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This study aims to examine how the knowledge breadth and depth of a patent affect its likelihood of being pledged. It also seeks to explore whether these relationships change diversely in different technological environments.

A complementary log-log model with random effects was conducted to test the hypotheses using a unique data set consisting of 348,927 invention patents granted by the China National Intellectual Property Administration from 1985 to 2015 belonging to 74,996 firms.

The findings reveal that both knowledge breadth and depth of a patent positively affect its likelihood of being pledged. Furthermore, the knowledge breadth and depth entail different degrees of superiority in different technological environments.

This study focuses on the effect of an individual patent’s knowledge base on its likelihood of being selected as collateral. It does not consider the influence of the overall knowledge characteristics of the selected patent portfolio.

Managers need to pay attention to patents’ knowledge characteristics and the changes in technological environments to select the most suitable patents as collateral and thus improve the success rate of pledge financing.

This study explores the impact of multidimensional characteristics of knowledge base on patent pledge financing within a systematic theoretical framework and incorporates technological environments into this framework.

This study aims to analyse the relationship between a patent’s network position in a knowledge search network and the likelihood and speed of patent transactions. Additionally, it explores whether patent scope moderates these relationships.

In this empirical study, the authors collected a sample of patents in the artificial intelligence industry over the period of 1985–2018. Then, the authors examined the direct roles of degree centrality, betweenness centrality and closeness centrality on the likelihood and speed of patent transactions and the moderating role of patent scope in the knowledge search network using the logit and accelerated failure time models.

The findings reveal that degree centrality positively affects both the likelihood and speed of patent transactions, while betweenness centrality enhances the likelihood, and closeness centrality significantly boosts both. However, regarding the speed of patent transactions, closeness centrality is the most impactful, followed by degree centrality, with no significant influence of betweenness centrality. Additionally, the patent scope moderates how betweenness centrality affects the likelihood of transactions.

This study has limitations owing to its exclusive use of data from the Chinese Intellectual Property Office, lack of visibility of the confidential terms of most patent transactions, omission of transaction directionality and focus on a single industry, potentially restricting the breadth and applicability of the findings. In the future, expanding the data set and industries and combining qualitative research methods may be considered to further explore the content of this study.

This study has practical implications for developing a better understanding of how network structure in the knowledge search network affects the likelihood and speed of patent transactions as well as the identification of high-value patents. These findings suggest future directions for patent holders and policymakers to manage and optimise patent portfolios.

This study expands the application boundaries of social network theory and the knowledge-based view by conducting an in-depth analysis of how the position characteristics of patents within the knowledge search network influence their potential and speed of transactions in the technology market. Moreover, it provides a theoretical reference for evaluating patent value and identifying high-quality patents by quantifying network positions. Furthermore, the authors construct three centrality measures and explore the development of patent transactions, particularly within the context of the developing country.

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.

Innovation quality is a critical component of enterprise innovation. Prior research primarily focuses on company-level and external policy-level factors that affect innovation quality, while ignoring social-level factors. Based on institutional isomorphism theory, this study examines how the innovation quality of three-dimensional institutional equivalence, which is an important and unique reference group for firms to follow the “law of imitation of close preference”, affects the likelihood of firms' innovation quality.

This study conducts firm random effects and industry/year fixed effects models using China's listed companies from 2002 to 2021.

This study finds that compared with the innovation quality of its other industry, community, or network peers, the innovation quality of three-dimensional institutional equivalence has a greater impact on firm innovation quality. Furthermore, technological intensity significantly increases the effect of three-dimensional institutional equivalence on focal company innovation quality, while financing constraints significantly attenuate this effect. Additionally, when there is no institutional equivalent, the innovation quality of network, industry, and community peers has significant positive effects on enterprise innovation quality. Heterogeneity analysis also indicates that, under the conditions of non-state-owned enterprises, a low regional legal environment, or low regional factor market development, three-dimensional institutional equivalence contributes significantly to firm innovation quality.

This study focuses on the effect of three-dimensional institutional equivalence on Chinese enterprises' innovation quality. Nonetheless, research samples from other countries are not considered in this study.

This study explores the impact of three-dimensional institutional equivalence on firm innovation quality within a systematic theoretical framework and incorporates firm attributes into this framework.

This research examines the relationship between green innovation and firm performance, focusing on identifying the moderating effects of government subsidies and digital transformation R&D investments. The study aims to provide insights on how firms can leverage green innovation for enhanced performance while addressing potential drawbacks.

This study adopts a mixed-methods approach, utilizing both analytical models and empirical analyses. It investigates the curvilinear relationship between green innovation and firm performance and explores the moderating roles of government subsidies and digital transformation R&D investments.

The findings reveal an inverted U-shaped relationship between green innovation and firm performance, indicating that initial investments in green innovation led to performance improvements, but beyond a certain point, the returns diminished. The study also finds that government subsidies and digital transformation R&D investments significantly enhance the positive impact of green innovation up to the optimal threshold and help mitigate negative effects.

The research provides practical guidance for firms on managing their green innovation investments to maximize performance benefits. It also offers insights for policymakers on designing effective subsidies and support mechanisms to promote environmental sustainability and economic growth.

This study contributes to the literature by elucidating the complex relationship between green innovation and firm performance and highlighting the critical roles of government subsidies and digital transformation R&D investments. It offers valuable implications for businesses seeking to balance environmental and economic objectives and policymakers aiming to foster sustainable and profitable practices.

