The People-Oriented Urban Planning Strategies in Digital Era—Inspiration from How Urban Amenities Shape the Distribution of Micro-Celebrities

Abstract

How to promote sustainable development and deal with the actual development demands in economic transformation through land-use planning is crucial for local governments. The urban sustainable development mainly relies on creativity and talents in the digital era, and talents are increasingly attracted by local people-oriented land use. However, the current planning ideology remains at meeting corporate and people’s basic needs rather than specific needs of talents, especially the increasingly emerging digital creatives. To promote the talent agglomeration and sustainable development through land planning, this paper uses micro-celebrities on Bilibili, an influential creative content creation platform among young people in China, as an example to study the geographical distribution of digital creative talents and its relationship with urban amenities by constructing an index system of urban amenities, comprising natural, leisure, infrastructure, and social and institutional amenities. The concept of borrowed amenities is introduced to examine the effects of amenities of surrounding cities. This study demonstrates that micro-celebrities show a stronger preference for amenities compared with other skilled talents. Meanwhile, social and institutional amenities are most crucial. Furthermore, urban leisure represented by green spaces and consumption spaces is also attractive. At the regional scale, with prefecture-level cities as units, the local talents agglomeration is also influenced by the borrowed amenities in the context of regional integration. It indicates that the local land use should consider the characteristics of the surrounding cities. This study provides strategic inspiration that a happy and sustainable city should first be people-oriented and provide sufficient space for consumption, entertainment, and interaction.

1. Introduction

In the process of globalization and urbanization, while some cities leveraging new technologies have risen rapidly, others have faced serious developmental challenges such as population decline, environmental degradation, and deteriorating quality of life [1]. Achieving urban sustainability has thus emerged as one of the most pressing challenges confronting contemporary urban societies. The conceptual framework and implementation pathways of sustainable development strategies are inherently multidimensional and comprehensive [2]. At their core, however, they hinge upon two critical factors: technological innovation and human capital [3]. Consequently, sustainable urban planning strategies must prioritize enhancing a city’s appeal to talents—those who contribute to social production through cognitive abilities or specialized expertise within specific technological contexts and market demands. These individuals typically engage in creative endeavors or specialized production requiring technical proficiency.

Research on talent migration has demonstrated that people-oriented urban scenarios and land-use planning are increasingly shaping the spatial distribution of skilled professionals [4]. However, mainstream urban planning strategies still predominantly follow the industrial economy paradigm, which prioritizes enterprises and land utilization while neglecting human-centric needs. In recent years, scholars in urban planning have recognized the significance of amenities in land-use strategies [5,6]. Consequently, a growing number of researchers advocate for future cities to be “designed for people” [7]. People-oriented urban planning, while prioritizing the fundamental living security of citizens, must simultaneously address the specialized needs of skilled talents. In urban development processes, planning approaches that incorporate talent demands do not inherently compromise the interests of general residents. This dual compatibility stems from two fundamental observations: First, most urban suitability factors constitute public goods that benefit all population groups equally. Second, talented individuals represent scarce resources that drive sustained urban wealth accumulation. The economic growth generated through talent agglomeration can subsequently enhance overall urban living standards through improved fiscal capacity and infrastructure development. Some developed countries are replacing factory and industrial land with amenities such as consumption and leisure venues, green spaces, creative communities, and infrastructure spaces, which have been proven to promote the industrial transformation and sustainable development [8] and even provided impetus for the revival of declining industrial cities. For instance, after Detroit went bankrupt, planners transformed idle industrial spaces into green spaces, creative parks, and consumption venues, which helped Detroit develop into a creative city [9].

China has also embarked on a people-oriented planning shift and attempt [10]. Currently, the basic living needs of citizens in most cities have been met, but there is no widespread attention paid to the specific needs of talents, especially the talent differentiation that is occurring in the digital era of rapid economic transformation. With digitalization and culturalization [11,12], an increasing number of creative talents have begun to break away from their reliance on industrial space and maintain flexible or short-term employment relationships with enterprises [13]. This type of talent represents the emerging creative group in the digital age, and its spatial location reflects the preferences of the new creative talents. Since spatial mobility does not directly affect the output and income of new creative talents, their spatial location choices would be highly free. However, they still disproportionately cluster in several high-cost cities, which scholars attribute to the quality-of-life characteristics related to local amenities [14]. However, there are also significant differences in the aggregation of digital creative talents among cities with similar economic levels and amenities. This indicates that the existing amenities indicators and planning strategies have failed to capture some key changes emerging in the digital age, and the extent of such changes during the economic transformation is particularly intense in China.

Furthermore, the enhancement of intercity rapid transportation networks and metropolitan development strategies is significantly reshaping land-use planning paradigms [15]. The expansion of rapid transit systems and urban growth have extended residents’ economic and social activity boundaries beyond municipal limits [16]. This spatial reorganization enables cross-jurisdictional resource sharing within metropolitan regions, allowing cities to compensate for local amenity deficiencies through intercity spatial borrowing—thereby optimizing regional spatial utilization efficiency. A representative case is the Beijing-Hebei metropolitan area, where recreational spaces in Hebei Province supplement Beijing’s leisure infrastructure, while Beijing’s commercial facilities serve Hebei residents, creating a symbiotic spatial relationship. This metropolitan spatial integration necessitates a fundamental reconsideration of urban land-use strategies that account for cross-border functional complementarity. However, prevailing research remains constrained by an administrative-boundary pattern, failing to adequately address how metropolitan development models transform conventional land-use planning approaches. Current studies continue to assume amenity accessibility is confined within single jurisdictional units, overlooking the emerging intercity spatial dynamics characteristic of modern urban regions.

The dual processes of digitalization and regional integration necessitate critical adjustments in urban planning and spatial governance to sustain talent attractiveness and meet sustainable development goals. Using micro-celebrities (a representative cohort of digital creative workers) as a case study, this research investigates their spatial distribution patterns and correlation with urban amenity characteristics to address these questions. This article has made three contributions. First, it adopts a people-oriented perspective to analyze urban planning and spatial governance strategies in the Digital Era, addressing the growing need for people-oriented development approaches. Second, it pays attention to the differentiation of creative occupations in the digital age to capture what adjustments urban planning should make during the rapid economic transformation process. Third, the research significantly expands the conventional amenity index framework by incorporating socio-institutional factors and interregional resource-sharing mechanisms—critical yet neglected dimensions in contemporary urban studies that disproportionately emphasize localized physical infrastructure and basic living conditions.

2. Literature Review

2.1. The Rise of Digital Creative Talents

In the process of digital technology affecting social production, there appears to be some people who participate in social production through digital platforms, including conventional digital laborers and digital creative talents [17,18]. Conventional digital laborers include those who blend physically active or emotional economy with digital technology, such as delivery riders and ride-hailing drivers. They just require superficial knowledge and cognitive abilities. Digital creative talents are a group that produces its ideas through the Internet platform. In the era of digital economy, the Internet platform has become an important channel for acquiring knowledge and information, learning skills, and outsourcing projects, so digital creative talents who meet such needs through the network have emerged.

