Search Results (4,225)

In this paper, we present a new integral operator that acts on a class of meromorphic functions on the punctured unit disc ${\mathbb{U}}^{*}$. This operator enables the definition of a new subclass of meromorphic univalent functions. We obtain sharp bounds for the Fekete–Szegö inequality and the second Hankel determinant for this class. The theoretical approach is based on differential subordination. Furthermore, we link these theoretical insights to applications in 2D electromagnetic field theory by outlining a physical framework in which the operator functions as a field transformation kernel. We show that the operator’s parameters correspond to physical analogs of field regularization and spectral redistribution, and we use subordination theory to simulate the design of vortex-free fields. The findings provide new insights into the interaction between geometric function theory and physical field modeling. Full article

Today’s linear nutrient flows are rooted in a long history of agronomic and wastewater engineering strategies that have created cascading environmental, social, and economic side effects, signaling the need for more holistic and circular approaches. Our examination of the regulatory pathways that enable and constrain urine recycling—an underutilized approach to repurposing human waste as fertilizer—addresses a persistent research gap related to the mainstreaming of transformative technologies. Framed around policy process theories—Street Level Bureaucracy and Multiple Streams Theory—our methods include a review and mapping of 54 regulatory documents; action research where we reflect on our own efforts to expand urine recycling; and interviews with 16 practitioners and regulators in four states which, to our knowledge, are the only places in the US with efforts to scale up urine recycling in community settings. Given its circular nature, a key challenge we find is a lack of clarity around which sectors, or what scales of government, “own” the decision to allow the collection and use of urine as a fertilizer. Working around these challenges, we show how practitioners use many practical strategies to simplify the approval process and reduce the risk aversion regulators face when confronted with ambiguous rulemaking. Full article

Smart mobility has emerged as a transformative enabler for achieving the United Nations Sustainable Development Goals (SDGs), offering technological and systemic solutions to pressing urban challenges such as congestion, environmental degradation, accessibility, and economic inclusion. Realizing this potential, however, depends not only on technological maturity but also on robust education and capacity-building frameworks. This paper addresses two critical gaps: the absence of a systematic review of structured academic curricula, vocational training programs, and professional development pathways dedicated to smart mobility, and the lack of a formal approach to demonstrate how structured, research-oriented education can effectively bridge theory and practice. The review examines a wide spectrum of initiatives, including academic programs, industry training, challenge-based competitions, and community-driven platforms. The analysis shows significant progress in Europe and North America but also reveals important gaps, particularly the limited availability of structured initiatives in the Global South, the underrepresentation of accessibility and inclusivity, and the insufficient integration of governance, ethical AI, policy, and cybersecurity. A case study of the AI for Smart Mobility course, developed using a design science methodology, illustrates how research-oriented education can be operationalized in practice. Since 2020, the course has engaged hundreds of students and professionals, with project dissemination through the AI4SM Medium hub attracting more than 20,000 views and 11,000 reads worldwide. The findings highlight both the progress made and the persistent gaps in smart mobility education, underscoring the need for wider geographic reach, stronger emphasis on inclusivity and governance, and structured approaches that effectively link theory with practice. Full article

The dialects discussed in this article were considered Belarusian in the early 20th century, and later, as a result of the transfer of the administrative (state) border, they became part of the Russian territory and were considered Russian. The changes occurring in these dialects as a result of the influence of the standard Russian language are interesting from various perspectives. Firstly, the linguistic self-identification of dialect speakers changes and the perception of their dialect as less prestigious compared to the standard language is formed. Secondly, linguistic features that dialectologists previously defined as characteristic of the Belarusian language are being replaced by standard Russian ones. By analyzing the linguistic data obtained from the dialect speakers of different generations, we can trace the emergence of variation and then its loss. Observing which linguistic features are subject to change first, and which remain more stable, allows us to examine linguistic changes through the lens of the “hierarchy of borrowings” theory. Additionally, given the linguistic inequality between the dialect and the standard language, we can observe the gradual transformation of the dialect under the influence of the prestigious standard idiom. Therefore, the loss of Belarusian–Russian variation can be viewed as a process of dedialectization, bringing the dialect closer to the standard language. Full article

