Skilled migration is a pivotal phenomenon underpinning globalization that has attracted widespread scholarly interest; a nuanced understanding of the patterns and mechanisms of skilled migration is considered essential for fostering coordinated regional development and enhancing labor market allocation. To compare the domestic and international talent mobility research in the 21st century and advance China's talent mobility theory, In this paper, we reviewed Chinese and English literature from fields such as geography, urban planning, demography, economics, and management since 2000 via quantitative and qualitative analysis. Initially, we conducted bibliometric and keyword co-occurrence analyses using CiteSpace to identify research hotspots and trends; subsequently, we performed Qualitative Data Analysis Miner qualitative analysis as a supplementary approach to derive in-depth insights and determine connections between literature sources. Herein, we summarize the research hotspots regarding skilled migration, domestically and internationally. We found that concerning research hotpots, domestic research emphasizes the spatial distribution of different types of talent, the impact of urban factors on skilled migration, and the interplay between talent and urban innovation. In contrast, international research emphasizes more on the mobility decisions of highly skilled migrants within a globalization context, focusing on the impact of international high-skilled migration on the destination and origin countries, the micro-level mechanisms of migration decision-making (such as family dynamics, gender roles, and early career stages), and social adaptation in destination countries (including identity, sense of belonging, and related factors). Theoretically, both domestic and international studies are based on labor migration theory, examining skilled migration mechanisms from macro-regional and micro-individual perspectives, and expanding theoretical frameworks to include amenities and the creative class. However, owing to differences in social, economic, institutional, and developmental contexts among countries, these theories are not entirely applicable in practice, particularly regarding their explanatory power in the Chinese context, which requires further examination. Furthermore, in terms of research progress, we found that international studies are increasingly highlighting the life course of migrants and the socio-cultural micro-mechanisms influencing skilled migration, emphasizing the adoption of a combination of quantitative and qualitative analytical methods. Conversely, domestic research predominantly focuses on the spatial patterns of skilled migration and the effects of macro-urban factors, relying on quantitative analyses. Future research in China should aim to examine micro-mechanisms, develop indigenous theoretical frameworks to foster theoretical innovation, and enhance the integration of qualitative and quantitative methods. Moreover, exploiting the potential of big data and emerging technologies could contribute towards overcoming limitations associated with data acquisition. On the basis of our survey of current theories and methods, we propose the following four directions for future research: (1) strengthening investigations into the micro-mechanisms of skilled migration; (2) developing indigenous theoretical frameworks to support theoretical innovation in China; (3) promoting the integration of qualitative and quantitative research methods; and (4) enhancing data acquisition and exploiting big data and advanced technologies to overcome the current limitations associated with acquiring data.
The number of highly educated individuals continues to grow, and the internal heterogeneity of this group is becoming increasingly evident. Examining these differences in location selection mechanisms from the perspective of heterogeneity is crucial for optimizing talent distribution. In this study, we used population census data from 2010 and 2020, along with 1% population sampling survey data from 2015 across various provinces. We employed the Gini coefficient and visualization methods to depict the spatiotemporal patterns of talent distribution at college, undergraduate, and graduate education levels in Chinese prefecture-level administrative regions. Employing a Beta regression model, we identified the factors that influence talent distribution across four dimensions: spatial sorting, spatial selection, spatial agglomeration, and comfort preferences. The key findings were as follows: 1) From 2010 to 2020, regional disparities in educational talent were ranked as postgraduate > undergraduate > college, with a decreasing trend in disparities for all three categories. 2) The proportion of college-, undergraduate-, and graduate-level educated individuals exhibited a clear administrative hierarchy, with the proportion of highly educated individuals decreasing from capital cities to provincial capitals (vice-provincial cities), prefecture-level cities, and regions. Hierarchical differentiation was most pronounced for graduate-level individuals, and was least pronounced for college-level individuals. 3) The Hu Huanyong Line serves as a dividing line for spatial structural differences in the distribution of highly educated individuals. To the southeast of the line, the spatial structure follows a pattern from the center (provincial capitals) to the periphery (general prefecture-level regions), with graduate-level individuals demonstrating the most characteristic spatial structure. Northwest of the line, a high-talent area for college and undergraduates extends from the Daxinganling Forest region in the east to Hami in the west. 4) Urban agglomerations and metropolitan areas are gradually becoming important spatial carriers of highly educated individuals, with the most typical examples being national-level urban agglomerations, especially the Yangtze and Pearl River Deltas. 5) From 2010 to 2020, dynamic changes in the concentration of talented individuals at the associate degree, undergraduate, and graduate levels exhibited a reverse core-periphery spatial structure. Specifically, the location quotient for talented individuals in capital and provincial-level cities (including sub-provincial cities) decreased, whereas it increased in prefecture-level cities and regions. Additionally, the dynamic changes in the concentration of talented people demonstrated regional differentiation; the location quotient for talented people in areas northwest of the Hu Huanyong Line showed an upward trend, whereas it decreased southeast of the line. Similarly, the location quotient for talented people in the eastern region declined, whereas it increased in the central and western regions. 6) In terms of spatial sorting, talented people at different educational levels tended to prefer prefecture-level administrative regions with higher incomes, higher administrative ranks, and larger urban populations, with the order of preference being graduate > undergraduate > college. Regarding spatial selection, higher housing costs and more competitive job markets in prefecture-level administrative regions generally demand higher educational qualifications, following the trend: graduate > undergraduate > college. In terms of spatial agglomeration, urbanization levels in prefecture-level regions foster clustering of talented people at all educational levels, with the effect being strongest for college-educated people, followed by undergraduate and graduate people. With regard to comfort preferences, regions with higher levels of social environmental comfort are more attractive for the aggregation of highly educated individuals. Our research findings will be helpful for different cities and regions in formulating differentiated talent recruitment policies.
