Patterns Of Innovation Research Articles

Innovation Diffusion in Land Resource Use Practices Around Cameroon’s Hollow Frontiers

Innovation diffusion has been extensively explored in several contexts, with little application to hollow frontiers—economically attractive areas with resource opportunities. This dearth of scientific data bedevils the design of resource-planning approaches for hollow frontiers. Using the innovation diffusion model as an analytical lens, this study; (1) maps key resources and actors engaged in the Mungo corridor hollow frontier, (2) analyzes the differential patterns of innovation and the forces that drive them, and (3) explores the management implications of resource-linked innovation diffusion. A random sample of 100 households was conducted in the Njombe-Penja communities of the Mungo Corridor. The analysis reveals the following: Firstly, rich fertile soils, forests, quarries and water resources are the key resources exploited by farmers, bureaucrats, businessmen, NGOs and other enterprises who constitute the key innovation actors in Njombe-Penja. Secondly, differential patterns of innovation exist, with techniques and products introduced by companies/state departments to farmers and by NGOs and technical/research departments to communities and state, private and community-based enterprises. This leads to varied resource use outcomes. Innovations are significant in the domain of agriculture (62%) and quarrying (65%), moderately significant in the forest sector (55%) and least significant in water resources (48%). Economic (63%), natural (25%), socio-cultural (23.7%) and political drivers (50%) explain the diverse outcomes linked to innovation diffusion. Finally, the most significant implications of innovations are in the domain of agriculture through improved cropping systems and the use of disease-resistant species. Here, specialization in cash crop cultivation and fruit culture (white pepper, pawpaw, pineapples) is predominant. Additionally, this sector has witnessed the introduction of new methods of cultivation. The least significant implications were recorded for forest use practices. Innovations sustain new dynamics for this resource-rich area and provide new opportunities for reflections on reorganizing resource use for successful management. Power manifestations in the context of the diffusion of innovations are new areas to consider for further research.

Ring-Opening Polymerization of Surface Ligands Enables Versatile Optical Patterning and Form Factor Flexibility in Quantum Dot Assemblies.

The evolution of display technologies is rapidly transitioning from traditional screens to advanced augmented reality (AR)/virtual reality (VR) and wearable devices, where quantum dots (QDs) serve as crucial pure-color emitters. While solution processing efficiently forms QD solids, challenges emerge in subsequent stages, such as layer deposition, etching, and solvent immersion. These issues become especially pronounced when developing diverse form factors, necessitating innovative patterning methods that are both reversible and sustainable. Herein, a novel approach utilizing lipoic acid (LA) as a ligand is presented, featuring a carboxylic acid group for QD surface attachment and a reversible disulfide ring structure. Upon i-line UV exposure, the LA ligand initiates ring-opening polymerization (ROP), crosslinking the QDs and enhances their solvent resistance. This method enables precise full-color QD patterns with feature sizes as small as 3µm and pixel densities exceeding 3788 ppi. Additionally, it supports the fabrication of stretchable QD composites using LA-derived monomers. The reversible ROP process allows for flexibility, self-healing, and QD recovery, promoting sustainability and expanding QD applications for ultra-fine patterning and on-silicon displays.

Role of Globalization and Innovation Pattern in Growth of Bank Credit: Evidence From Emerging and Advanced Asia