Accurate observations of Ocean Surface Wind Speed (OSWS) are vital for predicting extreme weather and understanding ocean–atmosphere interactions. However, spaceborne sensors (e.g., ASCAT, SMAP) often experience data loss due to harsh weather and instrument malfunctions. Existing inpainting methods often rely on reanalysis data that is released with delays, which restricts their real-time capability. Additionally, deep-learning-based methods, such as Transformers, face challenges due to their high computational complexity. To address these challenges, we present the Multimodal Wind Speed Inpainting Dataset (MWSID), which integrates 12 auxiliary forecasting variables to support real-time OSWS inpainting. Based on MWSID, we propose the MMamba framework, combining the Multimodal Feature Extraction module, which uses mutual information (MI) theory to optimize feature selection, and the OSWS Reconstruction module, which employs Attention-Mamba-2 within a Residual-in-Residual-Dense architecture for efficient OSWS inpainting. Experiments show that MMamba outperforms MambaIR (state-of-the-art) with an RMSE of 0.5481 m/s and an SSIM of 0.9820, significantly reducing RMSE by 21.10% over Kriging and 8.22% over MambaIR in high-winds (>15 m/s). We further introduce MMamba-L, a lightweight 0.22M-parameter variant suitable for resource-limited devices. These contributions make MMamba and MWSID powerful tools for OSWS inpainting, benefiting extreme weather prediction and oceanographic research. Full article

Driven by the new wave of technological revolution and industrial transformation, firms are accelerating strategic change to gain new competitive advantages. Situated within a complex adaptive system, firms must adapt to highly dynamic and uncertain external environments by adjusting executive cognitive structures, reconfiguring resources and capabilities, and strengthening collaboration with industrial ecosystem elements; hence, digital strategic change is characterized by continuous evolution. Using a sample of Chinese A-share listed firms from 2015 to 2023, this study develops a “cognition–capability–strategy” pathway model grounded in upper echelons theory and dynamic capabilities theory to examine how executive cognitive styles, i.e., cognitive flexibility and cognitive complexity, drive digital strategic change via absorptive capacity and how environmental dynamism moderates these relationships. The findings show that executive cognition, as a decision node in strategic change, can dynamically adjust firms’ strategic paths by activating absorptive capacity in rapidly changing external information environments; environmental dynamism differentially affects the two cognitive styles. Heterogeneity tests further indicate that the role of executive cognition varies significantly with regional digital economy development levels, firm life cycle, and industry factor intensities. The study reveals how firms can respond to high environmental uncertainty through cognition–strategy alignment and resource capability reconfiguration in a complex adaptive system, providing theoretical references and practical insights for emerging economies to advance digital transformation and enhance competitiveness. Full article

In order to scientifically and reasonably evaluate the digital transformation and upgrading level of “emerging industry” innovation ecosystems, this paper firstly uses the grounded theory to extract the factors influencing the digital transformation and upgrading of the emerging industry innovation ecosystems. Secondly, a cloud model is introduced to evaluate the importance of the influencing factors, select the important factors, and construct an evaluation index system. Thirdly, the projection pursuit model based on the quantum genetic algorithm is used to search for the optimal projection direction and determine the weight and comprehensive evaluation value of each index. Finally, the digital transformation and upgrading levels of 506 innovation subjects are divided into a budding level (I), growth level (II), and mature level (III) based on K-means and the SVM—most of which are at a medium–low level. Therefore, countermeasures and suggestions for promoting the digital transformation and upgrading of the emerging industry innovation ecosystems are put forward. This paper provides a systematic and complete method for the evaluation of digital transformation and upgrading of the emerging industry innovation ecosystems. Further, this paper promotes the combination of qualitative and quantitative analysis and realizes the effective integration of the overall logic chain of theoretical demonstrations, method design, and data analysis. Full article

The development of the digital economy has become a significant driving force for the innovation of green technology in the manufacturing sectors. Green technology innovation in the manufacturing sectors is not only a key engine for realizing economic green transformation and achieving the goal of achieving peak carbon emissions by 2030 and carbon neutrality by 2060, but also an important path for cultivating new quality productivity. Based on Schumpeter’s endogenous growth theory, in this study, we constructed an analytical model with a unified framework of digital economic development and environmental regulation, systematically explored the mechanism of digital economic development with respect to green technological innovation in the manufacturing sectors and the moderating effect of environmental regulation, and carried out empirical research based on panel data at the provincial level and the level of the subdivided manufacturing sectors in China. We found that the development of the digital economy promotes green technology innovation in the manufacturing industry. However, according to the theory of increasing marginal information costs, it shows a significant nonlinear relationship. Absorptive capacity is the key means of support that manufacturing enterprises can leverage to improve their level of green technological innovation. Environmental regulation plays a crucial role in guiding green technological innovation in the manufacturing sectors. A further heterogeneity analysis showed that the development of the digital economy exerts a stronger positive impact on green technological innovation in cleaner-production-oriented manufacturing sectors and those located in regions with more advanced financial regions and in technology-intensive industries. This study provides theoretical support for understanding the driving mechanisms of green technological innovation in the manufacturing sector against the backdrop of the digital economy, offering practical implications for optimizing environmental regulation policies and enhancing the level of green development in manufacturing. Full article