The emergence of smart cities, metropolises that integrate physical infrastructure, digital technology, and data analytics, and that focus on urban sustainability, have profoundly changed urban development. In the modern digital era, robust infrastructure has become an indispensable catalyst for urban advancement. Kuwait is dedicated to the integration of diverse renewable energy technologies in the development of smart cities that enhance energy security, promote innovation, and contribute to global climate change mitigation efforts. Focusing on smart cities within Gulf Cooperation Council (GCC) countries, a review is presented of how successfully they have effectively combined technology, infrastructure, and sustainability to serve as models for new global and regional developments. Insights into what makes a city smart are provided in different settings.

Coordinating low-carbonization and digitalization is a practical implementation pathway to achieve high-quality economic development. Regions are under great emission reduction pressure to achieve low-carbon development. However, why and how regional emission reduction pressure influences enterprise digital transformation is lacking in the literature. This study empirically tests the impact of emission reduction pressure on enterprise digital transformation and its mechanism.

This article takes the data of non-financial listed companies from 2011 to 2020 as a sample. The digital transformation index is measured by entropy value method. The bidirectional fixed effect model was used to test the hypothesis.

The research results show that emission reduction pressure forces enterprise digital transformation. The mechanism lies in that emission reduction pressure improves digital transformation by promoting enterprise innovation, and digital economy moderates the nexus between emission reduction pressure and digital transformation. Furthermore, the effect of emission reduction pressure on digital transformation is more significant for non-state-owned, mature and high-tech enterprises.

This paper discusses the mediating role of enterprise innovation between carbon emission reduction pressure and enterprise digital transformation, as well as the moderating role of digital economy. The research expands the body of knowledge about dual carbon targets, digitization and technological innovation. The author’s findings help update the impact of regional digital economy development on enterprise digital transformation. It also provides theoretical guidance for the realization of digital transformation by enterprise innovation.

This study explores how the high-end equipment manufacturing industry (HEMI) achieves intelligent development through the digital innovation ecosystem. While this industry urgently needs to achieve intelligent development through innovation breakthroughs, existing research lacks a deep analysis in conjunction with the digital innovation ecosystem. Considering the sophisticated nature of HEMI and the unique characteristics of the digital innovation ecosystem, this paper aims to uncover the innovation potential and synergetic development opportunities that arise from their integration.

This study uses Dynamic Qualitative Comparative Analysis (QCA) to explore the evolving relationship between the digital innovation ecosystem and intelligent development in HEMI enterprises. Data from 60 HEMI enterprises were collected from 2015 to 2022, and the study window was divided into two-year intervals for analysis. Compared to traditional QCA methods, this approach overcomes the limitations of cross-sectional analysis, fully accounting for time’s influence on causal relationships for more accurate results.

The study reveals that the digital innovation ecosystem of HEMI drives intelligent development through the coordinated interactions of its elements within each time window. Configuration paths and key driving factors evolve dynamically, reflecting the complexity of the ecosystem’s role in driving intelligent development. The study suggests that enterprises dynamically adjust their strategies to different stages, enhancing the effectiveness of intelligent transformation.

The paper proposes and validates a digital innovation ecosystem framework for HEMI, systematically exploring its role in driving intelligent development. The study fills a research gap and extends innovation ecosystem theory by identifying core driving factors and their evolutionary trends through Dynamic QCA. It offers a new perspective on the dynamic role of digital innovation ecosystems in intelligent transformation.

The concept of smart cities, driven by advancements in innovative information and communication technologies (ICTs), has gained significant attention in recent years. Smart cities aim to improve the quality of life for citizens by leveraging ICT to enhance the efficiency and effectiveness of urban services and infrastructure. One critical aspect of smart cities development is advanced innovations in water management, which play a vital role in achieving sustainability, prosperity of community and ensuring the availability of clean water resources. This chapter explores the relationship between advanced water management and smart cities development and highlights the synergies and benefits that arise from their integration. The chapter develops a framework for adopting innovative ICTs that support the gradual transformation toward next generation smart cities in the Gulf Cooperation Council (GCC) region. Such transformation aligns with the United Nations’ sustainable development goals (SDGs) and the maintenance of various social, economic, and environmental developments. The chapter begins by discussing the fundamental principles of smart cities and the role of advanced sensing technologies in enabling efficient and automated processes within urban environments. It then delves into the concept of water-sensitive cities, the importance of urban water mass balance analysis in designing sustainable water management strategies, and the emerging trends in water management. Furthermore, the chapter explores the integration of smart program management and the role of citizen engagement in the design and development of smart cities in the GCC countries and finally challenges and concerns facing these programs.

Metaverse is one of the technologies that has the most promise for the future. However, there is less discussion about teaching using the metaverse. It is possible that most of the educators are ignorant of the metaverse’s features and its potential uses. The objective of this chapter is to define the metaverse precisely and discusses the various applications, characteristics, and challenges of metaverse in Education. This chapter explores the pioneering efforts in leveraging the metaverse for educational purposes, highlighting key examples and their impact on the learning experience. The possible applications of metaverse and research encounters in context to education are further reviewed and then explained and included the Artificial Intelligence (AI) functions in the world of metaverse along with learning based on metaverse. Researchers in the domains of educational technology and computer science shall advance an inclusive insight of the metaverse and its potential applications in education using various metaverse techniques like gamified learning, virtual learning, etc. Also, the metaverse role in education starting from the perception of AI has been covered.