ABSTRACTThis study examines the role of globalization and innovation pattern (i.e., innovation by the residents and non‐residents) in the growth of domestic bank credit across emerging and advanced Asian economies spanning from 1996 to 2022. The bank credit growth model includes economic growth and real interest rate as important control variables. This study employs Cross Sectional‐Autoregressive Distributed Lag (CS‐ARDL) as an appropriate baseline method because of the cointegration, endogeneity, and cross‐sectional dependency present in the data. The long‐run results for emerging Asian economies indicate that globalization exhibits a negative impact on banking credit, contrasting with the positive influence observed in advanced Asian economies due to heightened economic growth and increased credit demand. Residential innovation consistently bolsters banking credit in both sets of economies, albeit with mixed effects stemming from non‐resident innovation. The long‐run results further indicate the positive (negative) impact of economic growth (real interest rate) on bank credit in emerging and advanced Asian economies. These findings are reliable due to the similar results obtained from using Driscoll‐Kraay Robust Standard Errors (DKSEs) as robust method. For policymakers in emerging economies, the imperative policy lies in striking a delicate balance between economic openness and bank credit, while counterparts in advanced economies are poised to bolster bank credit accessibility through foreign innovation while upholding stringent regulatory oversight.

Obsolescence and Innovation in the Middle English Religious Lexicon

AbstractLexical loss has long been of interest to scholars of the history of English, even though it is difficult to measure and has therefore received less attention than related processes, such as lexical innovation. Recently, the topic has received renewed interest, especially concerning the idea of French replacing large swathes of native vocabulary after the Norman Conquest. Using data from the Historical Thesaurus of English (HT), the present article tracks changes in the Middle English (ME) religious lexis, focusing on nouns and the influence of French and Latin, and investigates patterns of lexical obsolescence and innovation in conjunction with language of origin and semantic specificity. Following Sylvester et al. (2020), semantic specificity is measured by utilising the HT's structure, and etymological information is extracted from the OED and MED. Overall, most lexical items are found at the hypernymic level of the semantic hierarchy. Already in the early ME period, about 30% of the religious lexicon is of Romance origin and this proportion only continues to grow. The proportion of English‐origin items decreases accordingly, although the absolute number stays relatively stable. Peaks in first and last attestations are shown to coincide, likely due to the nature of the available data.

The Path to Urban Sustainability: Urban Intelligent Transformation and Green Development—Evidence from 286 Cities in China

Urban intelligence is reshaping urban innovation patterns, accelerating urban transformation, and significantly influencing green and sustainable development. By applying the non-radial directional distance function and an improved entropy method, this study measures the green development efficiency and levels across 286 Chinese cities from 2006 to 2020. The objectives of this study are twofold: first, to examine the impact of urban intelligence transformation on green development, and second, to investigate how urban intelligence influences common prosperity. The analysis employs a double/debiased machine learning model, with the “Smart City Pilot” policy as the focal point. The findings indicate that (1) urban intelligence transformation enhances both the level and efficiency of green development in Chinese cities; (2) this transformation fosters green development by driving urban innovation, upgrading industrial structures, and promoting green finance; and (3) the impact of urban intelligence varies across cities with different sizes, resource endowments, and marketization levels. Furthermore, the study constructs a common prosperity index to assess how urban intelligence contributes to residents’ well-being and social equity. The results suggest that urban intelligence transformation not only advances green development but also contributes to improving residents’ quality of life, thereby promoting a more equitable and prosperous society. These insights offer crucial policy guidance for China and other countries facing environmental and economic challenges in the digital age.

Evaluating efficiency of green innovations and renewables for sustainability goals

Understanding the efficiency dynamics of green innovations is essential for advancing sustainable economic systems. This study evaluates the efficiency of forty-two countries in producing and utilizing green innovations for clean energy production and in achieving sustainable development goals from 2000 to 2020. Employing a network bias-corrected data envelopment analysis (DEA) and Malmquist productivity analysis, this study explores the adoption of green technology and its effects on economic and environmental efficiency. Findings reveal limited progress in clean energy efficiency across most countries, indicating suboptimal use of green innovations for the goals of affordable and clean energy and climate action). The results show that the efficiency pattern of green innovations follows a U-shaped curve, with initial inefficiencies followed by long-term gains. South American nations and the European Union demonstrate strong performance in integrating green technologies. However, green innovations alone appear insufficient; supportive policies, such as green taxes on emissions and renewable energy initiatives, are crucial for enhancing impact and achieving environmental sustainability.