In the era of the knowledge economy, talent is important for the development of any country, region, or city, and attracting foreign talent to stay and settle down has gradually become an important issue. In this study, we analyzed the spatial distribution of highly educated migrants, their willingness to settle in the place they migrated to, and the social influencing factors from the perspective of migration networks using the 2017 China Migrants Dynamic Survey. We explored the differences in the influence of inter-provincial and intra-provincial migration patterns on the willingness of migrants to settle. The main conclusions are as follows: First, the willingness of the highly educated migrants to settle down shows a distribution pattern of "high in the north and low in the south." Migrants, especially highly educated people who are willing to migrate across provinces, showed highest preference for settling down in Beijing, Shanghai, and Tianjin, whereas those willing to migrate within provinces showed preference for settling down in Tibet, Shandong, and Hubei.. Second, the friendship and kinship networks of highly educated migrants show a clear pattern of "high in the north and low in the south," and the business network shows a clear pattern of "high in the west and low in the east," and the network of township ties has a clear pattern of "high in the east and low in the west." Third, migrant networks provide material and emotional social support for the migration of highly educated individuals and significantly influence their willingness to settle. Among these networks, kinship and friendship offer the greatest support and exert the strongest pull on their migration decisions. In contrast, the influence of township ties on the willingness of highly educated migrants to settle is smaller, highlighting a clear difference from the stronger reliance of migrant workers on township ties. Fourth, highly educated intraprovincial migrants, owing to their shorter migration distances and lower migration costs, are more influenced by kinship in their willingness to settle. By contrast, highly educated inter-provincial migrants who lack kinship ties in their destination areas showed a lower willingness to settle and are more influenced by friendships and hometown connections. Future research on talent migration and policies should place greater emphasis on social factors, thereby enriching the study of talent mobility from a societal perspective. This strategy is also beneficial in practice for attracting and retaining talent, not only through economic incentives but also by leveraging social policies. This fosters the integration of talent into destination cities and contributes to the socioeconomic development of these areas, thereby propelling the implementation of a talent-driven national strategy.
In recent years, the number of Chinese university graduates has been progressively increasing, and their employment situation has become increasingly poor under the influences of the COVID-19 epidemic and downward economic pressure. The employment issue of university graduates has attracted considerable attention. The migration of university graduates is synthetically affected by multiple factors including individual-, family-, and city-level factors. A systematic theoretical framework of the influencing mechanism of the migration of university graduates, which combines these factors, is lacking. Moreover, extant studies have scarcely investigated the migration of university graduates from the overall perspective of family capital, let alone different factors considered by graduates with different family capital levels in the migration decision-making process. The role of human capital in the relationship between the family capital and migration of graduates still remains unknown. To address this gap, based on first-hand survey data on the migration of new graduates from 78 universities in eight cities in 2022, this study employs a nested logit model to examine the influencing factors on the intercity migration of university graduates from both the individual and city levels, and reveals the dual influencing mechanism of family capital (economic, cultural, and social capital) and human capital (education qualification, university type, student cadre status, academic records, certificates, and internship experience). The results demonstrate that: 1) Family capital exerts a significantly positive impact on the intercity migration of university graduates. Graduates with higher levels of family capital are more inclined to move to higher-level cities. Compared with graduates whose parents have an annual income level below 90 thousand RMB and highest education qualification below a college degree, graduates whose parents have an annual income level above 90 thousand RMB and highest education qualification above a college degree are more likely to flow to first-tier and second-tier cities. 2) The influence of family capital on the migration of graduates presents significant heterogeneity. When choosing employment cities, graduates with a higher level of family capital pay more attention to urban economic and amenity factors. Compared with graduates with lower levels of family capital (represented by lower parental income levels, lower educational qualification levels, and parents' non-managerial or professional occupations), graduates with higher levels of family capital (opposite to their counterparts) are more affected by income levels, living costs, environmental quality, medical resources, and cultural resources, in selecting employment cities. 3) The human capital of graduates plays both a positive mediating role and a certain degree of a negative moderating role in the impact of family capital on the migration of graduates. All the variables of human capital play a positive mediating role, that is, family capital positively influences the migration of graduates by affecting their human capital; however, some variables of human capital (student cadre status, academic records, certificates, and internship experience) play a negative moderating role, that is, the human capital accumulated in the university can weaken the impacts of family capital on the migration of graduates. By introducing a spatial perspective, this study provides not only empirical evidence for the response to the social concern about whether getting good jobs depends on family background or personal efforts, but also scientific references for promoting the full employment of graduates and guiding the rational talent flows.