Compared with conventional creative talents engaged in creative work in enterprises, they have the following outstanding characteristics:

Freelance and work online: The integration of creative industries and digital technology has deepened and strengthened the differentiation of the creative stage. Creative talents are working on a freelance basis [19,20]. In most cases, such creative talents do not need to contact directly with employers or users.

Instability: Scholars discussing the gig economy have identified several risks, including job and income instability; lack of social security and support [20]; and difficulties in forming a group identity [21]. These factors are considered both occupational characteristics and local factors.

Compared to conventional digital laborers, digital creative talents have the following outstanding characteristics:

High Human Capital: The cognitive ability and creative ideas are essential and indispensable for digital creative talents in content creation.

Freedom and mobility: Since the knowledge and cognitive abilities needed in content creation are self-contained and do not change significantly with spatial movement of talents, they can create content from any location in consequence. Although the place plays a role in their later knowledge accumulation and cognitive improvement (face-to-face communication in big cities transmits much important tacit knowledge), the initial level of knowledge is a matter of individual ability rather than local factors. Therefore, in theory, they have a freer location choice and movement frequency.

Micro-celebrities represent a new wave of digital creative talents that have emerged in recent years [22]. Today, the lack of individual attention and the rising cost of information acquisition have become widespread due to the explosive growth of information and data. Consumers’ attention has been described as an important “new capital”, a “key resource”, or “the most valuable commodity” [23], making socio-economic activity a “competition for attention” [24]. Micro-celebrities are individuals who accumulate attention capital through content creation online [25], requiring an outstanding knowledge base, cognitive ability, observation, and creativity, thereby positioning them within the creative class. However, most micro-celebrities do not establish permanent employment relationships with firms, making them part of the gig economy [26].

2.2. Amenities

The connotation and influence mechanism of amenities in the existing literature show a dynamic evolution. Initially, amenities were defined as non-tradable public goods, such as climate [27]. Over time, scholars expanded this definition to include infrastructure and commercial entertainment spaces, with less emphasis on their tradability [28]. Subsequently, global immigration trends prompted scholars to focus on the concept of tolerance [29], shifting the notion of amenities from the material to the immaterial level. For example, Clark first conceptualized social and cultural amenities [30]. The rise of creative freelancers and the gig economy has made urban social character a significant aspect of “pleasant environments” [31], especially as the gap in natural and infrastructure amenities among cities has gradually narrowed.

In this paper, amenities are categorized into local amenities and borrowed amenities. Local amenities are further divided into four aspects: natural amenities, leisure amenities, infrastructure amenities, and social and cultural amenities (Figure 1). According to the center-periphery model [32], the varying usage frequencies of facilities at different hierarchical levels lead to spatial segregation between high-frequency daily facilities and low-frequency high-tier facilities. Consequently, at both urban and regional scales, we observe high-rent central zones characterized by a concentration of high-grade amenities, alongside low-rent peripheral areas dominated by daily necessities, green spaces, and low-density leisure venues. These two types of regions exhibit complementary amenities distributions, interconnected through transportation networks. Thus, in the process of location decision-making, talents consider not only the amenities of their immediate residential environment but also evaluate the combined accessibility of amenities across multiple regions at an expanded spatial scale. This phenomenon has been further reinforced by declining transportation costs [33]. Within regional integration and metropolitan development frameworks, cross-city amenities borrowing has become increasingly prevalent. Recent studies in spatial economics have noted that isolated urban studies in regional migration models have resulted in significant errors [34]. Consequently, scholars have shifted their attention from the urban scale to the regional scale in urban studies, proposing concepts such as “borrowed size” [35]. Unfortunately, this widespread and significant perspective has been neglected in the research on talent location and urban amenities. To address this gap, this paper introduces the concept of borrowed amenities to depict the complementarity in specific aspects of amenities between adjacent cities, which is different from central place theory, emphasizing the grade and coverage of facilities; for example, Beijing’s borrowing of green spaces from surrounding cities is not caused by differences in coverage and grade.

2.2.1. Natural Amenities

The influence of natural amenities can be summarized in terms of their adjustment function and aesthetic function. The adjustment function refers to the importance of natural climate to human health. The industrialization process has severely damaged the ecological environment, making a comfortable natural environment, temperature, and air quality special luxuries in the post-industrial era [36]. The aesthetic function involves the visual, recreational, and public space value of natural scenery. Recent studies based on the hedonic model have claimed that residents’ subjective well-being can be significantly improved by green space, open space, natural attractions, and water areas [37,38].

2.2.2. Leisure Amenities

Urban leisure opportunities are a vital component of urban life quality [39], and creative talents have a higher demand for leisure and entertainment [40]. In this paper, leisure amenities are summarized in three dimensions: scale, structure, and grade of leisure opportunities. The scale of leisure opportunities measures the leisure-carrying capacity and accessibility, determining the population size that a city can accommodate. The diversity of leisure opportunities is emphasized for talent agglomeration in classical literature, but structural characteristics are often overlooked in the empirical studies. The grade of consumption selects spiritual and cultural consumption indicators, such as theaters, concerts, and large-scale art exhibitions, which form the core of Florida‘s theory [29]. According to Maslow’s hierarchy of needs, spiritual and cultural consumption represents high-level demands related to taste and non-biological needs [41].

2.2.3. Infrastructure Amenities

Infrastructure amenities are divided into healthcare, education, and transportation dimensions. Infrastructure is the foundation of the quality of life. Considering the income level and mobility of creative talents, the index selection includes both conventional facilities and high-level facilities. Specifically, regarding transportation, in addition to the number of buses considered by the previous literature, this paper also considers other travel indicators calculated based on the big data: the response rate and night orders of Online Car-Hailing. Online Car-Hailing is more comfortable, convenient and widespread in China [42], especially at night or in areas outside the service radius of public transportation stations [43]. In addition, we also use the number of high-speed trains and flights departing from the local area to other cities within a week to measure the convenience of local external transportation. In terms of education facilities, we chose the number of primary and secondary schools. The number of beds and hospitals, and class A tertiary hospitals, were selected to measure basic and high-level medical facilities.

2.2.4. Social and Institutional Amenities

From a long-term perspective, as facilities across metropolises gradually homogenize, social and institutional factors are playing an increasingly significant role in the migration patterns of creative talents [44]. The discourse surrounding social and institutional amenities has been largely overlooked in most empirical investigations. Management theorists propose that a new career era is emerging, characterized by the universal rise of new occupations [45]. The most critical factors for the success of these new occupations are related to local social institutions [46]. Therefore, we have constructed three dimensions of social and institutional amenities: institutional environment, openness, career support, and development environment.

