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Contractor selection is critical in green buildings (GBs) since the preferred contractor has the responsibility to achieve construction sustainability as well as relationship sustainability. The developer satisfaction reflecting requirements can boost the cooperative relationship among stakeholders and act as an evaluation scale for the success of GB projects, which needs to be emphasized in the selection process but little involved in the existing research. This study explores improving GB contractor (GBC) selection by integrating developer satisfaction into selection procedures.

A systematic framework of GBC selection including twenty-five criteria from literature review and experts survey is firstly constructed. Both tactical and strategic criteria are further classified into Kano categories (must-be, one-dimensional, and attractive categories) using the fuzzy Kano model (FKM), and weighted by the developer satisfaction index. The model proposed by this study combining FKM and TOPSIS divides the selection process into the filtration phase and selection phase by Kano categories. The proposed model is finally verified through performance comparison among multiple methods in a case.

Selection criteria are measured linearly and nonlinearly, showing criteria having nonlinear satisfaction change accounts for two-thirds of all. Criteria at tactical level tend to be must-be or one-dimensional categories for the developer, and most strategic criteria are classed as the attractive category, indicating that adding strategic criteria is necessary for long-term cooperation. The proposed model, using developer satisfaction to improve the selection process, ensures the selected GBC to be the most satisfactory with requirements of the developer and makes the performance of GBCs easily distinguishable.

This study contributes to the existing body of knowledge for promoting relationship sustainability by supplementing an integrated model with emphasis on developer satisfaction in GBC selection, so as to establish a good initial foundation due to the match between performances of GBCs and needs of developers. It not only helps maximize developer satisfaction in GBC selection by applying satisfaction to pre-construction management, but also instructs GBCs to prioritize performance improvements. The framework is also conducive for developers to classify selection criteria and select other participants (like green suppliers) from the satisfaction perspective in GBs.

Big data challenges and opportunities on the Internet of Vehicles (IoV) have emerged as a transformative paradigm to change intelligent transportation systems. With the growth of data-driven applications and the advances in data analysis techniques, the potential for data-adaptive innovation in IoV applications becomes an outstanding development in future IoV. Therefore, this paper aims to focus on big data in IoV and to provide an analysis of the current state of research.

This review paper uses a systematic literature review methodology. It conducts a thorough search of academic databases to identify relevant scientific articles. By reviewing and analyzing the primary articles found in the big data in the IoV domain, 45 research articles from 2019 to 2023 were selected for detailed analysis.

This paper discovers the main applications, use cases and primary contexts considered for big data in IoV. Next, it documents challenges, opportunities, future research directions and open issues.

This paper is based on academic articles published from 2019 to 2023. Therefore, scientific outputs published before 2019 are omitted.

This paper provides a thorough analysis of big data in IoV and considers distinct research questions corresponding to big data challenges and opportunities in IoV. It also provides valuable insights for researchers and practitioners in evolving this field by examining the existing fields and future directions for big data in the IoV ecosystem.

The coordinated development of the urbanization and construction industry is crucial for the sustainable development of cities. However, the coupling relationship and coordination mechanism between them remain unclear. To bridge this gap, this study attempts to explore the level of coupling coordination between new urbanization and construction industry development and investigate the critical driving factors influencing their coupling coordination degree.

By referring to the existing literature, two index systems were established to evaluate the development level of the new urbanization and construction industry. The spatiotemporal characteristics of the coupled coordinated development of the new urbanization and construction industry in China from 2014 to 2020 were investigated using the coupling coordination model. The Markov chain and geographic detector were adopted to understand the transition probability and driving factors of the coupling coordination degree.

The results indicate that the coupling degree of China's new urbanization and construction industry is high, and the two systems exhibit obvious interaction phenomena. However, the construction industry in most provinces lags behind the new urbanization. A positive interactive relationship and coordination mechanism has not been established between the two systems. Furthermore, the  coupling contribution degree of the driving factors from high to low is as follows: market size > labor resource concentration > government investment ability > economic development level > industrial structure > production efficiency > technology level. Accordingly, a driving mechanism including market, policy, economic, and production technology drivers was developed.

This study contributes to the existing body of knowledge by providing a set of scientific analysis methods to address the deficiency of coordination mechanism research on new urbanization and the construction industry. The results also provide a theoretical basis for decision makers to develop differentiated sustainable development policies.

This study aims to identify and prioritize barriers to corporate social responsibility (CSR) in the construction sector.

A literature review was first conducted to identify barriers to CSR performance. After that, construction professionals were invited to validate the appropriateness of the obstacles. The discussion allowed the establishment of a list of barriers to CSR performance and their corresponding categories. Data collected from the survey were then analyzed to prioritize the importance of these barriers by the fuzzy DEMATEL-based ANP (DANP) technique.