Application of symbolic language and pattern innovation of Chaoshan peach cake mold in paper packaging design

To explore the symbolic language of the Chaoshan peach cake mold and its innovative applications in modern design, the material form and cultural connotations of the mold patterns were analyzed from a semiotic perspective. Through a symbolic language of the primary pattern elements, the essence of the traditional culture they embody was revealed. Building on this analysis, the generative rules of shape grammar were applied to creatively reinterpret and recombine these traditional pattern elements, resulting in a set of innovative designs that retain the essence of traditional culture while incorporating modern design aesthetics. Furthermore, these innovative patterns were implemented in paper packaging design, and their effectiveness was validated through product evaluation. Through an in-depth exploration and innovative application of the symbolic language of the Chaoshan peach cake mold, a successful fusion of traditional cultural symbols and contemporary design concepts was achieved. This approach provides a new pathway for the inheritance and innovation of Chaoshan peach cake mold culture and offers insights into the modern transformation of other traditional cultures.

Penerapan Metode Stable Diffusion Dengan Fine Tuning Untuk Pola Endek Bali

Endek Bali fabric is a cultural heritage of Bali renowned for its traditional decorative motifs, including floral, fauna, patra, and diamond patterns. Although rich in cultural value, artisans often face challenges in creating new designs that align with market trends while preserving cultural authenticity. Artificial Intelligence (AI) technology, particularly text-to-image generation models, offers a solution to this issue by streamlining the design process and enabling the exploration of new motifs. The Stable Diffusion model, introduced by Stability.AI in 2022 and open source, can be utilized to generate Endek Bali patterns through Fine Tuning techniques. Fine Tuning allows the model to be adapted to specific domains, enhancing its performance in generating textile patterns based on textual descriptions. This study aims to apply the Stable Diffusion model and Fine Tuning techniques to create new patterns and motifs. By using this model, it is hoped that innovative designs can be produced while maintaining the authenticity and local cultural values of Bali. The research demonstrates that the Fine-Tuned Stable Diffusion model is effective in creating Endek Bali patterns with high accuracy, as evaluated by Clip Similarity, with the highest scores achieved for Floral Patterns (92.43), followed by Decorative (free-form motifs) Floral (88.77), Decorative (free-form motifs) Geometric (87.94), and Decorative (free-form motifs) (85.79). These findings indicate the model’s flexibility and effectiveness in producing intricate textile designs, enabling designers and artisans to generate complex and innovative patterns solely from textual descriptions while preserving Bali’s cultural values.

Global Patterns of Innovation: Comparing Business Model Canvas Implementations in Fab Labs Around the World

This paper compares the implementation of the Business Model Canvas (BMC) across Fab Labs in the Netherlands, Indonesia, and the UK, focusing on their operational models and innovation practices within distinct cultural contexts. Through case studies of Waag Society’s FabLab (Netherlands), The House of Natural Fiber (HONF) FabLab (Indonesia), and Fab Lab Manchester (UK), the study highlights key differences in value propositions, customer segments, channels, customer relationships, revenue streams, key resources, key activities, key partners, and cost structures. These differences are largely influenced by cultural dimensions. The findings provide valuable insights for the global promotion and development of Fab Labs, offering reference points for policymakers, entrepreneurs, and educational institutions.

The effectiveness of Gen AI in assisting students’ knowledge construction in humanities and social sciences courses: learning behaviour analysis

ABSTRACT Currently, generative AI has undergone rapid development. Numerous studies have attested to the benefits of Gen AI in programming, mathematics and other disciplines. However, since Gen AI mostly uses English as the intrinsic training parameter, it is more effective in facilitating the teaching of courses that use international common notation, but few scholars have researched the fitness of Gen AI-assisted teaching of humanities courses in Chinese-language environments. To address these gaps, this study examined the learning behaviours of 30 students using Gen AI to help them answer questions on economic law tests using the Lag Sequential Analysis. The results show that the following: (1) The use of Gen AI to aid learning in an economic law course did not significantly improve the cognitive level of academics from the perspective of knowledge construction. (2) According to the characteristics of students’ behavioural paths via Gen AI-assisted learning, their behavioural patterns can be classified into autonomous and innovative, moderate, and lacking innovation. (3) Different learning modes when Gen AI-assisted teaching was used affected the final results, which were as follows: High-performing students favoured the autonomous and innovative pattern, medium-performing students favoured the moderate pattern, and low-performing students favoured the lacking innovation pattern.

