Creative development level of major Chinese cities can be divided into three echelons based on cluster analysis. Creative development level of major Chinese cities can be divided into three echelons based on cluster analysis.

Creative development level of major Chinese cities can be divided into three echelons based on cluster analysis. Creative development level of major Chinese cities can be divided into three echelons based on cluster analysis.

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There has been a cultural turn in urban development, as an increasing number of scholars are stressing the importance of culture in urban research and policy agendas. Specifically, the bohemian cultural scene could drive an integral cultural policy approach between the cultural scenes city and the creative city approach. Based on amenities data fro...

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... to two-step cluster analysis and the Bayesian information criterion, the creative development level of 65 major cities can be divided into three tiers. As shown in Figure 1, the first echelon (high) includes 11 cities: Beijing, Shanghai, Chengdu, Shenzhen, Guangzhou, Hangzhou, Nanjing, Tianjin, Xi'an, Chongqing, Wuhan, etc.; the second echelon (middle) ...
Context 2
... to two-step cluster analysis and the Bayesian information criterion, the creative development level of 65 major cities can be divided into three tiers. As shown in Figure 1 ...

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... Empirical research in the United States has found that self-expressive scenes significantly promote the gathering of innovative talents [24]. Chinese scholars have found that self-expressive scenes can promote the development of urban creativity [44]. ...
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In recent years, China has been steadily implementing its innovation-driven development strategy, underscoring the vital importance of attracting innovative talents to cities. Major cities have come to realize that securing such talent is essential for maintaining sustainable urban competitiveness in the future. This article takes a novel perspective by focusing on the role of urban scenes, with a particular emphasis on the cultural, lifestyle, and quality-of-life factors that are crucial for attracting and retaining innovative talent, which is essential for sustainable urban growth. Utilizing ridge regression analysis, this study scrutinizes the scores across various sub-dimensions of urban ambiance and the location quotient of innovative talent in 54 cities nationwide. We report several findings. Firstly, urban scenes play a pivotal role in talent agglomeration, a critical factor for sustainable development. Secondly, both rational and transgressive scenes positively impact the gathering of scientific and financial talents, with transgressive scenes having a more pronounced effect. Thirdly, self-expressive scenes may counterintuitively impede the clustering of scientific and cultural talents, a finding that contrasts with international research outcomes. In conclusion, this study sheds light on how urban scenes drive the sustainable concentration of innovative talents, thus contributing to the enrichment of theoretical understanding of sustainable talent development and practical insights for policymakers aiming to create urban environments that foster innovation and sustainability.
... The author chose the tea shop concept with a mix of Bohemian and Vintage themes. Bohemian is a concept that carries a unique theme and describes the freedom of nature [27]. Meanwhile, vintage is a design style with an antique classic theme to describe exclusivity. ...
... Under the background of economic globalization and international competition, cultural and creative industries have become an important symbol of a country's strength [1][2][3]. China also supports and develops cultural and creative industries as strategic emerging industries [4][5][6]. ...
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Traditional cultural and creative products need to be combined with cultural connotations on the basis of traditional cultural products, and modern visual communication design laws and design theories are used as the methods to broaden the product display medium and extend the product value. In this paper, we first sort out the cultural connotation of cultural and creative products and the design and development motives and explore the specific implementation path of cultural and creative product design based on visual communication design. Secondly, it studies the extraction of visual elements of traditional cultural and creative product patterns by the SURF image feature extraction method. Firstly, it realizes the acquisition of styling visual elements by the Canny operator in the edge detection algorithm. Then it acquires accurate color visual elements based on the K-Means primary color extraction algorithm improved by the contour coefficient method. In the traditional cultural and creative product design examples, it is found that the average Dice conventional culture coefficient image extraction based on the SURF method is 0.731, and the structural similarity of primary color extraction reaches 0.792 with the original image of traditional culture. Traditional cultural and creative products have a comprehensive evaluation score of between 4.3 and 4.5, which indicates high satisfaction. Carrying out the design of conventional cultural and creative products with visual communication design, its central performance is in visual attractiveness and formal innovativeness in order to burst the vitality of traditional cultural and creative products.