This paper proposes a formal descriptive model for understanding the evolution of characters in detective fiction from the 19th to the 20th century, using methodologies and technologies from the Semantic Web. The integration of Digital Humanities within the theory of comparative literature opens new paths of study that allow for a digital approach to the understanding of intertextuality through close reading techniques and ontological modelling. In this research area, the variety of possible textual relationships, the levels of analysis required to classify these connections, and the inherently referential nature of certain literary genres demand a structured taxonomy. This taxonomy should account for stylistic elements, narrative structures, and cultural recursiveness that are unique to literary texts. The detective figure, central to modern literature, provides an ideal lens for examining narrative intertextuality across the 19th and 20th centuries. The analysis concentrates on character traits and narrative functions, addressing various methods of rewriting within the evolving cultural and creative context of authorship. Through a comparative examination of a representative sample of detective fiction from the period under scrutiny, the research identifies mechanisms of (meta)narrative recurrence, transformation, and reworking within the canon. The outcome is a formal model for describing narrative structures and techniques, with a specific focus on character development, aimed at uncovering patterns of continuity and variation in diegetic content over time and across different works, adaptable to analogous cases of traditional reworking and narrative fluidity. Full article

In the era of digital business model innovation, multinational corporations face a dual challenge: leveraging digital technologies to overcome institutional barriers while reconfiguring value creation in cross-border operations. Grounded in institutional theory and the digital transformation literature, this study investigates how knowledge distance and political distance shape subsidiary exits through a U-shaped relationship, and how digital transformation breadth and depth differentially reconfigure these effects. We conduct empirical research on 1203 Chinese multinational enterprises from 2015 to 2019. The results indicate that both knowledge distance and political distance exhibit a U-shaped relationship with the subsidiary exit. The breadth of digital transformation strengthens the U-shaped relationship between knowledge distance and subsidiary exit but weakens the relationship between political distance and subsidiary exit. The depth of digital transformation mitigates the effects of both knowledge distance and political distance on subsidiary exit. These findings provide a novel explanatory perspective on the ‘Distance Paradox’ in internationalization theory, address a critical gap in the multinational enterprise (MNE) exit literature, and propose a modular governance blueprint for MNEs. Full article

This research investigates how transformational leadership affects the innovative behavior of knowledge-based employees in Chinese high-tech enterprises, highlighting the mediating role of organizational innovation climate. It aims to reveal how leadership shapes innovation-supportive climates to stimulate employee innovative behavior and strengthen organizational sustainable innovation. Using a questionnaire survey of 441 knowledge workers from 10 high-tech firms across four Chinese provinces, this study applies structural equation modeling (SEM) to test both the direct effect of transformational leadership on employee innovative behavior and its indirect effect via organizational innovation climate. The transmission effect of employee innovative behavior on sustainable innovation was also analyzed. Results indicate that transformational leadership significantly promotes employee innovative behavior directly and indirectly through organizational innovation climate. By fostering a supportive climate, leadership enhances employee enthusiasm for innovation, which in turn drives sustainable innovation. These findings provide contextual evidence of leadership’s role in shaping innovative behavior and long-term organizational outcomes in emerging economies. This study builds a cross-level framework of “transformational leadership—organizational innovation climate—employee innovative behavior—organizational sustainable innovation,” integrating four theories. It extends theoretical links between employee behavior and sustainable innovation, emphasizes the overlooked mediating role of organizational climate, and offers practical guidance for knowledge-intensive enterprises seeking to enhance sustainable innovation. Full article

