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This study reveals the green building development path and analyzes the optimal government subsidy equilibrium through evolutionary game theory and numerical simulation. This was done to explore the feasible measures and optimal incentives to achieve higher levels of green building in China.

First, the practice of green building in China was analyzed, and the specific influencing factors and incentive measures for green building development were extracted. Second, China-specific evolutionary game models were constructed between developers and homebuyers under the market regulation and government incentive mechanism scenarios, and the evolutionary paths were analyzed. Finally, real-case numerical simulations were conducted, subsidy impacts were mainly analyzed and optimal subsidy equilibriums were solved.

(1) Simultaneously subsidizing developers and homebuyers proved to be the most effective measure to promote the sustainability of green buildings. (2) The sensitivity of developers and homebuyers to subsidies varied across scenarios, and the optimal subsidy level diminished marginally as building greenness and public awareness increased. (3) The optimal subsidy level for developers was intricately tied to the building greenness benchmark. A higher benchmark intensified the developer’s responsiveness to losses, at which point increasing subsidies were justified. Conversely, a reduction in subsidy might have been appropriate when the benchmark was set at a lower level.

The expeditious advancement of green buildings holds paramount importance for the high-quality development of the construction industry. Nevertheless, the pace of green building expansion in China has experienced a recent deceleration. Drawing insights from the practices of green building in China, the exploration of viable strategies and the determination of optimal government subsidies stand as imperative initiatives. These endeavors aim to propel the acceleration of green building proliferation and materialize high-quality development at the earliest juncture possible.

The model is grounded in China’s green building practices, which makes the conclusions drawn more specific. Furthermore, research results provide practical references for governments to formulate green building incentive policies.

The purpose of this paper is to address the knowledge gap on the use of benchmarking techniques as utilized by facilities management (FM) professionals for the purpose of identifying means to improve industry benchmarking practices and guide the direction of future FM benchmarking research.

Data were collected through surveying 585 FM practitioners representing various countries, organization sizes, types, industries. The data were summarized and analyzed through creating frequency tables, charts, and cross-tabulations. The survey results were compared to a previously published study on benchmarking use to identify the similarities and differences between benchmarking for FM functions vs core business functions.

The findings indicate that while FM-oriented benchmarking has been adopted at similar levels as other industries, FM-oriented benchmarking tends to be simplistic, lacks a strategic position in the company, often relies upon self-report survey data, is often performed by an individual with no formal benchmarking team and does not utilize process benchmarking or benchmarking networks. These findings emphasize the need for benchmarking education, advocacy for FM as a strategic business partner, the development of verified data sources and networks specifically for the unique greater facilities management field functions.

These findings provide needed data on the state of FM practitioner use of benchmarking specifically for FM functions in North America. The results can be used as an assessment for the industry, to improve practitioner use and knowledge, and to identify further avenues for academic study.

The value of this study lies in filling in identified knowledge gaps on how FM practitioners are using benchmarking in practice. These data are absent from the research literature and offer the potential to help bridge the academic-practitioner divide to ensure that future research will focus on addressing practitioner needs for the industry.

This paper bridges the gap between the theory and practice by developing a life cycle sustainability tracker (LCST). The study is seeking to proffer solutions to an observed shortcoming of conventional life cycle sustainability assessment (LCSA) communication platforms. Notably, the static nature of the information provided on such platforms has made it difficult for them to be used for real-time decision-making and predictions. The main aim of this paper is to develop a LCST that facilitates a dynamic visualisation of life cycle sustainability results and allows for an integrated benchmark across the dimensions of sustainability.

The study leverages the model development capabilities of the design science research strategy in accomplishing a dynamic and novel communication platform. A life cycle thinking methodology and appropriate multicriteria decision approach (MCDA) is applied to accomplish a comprehensive, streamlined and replicable approach in mapping and tracking the progress of sustainable development goals (SDGs) in the National Infrastructure Pipeline (NIP) projects in India.

It was found that: (1) The use of the LCST tracker provides a dynamic and holistic insight into the key LCSA indicators with clearly defined benchmarks to assess the impact on the SDG 11, (2) The NIP projects achieve an upward trend across all the regions, and the percentage of opportunities ranges from 11 to 24%, with the South experiencing the highest growth and the North having the minimal increase in percentage and (3) The assessment score (52–58%) provides performance metrics that align well with the LCST – which ranges between “Fair” and “Average” for all the regions in India.

The novelty of this research is that the LCST provides a transparent and harmonised approach to reporting on the LCSA results. The LCST utilises heat maps and radial mapping to achieve an intuitive display of large amounts of highly heterogeneous data, thus allowing the synthesis of large sets of information compactly and with coherence. Progress towards the SDGs change on a yearly basis; hence, a dynamic LCSA tool provides a timely and the valuable context to map and track performance across different regions and contexts.

