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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.

The study focuses on influential factors of collaboration on government data security by the Chinese government.

The article explores the case of e-government in the Chinese centralized unitary state system context, using a structured–pragmatic–situational (SPS) approach and the boundary theory as an analytical lens.

The findings indicate that e-government operates in highly interconnected environments where the safe flow of government data requires collaborative and cross-boundary strategies. Any organization is a potential “weakest link”. In addition, collaboration is fragmented by ambiguous accountability and organizational inertia across government departments, resources differences and limited visibility and measurability of security efforts across government levels and conflicts and uncertainties in principal–agent relationships. The solutions for those obstacles are also discussed from the multi-function, multi-level and multi-actor dimensions, respectively. A multi-dimensional overarching security model for the flow of government data is proposed.

The study advances the technology-oriented micro-analysis of previous studies on government data security to cross-organizational revealing at the macrolevel by connecting streams of research in information systems and public administration. These findings will contribute to making the safe flow of government data more resilient in the transformation of e-government.

This study aims to distinguish how unabsorbed and absorbed slack affects market and financial performance via proactive and reactive supply chain resilience (SCRES), particularly under varying conditions of organizational ambidexterity.

By collecting survey data from 277 Chinese manufacturers, we verify the conceptual model applying structural equation modeling.

Proactive SCRES mediates the positive impacts of both unabsorbed and absorbed slack on market and financial performance, whereas reactive SCRES mediates only their positive effects on financial performance. High levels of organizational ambidexterity strengthen the indirect effects of both types of slack on market and financial performance via proactive SCRES, but not when mediated by reactive SCRES.

We introduce a new theoretical perspective to view fits (as mediation) between the use of unabsorbed/absorbed slack in different ways when switching attentions to proactive or reactive SCRES, both of which can be improved through organizational ambidexterity. This study offers novel insights into how managers can switch attentions between proactive and reactive SCRES knowing when to appropriately use unabsorbed/absorbed slack for which purposes, and the use of different learning modes (explorative vs exploitative).

The construction of smart cities holds the potential to drive digital innovation in the construction industry through various means, such as enhancing supply and demand. This study echoes the urgent need for the construction industry to overcome development challenges. Hence, it is necessary to study the extent and ways in which smart city policies promote digital innovation in the construction industry.

This study treats China’s smart city policies as quasi-natural experiments. Using a dataset of Chinese prefecture-level cities from 2007 to 2021 and a difference-in-differences model, the study scrutinizes the impact of smart city policies on digital innovation within the construction industry.

The study reveals a substantial positive influence of smart city policies on digital innovation in the construction industry. In addition, the study explains these results by analysing supply-side and demand-side mechanisms. Moreover, the effect of smart city pilot policies on promoting digital innovation within the construction industry displays noteworthy heterogeneity across cities at different regional and political levels.

By exploring the impact and mechanisms of smart city policies on digital innovation in the construction industry, this research contributes to a more comprehensive and profound comprehension of the role of policies in facilitating the digital transformation of the construction sector. It is a valuable reference for policymakers and industry practitioners aiming to advance digital development.

In the context of an evolving digital-based global economy, this study aims to investige the impact of digital transformation (DT) on a firm’s internal control (IC) quality. It also explores how the personal traits of (CEOs) – such as age, gender and educational background – intersect with DT to shape the IC quality in various types of state-owned enterprises (SOEs).

The study uses the data from China A-shares non-financial enterprises, listed on Shanghai and Shenzhen stock exchanges between 2007 and 2020. Using the fixed effect regression method alongside various statistical techniques, such as propensity score matching, alternative analysis and instrumental variables analysis, yields robust findings. These methods effectively address issues related to functional form misspecification and potential biases from omitted explanatory variables.

The findings reveal a positive impact of DT on firm IC quality, and this impact is more pronounced in firms when the CEO is female, young and possesses a higher level of education. Notably, the study also distinguishes between central and local state-owned enterprises (SOEs), highlighting that DT has a greater influence on IC quality in central SOEs, where CEOs often have higher political ranks and closer to government monitoring. Overall, the findings are robust and consist to alternative variable and other statistical methods.

Following are the significant implications for both academia and business. First, firms that effectively adopt DT to enhance IC not only gain a strategic advantage over competitors but also establish efficient risk management practices and a robust IC system. Second, better IC resulting from DT can enhance investor and stakeholder confidence. This is particularly important for publicly traded companies, where investors and analysts closely scrutinize the robustness of IC systems. Third, DT could result in cost savings over time, as automation and streamlined processes may reduce the need for manual efforts and resource-intensive tasks associated with IC.

The findings are contributed to the literature in multiple ways. It enhances our comprehension of the intricate DT-IC quality relationship, and provides valuable insights into the transformative impact of DT on organizational operations and risk management. It also introduces a novel perspective by investigating how CEOs personal traits intersect with DT to shape IC quality, contributing to upper echelons theory. Furthermore, it expands the discussions on firm ownership by considering the types of SOEs (central vs. local), in the DT-IC quality context.