The findings presented 16 barriers to CSR, which were categorized into four clusters. The fuzzy DANP analysis showed that strategic vision is the most crucial cluster, followed by the measurement system, stakeholder perspective and scarce resources. Among the sixteen barriers examined, lack of awareness, knowledge and information of CSR; low priority of CSR; lack of metrics to quantify CSR benefits; lack of guidelines and coherent strategies; and lack of CSR enforcement mechanism are the five most crucial barriers.

This study is one of the first that proposes a comprehensive model to prioritize barriers to CSR performance of contractors considering their interrelationships. It provides construction stakeholders with a framework for understanding the linkage between the barriers and CSR framework under the umbrella of stakeholder theory. Thus, the findings might assist construction practitioners and academics in fostering the success of CSR implementation.

While the COVID-19 pandemic has impacted the construction industry, it is still unclear from prior studies about adequately positioning the quality assurance (QA) for the post-pandemic era and future pandemics, especially cross-border construction logistics and supply chain (Cb-CLSC). Thus, this study aims to develop a managerial framework to position the QA of Cb-CLSC during pandemics and post-pandemics by taking lessons from how COVID-19 has impacted the existing QA systems and has been managed successfully.

This is achieved pragmatically through an embedded mixed-method design involving a literature review, survey and interview from experts within the Hong Kong SAR–Mainland China links, typically known as the world’s factory. The design is further integrated with the partial least squares structural equation modelling (PLS-SEM) approach.

The study revealed 10 critical managerial practices (MPs) to position the QA to be adequate for the post-pandemic and during future pandemics, with the top three including “strict observance of government regulations (MP1)”, “planning ahead the period of quality assurance with the quarantine days in host countries (MP6)” and “modification of contract to cater for uncertainties (MP4)”. This attained a relatively good percentage agreement of 53% between the industry and academia. However, the top four MPs regarded as very effective include “implementing digital collaborative inspections with subcontractors and trades (MP8)”, “implementing a digital centralized document and issue management system (MP7)”, “strict observance to government regulations, including vaccination of workers, social distancing, use of prescribed nose masks, etc. (MP1)” and “planning ahead the period of quality assurance with the quarantine days in host countries (MP6)”. Two underlying components of the MPs were revealed as policy-process (PP)-related practices and people-technology-process (PTP)-related practices, and these can be modelled into a managerial framework capable of effectively positioning the QA to be adequate during pandemics through to the post-pandemic era.

The findings of this study depicted significant theoretical and practical contributions to the proactive management of QA activities during pandemics through to the post-pandemic era. It could empower organisations to pay attention to smartly and innovatively balancing people, processes, pandemic policy and technology to inform decisions to effectively position the QA for the post-pandemic era and survive the risks of future pandemics.

The study contributes to the body of knowledge in that it develops a managerial framework to position the QA of Cb-CLSC during pandemics and post-pandemics by taking lessons from how COVID-19 has impacted the existing QA systems and has been managed successfully. It is original research with invaluable primary data in the form of surveys and interviews from experts within the Hong Kong SAR–Mainland China links, typically known as the world’s factory.

This paper aims to explore the impact of ebullient supervision on thriving at work, and relational social capital to stimulate employee creativity in the hospitality industry.

Using a purposive sampling approach, data were collected from 391 subordinates and their immediate supervisors in the hospitality industry through a structured questionnaire. To analyze the data, partial least structural equation modeling approach was considered.

Results show that ebullient supervision is supportive in generating personal resources of thriving at work and relational social capital, which later shape employee creativity.

The empirical findings of this study provide valuable insights for managers in the hospitality industry for human resource development strategy formulation to stimulate creativity in the hospitality industry.

The findings of this study suggest a novel antecedent of ebullient supervision for stimulating creativity in the hospitality industry. Hence, the paper has implications for researchers, practitioners and students.

Infrastructure financialization plays a critical role in infrastructure development and urban growth around the world. However, on the one hand, the existing research on the infrastructure financialization focuses on qualitative and lacks quantitative country-specific studies. On the other hand, the spatial heterogeneity and influencing factors of infrastructure financialization are ignored. This study takes China as a typical case to identify and analyze the spatial characteristics, development process and impact factors of infrastructure financialization.

To assess the development and characteristics of infrastructure financialization in China, this study constructs an evaluation index of infrastructure financialization based on the infrastructure financialization ratio (IFR). This study then analyzes the evolution process and spatial pattern of China's infrastructure financialization through the spatial analysis method. Furthermore, this study identifies and quantitatively analyzes the influencing factors of infrastructure financialization based on the spatial Dubin model. Finally, this study offers a policy suggestion as a governance response.