Nations are opening their “digital borders” to allow the free movement of business, employment and skills. However, this process of digitalization is fraught with challenges. This study aims to identify these challenges to build a solution-oriented framework for smart nations.

This study conducted a systematic literature review, analyzing 69 peer-reviewed academic papers out of 5,958 identified papers.

The identified challenges for smart nation building were categorized as follows: people and society, technology and innovation, digital infrastructure, politics, governance, economics and business and sustainability. To overcome these challenges, this study highlights the need for a holistic national approach, which includes solutions such as improving education, technology-driven innovations, investments for building smart nation infrastructure, top political leadership involvement, national vision and action plan, national regulatory frameworks, business environment and job creation, stakeholder engagement, renewable energy use and technological integration – all of which are key for sustainable development.

This study provides directions for building a smart nation framework, but the literature review results are confined to articles, conference papers and book chapters. This study could be further enriched if the findings are cross-checked with experts. This limitation will be addressed in future research.

Given the dearth of literature on this nascent concept, the insights from this study can guide policymakers and industry leaders involved in smart nation building and benefit researchers engaged in theoretical development.

The purpose of this paper is to present the investigation on contemporary applications of game design in architectural visualization, urban environmental planning and the results to address the problems of traditional methods specifically in terms of interactivity and visualization. The authors present the prototype that incorporates information modeling and virtual reality (VR) into interactive architectural visualization.

The proposed system supports a virtual walkthrough process that allows users to navigate in an architectural space of their imagination and design. The immersion in the design of living space or environment has been made possible through the inclusion of VR through the use of WebVR technology to deploy the design to be experienced.

This study investigates and establishes a framework that explores the intricacies of 3 imensional (3D) Architectural Visualization in a real-time engine by designing a visual experience with a better level of user interaction and then deploying it through VR.

To the best of the authors’ knowledge, this is one of the few experimental frameworks which perfectly integrates VR for visualization in digital home design environments. The prospective applications of this framework are in several fields of construction innovation, architectural design, 3D modeling, virtual and augmented reality.

By introducing Stacking algorithm to solve the underfitting problem caused by insufficient data in traditional machine learning, this paper provides a new solution to the cold start problem of entrepreneurial borrowing risk control.

The authors introduce semi-supervised learning and integrated learning into the field of migration learning, and innovatively propose the Stacking model migration learning, which can independently train models on entrepreneurial borrowing credit data, and then use the migration strategy itself as the learning object, and use the Stacking algorithm to combine the prediction results of the source domain model and the target domain model.

The effectiveness of the two migration learning models is evaluated with real data from an entrepreneurial borrowing. The algorithmic performance of the Stacking-based model migration learning is further improved compared to the benchmark model without migration learning techniques, with the model area under curve value rising to 0.8. Comparing the two migration learning models reveals that the model-based migration learning approach performs better. The reason for this is that the sample-based migration learning approach only eliminates the noisy samples that are relatively less similar to the entrepreneurial borrowing data. However, the calculation of similarity and the weighing of similarity are subjective, and there is no unified judgment standard and operation method, so there is no guarantee that the retained traditional credit samples have the same sample distribution and feature structure as the entrepreneurial borrowing data.

From a practical standpoint, on the one hand, it provides a new solution to the cold start problem of entrepreneurial borrowing risk control. The small number of labeled high-quality samples cannot support the learning and deployment of big data risk control models, which is the cold start problem of the entrepreneurial borrowing risk control system. By extending the training sample set with auxiliary domain data through suitable migration learning methods, the prediction performance of the model can be improved to a certain extent and more generalized laws can be learned.

This paper introduces the thought method of migration learning to the entrepreneurial borrowing scenario, provides a new solution to the cold start problem of the entrepreneurial borrowing risk control system and verifies the feasibility and effectiveness of the migration learning method applied in the risk control field through empirical data.

As an emerging visualization technology, virtual reality (VR) falls into the dilemma of having great potential but a low adoption degree in the architectural, engineering and construction (AEC) industry. However, few studies paid attention to studying barriers affecting VR’s adoption and their inner mechanisms. This makes AEC users hard to catch the key points for VR’s implementations. This study aims to get a clear structure of these barriers and provide insights for the improvement.

First, 12 major VR-AEC adoption barriers were identified by a systematic literature review and expert interviews (EI). Second, EI and similarity aggregation method were conducted to achieve reliable barrier relationships. Third, interpretive structural modeling was used to establish a multi-level model for barriers. Finally, ten crucial barriers were targeted with a comprehensive strategy framework.

The findings help AEC stakeholders get a thorough understanding of the VR-AEC adoption barriers. Besides, the inner mechanism among barriers is revealed and analyzed, followed by a systematic strategy framework. It is anticipated that users could conduct more effective VR-AEC promotions in the future.

This paper is the first to propose a comprehensive literature review on the VR-AEC adoption barriers. In addition, this paper is novel in building a hierarchy model that explores barriers’ inner mechanism, where structural strategies are proposed.