... Scene theory is a theoretical framework that aims to explain how individuals perceive and interpret their surroundings as dynamic "scenes." It suggests that environmental and situational factors influence cognitive processes and behavior [17]. In recent years, there has been increasing interest in applying scene theory principles to enhance the performance of deep learning algorithms in computer vision tasks. ...
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Tool products play a pivotal role in assisting individuals in various domains, ranging from professional work to everyday tasks. The success of these tools is not solely determined by their functionality but also by the quality of user experience they offer. Designing tool products that effectively engage users, enhance their productivity, and provide a seamless interaction experience has become a critical focus for researchers and practitioners in the field of interaction design. Scene theory proposes that individuals perceive and interpret their surroundings as dynamic "scenes," wherein environmental and situational factors influence their cognitive processes and behavior. This research paper presented a novel approach to the interaction design of tool products by integrating scene theory, flow experience, the Moth Flame optimization (MFO), cooperative game theory (CGT), and voting deep learning. Tool products play a vital role in various domains, and their interaction design significantly influences user satisfaction and task performance. Building upon the principles of scene theory and flow experience, this study proposes an innovative framework that considers the contextual factors and aims to create a seamless and enjoyable user experience. The MFO algorithm, inspired by the behavior of moth flame, is employed to optimize the design parameters and enhance the efficiency of the interaction design process. Furthermore, CGT is integrated to model cooperative relationships between users and tool products, fostering collaborative and engaging experiences. Voting deep learning is employed to analyze user feedback and preferences, enabling personalized and adaptive design recommendations. With the proposed CGT, this paper investigates the impact of the proposed approach on user engagement, task efficiency, and overall satisfaction. The findings contribute to the field of interaction design by providing practical insights for creating tool products that align with users' cognitive processes, environmental constraints, flow-inducing experiences, and cooperative dynamics.
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Cultural scenes are essential units and value collections within consumer spaces, and metro scenes in large cities are a new perspective for cultural scene research. Based on scene theory, we isolated distinct urban metro scenes through the perspective of slow travelling, through which we identified the dimensions of Shanghai’s metro cultural scenes. Furthermore, we identified five patterns of metro cultural scenes through factor analysis and cluster analysis of scene dimensions, namely, mechanically modern, charming and expressive, local and down-to-earth, public welfare and rationality, and ordinary scenes. We found that the names of metro stations could influence scene formation by influencing the category of amenities around the station, while the convenience of the metro stations could significantly promote the formation of some scene dimensions. In addition, urban planning and crowd distribution also have an impact on the metro culture scene. Our study reveals the characteristics and patterns of metro scenes in Shanghai and proposes a pathway by which metro scenes are formed, providing a new direction for urban scene research.
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This paper elaborates a multi-model approach to studying how local scenes change. We refer to this as the "4 D's" of scene change: development, differentiation, defense, and diffusion. Each posits somewhat distinct change processes, and has its own tradition of theory and empirical research, which we briefly review. After summarizing some major trends in scenes and amenities in the US context, for each change model, we present some initial findings, discussing data and methods throughout. Our overall goal is to point toward new research arcs on change models of scenes, and to give some clear examples and directions for how to think about and collect data to understand what makes some scenes change, others not, why, and in what directions.
Article
Full-text available
This paper elaborates a multi-model approach to studying how local scenes change. We refer to this as the "4 D's" of scene change: development, differentiation, defense, and diffusion. Each posits somewhat distinct change processes, and has its own tradition of theory and empirical research, which we briefly review. After summarizing some major trends in scenes and amenities in the US context, for each change model, we present some initial findings, discussing data and methods throughout. Our overall goal is to point toward new research arcs on change models of scenes, and to give some clear examples and directions for how to think about and collect data to understand what makes some scenes change, others not, why, and in what directions.
Article
Full-text available
This paper elaborates a multi-model approach to studying how local scenes change. We refer to this as the “4 D’s” of scene change: development, differentiation, defense, and diffusion. Each posits somewhat distinct change processes, and has its own tradition of theory and empirical research, which we briefly review. After summarizing some major trends in scenes and amenities in the US context, for each change model, we present some initial findings, discussing data and methods throughout. Our overall goal is to point toward new research arcs on change models of scenes, and to give some clear examples and directions for how to think about and collect data to understand what makes some scenes change, others not, why, and in what directions.