Driving Effects and Spatial Spillover of Technological Innovation on the Carbon Balance of Agriculture

<p style="text-align:justify"><span style="font-size:10.5pt"><span style="line-height:150%"><span style="font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:12.0pt"><span style="line-height:150%"><span style="font-family:"Times New Roman",serif">There is significant controversy over the overall effects of technological innovation on carbon balance. Based on panel data of agriculture from 28 provinces in China from 2009 to 2021, utilizing ArcGIS and spatial Durbin model, the spatial-temporal patterns of agricultural technological innovation and carbon balance are analyzed, and furtherly the spatial effects of technological innovation on carbon balance are examined. The results indicate: (1) the overall agricultural carbon surplus in Chinese provinces has been continuously increasing from 2009 to 2021; (2) the direct effect of technological innovation on the carbon surplus in agriculture is significantly positive, while the spatial spillover effect is significantly negative; (3) the mediating effect results show that technological innovation affects the output of the agricultural sector and thereby influences agricultural carbon balance; (4) the impact of technological innovation on agricultural carbon balance exhibits an asymmetric spatial spillover effect. Advantageous regions suffer from the positive effects of spatial spillover, while non-advantageous regions benefit from the negative impacts of spillover, resulting in an overall negative effect. This study's findings play an important role in addressing the existing controversy over the overall effects of technological innovation on carbon balance and provide important insights for formulating policies on low-carbon technological innovation in agriculture.</span></span></span></span></span></span></p>

Why high-speed rail causes heterogeneous spatial patterns in firm innovation: Perspectives from intensive and extensive margins.

This study examines the impact of high-speed rail (HSR) on corporate innovation in China, analyzing county-level patent applications. Utilizing difference-in-differences regression, we break down the overall impact of HSR connectivity on innovation into two categories: extensive margins, where a greater number of firms become innovative, and intensive margins, where individual firms increase their level of innovation. HSR access has increased patent applications, particularly in manufacturing and non-high-tech services, affecting both margins. However, in high-tech services, the impact is significant only on the extensive margin. Effects vary between urban areas and peripheral counties, with knowledge spillovers and brain drain as key predictors.

Combinatorial innovation and lifecycle analysis of low-carbon energy technologies in China

Measuring the lifecycle of low-carbon energy technologies is critical to better understanding the innovation pattern. However, previous studies on lifecycle either focus on technical details or just provide a general overview, due to the lack of connection with innovation theories. This article attempts to fill this gap by analyzing the lifecycle from a combinatorial innovation perspective, based on patent data of ten low-carbon energy technologies in China from 1999 to 2018. The problem of estimating lifecycle stages can be transformed into analyzing the rise of fall of knowledge combinations. By building the IPC co-occurrence matrix, this paper demonstrates the lifecycle evolution of technologies graphically constructs an efficient quantitative index to divide lifecycle stages. The mathematical measurement can effectively reflect the evolutionary pattern of technologies. Additionally, this article relates the macro evolution of lifecycle to the micro dynamic mechanism of technology paradigms. The sign of technology maturity is that new inventions tend to follow the patterns established by prior ones. Following this logic, this paper identifies different trends of paradigms in each technology field and analyze their transition. Furthermore, catching-up literature shows that drastic transformation of technology paradigms may open “windows of opportunity” for laggard regions. From the results of this paper, it is clear to see that latecomers can catch up with pioneers especially when there is a radical change in paradigms. Therefore, it is important for policy makers to capture such opportunities during the technology lifecycle and coordinate regional innovation resources.