The results demonstrate that infrastructure financialization effectively promotes the development of infrastructure in China. Second, there are significant spatial differences in China’s infrastructure financialization. Third, many factors affect infrastructure financialization, with government participation having the greatest impact. In addition, over-financialization of infrastructure has the potential to lead to government debt risks, which is a critical challenge the Chinese Government must address. Finally, this study suggests that infrastructure financialization requires more detailed, tailored,and place-specific policy interventions by the government.

This study not only contributes to enriching the knowledge body of global financialization theory but also helps optimize infrastructure investment and financing policies in China and provides peer reference for other developing countries.

This research is aimed to mainly be applicable to expediting engineering projects, uses the method of inverse optimization and the double-layer nested genetic algorithm combined with nonlinear programming algorithm, study how to schedule the number of labor in each process at the minimum cost to achieve an extremely short construction period goal.

The method of inverse optimization is mainly used in this study. In the first phase, establish a positive optimization model, according to the existing labor constraints, aiming at the shortest construction period. In the second phase, under the condition that the expected shortest construction period is known, on the basis of the positive optimization model, the inverse optimization method is used to establish the inverse optimization model aiming at the minimum change of the number of workers, and finally the optimal labor allocation scheme that meets the conditions is obtained. Finally, use algorithm to solve and prove with a case.

The case study shows that this method can effectively achieve the extremely short duration goal of the engineering project at the minimum cost, and provide the basis for the decision-making of the engineering project.

The contribution of this paper to the existing knowledge is to carry out a preliminary study on the relatively blank field of the current engineering project with a very short construction period, and provide a path for the vast number of engineering projects with strict requirements on the construction period to achieve a very short construction period, and apply the inverse optimization method to the engineering field. Furthermore, a double-nested genetic algorithm and nonlinear programming algorithm are designed. It can effectively solve various optimization problems.

This review provides an overview of recent advances in electrochemical sensors for analyte detection in saliva, highlighting their potential applications in diagnostics and health care. The purpose of this paper is to summarize the current state of the field, identify challenges and limitations and discuss future prospects for the development of saliva-based electrochemical sensors.

The paper reviews relevant literature and research articles to examine the latest developments in electrochemical sensing technologies for saliva analysis. It explores the use of various electrode materials, including carbon nanomaterial, metal nanoparticles and conducting polymers, as well as the integration of microfluidics, lab-on-a-chip (LOC) devices and wearable/implantable technologies. The design and fabrication methodologies used in these sensors are discussed, along with sample preparation techniques and biorecognition elements for enhancing sensor performance.

Electrochemical sensors for salivary analyte detection have demonstrated excellent potential for noninvasive, rapid and cost-effective diagnostics. Recent advancements have resulted in improved sensor selectivity, stability, sensitivity and compatibility with complex saliva samples. Integration with microfluidics and LOC technologies has shown promise in enhancing sensor efficiency and accuracy. In addition, wearable and implantable sensors enable continuous, real-time monitoring of salivary analytes, opening new avenues for personalized health care and disease management.

This review presents an up-to-date overview of electrochemical sensors for analyte detection in saliva, offering insights into their design, fabrication and performance. It highlights the originality and value of integrating electrochemical sensing with microfluidics, wearable/implantable technologies and point-of-care testing platforms. The review also identifies challenges and limitations, such as interference from other saliva components and the need for improved stability and reproducibility. Future prospects include the development of novel microfluidic devices, advanced materials and user-friendly diagnostic devices to unlock the full potential of saliva-based electrochemical sensing in clinical practice.

The construction industry has been traditionally referred to as slow when it comes to technological transformation. This study aims to investigate and present a scorecard of the construction industry in the past decade, the paper adopted Bibliometrics. The study identified the various digital transformation (DT) aspects in the construction industry and future research directions are also identified.

To achieve the aim of this research, an inductive approach was adopted through a grounded theory strategy. Secondary data was retrieved from the Scopus database and analysed using Biblioshiny and VOSviewer. The data was retrieved through specific keywords related to the study focus.

The study also proposed a balanced flow model for DT discussion in the construction industry. DT in the construction industry disrupts every aspect of the industry, albeit at different rates due to the existing barriers; hence, the study identified areas that require further research. It, thus, provides a theoretical and practical basis for researchers and practitioners alike.

The study reviewed the DT research discuss in the construction industry. It is worthy of note that this is the first study that analyses the DT of the construction industry in the past decade.