The usefulness of technology for managing projects in the construction industry is indisputable. The potential utility of immersive technologies (ImTs), including virtual and augmented reality, has recently received significant attention. However, the construction industry, especially in developing countries, lags on the implementation of technology generally and ImTs specifically. Forecasting the potential successful ImTs acceptance at the individual level is essential to strategic planning. The study's objective was to develop and test a conceptual model of factors influencing ImTs acceptance at the individual level in the construction industry.

A survey of construction management-level professionals in South Africa was undertaken. The study extended two complementary models, the technology acceptance model (TAM) and the theory of planned behavior (TPB), to analyze behavior towards technology acceptance using structural equation modelling.

Results indicated that attitude significantly influenced the intention to use ImTs and perceived usefulness (PU) positively and significantly predicted the intention to use and usage attitude (UA). Further, the effects of perceived enjoyment (PEn) on UA, and social norms (SNs) and perceived behavioral control (PBC) on intention to use were positive and significant. Perceived ease of use (PEU) had negative and non-significant effects on intention to use and UA. By explaining 82% of the variance, the study established that the proposed model successfully evaluates how management-level professionals in the construction industry accept ImTs.

The study provides valuable insight into the acceptance of ImTs from the perspective of management-level stakeholders in the South African construction industry. It offers fundamental direction to create a general theory on integrating ImTs in construction.

This study systematically surveyed the intention to accept ImTs in the South African construction industry using an extension of the TAM and TPB models.

The purpose of this study is to assess the level of energy efficiency (EE) practices and worshippers’ comfort experience towards energy consumption of a selected energy retrofitted mosque. This study identifies whether the work was done on ad hoc or planned basis and to gauge the success level of the retrofit work.

Mixed method was used in this study. A selected mosques with a capacity of more than 1,000 worshippers under the Class A of classification places of assembly with operating hour ranging from 45 to 65 h and the penarafan hijau jabatan kerja raya (pHJKR) rating tool as a benchmarking for EE assessment is used. A total of 45 respondents were involved in this study to obtain their perception on comfort experience in mosque. Meanwhile, energy audit and walk-through surveys were conducted to obtain data on energy consumption. To identify whether the work was done on ad hoc or planned basis and to gauge the success level of the retrofit work, pHJKR rating tool and efficiency standard MS1525:2019 are used for benchmarking in keeping with sustainability guidelines.

The results of this study indicated that the EE score achieved by the mosque is good while there are still rooms for improvement to increase the higher score to the pHJKR’s EE benchmarking tool.

EE is one of the most important agenda under sustainable development initiatives. Part of the initial government strategy is to encourage the use public buildings in demonstrating initiatives for sustainable development to justify high capital resources investment. Mosque buildings have huge potential for this purpose because as religious public buildings for the majority Muslim community, their operations are fully funded from public funds. Selection of mosques is also driven by its unique intermittent energy consumption pattern, while early mosques adopted natural ventilation, modern mosques are often designed with mechanical ventilation (air conditioning).

An encouragement on government initiative towards sustainable development can be escalating by producing exemplary building for intermittent use pattern categories by mosque as a model.

Sustainable development especially in EE becomes normal practices and energy and impact towards environment possibly be saved.

Sustainable development especially in EE becomes normal practices and energy and impact towards environment possibly be saved. This research is based on supportive national agenda by assessing EE measure for development of energy management in intermittent use buildings (mosque).

Modular construction is an innovative method that enhances the performance of building construction projects. However, the performance of steel modular construction has not been systematically understood, and the existing measurement methods exhibit limitations in effectively addressing the features of steel modular building construction. Therefore, this study aims to develop a new performance measurement framework for systematically examining the performance of steel modular construction in building projects.

This study was conducted through a mixed-method research design that combines a comprehensive review of the state-of-the-art practices of construction performance measurement and a case study with a 17-story steel modular apartment building project in Hong Kong. The case project was measured with data collected from the project teams and other reliable channels, and the measurement practices and findings were referenced to establish a systematic performance measurement framework for steel modular construction.

Considering steel modular construction as a complex socio-technical system, a systematic performance measurement framework was developed, which considers the features of steel modular construction, focuses on the construction stage, incorporates the views of various stakeholders, integrates generic and specific key performance indicators and provides a benchmarking process. Multifaceted benefits of adopting steel modular construction were demonstrated with case study, including improved economic efficiency (e.g. nearly 10% cost savings), improved environmental friendliness (e.g. approximately 90% waste reduction) and enhanced social welfare (e.g. over 60% delivery trips reduction).

This paper extends the existing performance measurement methods with a new framework proposed and offers experience for future steel modular construction. The measured performance of the case project also contributes in-depth understanding on steel modular construction with benefits demonstrated. The study is expected to accelerate an effective uptake of steel modular construction in building projects.