Territorial Patterns of European Innovation in the Context of Different Innovation Output Proxies: A Spatial MGWR-SAR Approach

AbstractThe paper seeks to explore the drivers of European innovation represented by three innovation outputs (patent, trademark, and design applications), emphasizing spatial autocorrelation and heterogeneity. It includes data from 202 regions from 22 European Union (EU) Member States, along with 18 regions from Switzerland, Norway, and Serbia in 2019, providing a more comprehensive geographic scope. By considering multiple indicators of innovation output, including patents, trademarks, and design applications, the main objective is to examine spatial innovation spillovers and the heterogeneous responses of regional innovation output to innovation inputs in the context of European regions. To achieve this goal, the main instrument of the analysis is a newly proposed methodological framework called Mixed Geographically Weighted Regression-Spatial Autoregressive (MGWR-SAR) models. The analysis suggests that while all innovation inputs (most-cited publications, research and development expenditure in the business sector, human resources in science and technology, and population density) are justified in increasing all innovation outputs, the strength of particular determinants of innovation might vary across regions. Moreover, the analysis reveals valuable insights into how spatial spillovers influence regional innovation. The impact of spatial connections varies across the regions, with patents showing the strongest linkages, affecting about 92.27% of regions. Although trademarks and designs have fewer spatial connections (approximately 50% of regions), they still play a significant role in innovation. Although patents have traditionally dominated discussions of innovation, the findings reveal the importance of incorporating designs and trademarks as complementary indicators. Overall, the study highlights the need for multiple metrics to comprehensively evaluate innovations.

Laser-induced in-situ electrohydrodynamic jet printing of micro/nanoscale hierarchical structure

With the rapid advancement of micro/nanoscale devices, there is a growing demand for hierarchical micro/nano porous-structure, particularly in fields of high-performance sensors, electrochemical energy storage, and photocatalysis. The fabrication methods for hierarchical micro/nano-porous structures have been limited by complex processes and high costs, making further development and application difficult. In this paper, a novel strategy of laser-induced in-situ electrohydrodynamic jet (E-Jet) printing of hierarchical micro/nano-porous structures was proposed. Based on the mechanism of high-energy laser beam induction on the jet, it successfully fabricated hierarchical porous ZnO structures from nanoscale to dozens of microns. The jet size focusing and solidification behavior were analyzed by combining experimental and simulative exploration. The resultant effects of the thermal field, flow field, and laser field on the spatial temperature distribution and the jetting morphology were examined. Furthermore, the laser-induced influence on the morphology of the printed micro/nano-porous ZnO structures was explored. Meanwhile, the performance of micro/nano-porous ZnO photoelectric sensors printed by E-Jet under different laser powers was investigated. The laser-induced in-situ E-Jet printing method provided an innovative pattern for the high-resolution additive manufacturing of hierarchical porous structures, demonstrating its potential for applications in advanced material and high-performance devices.

Different patterns of national innovation under COVID-19: The moderating role of culture

In the post-pandemic era, there has been a renewed examination of the impact of COVID-19 on the global economy, aiming to discern potential patterns within this intricate phenomenon. This study categorizes the spread of COVID-19 into five distinct phases, as delineated by Huang et al. (2023), utilizing data from 115 nations within the Global Innovation Index. We analyzed the impact of the spread rate of COVID-19 on national innovation and the moderating role of collectivist culture during the period between 2020 and 2022. The results showed that collectivist culture positively moderated the correlation between the spread rate of COVID-19 and knowledge as well as technological output in the Entry and Takeoff phases. In the Proliferation phase, individualistic culture positively moderated the correlation between the spread rate of COVID-19 and national innovation, and in-group collectivist culture positively moderated the correlation between the spread rate of COVID-19 and the input and output of national innovation.

