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T Education is a leading educational science and technology enterprise in China with technology-driven, talent intimacy and quality leadership as the core development objectives. Since its inception, it has been committed to creating better learning experience for children. As the predecessor of T-education, X-education was founded in Beijing in 2003. At first, it mainly provided after-school math counseling for school-age children. Over the past 10 years, its business has been expanding, covering almost every aspect of school-age education. This case studies accounting issues and business ethics challenges that firms may face when they transform from a single (traditional education) line of business to a multiple channel business.

In recent years, knowledge graph completion has gained increasing research focus and shown significant improvements. However, most existing models only use the structures of knowledge graph triples when obtaining the entity and relationship representations. In contrast, the integration of the entity description and the knowledge graph network structure has been ignored. This paper aims to investigate how to leverage both the entity description and the network structure to enhance the knowledge graph completion with a high generalization ability among different datasets.

The authors propose an entity-description augmented knowledge graph completion model (EDA-KGC), which incorporates the entity description and network structure. It consists of three modules, i.e. representation initialization, deep interaction and reasoning. The representation initialization module utilizes entity descriptions to obtain the pre-trained representation of entities. The deep interaction module acquires the features of the deep interaction between entities and relationships. The reasoning component performs matrix manipulations with the deep interaction feature vector and entity representation matrix, thus obtaining the probability distribution of target entities. The authors conduct intensive experiments on the FB15K, WN18, FB15K-237 and WN18RR data sets to validate the effect of the proposed model.

The experiments demonstrate that the proposed model outperforms the traditional structure-based knowledge graph completion model and the entity-description-enhanced knowledge graph completion model. The experiments also suggest that the model has greater feasibility in different scenarios such as sparse data, dynamic entities and limited training epochs. The study shows that the integration of entity description and network structure can significantly increase the effect of the knowledge graph completion task.

The research has a significant reference for completing the missing information in the knowledge graph and improving the application effect of the knowledge graph in information retrieval, question answering and other fields.

In today's complex and rapidly changing business environment, cross-boundary growth is increasingly critical to the survival or even success of organizations. The purpose of this study is to examine the forming mechanism of firm’s cross-boundary growth by integrating the two important antecedent factors of performance pressure and managerial discretion into a united framework and theoretically analyze the direct role of performance pressure on firm’s cross-boundary growth as well as reveal the moderating role of managerial discretion. Also, the authors select listed manufacturing companies in China as samples to empirically test the research hypotheses.

The authors design a multiple regression model to perform empirical analysis by using a panel of 4,002 year-observations in 1,334 listed manufacturing companies between 2013 and 2016. The sample data sources mainly come from the Wind Database, which is mainland China's leading financial database and software services provider. The hypotheses proposed are tested by adopting a panel data set of the listed manufacturing companies of China.

Empirical results show that performance pressure has a positive effect on the cross-industry growth and cross-domestic regional growth but a negative effect on the cross-international regional growth, and managerial discretion has a different moderating effect. Specifically, capital intensity strengthens the positive effect of performance pressure on cross-industry growth but weakens the negative effect of performance pressure on cross-international regional growth. State ownership enhances the positive effect of performance pressure on cross-domestic regional growth but decreases the negative effect of performance pressure on cross-international regional growth. CEO duality increases the negative impact of performance pressure on cross-international regional growth.

This study provides several implications for top executives, including how to dialectically consider the double-edged effect of performance pressure on cross-boundary growth of firms, create an appropriate environments of managerial discretion and design the types of cross-boundary growth strategies that top executives can follow in the volatility, uncertainty, complexity and ambiguity era.

Although the relevant literature highlights the importance of performance pressure, it has not been related to the cross-boundary growth of firms. This paper makes an incremental contribution to the literature on the forming mechanisms of firm’s cross-boundary growth by providing an important perspective of performance pressure to firm growth determinants and taking into account the moderating role of managerial discretion.

Considering the unmeasurable states of the systems and the previewed reference signal, a novel fuzzy observer-based preview controller, which is a mixed controller of the fuzzy observer-based controller, fuzzy integrator and preview controller, is considered to address the tracking control problem.

The authors employ an augmentation technique to construct an augmented error system for uncertain T-S fuzzy discrete-time systems with time-varying uncertainties. Additionally, the authors obtain the corresponding linear matrix inequality (LMI) conditions for designing the preview controller.