As Chinese cities move toward stock-based development, the redevelopment of inefficient industrial land has become essential for urban spatial restructuring and sustainable transformation. Building on Lefebvre’s triadic theory of spatial production, this study establishes a comprehensive analytical framework consisting of spatial practice, representations of space, and representational spaces, aiming to elucidate the mechanisms underlying spatial reconfiguration. Through a multi-case inductive approach, twelve representative cases from Zhejiang Province are systematically analyzed to reveal the fundamental logic driving spatial reconstruction within the context of inefficient land redevelopment. The results reveal the following: (1) In the process of inefficient land redevelopment, spatial practice involves land reuse and functional integration, representations of space reflect institutional planning, and representational spaces shape meaning through cultural identity and user experience. These dimensions interact dynamically to drive the transformation of both the form and meaning of inefficient land. (2) The redevelopment of inefficient land in Zhejiang can be classified into two primary models: increment-driven and qualitative transformation, which are further divided into seven subtypes. The increment-driven model includes enterprise-initiated renewal, integrated upgrading, platform empowerment, and comprehensive remediation; the qualitative transformation model comprises mine remediation, cultural empowerment, and use conversion. (3) Significant differences exist between these models: the increment-driven model emphasizes land expansion and floor area ratio improvement, while the qualitative transformation model enhances land value through mine restoration, cultural embedding, and functional transformation. This study extends the application of spatial production theory within the Chinese context and offers theoretical support and policy insights for the planning and governance of inefficient industrial land redevelopment. Full article

As protected areas (PAs) expand globally at an accelerating rate, reconciling biodiversity conservation with socioeconomic development in adjacent communities has become a critical challenge for landscape sustainability. This systematic review synthesizes literature (1990–2025) to trace three interconnected transitions: (1) the conceptual evolution from exclusionary to inclusive PA–community paradigms, grounded in shifting perceptions of cultural landscapes; (2) the governance transformation from tokenistic participation to power-sharing co-management frameworks; and (3) the spatial planning progression from fragmented “island” models to integrated protected area networks (PANs) leveraging ecological corridors. Our analysis reveals that disconnected PA–community relationships exacerbate conservation–development conflicts, particularly where cultural landscapes are undervalued. A key finding is that cultural–natural synergies act as pivotal mediators for conservation efficacy, necessitating context-adaptive governance approaches. This study advances landscape planning theory by proposing a rural landscape network framework that integrates settlement patches, biocultural corridors, and PA matrices to optimize ecological connectivity while empowering communities. Empirical insights from China highlight pathways to harmonize stringent protection with rural revitalization, underscoring the capacity of PANs to bridge spatial and socio-institutional divides. This synthesis provides a transformative lens for policymakers to scale locally grounded solutions across global conservation landscapes. Full article

The rapid expansion of e-commerce has pushed firms to adopt more sophisticated digital marketing strategies to reach, engage, and retain consumers. Research has shown that digital marketing significantly enhances firm performance by enhancing marketing-related capabilities, yet overlooks its role in driving transformation across other business functions. Grounded in resource orchestration theory, this study examines how digital marketing resources and capabilities support broader business transformation and comprehensively improve firm performance. Drawing on empirical data from Chinese A-share listed manufacturing firms from 2010 to 2023, this study demonstrates that there is a significant positive relationship between digital marketing capability and firm performance. Notably, this relationship is mediated by production capability and R&D capability. Moreover, the effect is more pronounced in firms operating in highly marketized regions, within competitive industries, and among digitally advanced firms. This study contributes to the digital marketing literature by developing a novel framework for measuring digital marketing capability, and uncovering the mechanisms through which it influences firm performance. In addition, this study contributes to the digitalization literature in the manufacturing sector by demonstrating the strategic role of digital marketing in driving value creation. Implications for digital marketing in manufacturing industry are discussed. Full article

Banking has evolved from ancient times of using grain banks and temple lending to modern banking practices. The transformation of the banking sector has ensured that banks play the crucial role of facilitating faster and efficient service delivery. This paper traced the evolution of banking and examined associated disruptions, opportunities, and challenges. With the specific objective of influencing policy-oriented discussions on the future of banking, this study adopted a literature review methodology of integrating various sources, such as scholarly journals, policy reports, and institutional publications. Public interest theory and disruptive innovation theory underpinned this study. Findings revealed that banking has evolved from Banking 1.0 to Banking 5.0 due to disruptive factors which have been pivotal to the significant structural sector changes: Banking 1.0 (pre-1960s); Banking 2.0 (1960s to 1980s); Banking 3.0 (1980s–2000s); Banking 4.0 (2000s–2020s); and Banking 5.0 (2020s to the future). Despite the existence of opportunities in the transformation, challenges include regulations, skills shortages, legacy systems, and cybersecurity that must be addressed. This calls for a coordinated response from stakeholders, with banking’s future requiring collaborations as cashless economies, digital economies, and digital currencies take centre stage. Full article