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Flooding is China’s most frequent and catastrophic natural hazard, causing extensive damage. The aim of this study is to develop a comprehensive assessment of urban flood risk in the Hubei Province of China, focusing on the following three issues: (1) What are the factors that cause floods? (2) To what extent do these factors affect flood risk management? (3) How to build an effective comprehensive assessment system that can be used to reduce flood risk?

This study combines expert opinion and evidence from the extent literature to identify flood risk indicators across four dimensions: disaster risk, susceptibility, exposure and prevention and mitigation. The Criteria Importance Through Intercriteria Correlation (CRITIC) and the Grey Relational Analysis (RA)-based Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) decision-making approach were applied to calculate the weighting of factors and develop a model of urban flood risk. Then, ArcGIS software visualizes risk levels and spatial distribution in the cities of Hubei Province; uncertainty analysis verified method accuracy.

The results show that there are significant differences in the level of urban flood risk in Hubei Province, with cities such as Tianmen, Qianjiang, Xiantao and Ezhou being at high risk, while cities such as Shiyan, Xiangyang, Shennongjia, Yichang, Wuhan and Huanggang are at lower flood risk.

The innovative method of combining CRITIC-GRA-TOPSIS reduces the presence of subjective bias found in many other flood risk assessment frameworks. Regional data extraction and uncertainty analysis enhance result reliability, supporting long-term decision-making and urban planning. Overall, the methodological approach developed provides an advanced, highly effective and efficient analysis and visualization of flood risk. This study deepens the understanding of flood risk assessment mechanisms and more broadly supports the development of resilient cities.

Predicting commodity futures trading volumes represents an important matter to policymakers and a wide spectrum of market participants. The purpose of this study is to concentrate on the energy sector and explore the trading volume prediction issue for the thermal coal futures traded in Zhengzhou Commodity Exchange in China with daily data spanning January 2016–December 2020.

The nonlinear autoregressive neural network is adopted for this purpose and prediction performance is examined based upon a variety of settings over algorithms for model estimations, numbers of hidden neurons and delays and ratios for splitting the trading volume series into training, validation and testing phases.

A relatively simple model setting is arrived at that leads to predictions of good accuracy and stabilities and maintains small prediction errors up to the 99.273th quantile of the observed trading volume.

The results could, on one hand, serve as standalone technical trading volume predictions. They could, on the other hand, be combined with different (fundamental) prediction results for forming perspectives of trading trends and carrying out policy analysis.

This study aimed to analyze the impact of enterprise digital transformation on bank loan contracting from 2007 to 2021.

This study used an empirical approach to examine the impact of digital transformation on bank loan interest rates and the possible mechanisms. The digital transformation data of firms were obtained by Python, and the bank loan contracting information of Chinese listed firms was hand-collected from the notes of the annual report.

The results show that digital transformation can significantly reduce the bank loan interest rate and show heterogeneity in the nature of property rights, industry type and firm size. The above results remain significant after conducting a series of robustness tests. Channel tests suggest that digital transformation can promote total factor productivity, improve firms’ information environment and reduce the risk of financial distress, thus helping them reduce their loan interest rate. In addition, banks’ digital transformation can also affect the link between enterprise digital transformation and bank loan interest rates.

First, this paper deeply investigates the relationship between enterprise digital transformation and bank loan contracting, and the mechanisms behind it which expands the research on economic consequences of digitalization. Developing digitalization society has been a top priority in China as it is an urgent task to survive in the competitive global economic environment as a developing country. Second, in developed countries, the evidence relating to bank loan contracting is plentiful. However, the Chinese studies are still very limited as it has no database like Dealscan in US.

This study aims to fabricate the reduced graphene oxide (rGO)/ethylene vinyl acetate copolymer (EVA) composite films with electric-driven two-way shape memory properties for deployable structures application. The effect of dicumyl peroxide (DCP) and rGO on the structure and properties of the rGO/EVA composite films were systematically investigated.

The rGO/EVA composite films were fabricated by melting blend and swelling-ultrasonication method, DCP and rGO were used the crosslinking agent and conductive filler, respectively.

The research results indicate that the two-way shape memory properties of rGO/EVA composite films were significantly improved with the increase of DCP content. The rGO endowed rGO/EVA composite films with excellent electric-driven reversible two-way shape memory and anti-ultraviolet aging properties. The sample rGO/EVA-9 can be heated above Tm within 8 s at a voltage of 35 V and can be heated above the Tm temperature within 12 s under near-infrared light (NIR). Under a constant stress of 0.07 MPa, the reversible strain of the sample rGO/EVA-9 was 8.96% and its electric-driven shape memory behavior maintained great regularity and stability.

The rGO/EVA composite films have potential application value in the field of deployable structures.