Institutional environment is an important aspect that affects the local life experience. We use e-government level to measure the ability and willingness of governments to provide convenient and quality services to local enterprises and residents [47]. Because digital creative talents have lost the protection provided by enterprises, they have a higher demand for handling personal affairs, such as social insurance payment and business management in different places, etc. The convenience of handling such affairs can measure the efficiency, fairness, and friendliness of a city. In addition, e-government level is also a good fit for government integrity and transparency [48]. Open and tolerant cities are more attractive to creative talents due to the preference for diverse lifestyles and the increasingly widespread domestic and international migration [49]. Career support and development environment includes three aspects: communication within occupational clusters facilitates the flow and sharing of tacit knowledge [50] and also strengthens group identity, a significant source of happiness for new careers [51]; the local demonstration effect provides initial career choices and references, motivating local aspiring creatives to explore new occupations. This demonstration effect is measured by the number of the first group of individuals who successfully pursued micro-celebrity careers (e.g., the first Bilibili top 100 micro-celebrities); MCN and associations address the occupational instability associated with the temporary nature of freelance projects [52].

2.3. Amenities and Location of Micro-Celebrities

Sociology and economics initially focused on the differentiation of creative occupations without recognizing the significant role played by “place.” They separated the occupational characteristics of creative freelancers from spatial considerations, describing them as “roles, no places” [31]. Economic geography, however, provides a meaningful complement to this perspective. In the process of occupational evolution, “place” plays two irreplaceable roles. First, quality of life is provided heterogeneously across different locations [53]. Although digital creative talents who have moved away from fixed workplaces and complete their work online, substantial empirical evidence suggests that they do not leave big cities for areas with lower living costs due to concerns about life quality. Second, the localized sociocultural environment determines the ability of creative talents to manage instability and satisfy their need for group identity [54]. These factors constitute the mechanisms through which amenities influence the distribution of creative talents.

Cities with high levels of amenities attract abundant people who pursue quality of life across various industries. A tolerant social atmosphere and industrial digital development stimulate residents to constantly explore new occupations and lifestyles, such as becoming micro-celebrities. When micro-celebrities succeed in their occupational endeavors and achieve high incomes, they inadvertently motivate local imitation. Communication with shared identities strengthens the acceptance of their identity as non-mainstream occupations [55]. The gradual integration of new occupations with the local occupational system reshapes cultural and social norms, facilitating the success of new careers as freelancers [56]. Subsequently, the emergence of related service providers strengthens the local society’s resistance to the occupational instability inherent in new occupations, thereby attracting micro-celebrities to peripheral areas.

The spatial process of micro-celebrities can be divided into inter-urban and intra-urban agglomeration. The intra-urban agglomeration of micro-celebrities may depend on the existing economic level to a certain extent. Big cities are typically the first places where new occupations emerge due to the advantages of initial amenities and local labor [57]. However, economic foundations can only partially explain the differences in micro-celebrity agglomeration. Cities with similar economic scales may exhibit different levels of micro-celebrity agglomeration in reality. This variation is not only related to local amenities but also to the characteristics of the surrounding cities. Both big cities and small cities have their own advantages in terms of amenities and living costs, and the spatial relationship enables the inter-urban complementation of advantages for micro-celebrity agglomeration, which is essentially similar to the concept of borrowed size.

In summary, the emergence of micro-celebrities is related to the initial advantage of amenities. Subsequently, the agglomeration of micro-celebrities is influenced by local social culture, primarily concerning career development, career success, and career satisfaction. Finally, borrowed amenities may affect the urban attractiveness of micro-celebrities.

3. Methods

3.1. Research Object

For this study, Bilibili was selected as the platform for data acquisition for several reasons. First, it has a substantial and growing user base, which provides a rich dataset for analysis. Second, Bilibili offers a diverse array of content creation formats, including short videos, long videos, and images, making it particularly suitable for studying micro-celebrities. Thirdly, the content creation of Bilibili is more original and focuses on the creative fields of knowledge, science and technology, film and television, music and culture (https://www.thepaper.cn/newsDetail_forward_27129871 (accessed on 1 December 2023)). And Douyin focuses on humorous short videos, gender performance, live sales, and record life (https://zhuanlan.zhihu.com/p/711963356 (accessed on 1 September 2024)). Even for the same topic, the two platforms display different emphasis. Therefore, the content creators of Bilibili are more in line with the definition of “digital creative talents”.

The study focused on “up owners” with more than 100,000 followers as the research object, considering factors such as income potential, successful case demonstration, and the originality of creative content. Bilibili grants content creators the designation of “high-quality creator”, along with a commemorative medal upon reaching the milestone of 100,000 followers. Furthermore, these certified creators constitute a demographic characterized by relatively high-income levels, particularly those specializing in technology, beauty, and educational content domains. During the sample selection process, official accounts of brands and public media were excluded to ensure that the location attributes of personal accounts more accurately reflect the subjectivity and individual characteristics of micro-celebrities [58].

The research considered Chinese cities at the prefecture level and above, ultimately selecting 207 cities that met the criteria, excluding those with zero micro-celebrities. Preliminary sorting of amenities in the excluded cities showed that most did not have significant advantages in population size or the level of amenities. Therefore, the exclusion of these cities had a minimal impact on the study’s results.

3.2. Data and Variables

The data sources utilized in this study are as follows: Micro-celebrities’ location information was obtained from their profiles and the website https://xz.newrank.cn/; the collection time was December 2023. The number of micro-celebrity linkages (the amount of co-creation by multiple micro-celebrities) and data on the first Bilibili Top 100 Up (the top 100 micro-celebrities with the most influence, as selected by the Bilibili platform) were sourced from bilibili.cn. Additional data, such as wholesale and retail volumes above the quota, road areas, park and green space areas, and the number of hospitals and schools, were derived from the China Urban Statistical Yearbook 2023. The number of concerts was sourced from Damai.com (https://www.damai.cn, accessed on 1 September 2024), a major ticketing website in China. Data on MCNs (Multi-Channel Networks) and self-media associations were obtained from qcc.com (https://www.qcc.com, accessed on 1 September 2024). Urban high-speed rail and flight data were sourced from the Chinese High-Speed Rail and Airline Database, while weather and temperature data were collected from China’s Air Quality Monitoring Platform. Household registration data, permanent resident population, information technology employees, and general skilled workers data were obtained from China’s seventh population census. The Leisure Diversity Indicator was calculated using Point of Interest (POI) data from Amap (https://www.amap.com, accessed on 1 September 2024), one of the most reliable navigation systems in China. POI data from open sources have been widely used in various studies to represent spatial patterns of urban amenities. Missing data were supplemented using local statistical yearbooks and government work reports. The response rate and night orders of Online Car-Hailing come from Didi Platform, the largest Online Car-Hailing platform in China. The e-government level index is calculated with Peking University Open Research Data (https://doi.org/10.18170/DVN/9NJDWE, accessed on 1 September 2024), and the efficiency level of local governments in handling business and resident services is comprehensively quantized based on the four service channels of Chinese urban government’s affairs website, government WeChat, government Weibo, and government APP (accessed on 1 September 2024).

The variables used in this study are arranged in

Table 1. Variables and indicators used in the analysis.