This paper discusses the preview tracking problem for nonlinear systems. First, considering the unmeasurable states of the systems and the previewed reference signal, a novel fuzzy observer-based preview controller, which is a mixed controller of the fuzzy observer-based controller, fuzzy integrator, and preview controller, is considered to address the tracking control problem. Then, using the fuzzy Lyapunov functional with the linear matrix inequality (LMI) technique, new sufficient conditions for the asymptotic stability of the augmented system are derived by applying the LMI technique. The preview controller and fuzzy observer can be designed in one step. Finally, a numerical example is used to illustrate the effectiveness of the results.

An augmented error system is successfully constructed by the state augmentation approach. A novel preview controller is designed to address the tracking control problem. The preview controller and fuzzy observer can be designed in one step.

This paper aims to present a catalogue of the influential aspects resulting from a bibliometric meta-analysis of political connection literature.

This study undertakes a bibliometric meta-analysis review of political connections literature, covering 138 research papers from 2000 to 2020 using the visualization of similarities viewer program.

The authors identify six research groups: the value of political connections; political connections and finance; political connections in banks; political connections and debt; management and political connections; and political connections and governance. This study discusses each stream through a cartographic analysis, including co-authorship, countries and time networks.

This study makes an important and novel contribution to political connection literature. So far, to the best of the authors’ knowledge, it is the only bibliometric study on political connections. This study is the first to use network analysis and community detection to understand social clustering and to identify main research steams in political connection literature.

How does the regional institutional environment of China’s transitional economy influence the relationship between a firm’s R&D investment intensity and innovation performance? Based on the resource-based view and institution-based view, an empirical study was executed to identify the moderating effects of institutional environment variables from the Marketization Index of China’s Provinces: National Economic Research Institute (NERI) Report on the relationship between a firm’s R&D investment intensity and innovation performance. This paper aims to study how effectively improve the impact of R&D investment intensity on innovation performance under the influence of the institutional environment.

Against the background of China’s transitional economy, the authors present empirical evidence from panel data covering 374 Chinese A-share listed high-tech manufacturing firms on the Shanghai and Shenzhen Stock Exchange to examine the relationship between R&D investment intensity and innovation performance.

Empirical results illustrate the following: The R&D investment intensity and innovation performance displayed an inverse U-shaped relationship, and R&D investment intensity had a lagged effect on R&D output according to the uncertainty and industrialization period of R&D activities. The level of financial market development can intensify the effects of R&D investment intensity on innovation performance. The degree of government intervention weakens the effect of R&D investment intensity on innovation performance.

Based on the background of China’s institutional environment during the transition period, combined with previous research and the Marketization Index of China’s Provinces: NERI Report, selecting financial market development, government intervention level and legalization level as moderating variables to study how effectively improve the impact of R&D investment intensity on innovation performance under the influence of the institutional environment. Due to the different ownership of firms during the transition period, the appropriate impact of the institutional environment on the relationship between R&D investment intensity and innovation performance will vary. Moreover, the level of legalization would impact on innovation insignificantly.

This study aims to discuss the state-of-the-art digital factory (DF) development combining digital twins (DTs), sensing devices, laser additive manufacturing (LAM) and subtractive manufacturing (SM) processes. The current shortcomings and outlook of the DF also have been highlighted. A DF is a state-of-the-art manufacturing facility that uses innovative technologies, including automation, artificial intelligence (AI), the Internet of Things, additive manufacturing (AM), SM, hybrid manufacturing (HM), sensors for real-time feedback and control, and a DT, to streamline and improve manufacturing operations.

This study presents a novel perspective on DF development using laser-based AM, SM, sensors and DTs. Recent developments in laser-based AM, SM, sensors and DTs have been compiled. This study has been developed using systematic reviews and meta-analyses (PRISMA) guidelines, discussing literature on the DTs for laser-based AM, particularly laser powder bed fusion and direct energy deposition, in-situ monitoring and control equipment, SM and HM. The principal goal of this study is to highlight the aspects of DF and its development using existing techniques.