With the increase of DCP content, the two-way shape memory properties of rGO/EVA composite films were significantly improved, which effectively solved the problem that the shape memory properties of EVA matrix decreased caused by swelling. The rGO endowed rGO/EVA composite films with excellent electric/NIR driven reversible two-way shape memory properties.

Open innovation platform has become an effective field through which enterprises can acquire valuable knowledge for incremental and breakthrough innovation. However, as more entities join the innovation platform, the knowledge activities in the platform ecosystem are now facing higher complexity and vulnerability due to the differences in the knowledge demands as well as conflicting interest claims of participants. The lack of mature governance mechanisms has caused opportunistic behaviors like knowledge infringement, leakage and hiding, which seriously hinder the in-depth knowledge sharing and effective utilization. What’s more, the enthusiasm for collaborative innovation also reduced among multi-subjects. Therefore, the purpose of this study is to improve platform participants’ innovation ambidexterity under the guidance of scientific design of platform knowledge governance mechanisms through improved knowledge transformation processes.

Therefore, based on knowledge governance theory and knowledge transformation model (SECI, socialization-externalization-combination-internalization), the study explored the influence of relationship and contractual knowledge governance on the innovation ambidexterity of platform participants through the mediation effect of knowledge transformation. To better analyze complex causal relationships among variables and the chain multiple mediation effect, structural equation modeling is used, coupled with bootstrap analysis verification.

Platform contractual governance and relationship governance can positively influence the innovation ambidexterity of participants through knowledge trading and reuse, as well as through knowledge sharing and creation. The findings not only contribute to optimizing the effectiveness of knowledge activities on digital platforms but also provide empirical evidence and practical insights to support enterprises’ incremental and breakthrough innovation according to their own knowledge bases.

The findings offer valuable insights for providing decision-making guidance not only for platform-leading enterprises but also for individual and enterprise users on effectively using open innovation platforms to conduct knowledge seeking, trading or sharing and knowledge reuse or creation to enlarge the incremental innovation value and to trigger breakthrough innovation value in their product and technology developments.

Through diverse knowledge governance mechanisms, platform-leading enterprises do not only act as “economic agents” with private attributes to reduce knowledge asymmetry in the public trading market, diffuse knowledge broadly and mitigate cooperation costs to increase economic value; they also serve as “social actors” for multilateral participants to increase the cohesion of knowledge sharing and creation to provide sustainable knowledge fuel for the higher level of breakthrough innovation. Overall, knowledge arrangement efficiency can be optimized, and breakthrough innovation value can be activated in a well-governed platform, gradually escaping the diminishing marginal benefits of exploitative innovation.

This study has extended the views of the knowledge transformation model under the platform context and proposed dualistic knowledge transformation pathways, named “tacit knowledge socialization” and “explicit knowledge combination,” respectively. Besides, it discovered that under the contractual and relationship knowledge governance mechanisms’ guiding, participants in open innovation platforms may choose different knowledge searching and exchange ways according to their knowledge needs and thus trigger the different knowledge transform process. Then, “tacit knowledge socialization” transformation can show larger positive impact on breakthrough innovation, while “explicit knowledge combination” transformation makes larger impact on incremental innovation.

Over the past 20 years, entrepreneurial ecosystems (EEs) have emerged as a significant research field, inspiring several scholars to provide valuable contributions. The chapter aims to map the current state of literature by highlighting the most prominent research strands and the main theoretical lenses employed in the research field. By carrying out a systematic literature review and bibliometric analysis, the study examines articles published over a period of 27 years. The time frame from 1996 to 2023 offers an extensive outlook of the field’s evolution and current trends, resulting in the identification of five research strands and different future research avenues. From the analysis of prior research works, this study provides an in-depth examination of the complex nature of EEs. The results hold theoretical and practical implications. From the scholars’ point of view, they offer future research directions to move the current level of knowledge forward. From the entrepreneurs’ perspective, they provide valuable insights to address ongoing challenges and catch new opportunities within the dynamic panorama of EEs. Therefore, the insights are poised to drive future research, inform policymakers, and enhance business strategies aimed at fostering resilient EEs. In other words, the purpose is to provide readers with a well-rounded understanding over the state of the literature on EEs and the research strands that deserve further exploration.

Cross-cultural cognitive paradoxes have frequently broken the existing boundaries of knowledge and stimulated demands for knowledge creation (KC), and such paradoxes have triggered and will continue to trigger novel risks in the context of international business (IB). Given the nascency of relevant issues, this study aims to develop a more comprehensive understanding of KC across cultures by proposing a Yin-Yang dialectical systems theory of KC as micro-foundation to more systematically frame the risk/paradox-resolving mechanism elicited by cultural collisions.

This paper is conceptual in nature. The authors first critically review the literature to lay a broad theoretical foundation. Integrating the philosophy- and praxis-based views, the authors reposition knowledge as a Yin-Yang dialectical system of knowing, with yin representing the tacit while yang represents the explicit. Next, the authors justify the underling logic of realising KC through a contradiction-resolving process. On this basis, the authors draw upon the Yijing’s Later Heaven Sequence (LHS) as the source domain of a heuristic metaphor to reconceptualise KC as a dynamic capability in the IB context.

