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In the digital economy, digital capability has become an important dynamic capability of enterprises and plays an essential role in enhancing firm resilience. This study aims to investigate the relationships among digital capability, knowledge search, coopetition behavior and firm resilience based on knowledge-based view and resource-based view.

This study uses the hierarchical regression and bootstrapping methods to test the theoretical framework and research hypotheses. The survey data were collected from 241 Chinese enterprises.

Digital capability has significantly positive effects on knowledge search and firm resilience. Knowledge search positively affects firm resilience and partially mediates the relationship between digital capability and firm resilience. Coopetition behavior weakens the relationship between digital capability and knowledge search, and the mediating effect of knowledge search in the relationship between digital capability and firm resilience. The moderating effect of coopetition behavior on the relationship between digital capability and firm resilience is insignificant.

This study clarifies the effect of digital capability on firm resilience and uncovers the “black box” from digital capability to firm resilience. In addition, this research enriches the literature on digital capability and firm resilience and expands the application of knowledge-based view and resource-based view in the digital context.

The purpose of this study is to explore the knowledge network-based intellectual capital of corporate universities and its co-evolution process with knowledge management activities.

An exploratory and multiple case study was conducted, investigating three Chinese corporate universities. Grounded theory was used for data analysis.

This paper finds that the intellectual capital of corporate universities comprises teacher network capital, knowledge process capital and knowledge ba. The steering wheel model is established through the synergistic interaction and promotion among these three types of intellectual capital. The interaction between intellectual capital and the knowledge network within corporate universities constructs the intellectual capital network, which plays the roles of coordinator, knowledge gatekeeper and innovation bridge. The intellectual capital of corporate universities is characterized by sequential inertia. Moreover, the intellectual capital and intellectual capital network are aligned with knowledge management activities at each stage of corporate university development, interacting and following the principles of ladder evolution.

A significant contribution of this paper lies in applying the concept of intellectual capital within the fourth-stage ecosystem to a broader range of knowledge networks. By exploring the dynamics and network of intellectual capital in corporate universities, especially the role of intellectual capital networks and the synergy between intellectual capital and knowledge management activities, this study enriches the existing research on knowledge management and intellectual capital of corporate universities. Furthermore, it advances the development of knowledge management promotion in corporate universities from a new perspective of intellectual capital.

This study is aimed at making an inspection of the effects of collaborative innovation network characteristics on firm innovation performance, and the intermediary roles of knowledge transfer efficiency is taken into account.

This study used a convenient sampling method to obtain population and samples. Using data obtained by publishing online and paper questionnaires, and using on-site interviews in Anhui Province in the Yangtze River Delta region of China, descriptive analysis, regression analysis and correlation analysis are utilized to study the direct influence of collaborative innovation network characteristics on knowledge transfer efficiency as well as firm innovation performance, and the intermediary roles of knowledge transfer efficiency on firm innovation performance, respectively. In this study, 3,000 questionnaires were distributed to the employees of enterprises engaged in research and development (R&D) activities, of which 2,560 were valid. With the help of SPSS24.0 software, the reliability and validity of the questionnaire was analyzed.

The results are indicative of that network centrality and relationship strength positively affect knowledge transfer efficiency and firm innovation performance. Nevertheless, network scale has no significant correlation with knowledge transfer efficiency and enterprise innovation performance. In addition, knowledge transfer efficiency is an intermediary between collaborative innovation network characteristics and enterprise innovation performance, and positively affects enterprise innovation performance, which demonstrated that managers should take advantage of collaborative innovation network characteristics to elevate knowledge transfer efficiency because well-realized transferals of knowledge can help accelerate the coordination of resources in knowledge, and finally bring about the advancement of firm's innovation abilities and performance.

There are few previous studies that fully examined the relationships among collaborative innovation network characteristics, knowledge transfer efficiency and firm innovation performance. This paper developed previous researches on the relationships between collaborative innovation network characteristics, knowledge transfer efficiency and firm innovation performance. The mediation of knowledge transfer efficiency on the relationship between collaborative innovation network characteristics and firm innovation performance is analyzed. Further, studies on collaborative innovation network characteristics using data obtained from employees engaged in R&D activities are very limited in the literature. On account of that, the findings in this study may make sense to the innovation ability of innovative enterprise and expand the literature in the field of enterprise strategic management and knowledge management.

This analysis shows that collaborative innovation network characteristics have both positive and negative effects on firm innovation performance. Therefore, business managers should pay attention to their position in the collaborative innovation network and maintain the relationship strength with other innovation subjects. Special consideration should be given to the knowledge transfer of innovative enterprises, so as to improve firm innovation performance practically.

The study may provide additional understandings for researchers, government managers, universities and enterprises with regard to strategic management from the visual angle of innovation ecosystems. It is instrumental in the exploration of the mechanisms enabling firm innovation performance.