Variable	Indicator	Indicator Description	Average	Max	Min	Std.Vep.	Mean
Digital creative talents	MCs	Micro-celebrities	15.07	531	1	49.27	2439.86
Natural amenities	tem-s	Summer temperature	23.54	28.33	12.48	3.3	10.89
	tem-w	Winter temperature	8.78	22.54	−14.77	6.94	48.23
	nats	Natural scenery	15.07	531	1	49.27	2439.86
	airq	The proportion of days with good air quality	0.86	1	0.55	0.11	0.01
	grep	Per-capita green park	4.59	46.75	0	4.4	19.41
Leisure amenities	div-c	Consumption diversity	0.31	0.7	0.13	0.11	0.01
	cons	Total retail sales of consumption goods above the quota	3089.97	120,468.25	22.22	10,743.12	1,159,777,405,108
	conc	Number of concerts	86.09	720	1	124.95	15,689.24
Infrastructure amenities	bus	Number of buses per capita	3.51	21.85	0.6	2.75	7.6
	Repr	Online car-hailing response rate	0.76	0.95	0.52	0.05	0.01
	nigo	Night order ratio of online car hailing	0.56	0.91	0.27	0.16	0.01
	sch-m	Middle school	106.99	867	15	120.3	14,541.78
	sch-g	Grade school	187.45	1811	10	204.28	41,932.54
	flig	The number of flights a week	715.72	6026	0	1293.37	1,680,978.87
	HSR	The number of high-speed trains a week	489.16	2672	0	451.44	204,787.89
	hospital	Hospital	0.14	0.36	0.02	0.08	0.01
	Hosp-3A	Class A tertiary hospitals	12.1	82	1	9.74	118.32
Social and institutional amenities	top MC	Top 100 up	0.43	28	0	2.31	5.35
	inte	The interactions between micro-celebrities	2.48	61	0	5.58	31.3
	tole	The proportion of the population registered in other cities	55.16	1047.96	0.78	132.6	176,696,082.4
	E-Gov	E-government level	5013.64	95576	249	11036.03	122,388,003
	MCN	MCNs and associations	203.21	3737	1	432.71	188,154.12
Control variable	size	Urban size	546.03	3205.42	68.96	414.39	172,553.99
	GDP	GDP per capita	78,573.32	164,889	24,353	34,991.47	1,224,403,591
Jobs	Ln Emp	Number of whole practitioners	6.06	6.12	6.04	5.58	0.17
Other creative talents	PTT	Professional and technical talents	28,211.59	262,407	2196	35,277.18	1,244,479,454

Note: Variables including MCs, cons, conc, sch-m, sch-g, flig, HSR, beds, tole, info, MCN, size, GDP, and PTT are logarithmically transformed in the regression analysis.

. Multicollinearity tests were conducted for all variables, and those with very strong multicollinearity were removed. The remaining variables exhibited acceptable levels of multicollinearity, which did not significantly alter the model results according to preliminary tests.

This research examines the distinctiveness of micro-celebrities in terms of their geographical distribution compared to other creative talents. As a benchmark for comparison, the study selects professional and technical talents, classified as part of the creative class according to Florida’s definition [29]. These creative talents largely overlap with the professional and technical personnel categories in census data issued by China’s National Bureau of Statistics, which includes scientific researchers, engineering and technical personnel, aircraft and ship technicians, health professionals, economic and financial professionals, legal, social and religious professionals, teaching personnel, literature and art professionals, sports professionals, press and publication professionals, cultural professionals, and other professional and technical personnel.

3.3. Method

3.3.1. Amenities Measurement Formula

In this paper, the entropy weight method is utilized to calculate the weight of each amenity indicator. The indicators for natural, infrastructure, leisure, institutional, and social amenities are obtained by multiplying these weights with the standardized indicators. Borrowed amenities need to account for the spatial relationship and the amenities gap between local and surrounding cities. Whether an amenity can realize spillover and borrowing largely depends on this amenities gap. For instance, areas lacking high-grade hospitals can borrow medical resources from central cities, and densely populated areas lacking green spaces can borrow natural spaces from peripheral cities. In China, for example, residents of Beijing might travel to Ulanqab or Chengde for a rest, while those living in Chengde might seek medical treatment in Beijing. This paper assumes that borrowed amenities occur only when there is a gap in amenity levels between cities, and the degree of borrowing is inversely proportional to the distance between cities. The calculation for borrowed amenities is as follows:

First, construct the two-dimensional (0–1) matrix $M_{ij}^{ame-k}$ of the relative advantage of amenities; k represents the natural, infrastructure, leisure, social, and institutional dimensions of amenities. If the specific amenities ame-k for city i is greater than ame-k for city j, denoted as 0, it indicates that the talents in city i do not need to borrow this amenity from city j. Conversely, it is recorded as 1, indicating that the amenities of city i is lower than that of the city j, and, thus, it is possible to borrow. The degree of borrowing is inversely proportional to the distance.

$${Bame}_i^k={\sum }_{i=1}^j{\displaystyle \raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$D_{ij}$}\right.}{Ame}_j^k* M_{ij}^{ame-k}$$

(1)

where ${Bame}_i^k$ indicates the borrowed amenities level of city i, $D_{ij}$ indicates the distance between city i and the surrounding cities, and ${Ame}_j^k$ indicates the amenities level of surrounding city j.

3.3.2. The Rank-Size Rule

The rank-size rule is used to describe the degree of micro-celebrities’ agglomeration within a city. Zipf’s law, a classic application of the rank-size rule, states that the size of a feature in a city multiplied by its rank order is equal to the size of the first city [59]. A more general model includes adding a power index to the rank variable as an elastic coefficient, thereby enhancing the universality of the rank-size rule.

$$P_i^C=P_1^C\times {\left(R_i^O\right)}^{-u}$$

(2)

$${lnP}_i^C={lnP}_1^C-u{lnR}_i^C$$

(3)

where $P_i^C$ represents the number of micro-celebrities in city i, $P_1^C$ denotes the number of micro-celebrities in the city with the highest rank, and $R_i^O$ represents the ordinal rank of city i. The absolute value of u indicates the degree of agglomeration in high-level cities. If u is greater than 1, it means that the agglomeration in high-level cities is pronounced, while the development in low-level cities is insufficient.

3.3.3. Spatial Correlation Analysis

While the rank-size rule can describe the scale and rank characteristics of micro-celebrities at the city level, it does not sufficiently address competition and communication between cities. Spatial correlation analysis is used to describe the similarity degree of spatial unit attributes. This analysis includes both global autocorrelation and local autocorrelation, utilizing the global Moran’s I and local Moran’s I, respectively. The calculation formula is as follows:

$$I={\displaystyle \frac{n\sum _{i=1}^n\sum _{j=1}^n{W}_{ij}(x_i-\overline{x})(x_j-\overline{x})}{\sum _{i=1}^n\sum _{j=1}^n{W}_{ij}{(x_i-\overline{x})}^2}}$$

(4)

where $x_i$ and $x_j$ are the total number of micro-celebrities in cities i and j, respectively; $\overline{x}$ is the mean value. I represents the global Moran’s I of the total number of micro-celebrities, and the value range of I is between [−1, 1], where less than 0 means negative correlation, equal to 0 means no correlation, and greater than 0 means positive correlation. For the Moran’s I, the standardized statistic Z is used to test whether there is a spatial autocorrelation among n regions. A positive and significant Z-value means that urban micro-celebrities tend to be spatially clustered, while a Z-value of 0 means independent random distribution.