Spatial–Temporal Pattern Evolution and Differentiation Mechanism of Urban Dual Innovation: A Case Study of China’s Three Major Urban Agglomerations

Breakthrough innovation and incremental innovation have different impacts on economic development. For regional development, it is important to find a balance in dual innovation, which entails effective coordination of allocating innovation resources and managing risks. However, little attention has been given to the spatial relationship and differentiation mechanisms between breakthrough innovation and incremental innovation. Therefore, our research takes China’s three major urban agglomerations as examples, aiming to explore the spatial–temporal pattern evolution, influencing factors, spatial relationship, and spatial organizational patterns of breakthrough innovation and incremental innovation from 2000 to 2021. The research found that the spatial distribution of urban dual innovation is affected by the law of distance decay, and the spatial distribution of incremental innovation is more polycentric than that of breakthrough innovation. In terms of the differentiation mechanism, breakthrough innovation is more affected by the innovation atmosphere, while incremental innovation is more likely to be affected by the economic foundation and built environment. Our research effectively supplements the shortcomings in the spatial relationship research of breakthrough innovation and incremental innovation and provides references for formulating innovation policies.

The Spatial Pattern Evolution of Urban Innovation Actors and the Planning Response to Path Dependency: A Case Study of Guangzhou City, China

The capacity for urban innovation is a significant symbol of contemporary urban development. In order to promote sustainable urban innovation, it is crucial to match and optimize innovation spaces, actors, and their behavioral needs. Based on the data from patent inventions, which are commonly used to represent urban innovation, in this study, we investigated the formation mechanism of Guangzhou’s innovation pattern and its characteristics from 1990 to 2020 using Geographic Information System (GIS) technology. The results indicated that Guangzhou’s innovation spaces developed a center-radiation structure of “two districts and seven cores”. We investigated the path dependence of spaces, actors, and behavioral needs by examining the interaction between the innovation space layout and behavioral needs. The findings provide theoretical support for the city’s sustainable development in terms of innovation in the future.

Identifying innovation roadblocks: unveiling knowledge and innovation patterns that hinder commercialisation

ABSTRACT While intellectual property (IP) management is critical for innovation, specific knowledge and innovation patterns within it can obstruct commercialisation. This study explores how these patterns impede the path to market success for emerging innovations. We introduce a novel method to detect and recognise these patterns, offering insights into factors contributing to innovation system failure. Applying the Triple Helix Model, we leverage text mining, network analysis, and structural equation modelling within the Russian pharmaceutical industry. Our research reveals limitations in the triple helix model’s ability to capture problematic innovation patterns. Notably, local-closed and local semi-closed innovation networks emerge as significant barriers to commercialisation, further exacerbated by foreign dominance. While strong actor synergy is crucial, it alone cannot guarantee competitive advantage. Factors like geographical distance, disciplinary silos, and limited external collaboration further hinder success. This study highlights the need for effective knowledge production and collaboration practices, alongside strong synergy, to achieve market-leading innovations. Recognising and addressing these patterns can inform policy decisions, ultimately fostering more robust innovation outcomes, advancing innovation system theory in the process.

A longitudinal analysis of local innovation in Italy: How do proximity measures matter?

ABSTRACT This paper investigates the factors influencing local innovation from a longitudinal perspective while assessing geographical, economic and technological proximity. The research hypotheses concern spatial interactions, spillover effects and proximity measures that best fit innovation patterns and territorial interactions in Italy. The estimation strategy is the spatial Durbin panel model. The optimal specification to handle cross-sectional dependence in the data was derived from statistical tests evaluating (i) individual-specific effects, (ii) time-specific effects and (iii) both individual and time effects. The model was estimated using data from 107 Italian provinces over 2010–2019. The results show that both endogenous and exogenous interaction effects drive innovation processes and the underlying spillovers are global. Economic proximity explains local innovation patterns more effectively than geographical contiguity and technological proximity.