This paper aims to analyze the role and advantages of knowledge resources in the carbon emission reduction of the industrial chain, and how it can be used to promote the carbon emission reduction of the industrial chain, so that the industry can better achieve the saving of energy and the reduction of emission.

This paper argues that the traditional resource-plundering industrial chain production method can no longer meet the needs of sustainable development of the green and low-carbon industrial chain, and builds the coupling and coordination of knowledge technology innovation drive and industrial chain carbon emission reduction mechanism, in the four dimensions of industrial chain organization, government support, internet support and staff brainstorming, put forward suggestions for knowledge resources to drive carbon emission reduction in the industrial chain.

This paper holds that the use of knowledge resource advantages can better help industrial chain enterprises to carry out technological innovation, knowledge resource digital platform construction, knowledge resource overflow and transfer, application and management of network information technology, so as to reduce carbon emission in industrial chain.

This paper contributes to the discussion about the high-quality implementation of the revitalization strategy of the industrial chain and also deepens research on the knowledge resource-driven carbon emission reduction of the industrial chain. Further, this paper enriches the role of knowledge resources in the industrial industry, and the theoretical results support the advantages of knowledge resource in the field of chain carbon emission reduction.

Traditional case-adaptation methods have poor accuracy, low efficiency and limited applicability, which cannot meet the needs of knowledge users. To address the shortcomings of the existing research in the industry, this paper proposes a case-adaptation optimization algorithm to support the effective application of tacit knowledge resources.

The attribute simplification algorithm based on the forward search strategy in the neighborhood decision information system is implemented to realize the vertical dimensionality reduction of the case base, and the fuzzy C-mean (FCM) clustering algorithm based on the simulated annealing genetic algorithm (SAGA) is implemented to compress the case base horizontally with multiple decision classes. Then, the subspace K-nearest neighbors (KNN) algorithm is used to induce the decision rules for the set of adapted cases to complete the optimization of the adaptation model.

The findings suggest the rapid enrichment of data, information and tacit knowledge in the field of practice has led to low efficiency and low utilization of knowledge dissemination, and this algorithm can effectively alleviate the problems of users falling into “knowledge disorientation” in the era of the knowledge economy.

This study provides a model with case knowledge that meets users’ needs, thereby effectively improving the application of the tacit knowledge in the explicit case base and the problem-solving efficiency of knowledge users.

The adaptation model can serve as a stable and efficient prediction model to make predictions for the effects of the many logistics and e-commerce enterprises' plans.

This study designs a multi-decision class case-adaptation optimization study based on forward attribute selection strategy-neighborhood rough sets (FASS-NRS) and simulated annealing genetic algorithm-fuzzy C-means (SAGA-FCM) for tacit knowledgeable exogenous cases. By effectively organizing and adjusting tacit knowledge resources, knowledge service organizations can maintain their competitive advantages. The algorithm models established in this study develop theoretical directions for a multi-decision class case-adaptation optimization study of tacit knowledge.

This study aims to empirically examine the relationships among perceived environmental uncertainty (EV), the level of knowledge distance (KD) and the impact of value network on firm performance.

The quantitative analysis is based on data from 243 Chinese companies with engineering, procurement and construction (EPC) business in the context of the COVID-19 pandemic.

The two dimensions of value network [network centrality (NC) and network openness (NO)] have a different impact on firm performance [financial performance (FP) and market performance (MP)]. NC has a positive impact on FP, but not on MP. NO has a positive effect on MP, but not on FP. A reduced KD mediates the relationship between value network and firm performance. Moreover, it fully mediates the relationship between NC and MP, NO and FP. Finally, during the COVID-19 pandemic, only EV has a moderating effect on KD and MP.

This study is limited in terms of data set because it relies on a limited amount of cross-sectional data from one specific country. Therefore, researchers are encouraged to test the proposed propositions further.

The present findings suggest that EPC professionals should pay more attention to the EV, which may be impacted by policy, technology and the economy. This research has actionable implications for the reform of EPC in the construction industry, and practical recommendations for EPC firms to improve their corporate performance.

The results measure the complementary effects of both dimensions of value network (NC and NO) on two distinct aspects of firm performance (MP and FP) and assess the moderating effect of EV and KD in the context of the COVID-19 pandemics.

Learning from safety accidents and sharing safety knowledge has become an important part of accident prevention and improving construction safety management. Considering the difficulty of reusing unstructured data in the construction industry, the knowledge in it is difficult to be used directly for safety analysis. The purpose of this paper is to explore the construction of construction safety knowledge representation model and safety accident graph through deep learning methods, extract construction safety knowledge entities through BERT-BiLSTM-CRF model and propose a data management model of data–knowledge–services.