3.3.4. Regression Model

The following regression model is constructed to study the influence of amenities on the distribution of micro-celebrities:

$$lnMcs=x_1{Ame}_n+x_2{Ame}_i+x_3{Ame}_l+x_4{Ame}_s+{\beta }_1{Bame}_n+{\beta }_2{Bame}_i+{\beta }_3{Bame}_l+{\beta }_4{Bame}_s+Con+\mathit{\partial }$$

(5)

where $Mcs$ stands for the number of micro-celebrities, Ame stands for amenities, including natural (${Ame}_n$), infrastructure (${Ame}_i$), leisure (${Ame}_l$), and social and institutional (${Ame}_s$), and ${Bame}_n$, ${Bame}_i$, ${Bame}_l$, and ${Bame}_s$ measure the natural, infrastructure, leisure, social, and institutional dimensions of borrowed amenities. Con represents the control variables and chooses per-capita GDP, urban population size, and the scale of college students. To provide a more accurate explanation basis and policy recommendations, the influence of different dimensions of each amenities type is analyzed by controlling for other amenity levels and economic scale factors.

4. Results

4.1. Spatial Distribution of Micro-Celebrities

The Hierarchical Distribution of Micro-Celebrities

A total of 2976 personal accounts matching the characteristics of micro-celebrities were analyzed. The five cities with the most micro-celebrities are Shanghai, Beijing, Hangzhou, Chengdu, Guangzhou, and Shenzhen (Figure 2). Together, these cities account for more than half of the total number of micro-celebrities in China. Beijing, Hangzhou, and Shanghai represent prominent historical metropolises in China that simultaneously function as economically advanced urban centers, demonstrating strong competitiveness in both economic vitality and development levels. These cities exhibit remarkable attractiveness to diverse demographic groups by offering comprehensive urban amenities that cater to varied population needs. Despite micro-celebrities’ reduced dependence on fixed employment agreements and specific work locations, they still tend to cluster in high-cost metropolitan areas. This suggests that location choice is not merely a rational decision based on cost of living and income but also involves a combination of various assets, especially non-economic amenities. Furthermore, the distribution pattern reveals that, unlike other types of labor, which show a linear relationship with city size, the polarization of micro-celebrities in central cities far exceeds that of the population size. This implies that the gap between the concentration of creative talents in peripheral areas and central cities is likely to continue widening [60].

The rank-size test indicates that the distribution of micro-celebrities follows a Pareto distribution (Figure 3b), confirming their tendency toward agglomeration. Knowledge externalities among micro-celebrities arise from tacit knowledge, which does not require direct and frequent interaction with consumers. This suggests that micro-celebrities exhibit greater reliance on sustained peer interactions rather than audience engagement, consequently demonstrating stronger agglomeration tendencies similar to creative professionals such as artists, media practitioners, and scientists. This pattern, however, does not extend to client-facing professions like psychologists and lawyers, whose practice necessitates frequent in-person client consultations, despite the acknowledged importance of peer interaction in these fields [49]. This clustering primarily occurs in metropolitan areas. The tolerance found in these cities encourages local creative talents to experiment with new occupations and attracts non-native creative talents to relocate. Additionally, employment advantages and complementary service industries can mitigate occupational instability. Cultural consumption and infrastructure advantages further contribute to an improved quality of life.

However, it was found that despite the economic scale and quality-of-life advantages of some large cities, the agglomeration of micro-celebrities remains limited. For example, cities like Chongqing and Tianjin have significantly fewer micro-celebrities compared to Hangzhou and Chengdu, while Guangzhou has only a quarter of Shanghai’s number. This unexpected trend reflects the reconstruction of the postindustrial economic landscape, demonstrating that although large cities have fundamental advantages in the emergence of new occupations, only a select few cities can truly attract these new occupations. This divergence reflects the sustainable development and competitiveness of urban economies. For instance, the per-capita income and innovation in Los Angeles are only two-thirds that of San Francisco, despite there being no difference at the end of the last century [61]. In China, cities like Hangzhou, Chengdu, and Shanghai have the highest concentration of new occupations and are showing the most dynamic economic performance, in contrast to other sleepy, conservative industrial metropolises that are struggling to grow.

To preliminarily characterize this divergence, a comparison was made between the size rank of the population and micro-celebrities (Figure 4A) and the rank difference between population size and micro-celebrities (Figure 4B). Cities positioned above the linear fitting curve exhibit a higher trend of micro-celebrity agglomeration. Among megacities, Shanghai and Beijing show more pronounced advantages, while Chengdu, Hangzhou, Changsha, and Nanjing demonstrate higher agglomeration advantages than other new first-tier cities. In contrast, cities dominated by traditional industries, such as Datong, Lanzhou, Harbin, Jinan, and Changchun, display much lower agglomeration of micro-celebrities relative to their population and economy. This suggests that while the size of local talent and economic foundations can partially explain the agglomeration distribution of micro-celebrities, other crucial non-economic factors play a significant role in shaping this distribution.

The results of the Global Moran’s I analysis are significantly positive (

Table 2. Moran’s I of Micro-Celebrities’ Distribution.

Indicator	Value
Moran’s Index	0.358
Expected index	−0.002
Variance	0.0001
Z	25.665
p-value	0.000

), indicating that the distribution of micro-celebrities exhibits a pattern of agglomeration among neighboring cities. On one hand, the demonstration and imitation effects of successful new occupations have a strong spatial proximity. On the other hand, regions that already possess an advantage in micro-celebrity clustering have gradually institutionalized complementary services and formal institutions. The diffusion effect and the borrowed size of these institutions also conform to the law of distance decay.

4.2. The Influence Mechanism of the Distribution of Micro-Celebrities

4.2.1. Urban Amenities Level and Micro-Celebrities’ Distribution

The results of the four amenities visualizations are depicted in Figure 5. Natural amenities gradually decrease from southeast to northwest, with the southern regions being more habitable due to smaller temperature differences, warmer winters, and higher coverage of vegetation and water, aligning with the overall population density across the country. Although the level of infrastructure correlates with economic development, the per-capita infrastructure and resources for municipal districts show a trend of convergence, as indicated by the Moran’s I value of 0.0009. The polarization of social and cultural amenities, as well as leisure amenities, is the highest, with Moran’s I values of 0.156 and 0.137, respectively. Regions such as Beijing, Chengdu-Chongqing, the Yangtze River Delta, and the Pearl River Delta significantly outperform other areas in these amenities.

By comparing Figure 2 and Figure 5, a basic correlation between urban amenities and micro-celebrities emerges. Nationwide, the disparity in natural and infrastructure amenities among cities is minimal, while the disparity in leisure and social and cultural amenities is substantial, closely resembling the distribution pattern observed among micro-celebrities. There are numerous cities with high levels of natural and infrastructure amenities that struggle to attract micro-celebrities (e.g., Kunming and Haikou). However, leisure amenities and social and cultural amenities provide a more robust explanation for the distribution of micro-celebrities due to their more similar distribution, as confirmed by the scatter plot in Figure 6 and the regression results.

