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Low levels of human capital in rural China are rooted in the poor schooling outcomes of elementary school students. The purpose of this paper is to provide insight into the distribution of academic performance in rural China and identify vulnerable groups.

The authors draw on a data set of 25,892 observations constructed from 11 school-level surveys spanning nine provinces and one municipality in China conducted from 2013 to 2015.

The authors find that the distribution of academic performance is uneven across provinces and subgroups. In general, male students, Han, living in richer counties, living with their parents and studying in rural public schools do better academically than female students, non-Han, living in poorer counties, left behind and studying in private migrant schools in cities.

Using the results of this study, policymakers should be able to better target investments into rural education focusing on at risk subpopulations.

With limited data sources, the research on the academic performance of students in rural China is largely absent. The findings of this study help to fill the gaps in the literature base.

The purpose of this paper is to measure the turnover (or stability in employment) of village clinicians in rural China over the past decade. The authors also want to provide quantitative evidence on the individual characteristics of the clinicians who provide health care to villagers in rural China and whether we should expect these individuals to be interested in continuing to supply quality health care in China’s villages in the coming years.

This paper uses data from a survey of rural China’s village clinicians conducted in five provinces, 25 counties, and 101 villages in 2005 and 2012. This paper also uses qualitative data from interviews with 31 village clinicians. Using a mixed methods approach, this study describes the turnover of village clinicians and the main factors that impact the career decisions of clinicians.

Turnover of China’s village doctors, while not trivial (about 25 percent of village doctors exited their field between 2005 and 2012), is still not overly high. Only five out of 101 villages did not have village clinicians in 2012. Of those that lost village doctors between 2005 and 2012, nearly all of them still had a village doctor in 2012 (either taken over by another local clinician or the position was taken by a newcomer). The authors find that three main sets of factors are correlated with the career decisions of village clinicians: village clinicians’ opportunity cost, the profitability of running a village clinic, and commitment to the field of medicine. In general, clinicians who left the village faced a much higher opportunity cost, had been running a clinic that was not profitable, and had fewer ties to the field of medicine. Newcomers over the same period had higher levels of education, went to higher profit clinics between 2005 and 2012, and had a stronger commitment to the field.

This study makes use of a data set with a large and nationally representative sample to provide a new perspective to better understand clinician turnover at village clinics, the career decisions of clinicians, and the implied trends for the quality and access to rural health care services in the future.

This paper aims to report on a study that used the practice theory lens to understand how Chinese ethnic culture influences restaurant workers' learning through engagement in everyday work practices.

A multiple case study approach was used. Data were collected from semi-structured interviews and site observations. Thematic analysis was conducted to identify how workers learnt the sayings, doings and relatings in their workplaces.

The findings show that the ethnic culture of the participants influences and enriches their learning in practice settings such as small Chinese restaurants.

The understandings presented here need to be verified through more research in different regions and nations. In addition, cross-cultural studies on other ethnic restaurants may contribute to deeper understandings of the influences of ethnic culture on practice-based learning.

The research contributes to understanding the influence of ethnic culture on practice-based learning.

The understandings gained from the findings of this study form a useful basis for curriculum development and instructional design of training programmes for practice-based as well as work-integrated-learning components of vocational curriculum. Furthermore, awareness of the strengths of the ethnic culture is of interest to owner/managers of small Chinese restaurants to afford supportive learning environments for workers.

The purpose of this paper is to examine the important application value of extending the concept of classification rule, so that it can describe and measure the uncertainty of classification knowledge.

The rough concept lattice (RCL), which is an effective tool for uncertain data analysis and knowledge discovery, reflects a kind of unification of concept intent and upper/lower approximation extent, as well as the certain and uncertain relations between objects and attributes.

A classification rules extraction algorithm, extraction algorithm of classification rule (EACR), based on the RCL is presented by adapting the rough degree to measure uncertainty of classification rule. The algorithm EACR is experimentally validated by taking the star spectrum data as the decision context.

An efficient way for classification rule extraction is provided.

The algorithm EACR based on the RCL is presented by adapting the rough degree to measure uncertainty of classification rule.

The applications of multi-agent systems (MASs) are considered to be among the most promising paradigms for detailed investigations and reliable problem-solving methods, and MAS applications make it possible for researchers and practitioners to better understand complex systems. Although a number of prior studies have been conducted to address complex issues that arise from construction projects, few studies have summarised the applications and discussed the capacity of MASs from the perspective of construction management. To fill the gap, this paper provides a comprehensive literature review of MAS applications from the perspective of construction management.

Web of Science and Scopus are the most commonly used international databases in conducting the literature reviews. A total of 86 relevant papers published in SCI-Expanded, SSCI and Ei Compendex journals related to the application of MASs from the perspective of construction management are selected to be analysed and discussed in this paper.

Based on the 86 collected publications, the utilisations of MASs to support the management of the supply chain and the improvement of project performance are identified from the perspective of construction management, the characteristics and barriers of current MAS applications are analysed, a framework for developing agent-based models to address complex problems is proposed, and future research directions of MAS applications are discussed.

This review can serve as a useful reference for scholars to enhance their understanding of the current research and guide future research on MASs. The proposed framework can help build agent-based models to address complex problems in construction management.