A comprehensive literature review finds a substantial lack of complete techniques that incorporate cyber-physical systems, advanced data analytics, AI, standardized interoperability, human–machine cooperation and scalable adaptability. The suggested DF effectively fills this void by integrating cyber-physical system components, including DT, AM, SM and sensors into the manufacturing process. Using sophisticated data analytics and AI algorithms, the DF facilitates real-time data analysis, predictive maintenance, quality control and optimal resource allocation. In addition, the suggested DF ensures interoperability between diverse devices and systems by emphasizing standardized communication protocols and interfaces. The modular and adaptable architecture of the DF enables scalability and adaptation, allowing for rapid reaction to market conditions.

Based on the need of DF, this review presents a comprehensive approach to DF development using DTs, sensing devices, LAM and SM processes and provides current progress in this domain.

Laser-based powder bed fusion (LPBF) is a new method for forming thin-walled parts, but large cooling rates and temperature gradients can lead to large residual stresses and deformations in the part. This study aims to reduce the residual stress and deformation of thin-walled parts by a specific laser rescanning strategy.

A three-dimensional transient finite element model is established to numerically simulate the LPBF forming process of multilayer and multitrack thin-walled parts. By changing the defocus amount, the laser in situ annealing process is designed, and the optimal rescanning parameters are obtained, which are verified by experiments.

The results show that the annealing effect is related to the average surface temperature and scan time. When the laser power is 30 W and the scanning speed is 20 mm/s, the overall residual stress and deformation of the thin-walled parts are the smallest, and the in situ annealing effect is the best. When the annealing frequency is reduced to once every three layers, the total annealing time can be reduced by more than 60%.

The research results can help better understand the influence mechanism of laser in situ annealing process on residual stress and deformation in LPBF and provide guidance for reducing residual stress and deformation of LPBF thin-walled parts.

Digital transformation continues to rapidly progress in higher education globally, spanning all aspects of higher education operations, values and culture. Despite expanding literature, guidance remains focussed on emergency application during pandemic lockdowns and/or on single organisational case studies. Digital transformation frameworks that move beyond these foci are heavily criticised for being commercially contextualised (outside of higher education) and are often too narrowly conceptualised. The purpose of this paper is to review the most common framework currently used in the UK, which takes a strategic and organisational perspective on digital transformation.

This is a technical review article that summarises key guidance for organisational digital capability and then reflects on its application in the UK (a developed economy and higher education system) and in Vietnam (one of the fastest-growing economies with a developing higher education committed to digital transformation) as an initial attempt to explore its applicability beyond the UK context. Vietnam has been chosen as a reference context, given its significant current digital transformation policy reform at the national level and as a collaboration partner with the UK in its digital transformation.

The guidance highlights six core areas to consider for digital capability: information and communication technology (ICT) infrastructure, content and information, research and innovation, communication, learning, teaching and assessment and organisational digital culture. Although the framework is normative, findings suggest it is sufficiently open-ended to enable its users to determine practical steps to drive digital transformation. However, complementary tools are suggested to deal with the rapidly developing digital transformation policy context of Vietnam.

This is the first time a review has been conducted from the perspective of different countries, with a view to supporting leaders, managers and policymakers in the UK, Vietnam and other Association of South Eastern Nations (ASEAN) networks in their own digital transformation transitions.

This study aims to find out the role of green curriculum (GC) in making a green generation (GG) and ensuring sustainability. The study considers the green curriculum a key factor for understanding environmental values orientation (EVO) and adopting pro-environmental behaviors (Pr-EnB) for social, economic, human and environmental sustainability.

The study is quantitative and cross-sectional. Partial least square-structural equation modeling was used to test the research model and data which was collected through a questionnaire survey from university faculty and students in Pakistan, Saudi Arabia and China.

The findings show that the GC has significant positive effects on EVO and pro-environmental behavior. However, it has no significant effect on social sustainability. There is a positive significant effect of pro-environmental behavior on economic, environmental, human and social sustainability. Whereas, environmental orientation has no significant effect on economic sustainability but significantly influences environmental, human and social sustainability. GC has no significant effect on economic, environmental and human sustainability. However, when considering the combined effects of GC and environmental values orientation or pro-environmental behavior, significant positive effects were found on economic, environmental, human and social sustainability.

The result suggests that implementing a GC positively influences environmental orientation, pro-environmental behavior and various dimensions of sustainability.

These results have implications for educational institutions and policymakers aiming to promote sustainability through green curriculum and help in the attainment of sustainable development goals.

The study fulfills an essential need to obtain sustainability and sustainable development goals through education.