The scatter plot (Figure 6) reveals a steeper slope in the fitted trend line for amenities and micro-celebrities, indicating that micro-celebrities demonstrate a stronger preference for urban amenities compared to professional and technical talents. The magnitude of this preference differential is contingent upon micro-celebrities’ ability to overcome geographical constraints associated with physical office locations. Since spatial factors exert minimal influence on their content creation processes, micro-celebrities enjoy greater mobility and location flexibility. Notably, the fitted curve for social and cultural amenities exhibits the steepest slope, underscoring the pivotal role these amenities play in micro-celebrity agglomeration. This pronounced reliance on social and cultural amenities can be attributed to three key factors characterizing micro-celebrities’ professional circumstances: (1) occupational instability, (2) lack of institutional safeguards, and (3) limited identity recognition and social support—all of which are less prevalent among enterprise-employed skilled workers. This interpretation is further corroborated by comparative analysis showing that the average amenity levels in the top 10 micro-celebrity agglomeration cities significantly exceed national averages.

4.2.2. Influencing Mechanism

• Baseline Regression Results

The regression results are listed in

Table 3. Regression Results.

	Mod1	Mod2	Mod3	Mod4
${Ame}_n$	1.450	0.390	1.433 *	−0.415
${Ame}_s$	3.471 ***	1.299 ***	3.186 ***	0.881 ***
${Ame}_l$	1.747 **	0.822 ***	1.832 **	0.949 ***
${Ame}_i$	1.241 *	0.666 ***	1.432 *	0.946 ***
Emp			0.307	0.450 ***
Size	0.321 **	0.741 ***	0.327 **	0.749 **
GDP	0.024	0.085 **	0.011	0.067 *
Constant	−2.954 *	3.787 ***	−4.396 *	1.204
Adjust R2	0.757	0.853	0.771	0.861

Note: *, **, *** denote statistical significance at the 10%, 5%, and 1% levels, respectively. The dependent variable in Mod1 and 3 is the number of micro-celebrities, while in Mod2 and 4, it is professional and technical talents.

. Natural amenities display a weak influence on micro-celebrities. Although the scatter plot and separate regression model show a significant correlation, the effect of natural amenities is notably weakened when other socio-economic and cultural factors are considered. This finding indicates that the classic natural factors highlighted in migration literature—such as warm winters, cool summers, and air quality—are insufficient to be the primary factors influencing micro-celebrities’ location choices.

However, this does not imply that natural amenities are irrelevant. The narrowing gap in air quality across Chinese cities due to green development strategies and the fact that the natural environment tends to be more appealing to the elderly, while most micro-celebrities are younger, may also contribute to these findings. When controlling for employment factors, the influence of natural amenities becomes significant, highlighting their importance to some extent (

Table 4. Regression Results of Natural Amenities.

	Mod1	Mod2
Amen	4.492 ***	1.097 ***
Ln emp	0.404	0.432 **
Ln GDP	0.437 **	0.197 **
Size	1.117 ***	1.068 ***
Adjust R2	0.525	0.605

Note: **, *** denote statistical significance at the 5%, and 1% levels, respectively. The dependent variable in Model 1 is the number of micro-celebrities, while in Model 2, it is professional and technical talents.

).

Infrastructure, leisure, and social and institutional amenities consistently exert a significant positive impact on the distribution of micro-celebrities when controlling for economic factors and employment opportunities. Previous literature has recognized infrastructure and leisure opportunities as the basis of urban life quality and objective happiness. Scholars have argued that cities are more defined as places providing employment opportunities for professional and technical talents [62], while creative talents view cities as places to enjoy life [63]. This can be confirmed by comparing the results of Models 1 and 2 (

Table 5. Amenities and Micro-Celebrities of Hangzhou, Nanjing, and Suzhou.

City	${\mathit{A}\mathit{m}\mathit{e}}_{\mathit{n}}$	${\mathit{A}\mathit{m}\mathit{e}}_{\mathit{i}}$	${\mathit{A}\mathit{m}\mathit{e}}_{\mathit{l}}$	${\mathit{A}\mathit{m}\mathit{e}}_{\mathit{s}}$	MCs
Hangzhou	0.406	0.529	0.341	0.657	192
Nanjing	0.404	0.518	0.298	0.399	80
Suzhou	0.385	0.375	0.316	0.309	53

). The impact of amenities is lower for professional and technical talents, supporting Florida’s assertion that “the creative class is more inclined to high-amenities cities than professional and technical talents”. Specifically, convenient infrastructure meets residents’ daily needs [64], while the scale, diversity, and selectivity of leisure opportunities satisfy creative talents’ pursuit of personal quality of life and various post-work consumption activities.

As can be seen from model 1 (Table 3), the influence of social and institutional amenities on digital creative talents is significantly higher than other amenities and increases with the enhancement of talent mobility and autonomy (model 1 and 2). This shows that the local social institutional environment has become the core condition for cities to attract creative talents in the digital era, because the spatial binding and social contract relationship between digital creative talents and enterprises is weak, while obtaining mobility and freedom, identity, social support, security, and income stability has gradually become important challenges for them. The social and institutional amenities are the key to solving such challenges. Once social and institutional amenities are established, the resulting regional brand effect and circular cumulative effect strengthen the attraction of digital creative talents. This phenomenon explains why Hangzhou has formed a micro-celebrity cluster while Suzhou and Nanjing have not (Table 5). However, social and cultural amenities are not the primary factors shaping the distribution of creative talents unless other amenity dimensions are sufficiently high. For example, most cities in Hebei Province have failed to attract micro-celebrities, despite many incentive policies introduced for digital media and entrepreneurship subsidies, due to the low levels of other amenities. This suggests that different dimensions of amenities have more complex sequences and interactions than simple correlations in their functioning.

These results remain robust even after considering urban employment levels. The debate on the importance of economic opportunities versus amenities in talent location decision-making has persisted since Florida introduced the creative class theory [65]. Previously, it was acknowledged that amenities had an insignificant impact on the location of skilled talents [66]. However, recent evidence suggests a growing significance of amenities, although economic factors continue to have a significantly greater impact on creative talents [67]. Our findings indicate that employment opportunities do not significantly diminish the pursuit of amenities by digital creative talents, marking a distinct difference from professional and technical talents. Nonetheless, our results show that amenities exert a more pronounced influence on technical professionals than employment.

• The Influence of Specific Indicators of Amenities

The analyses reveal that the adjustment function indicators of natural amenities have a weak and unrobust influence on the micro-celebrity distribution after controlling for other amenities and economic factors (

Table 6. Regression Results of Specific Natural Amenities.