Using the LHS paradigm to metaphorically map the intricate patterns of interaction and interconnectivity among the involved individuals, organisations and all related stakeholders, this research identifies and theorises the overall dynamic capability of KC in the IB context, which comprises five sets of processes: contradiction, conflict, communication, compromise and conversion.

This research highlights that KC is simultaneously activated and constrained by human actions as well as by the socially constructed context in which it emerges, which helps individuals, organisations and policy makers more clearly frame the novel risks induced by cross-cultural cognitive conflicts in the IB context.

The authors synthesise Yin-Yang dialectics with the approach of collective phronesis, proposing a novel, praxis-oriented Yin-Yang dialectical systems theory of KC. It provides a deeper understanding of the epistemological paradox inherent in all knowledge, thus enabling KC to be rationalised by a sounder logical reasoning. By fusing the macro and micro perspectives on KC, the authors also enrich existing theory and future theory building in the domain of knowledge management.

With the accumulation of theoretical research and practical experience in the field of garment production research, it is imperative to methodically analyze and reflect on the achievements that have been made. This review aims to systematically map the academic landscape of research articles on garment production, elucidate the evolutionary trajectory of this discipline, identify emerging research frontiers and provide insights into its prospects.

Based on the Web of Science core database, 307 research articles were systematically analyzed by CiteSpace software. The study employed bibliometric and thematic analyses to offer in-depth insights into the dynamics and evolution of research on garment production.

Results reveal that keyword analysis emphasizes the significance of topics such as apparel assembly line, lean production, circular economy, fuzzy logic, global production networks, social sustainability and supply chain management in garment production research. Citation analysis demonstrates that articles related to environmental impact, supply chain management, production process and production technology constitute the knowledge base and core of garment production research. Eight principal research themes emerge: customized garment production, production technology, quality assurance, equipment, production lines, supply chain management, environmental impact and social and human impact. Future research hotspots will focus more on sustainable, intelligent and digital clothing production.

The findings systematically sort out the hotspots and trends in garment production, establish knowledge structures and display them through intuitive representations. The rich insights set the stage for the development of garment production and provide future guidance for theoretical research.

The purpose of this study is to explore the interfacial adhesion between superhydrophobic coatings FC-X (X = 1%, 2%, 3%, 4% and 5%) and the concrete substrate, along with the impact of FC-X on the water repellency characteristics of the concrete substrate.

One synthetic step was adopted to prepare novel F-SiO₂ NP hybrid fluororesin coating. The impact of varying mass fractions of F-SiO₂ NPs on the superhydrophobicity of FC-X was analyzed and subsequently confirmed through water contact angle (WCA) measurements. Superhydrophobic coatings were simply applied to the concrete substrate using a one-step spraying method. The interfacial adhesion between FC-X and the concrete substrate was analyzed using tape pasting tests and abrasion resistance measurements. The influence of FC-X on the water repellency of the concrete substrate was investigated through measurements of water absorption, impermeability and electric flux.

FC-4% exhibits excellent superhydrophobicity, with a WCA of 157.5° and a sliding angle of 2.3°. Compared to control sample, FC-X exhibits better properties, including chemical durability, wear resistance, adhesion strength, abrasion resistance, water resistance and impermeability.

This study offers a thorough investigation into the practical implications of enhancing the durability and water repellency of concrete substrates by using superhydrophobic coatings, particularly FC-4%, which demonstrates exceptional superhydrophobicity alongside remarkable chemical durability, wear resistance, adhesion strength, abrasion resistance, water resistance and impermeability.

Through the examination of the interfacial adhesion between FC-X and the concrete substrate, along with an assessment of FC-X’s impact on the water repellency of the concrete, this paper provides valuable insights into the practical application of superhydrophobic coatings in enhancing the durability and performance of concrete materials.

This paper aims to examine how the number of short videos posted and the number of influencers employed, two important strategies in short video marketing, affect consumer behavior and how price discounts moderate the effects of influencer endorsement on consumer browsing and purchasing behavior.

Drawing on the literature on influencer endorsement, this study used an ordinary least square model to empirically examine the two effects of endorsement strategies in increasing product traffic and sales for consumers at a short video app, Douyin (TikTok).

The results show that the number of short video ads produces the classic inverted U-shape for traffic and sales, and both effects were strengthened under a high discount condition. Whereas the number of influencers has a positive effect on traffic but produces an inverted U-shape for sales, both effects were undermined under a high discount condition.

This study is the first to explore the two distinct effects (repetition effect and diffusion effect) of influencer endorsement on browsing and purchasing behavior and theorize about the moderate effects of discounts on these effects.