Urban digital transformation has become a key strategy in global countries. This study aims to provide a comprehensive and dynamic exploration of the intrinsic traits associated with urban digital transformation, in order to yield detailed insights that can contribute to the formulation of well-informed decisions and strategies in the field of urban development initiatives.

Through analysis of parallels between urban digital transformation and gyroscope motion in physics, the study developed the urban digital transformation gyroscope model (UDTGM), which comprises of seven core elements. With the balanced panel dataset from 268 cities at and above the prefecture level in China, we validate the dynamic mechanism of this model.

The findings of this study underscore that the collaboration among infrastructure development, knowledge-driven forces and economic operations markedly bolsters the urban digital transformation gyroscope’s efficacy.

This research introduces a groundbreaking framework for comprehending urban digital transformation, potentially facilitating its balanced and systemic practical implementation.

This study pioneers the UDTGM theoretically and verifies the dynamic mechanism of this model with real data.

With the rapid development in the internet technologies, the applications of big data in construction have seen considerable attention. Currently, there are many input/output modes of capturing construction knowledge related to all construction stages. On the other hand, building information modelling (BIM) systems have been developed to help in storing various structured data of buildings. However, these systems cannot fully capture the knowledge and unstructured data used in the operation of building systems in a usable format that uses the intelligent capabilities of BIM systems. Therefore, this research aims to adopt the concept of big data and develop a spoken dialogue BIM system to capture buildings operation knowledge, particularly for building maintenance and refurbishment.

The proposed system integrates cloud-based spoken dialogue system and case-based reasoning BIM system.

The system acts as an interactive expert agent that seeks answers from the user for questions specific to building maintenance problems and helps searching for solutions from previously stored knowledge cases. The practices of monitoring and maintaining buildings performance can be more efficient by the retrieval of relevant solutions from the captured knowledge to new problems when maintaining buildings components. The developed system enables easier capture and search for solutions to new problems with a more comprehensive retrieval of information.

Capturing multi-modes data into BIM systems using the cloud-based spoken dialogue systems will help construction teams use the high volume of data generated over building lifecycle and search for the most suitable solutions for maintenance problems. This new area of research also contributes to the current BIM systems by advancing their capabilities to instantly capture and retrieve knowledge of operations instead of only information.

The next generation of Building Information Modelling (BIM) seeks to establish the concept of Building Knowledge Modelling (BKM). The current BIM applications in construction, including those for asset management, have been mainly used to ensure consistent information exchange among the stakeholders. However, BKM needs to utilise knowledge management (KM) techniques into building models to advance the use of these systems. The purpose of this paper is to develop an integrated system to capture, retrieve, and manage information/knowledge for one of the key operations of asset management: building maintenance (BM).

The proposed system consists of two modules; BIM module to capture relevant information and case-based reasoning (CBR) module to capture the operational knowledge of maintenance activities. The structure of the CBR module was based on analysis of a number of interviews and case studies conducted with professionals working in public BM departments. This paper discusses the development of the CBR module and its integration with the BIM module. The case retaining function of the developed system identifies the information/knowledge relevant to maintenance cases and pursues the related affected building elements by these cases.

The paper concludes that CBR as a tool for KM can improve the performance of BIM models.

As the research in BKM is still relatively immature, this research takes an advanced step by incorporating the intelligent functions of knowledge systems into BIM-based systems which helps the transformation from the conventional BIM to BKM.

This study aims to analyze the impact of Artificial Intelligence (AI) and Machine Learning (ML) on heritage conservation and preservation, and to identify relevant future research trends, by applying scientometrics.

A total of 1,646 articles, published between 1985 and 2021, concerning research on the application of ML and AI in cultural heritage were collected from the Scopus database and analyzed using bibliometric methodologies.

The findings of this study have shown that although there is a very important increase in academic literature in relation to AI and ML, publications that specifically deal with these issues in relation to cultural heritage and its conservation and preservation are significantly limited.

This study enriches the academic outline by highlighting the limited literature in this context and therefore the need to advance the study of AI and ML as key elements that support heritage researchers and practitioners in conservation and preservation work.

Building information modelling (BIM) is increasingly being adopted during construction projects. Design and construction practices are adjusting to the new system. BIM is intended to support the entire project life-cycle: the design and construction phases, and also facility management (FM). However, BIM-enabled FM remains in its infancy and has not yet reached its full potential. The purpose of this paper is to identify major aspects of BIM in order to derive a fully BIM-enabled FM process.

In total, 207 papers were classified into main and subordinate research areas for quantitative analysis. These findings were then used to conceptualise a BIM-enabled FM framework grounded by innovation diffusion theory for adoption, and for determining the path of future research.

Through an extensive literature review, the paper summarises many benefits and challenges. Major aspects of BIM are identified in order to describe a BIM-enabled FM implementation process grounded by innovation diffusion theory. The major research areas of the proposed framework include: planning and guidelines; value realisation; internal leadership and knowledge; procurement; FM; specific application areas; data capture techniques; data integration; knowledge management; and legal and policy impact. Each element is detailed and is supported by literature. Finally, gaps are highlighted for investigation in future research.

This paper systematically classifies and evaluates the existing research, thus contributing to the achievement of the ultimate vision of BIM-enabled FM. The proposed framework informs facility managers, and the BIM-enabled FM implementation process. Further, the holistic survey identifies gaps in the body of knowledge, revealing avenues for future research.