	Mod1	Mod2
Constant	−15.321 **	−10.314 **
tem-s	0.032	0.038 *
tem-w	0.018 *	−0.012
nats	0.209 **	0.192 **
grep	0.036 **	0.021 *
Other amenities		Control
Control variable	Control	Control
Adjust R2	0.719	0.749

Note: *, ** denote statistical significance at the 10% and 5% levels, respectively. The regression results excluded highly collinear and insignificant variables, including airq.

). In contrast, aesthetic functions indicators consistently show significant positive effects, indicating that creative talents prefer natural public spaces offering leisure, relaxation, and entertainment functions. These spaces, which are the objective basis of happiness [68], have been lost to varying degrees during the rapid urban expansion that China has experienced in the past few decades.

The influence of leisure amenities is primarily realized through structural and scale indicators rather than hierarchical indicators (

Table 7. Regression Results of Specific Leisure Amenities.

	Mod1	Mod2
Constant	−4.349 **	2.297 *
div-c	2.108 **	1.761 **
cons	0.449 **	0.282 **
conc	0.05	0.054
Other amenities		Control
Control variable	Control	Control
Adjust R2	0.717	0.787

Note: *, ** denote statistical significance at the 10% and 5% levels, respectively. There is no problem of high collinearity among the variables.

). Experiences from developed countries show that the high levels of spiritual consumption opportunities are more attractive to creative talents than the convenience of daily consumption. Our findings, however, suggest that the effect of higher levels of cultural consumption is not essential in developing countries after controlling for daily consumption opportunities. This does not mean that high-level spiritual consumption activities are dispensable, as these activities can be accessed inter-urban due to their low frequency of consumption in most cases. Florida’s emphasis on “a theater is more important than a shopping mall” does not consider the complementary and borrowing amenities of neighboring cities.

The regression results for infrastructure amenities indicate that the inter-urban communication ability plays a positive role, remaining robust after controlling for other dimensions of amenities (

Table 8. Regression Results of Specific Infrastructure Amenities.

	Mod1	Mod2
Constant	−5.136 **	−3.223 **
Resr	0.021 **	0.011 *
Nigo	0.038 *	0.061 *
bus	0.107 **	0.042
sch-m	0.085 **	0.037 **
flig	0.049 **	0.043 **
HSR	0.219 **	0.159 **
Hos-3A	0.102 **	0.071 **
Other amenities		Control
Control variable	Control	Control
Adjust R2	0.689	0.779

Note: *, ** denote statistical significance at the 10% and 5% levels, respectively. The regression results excluded highly collinear and insignificant variables, including hospital and sch-g.

). However, the influence of intra-urban transportation accessibility decreases significantly. Micro-celebrities exhibit higher mobility than other occupational types due to the freelance nature of their work. This finding provides evidence that the ability to communicate outside the city is more attractive to creative talents than intra-city accessibility. Meanwhile, flexible ride-hailing is more favored by digital creative talents than public transportation. In terms of medical facilities, basic medical facilities seem to be insufficient to affect the distribution of digital creative talents, but high-level hospitals have a significant impact.

The coefficients of social and institutional amenities indicators were all significantly positive (

Table 9. Regression Results of Specific Social and Institutional Amenities.

	Mod1	Mod2
Constant	−4.201 ***	−3.862 ***
top MCs	0.037 *	0.078
inte	2.246 ***	3.053 ***
tole	0.071 ***	0.012 *
MCN	0.203 ***	0.183 **
E-gov	0.041 *	0.034
Other amenities		Control
Control variable	Control	Control
Adjust R2	0.771	0.779

Note: *, **, *** denote statistical significance at the 10%, 5%, and 1% levels, respectively. There is no problem of high collinearity among the variables.

), the coefficient for MCNs decreases after considering other amenities levels, and the influence of interaction between micro-celebrities increases. On the one hand, communication based on shared identity strengthens group identity. On the other hand, micro-celebrities build and strengthen personal social networks, accumulate social capital, and improve their resistance to career instability through co-creation with other micro-celebrities [69]. This also explains the impact of MCNs, which provide temporary services such as advertising, media design, and technical support, even though most micro-celebrities do not directly join MCNs. Such partnerships, based on temporary projects, can also create informal social networks to withstand instability. Interestingly, the initial distribution pattern of micro-celebrities appears non-significant for subsequent distribution when other amenities are controlled. The initial micro-celebrities introduced this new occupation to the public, leading to its gradual acceptance by the mainstream, which caused local imitation and, consequently, more micro-celebrities. This demonstration effect is spatially dependent, making the current situation significantly related to the initial pattern of micro-celebrity distribution. However, the influence of this demonstration effect is more critical in the early stages, and as the number of we-media creators has soared in recent years, the occupation of micro-celebrity has become widely accepted, weakening the demonstration effect when other amenities indicators are controlled. This means that many cities that do not have the advantage of initial agglomeration of digital creative talents can catch up through amenities. For example, the number of the first Top 100 MCs in Hangzhou, Chengdu, and Nanjing is much lower than that in Beijing and Shenzhen, but to date, the number of MCs in these cities has been close to Shenzhen. According to the above analysis, this kind of catch-up depends more on social and institutional factors.

• Spatial Interactions of Amenities

The results indicate that leisure, infrastructure, and social and cultural amenities can be borrowed between cities. Notably, the effects of leisure and institutional amenities remain significant even after controlling for local amenities levels. This finding confirms the importance of considering spatial borrowing in the analysis of amenities. Without accounting for this, the impact of local amenities may be overestimated, especially concerning creative talents. It further suggests that the location decisions of micro-celebrities are influenced not only by a combination of economic and social factors within a city but also by the amenities available in surrounding cities.

When the level of local infrastructure amenities is controlled, the borrowing effect of infrastructure amenities becomes insignificant, highlighting the greater importance of local infrastructure conditions. Although the investment in transportation, medical care, education, and other infrastructure in cities at the prefecture level and above is somewhat correlated with the local economic level, national policies aimed at ensuring fairness in infrastructure distribution generally maintain a consistent level of infrastructure across these cities [70]. The Moran’s I result also supports the finding that infrastructure amenities exhibit lower agglomeration and narrower inter-city gaps compared to other amenities, making it less likely for people to change their location based on such narrow differences in infrastructure. In reality, it is common for smaller cities to borrow high-level medical and transportation infrastructure from central cities, but this borrowing is more prevalent between county towns and prefecture-level cities rather than between cities of the same administrative level.

The borrowing of leisure amenities remains significant even after controlling for local amenities levels, indicating the equal importance of both local leisure opportunities and inter-urban leisure accessibility. These results provide empirical support for the “spatial quality” models in new spatial economics. However, the influence of leisure amenities in surrounding areas diminishes when local leisure opportunities are taken into account. This finding confirms that amenities related to daily life are the main factors affecting the distribution of micro-celebrities, while the influence of high-level consumption is statistically insignificant. A possible reason is that low-frequency consumption can be accessed inter-urban.

Social and institutional amenities borrowed from surrounding cities continue to impact the distribution of micro-celebrities, even when other variables and local amenities are controlled (

Table 10. Regression Results of Borrowed Amenities.

