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Coal is the basic energy and essential resource in China, which is crucial to the economic lifeline and energy security of the country. Coal mining has been ever exposed to potential safety risks owing to the complex geologic environment. Effective safety supervision is a vital guarantee for safe production in coal mines. This paper aims to explore the impacts of the internet+ coal mine safety supervision (CMSS) mode that is being emerged in China.

In this study, the key factors influencing CMSS are identified by social network analysis. They are used to develop a multiple linear regression model of law enforcement frequency for conventional CMSS mode, which is then modified by an analytical hierarchy process to predict the law enforcement frequency of internet+ CMSS mode.

The regression model demonstrated high accuracy and reliability in predicting law enforcement frequency. Comparative analysis revealed that the law enforcement frequency in the internet+ mode was approximately 40% lower than the conventional mode. This reduction suggests a potential improvement in cost-efficiency, and the difference is expected to become even more significant with an increase in law enforcement frequency.

To the best of the authors’ knowledge, this is one of the few available pieces of research which explore the cost-efficiency of CMSS by forecasting law enforcement frequency. The study results provide a theoretical basis for promoting the internet+ CMSS mode to realize the healthy and sustainable development of the coal mining industry.

Land transactions are a key indicator of urban sustainable development and urban space expansion. Therefore, this paper aims to study the spatial correlation of different types of land transactions.

Based on the big data of land micro transactions in Yangtze River Delta urban agglomeration, this paper uses the generalized forecast error variance decomposition (GFEVD) method to measure the correlation level of urban land markets. Also, social network analysis (SNA) is used to describe spatial correlation network characteristics of an urban agglomeration land market. In the meantime, the factors that influence the spatial correlation of urban land markets are investigated through a quadratic assignment procedure (QAP).

The price growth rate of urban residential land was higher than that of industrial land and commercial land. The spatial relevance of urban residential land is the highest, while the spatial relevance of the urban commercial land market is the lowest. The urban industrial land market, commercial land market and residential land market all present a typical network structure. Population distance (POD) and Engel coefficient distance (EGD) are negatively correlated with the correlation degree of the urban residential land network; traffic distance (TRD) and economic distance (ECD) are negatively correlated with the correlation degree of the urban industrial land network and commercial land network.

This paper uses a systematically-integrated series of problem-solving models to better explain the development path of urban land markets and to realize the integration of the interdisciplinary methods of geography, statistics and big data analysis.

Robots are widely used in industrial manufacturing and service industries around the world. However, most of the previous studies on industrial robots use data at the national or industry level in the context of developed countries. This study examines the impact of imported industrial robots on firm innovation at the firm level in China.

Drawing on a large dataset of more than three million records in China, including non-publicly traded small and medium firms, the authors adopt a difference-in-differences method to investigate the impact and channels of industrial robots on firm innovation.

The authors find that the application of industrial robots increases firm innovation. Two possible channels are identified through which robots promote innovation: alleviation of financial constraints and the improvement of human capital. Further analysis shows that the effect of robots on innovation is more pronounced for firms that are highly dependent on external financing, belong to high-tech industries, import high-end robots, have insufficient supply of skilled labor and private firms (non-SOEs). The authors also find that industrial robots increase the firms' innovation quality and the marginal contribution of innovation to firms' total factor productivity.

This study provides big data evidence of the unintended positive consequences of industrial robots on firm innovation. The results are helpful to clarify the controversy of industrial robots. It also has important implications for government industrial policy making, firm innovation and human resource management.

The purpose of this study is to investigate the relationship between tourism development and urban housing prices in Chinese cities. Specifically, the study aimed to explore whether there is a relationship between the two variables in tourist and non-tourist cities and whether there is a non-linear relationship between them.

In this study, the entropy method was used to construct the China City Tourism Development Index, which provides a more comprehensive measure of the level of tourism development in different cities. In total, 45 major cities in China were studied using the panel data approach for the period of 2011 to 2019.

The empirical analysis conducted for this study found that tourism development affects urban house prices, and that there is an inverted U-shaped relationship. However, this varies across cities, with house prices in tourist cities tending to be more influenced by tourism development than non-tourist cities. Also, foreign direct investment, population size, fixed asset investment and disposable income per capita were found to have an impact on house prices in both tourism and non-tourism cities.

There are significant differences in tourism development and urban house prices in different cities in China. This study considers these differences when examining the impact of tourism on house prices in 45 major cities in China by dividing the sample cities into tourist and non-tourist cities.

This paper aims to explore how firms enter or exit B Corp certification faced with the tension between local and B Corp institutions, providing a better understanding of the unique impact of institutional complexity on B Corps' decision-making.

This paper applies multi-case analysis to 20 Chinese firms in various stages of B Corp certification, including eight certified B Corps, six decertified firms and six candidates. The qualitative data was used to code separately for two research questions.

The study findings reveal that: (1) Participants who can obtain expected social and economic benefits by innovating their operational mode to efficiently deal with this tension attempt to continuously pursue B Corp certification. A self-renewal model was developed to show how firms hybridize the two institutional logics; (2) Participants who find it hard to mitigate this tension tend to compromise with the local institution and conform less with the B Corp institution due to high opportunity and accounting costs, low short-term benefits and collective culture.

By highlighting the different responses of firms to institutional complexity, this study contributes to B Corp research, social identity theory and institutional complexity, providing practical implications for B Lab strategies in China.

Higher education institutions have a critical role in creating and disseminating the knowledge required to address the complex global challenges faced by global society, as summarized in the Sustainable Development Goals (SDGs). This role of higher education is linked with the concept of internationalization, which has recently been called upon to help contribute to tackle the global challenges and meet the SDGs, particularly through more attention to “Internationalization at Home” (IaH). This paper aims to examine the role of higher education in addressing the SDGs, especially with respect to the links between IaH and the SDGs.

A case study of the International Campus of Zhejiang University (iZJU) is conducted to illustrate how iZJU, which is a pioneer of “Internationalization at Home” and an exemplar of sustainable campus in China, contributes to the value of the SDGs and makes an impact.

The authors examine the practice of IaH at iZJU in the dimensions of organization, curriculum, people and campus, and the authors find evidence from the iZJU model in addressing the value of the SDG4, 6, 7, 11, 13, 14, 15, 16 and 17.

First, the authors contribute to the literature on the role of higher education in addressing the SDGs, especially with respect to the links between IaH and the SDGs. Second, the authors contribute to the IaH literature by examining IaH from a Chinese perspective, as there has been little exploration of what IaH means beyond the European context. Third, the authors build on the analytical framework in the IaH literature in the dimensions of organization, curriculum and people and extend with a new dimension of campus. Fourth, the authors show that IaH is a comprehensive approach to include both curriculum internationalization and campus internationalization.