The ontology model of knowledge representation of construction safety accidents is constructed by integrating entity relation and logic evolution. Then, the database of safety incidents in the architecture, engineering and construction (AEC) industry is established based on the collected construction safety incident reports and related dispute cases. The construction method of construction safety accident knowledge graph is studied, and the precision of BERT-BiLSTM-CRF algorithm in information extraction is verified through comparative experiments. Finally, a safety accident report is used as an example to construct the AEC domain construction safety accident knowledge graph (AEC-KG), which provides visual query knowledge service and verifies the operability of knowledge management.

The experimental results show that the combined BERT-BiLSTM-CRF algorithm has a precision of 84.52%, a recall of 92.35%, and an F1 value of 88.26% in named entity recognition from the AEC domain database. The construction safety knowledge representation model and safety incident knowledge graph realize knowledge visualization.

The proposed framework provides a new knowledge management approach to improve the safety management of practitioners and also enriches the application scenarios of knowledge graph. On the one hand, it innovatively proposes a data application method and knowledge management method of safety accident report that integrates entity relationship and matter evolution logic. On the other hand, the legal adjudication dimension is innovatively added to the knowledge graph in the construction safety field as the basis for the postincident disposal measures of safety accidents, which provides reference for safety managers' decision-making in all aspects.

The main purpose of this paper is to explore the impact of digital transformation on enterprises' performance considering financing constraints in the capital market to explore whether digital transformation improves enterprises' performance through the financing constraints channel.

This study, using a panel data set of 14,669 observations of 2,858 non-financial enterprises that issued A shares on the Shanghai and Shenzhen stock exchanges from 2013 to 2019, theoretically and empirically tests the impact and mechanism of digital transformation on enterprise performance.

Digital transformation has a significant positive effect on enterprise performance; this conclusion remains the same after the robustness test and endogeneity problems are dealt with. Financing constraints play a mediation role between digital transformation and enterprise innovation. The effect of digital transformation on enterprise performance varies significantly by size, ownership and industry.

The theoretical contributions of this study not only enrich the literature on the economic benefits and mechanism of digital transformation but also expand the literature on the factors that influence enterprise performance. The practical contribution of this study is the reference that it provides for implementing decisions about enterprise digital transformation and formulating differentiated policies for government digital transformation.

This paper is part of the ERASMUS+-funded Strengthening University Enterprise Collaboration for Resilient Communities in Asia (SECRA) project. This study aims to map collaborative architecture between partner universities and the public/private sectors to provide a contextualised collaboration framework for disaster resilience (DR) in South-East Asia.

Documentary reviews were conducted in partner countries to establish the current context of university enterprise collaborations (UEC) in South-East Asia. A concept-centric approach permitted the synthesis of concepts from each country review, allowing for comparisons between collaborative practices that impact the success of DR collaborations.

The review identified that funding, continuity, long-term strategic plans and practical implementation are lacking in partner countries. However, each country demonstrated good practices and identified enablers and barriers that impact DR collaborations.

The synthesis revealed a lack of a practical understanding of real-world barriers. Further research is needed to understand real-world experiences in DR collaborations and to provide insights into barriers, enablers and good practices in DR collaborations. Gaining an “on-the-ground” perspective will provide detailed insights and the feasibility of implementation.

The findings provide the foundations for developing a heuristic UEC framework that can inform policies and practices for DR in partner countries.

The findings can inform various stakeholder policies and practices and promote the exchange of ideas between stakeholders to enhance DR in South-East Asia.

The results are relevant within the South-East Asian, as governments have intensified the adoption of measures to encourage UEC for DR.

The current study aims to ascertain how green entrepreneurial orientation (GEO) affects green innovation performance (GIP) through the mediating mechanism of the knowledge creation process (KCP) and whether or not these associations can be strengthened or hampered by the moderating impacts of resources orchestration capabilities (ROC).

The research used data from managers at various levels in 154 manufacturing enterprises in Pakistan to evaluate the relationships among the constructs using hierarchical regression analysis and moderated mediation approach.

The study indicates that GEO substantially impacts firms' GIP. GEO and GIP's relationship is partially mediated by two KCP dimensions: knowledge integration (KI) and knowledge exchange (KE). Furthermore, ROC amplifies not only the effects of GEO on KE but also the effects of KE on GIP. The moderated mediation results demonstrate that KE has a greater mediating influence on GEO and GIP when ROC is higher.

To better understand GEO's advantages and significance, future studies should look into the possible moderating mechanisms of environmental, organizational culture/green capability in the association between GEO, KCP and GIP.

The research helps expand the field of green entrepreneurship and GIP literature by providing a deeper knowledge of GEO and offering insight into how to boost GI in manufacturing firms.

This research helps fill in knowledge gaps in the field by delving further into the mechanisms by which GEO promotes GIP, both directly and indirectly, via the mediating role of KCP and the moderating impacts of ROC.