	Mod1		Mod2
${Bame}_n$	−11.112		9.453
${Bame}_i$	18.132 **		9.213
${Bame}_l$	9.076 *		2.871 *
${Bame}_s$	31.213 **		35.613 **
${Ame}_n$		1.450	−0.724
${Ame}_i$		1.241 *	0.829 *
${Ame}_l$		1.747 **	1.135 *
${Ame}_s$		3.471 ***	3.469 **
Control variable	Control	Control	Control
Adjust R2	0.623	0.757	0.889

Note: *, **, *** denote statistical significance at the 10%, 5%, and 1% levels, respectively.

). Institutions, especially informal ones in traditional industries, tend to be highly localized, and the conditions for spatial spillover of economic effects from institutions are much more complex than those for infrastructure and leisure opportunities. However, the agglomeration of micro-celebrities in surrounding cities can be promoted by the institutions and social amenities of a central city, meaning that demonstration and imitation also occur between cities, particularly when transportation between them is convenient. Overall, the professionalization of micro-celebrities may be achieved through a combination of complementary institutions, informal micro-celebrity social networks, brand cooperation in the central city, and local cost advantages in peripheral areas. This complementary combination generally occurs in urban agglomerations with well-developed intercity transportation networks, but it does not universally apply unless the peripheral areas have sufficiently high amenities. For example, Hebei Province, despite its proximity to Beijing and the availability of convenient transportation networks and low living costs, has failed to form a micro-celebrity cluster.

5. Discussion

The critical role of urban land-use planning and governance in advancing sustainable development has gained heightened significance. Notably, human-centered urban design enhances regional attractiveness to skilled professionals by improving quality of life, thereby stimulating technological innovation and sustainable growth. Nevertheless, despite the transition from industrial to post-industrial economies, prevailing planning paradigms remain entrenched in industrial-era frameworks, increasingly misaligned with the spatial needs of creative talent populations. Especially, an increasing number of creative talents are breaking free from the constraints of industrial space at the physical level, thus demonstrating more flexible location choices than traditional talents. Surprisingly, however, they are still disproportionately concentrated in a few high-cost cities. Current theories fail to explain this agglomeration phenomenon, and scholars have conducted relatively few studies on such emerging creative talents. This study examines urban spatial planning strategies from the perspective of human needs and provides meaningful, concrete recommendations for urban land use in the digital era.

Future research should pursue three key directions. First, as economic transformation alters the spatial agglomeration patterns of production factors, urban planning must dynamically respond to evolving spatial demands. Systematic case studies of creative talent distribution patterns are needed to derive evidence-based land-use and spatial planning adaptations. Second, while digitalization and regional integration have created development opportunities for peripheral cities—particularly in mature urban agglomerations where cross-jurisdictional space-sharing and functional complementarity have become prevalent—current planning frameworks inadequately address this trend. Targeted research is required to establish how peripheral cities can optimize land governance systems to promote regional equilibrium. Third, methodological innovation is crucial to quantify intercity spatial integration metrics, including intensity of shared space utilization and degree of functional complementarity. Such measurements would significantly enhance evidence-based land-use planning in regional integration contexts.

Regarding the limitations of this article, the potential bidirectional causality between talent agglomeration and urban amenities may introduce endogeneity bias in our regression estimates. Specifically, while urban amenities demonstrably influence the spatial distribution of digital creative talents, the concurrent concentration of these talents may reciprocally enhance local institutional and cultural amenities. Constrained by data availability, we were unable to construct a complete longitudinal dataset that would permit more robust causal inference through time-series analysis.

6. Conclusions

This article uses the concept of amenities to explain the aggregation of this type of talents by constructing an index system of urban amenities, including natural, leisure, infrastructure, and social and institutional dimensions, and explores the spatial distribution of micro-celebrities in relation to these amenities. The main conclusions are as follows:

• First, urban amenities serve as the predominant factor influencing talent agglomeration, with this effect being particularly pronounced among digital creative professionals and demonstrating greater explanatory power than traditional employment factors. Specifically, digital creative talents exhibit distinct amenity preferences: they value designed aesthetic spaces such as urban parks and scenic areas more than climatic conditions or air quality metrics, contrasting with conventional environmental preference assumptions. Furthermore, their leisure preferences emphasize practical consumption infrastructure, including integrated shopping complexes and creative districts featuring specialty cafés, rather than the high-cultural facilities like concert halls emphasized in existing creative class theories. These findings challenge traditional notions of talent attraction factors and highlight the need to reconceptualize urban amenity planning for the digital creative economy.
• Secondly, digital creative talents also have obvious differences in their preference for amenities structure compared with other creative talents, and they are highly sensitive to local social and institutional amenities. It is related to the general occupational particularity of digital creative talents—while obtaining mobility and freedom, they also face challenges such as lack of identity, unstable income and projects, and insufficient social support and security, and the local institutional social environment is the key to solving such challenges. It further explains that the people-oriented planning strategy is not fixed and unchangeable. The urban planning strategy needs to be dynamically adjusted according to the stage of economic development. It further explains that the people-oriented planning strategy is not fixed and unchangeable. The urban planning strategy needs to be dynamically adjusted according to the stage of economic development. It means that although infrastructure and natural amenities still matter in the digital era, such amenities will converge with the improvement of economic level in the long run, and the influence of social and institutional amenities is gradually emerging and becoming more dominant. Furthermore, it is essential to emphasize that different dimensions of amenities do not simply play independent roles or perform linear addition in influencing the location choices of creative talents. There may be a complex sequence or substitution relationship, which warrants further discussion.
• Lastly, this article demonstrates that amenities “borrowed” from surrounding cities influence the location choices of micro-celebrities. This significant finding extends amenity research from the community and urban scales to the regional scale and requires further examination in other regions.

In summary, this paper, by analyzing the relationship between the agglomeration of creative talents and local amenities, and considering the mutual influence among cities, provides inspiration and suggestions for urban land use and spatial governance from a people-oriented perspective. This has significant practical significance under the trend of increasing attention to the non-production functions of cities in the post-industrial era.

This study offers critical insights for reforming urban planning and land-use strategies. First, municipal authorities must fundamentally reconsider industrial–economic paradigms in urban development, addressing a central question in urban happiness research: “What constitutes a happy city?” [71]. Effective land-use policies should equitably balance corporate requirements with human needs, particularly through increased provision of green infrastructure, recreational facilities, and transportation networks that enhance livability and life satisfaction. Second, due to digital creative workers’ heightened sensitivity to socio-institutional amenities, urban planners should prioritize developing (a) creator communities, (b) co-working hubs, and (c) interactive public spaces. These interventions can mitigate career precarity while fostering professional identity and social capital formation among young talents. Finally, from a regional perspective, local planning needs to consider the borrowing and complementarity of amenities with the surrounding urban space, thereby improving the efficiency of space utilization and reducing resource consumption and idle facilities. At the same time, it is necessary to further enhance the accessibility among cities, which is crucial for promoting the borrowing of amenities among cities, improving the efficiency of land use, giving full play to the advantages of local amenities, and achieving sustainable development.