In recent decades, interest in digital transformation (DX) within the architecture, engineering, and construction (AEC) industry has significantly increased. Despite the existence of several literature reviews on DX research, there remains a notable lack of systematic quantitative and visual investigations into the structure and evolution of this field. This study aims to address this gap by uncovering the current state, key topics, keywords, and emerging areas in DX research specific to the AEC sector.

Employing a holistic review approach, this study undertook a thorough and systematic analysis of the literature concerning DX in the AEC industry. Utilizing a bibliometric analysis, 3,656 papers were retrieved from the Web of Science spanning the years 1990–2023. A scientometric analysis was then applied to these publications to discern patterns in publication years, geographical distribution, journals, authors, citations, and keywords.

The findings identify China, the USA, and England as the leading contributors in the field of DX in AEC sector. Prominent keywords include “building information modeling”, “design”, “system”, “framework”, “adoption”, “model”, “safety”, “internet of things”, and “innovation”. Emerging areas of interest are “deep learning”, “embodied energy”, and “machine learning”. A cluster analysis of keywords reveals key research themes such as “deep learning”, “smart buildings”, “virtual reality”, “augmented reality”, “smart contracts”, “sustainable development”, “building information modeling”, “big data”, and “3D printing”.

This study is among the earliest to provide a comprehensive scientometric mapping of the DX field. The findings presented here have significant implications for both industry practitioners and the scientific community, offering a thorough overview of the current state, prominent keywords, topics, and emerging areas within DX in the AEC industry. Additionally, this research serves as an invaluable reference and guideline for scholars interested in this subject.

The purpose of this study is to solve the problem that existing researches ignore the long-term and staged nature of digital transformation, failing to conduct specific discussions for different stages. It responded the call by constructing a three-stage evolutionary model to analyze the impact of digital transformation at different stages on the sustainable performance of manufacturing enterprises. The moderating effect of core technology capabilities is also explored, guided by the theory of assimilation innovation.

Based on the panel data of Chinese listed manufacturing companies from 2012 to 2020, this study empirically investigate the impact of digital transformation (digital process, digital operation and digital ecology) on sustainability performance (economic performance and environmental performance).

The findings indicate that digital operations and digital ecology significantly improve economic performance and environmental performance. Furthermore, the core technological capacity of the enterprise serves to modify the positive correlation between digital transformation at each stage and sustainable performance to some extent. In other words, when an enterprise is equipped with the requisite technological capacity, the digital transformation at each stage accelerates both economic performance and environmental performance, which in turn is conducive to an improvement in the enterprise’s sustainable development performance.

The findings contribute to the theoretical framework of digital transformation and sustainable development in all stages of enterprises. Furthermore, they provide guidance for achieving sustainable development through the implementation of digital transformation and the enhancement of core technological capacity.

This study aims to examine the impact of digital transformation on firms’ value and explore the mediating impact of ESG performance and moderating impact of information interaction.

Data was collected from companies listed on the Shanghai and Shenzhen stock exchange between 2012 and 2020 with 21,488 observational samples, featuring a selection of 3,348 companies. Panel data regression techniques were used to test the mediating role of ESG performance and the moderating role of information interaction.

The study found that digital transformation can improve firms’ ESG performance, which in turn positively affects their value. The firms that engage in more interaction with outsiders benefit more from digital transformation and have a higher value.

This study provides new theoretical insight into improving firms’ value through digital transformation and ESG performance. It is the first to discuss and study the moderating role of information interaction in the relationship between digital transformation and firms’ value.

This study aims to deliver a new perspective on how the interaction of independent and cooperative innovation affects firm digitization. Based on resource constraint theory, this study argues that the aforementioned interaction negatively affects firm digitization. The moderating role of managerial discretion is also discussed in light of the principles of the awareness-motivation-capability (AMC) framework.

The proposed hypotheses are empirically tested using a negative binomial modeling approach. The data used are from A-share listed companies in China’s Shanghai and Shenzhen stock markets from 2006 to 2020.

This study suggests that the interaction of independent innovation and cooperative innovation negatively impacts digitization. In addition, this study argues that environmental discretion and organizational discretion weaken the negative impact of the mentioned interaction on digitization. However, additional discretion in the Chinese context has no effect on above relationships.

This study explores the impact of the interaction of independent and cooperative innovation on digitization and incorporates managerial discretion into this framework based on the AMC framework.

The research aims to show the importance of considering the specific threats to economic security that arise in the context of digital transformation. The classification and understanding of these threats allow us to develop the most effective public policy tools to overcome them. The research is based on content analysis of information from government documents and internet resources. According to the authors, economic security in the digital environment is the state of the subject of economic activity (individual, society, or state), which ensures its normal functioning in the virtual world and maintains the security, stability, and predictability of the relations in which this subject participates in the digital environment. Moreover, there should be no factors of the digital environment that can cause harm in the virtual and real world, or these factors should not affect the subject. The government plays a central role in solving the problem of ensuring economic security in the digital age because it concentrates on the social will and aspirations and sets the vector for the development of society, including in the digital environment. Simultaneously, the form that evolutionary processes take in a particular society has its own national, regional, and historical specifics.