufacturers, followed by Australian suppliers/dealers and overseas manufacturers. Panelised prefabrication and components-based prefabrication are ranked as the most suitable OSC approaches for Australian manufacturers. Modular prefabrication is regarded as the most suitable for overseas manufacturer, while components-based prefabrication is the most suitable for Australian suppliers/dealers.

The selection of various OSC approaches and different procurement options in the low-rise residential buildings are scarcely explored topic, and thus, this study provides knowledge of interest for both researchers and practitioners.

The purpose of this paper is to explain what information is contained in mutual funds' trading behaviors and to try to further assess the impact on the stock market.

The objective is achieved by an empirical examination using the high‐frequency intraday data. The main methods used for the research are the autoregressive conditional duration model and the UHF‐GARCH model.

This paper gives an empirical study of mutual funds' behavior on two aspects. The first aspect is the direct impact on micro variables. The results show that mutual funds changing their positions will have different influences to the spread, adding position broadens the spread, while decreasing position makes the spread narrow; behaviors of funds change the clustering characteristic of the duration. The second aspect is the impact on the relationships among micro variables. The results indicate that trading started by liquidity buyers will make volatility larger.

This paper supposes funds as informed traders and individual investors as liquidity traders in China's stock market. If it is not true, some interpretations of empirical results would be wrong. The authors' results may help researchers to understand the information content of funds' trading behaviors in the microstructure aspect.

The paper is an original work, which will be interesting to scholars in market microstructure and to practitioners in the Chinese stock market. The main contributions of the paper are: the use of high‐frequency data to study funds' behaviors and combine the trading duration and investors' trading behavior to analyze the information content of trading behaviors; second, the use of 14 stock samples in the Shanghai Stock Exchange to do the empirical study, which ensures the reliability of the results.

The need to stay competitive amidst ever-changing business environment has shifted competitive strategies from firms to supply chains. Managers are now basing competitive strategies on supply chains acknowledging that supply chains present competitive advantages among other resources. The purpose of the study is to explore the predictive relevance of supply chain collaboration and the extent to which it influences supply chain visibility, stakeholder trust, environmental and financial performances. This study focused on manufacturing firms due to their supplier relationships, consumption of resources, energy and emissions of greenhouse gasses.

The study adopted a survey research design, a quantitative approach and partial least square structural equation modelling technique in making data analysis and interpretations due to its suitability for predictive research models as is the case in this study.

The study hypothesized that supply chain collaboration positively and significantly interacts with supply chain visibility, stakeholder trust, environmental and financial performances. The study results confirmed supply chain collaboration as a significant, positive and a robust influence on supply chain visibility, stakeholder trust, environmental and financial performances thereby projecting win-win scenarios for firms that engage in collaborative supply chain practices.

The study is among the few to indicate findings in relation to the scope of supply chain collaboration's potency in influencing performance from the perspective of manufacturing firms operational in an emerging economy. Thus, this study contributes to understanding the wider scope of supply chain collaboration, its interactions with other firm variables and how it informs decisions of managers, scholars and supply chain partners.

Sustainable management has become a strategic and popular requirement for stakeholders, as the ability to create competitive advantages in the current dynamic business environment and the pressures of digital transformation need to be increased attention in achieving the highest level of sustainable performance. The main objective of this paper is to explore the direct effects of the industrial Internet of things and supply chain visibility on sustainable performance (economic performance, environmental performance and social performance), in addition to evaluating the indirect effects that supply chain visibility plays in these relationships.

To achieve the purposes and objectives of this work, a conceptual model was developed by referring to the current works in the literature, and the theoretical model was developed, and then data were collected through the questionnaire and by the snowball sampling method, as 380 questionnaires were used. In the data analysis, the multivariate analysis technique was used via Covariance-based Structural Equation Modeling (CB-SEM), as hypothesized relationships were evaluated through confirmatory factor analysis (CFA), and then the hypotheses were tested through a structural model.

The results reached the acceptance of all hypotheses, and this means that all hypothesized relationships were positive, as the impact of the industrial Internet of things was positive on each of the supply chain visibility and economic performance, environmental performance and social performance, and also the supply chain visibility mediated the relationship between each of the industrial Internet of things and economic performance, environmental performance and social performance.

The current paper reported a range of theoretical and practical contributions, as this study is the first to examine these hypothesized relationships together in this way and thus helped this study to develop new perceptions about Industry 4.0 technologies and their potential impacts on supply chain and sustainable performance. Also, this study had a variety of management recommendations that allow managers of pharmaceutical manufacturing companies operating in Jordan to develop their technological capabilities and use them to enhance sustainable performance.

The purpose of this study is to use empirical data to examine the hierarchical impact of the Internet of things capability on supply chain integration (SCI), supply chain capability (SCC) and firm performance (FP) in the UK retail industry.

A deductive approach was employed to carry out this research. Structural equation modelling (SEM) was performed using the partial least square method (SmartPLS 3.3.3) to test theoretical predictions which underlie the relationships among Internet of things capability (IoTC), SCI, SCC and FP. Data are collected using an online survey completed by senior executives of 66 large, medium and small firms within the UK retail industry.

The empirical results of this research reveal that IoTC has a significant positive effect on the UK retail industry FP through the mediating role of SCI and SCC.

The research results from this study provide useful management insights for firms within the retail industry into the development of effective strategies for integrating their supply chain alongside the adoption of IoTC into SCI, consequently leading to improvements in FP.

Although previous studies have explored the impact of IoT on FP through the sequential mediating role of SCI and SCC, few have explored the impact of the IoT capability (IoTC) on FP through sequential mediators, i.e. SCI and SCC. This study examines the relationship between IoTC, SCI, SCC and FP in the UK retail industry supply chain to address this knowledge gap. Moreover, this study examines the effects of IoTC on FP by applying partial least square (PLS)-SEM techniques. Testing the sequential mediating role of SCI and SCI is undertaken, and the relationships among IoT-enabled SCI and SCC is analysed to improve FP. The robustness check's result through PLSpredict analysis also confirms the power of the model proposed in this study.

This paper aims to investigate the characteristics of house price dynamics for a sample of 16 emerging economies from Asia and Central and Eastern Europe over the period of 1995-2011.

Linking housing valuations to a set of conventional fundamental determinants – relative to both the supply and the demand side of the market, institutional factors and other asset prices – and modelling short-term price dynamics – which reflect gradual adjustment to underlying fundamentals –conclusions about the existence and the basic nature of house price overvaluation (undervaluation) are drawn.

Overall, it was found that actual house prices in the sample of emerging economies are not overly disconnected from fundamentals. Rather, they tend to reflect a somewhat slow adjustment to shocks to the latter. Moreover, the evidence that housing valuations may be driven by overly optimistic (or pessimistic) expectations is, in general, weak.

Residential property prices used in the empirical analysis have many limitations: while some series are derived using a hedonic pricing method, others are based on floor area prices collected by national authorities; while some countries publish house prices in national currency per-square metre (or per apartment or per dwelling), others calculate an index number scaled to some base year; while some countries publish statistics for the whole national territory, others produce data only for the capital city or for the largest cities in the country; data from national sources refer to different types of residential property; finally, available time series are relatively short, which may adversely affect the robustness of estimation results.

The decomposition suggested in the paper has important implications: it would be paramount, in fact, for policymakers to implement market-specific diagnoses, and to find the right policy instruments that can ideally distinguish between the two underlying components driving house price short-run dynamics.

There is a very small body of empirical literature on housing market developments in emerging economies, especially if focussed on the comparisons between the actual dynamics of housing valuations and the equilibrium ones.