Understanding the factors influencing the return of high-level scientific and technological talent from outside China's customs borders is important for optimizing the policy practice of introducing high-level talent from abroad. Based on the biographical information of 1,248 high-level scientific and technological talents who had studied or worked outside China's customs borders and then returned to China to obtain the National Outstanding Young Scientist Fund from 2009 to 2020, this study analyzes the characteristics of the spatial pattern of the return of high-level scientific and technological talents from outside China's customs borders and their influencing factors using social network analysis and a nested logit model, respectively. The results reveal the following: The outflow city network for talents from outside China's customs borders centers around Hong Kong (China) and Cambridge (USA), while the inflow city network is centered on Beijing and Shanghai. There are notable regional differences in the distribution of cities where these talents return.Cambridge (USA) is the primary source of returning talents to Beijing and Shanghai, while Singapore is the main source of returning talents to Nanjing. For Guangzhou and Wuhan, Hong Kong (China) serves as the main source of returning talents.At the individual level, academic ties and the level of talent introduction programs significantly influence the choice of cities for returning talents. At the macro level, high salaries, significant investment in science and technology, and a high concentration of top-tier scientific research platforms in Chinese cities are the primary factors attracting high-level talents from outside China's customs borders. Additionally, the quality of educational service facilities and favorable climate conditions also play a significant role in influencing city choices.Individual heterogeneity exists in the influence of urban macro-factors on location choices for talent return. Male talents, those with mobility experience, or those who have resided outside China's customs borders for an extended period tend to place greater emphasis on academic and social ties as well as support from high-level talent introduction programs. Conversely, talents returning later are more influenced by higher salary levels and the availability of top-tier scientific research platforms in the city.Compared with existing studies that primarily focus on analyzing the influence mechanisms of talent return driven mainly by policy factors, this study contributes to revealing the joint impact of government policy factors and market-oriented factors on the return of high-level scientific and technological talents.
As China transitions to high-quality economic development, the innovation-driven growth model places increasing demand on the high-tech industry, highlighting the critical role of high-tech talent in enhancing regional competitiveness. Existing studies have primarily focused on talent distribution patterns at national or provincial levels, with limited exploration at the city level. Furthermore, most studies concentrate on the distribution patterns and influencing factors at a single stage, treating talented individuals as a homogeneous group without a comparative analysis of the differences in talent distribution across employment stages, educational qualifications, or school levels. To address these gaps, in this study, we employed big data on high-tech talent resumes spanning 2003 to 2021 using spatial analysis techniques and spatial econometric models to examine the spatial distribution patterns and influencing factors of high-tech talent across different employment stages at the urban scale. Additionally, we explored the heterogeneity of the influencing factors at various educational qualifications and institutional levels. The results reveal the following. First, high-tech talents in China are predominantly clustered in economically developed eastern coastal regions, provincial capitals, municipalities, and urban agglomerations. Compared with the initial employment stage, the spatial concentration of high-tech individuals intensified during the current employment stage. The number of dense clusters in the eastern coastal regions decreased, whereas the number of non-dense clusters in the western and northeastern regions increased. A strengthened "high-high" clustering pattern around central cities in urban agglomerations reflects the increasing preference for high-tech talents in such areas. Second, the factors influencing the distribution of talented individuals differ significantly across employment stages, and are shaped by economic conditions, amenities, talent policies, and administrative hierarchies. Economic factors, particularly income levels, play a dominant role during the initial employment stage, whereas amenities become more influential in the current stage, reflecting a growing focus on quality of life as material needs are met. Talent policies significantly affected talent distribution at both stages. Third, the distribution of high-tech individuals exhibits heterogeneity across educational qualifications and university tiers. High human capital groups, such as postgraduate degree holders and graduates from "double first-class" universities, demonstrate a stronger preference for amenity factors, particularly during the current employment stage. These findings have important implications for understanding talent distribution dynamics, optimizing talent allocation, and fostering supportive environments for talent development. This underscores the urgent need for effective management of high-tech talent mobility, formulation of targeted and actionable talent policies, and enhancement of talent governance modernization.
As China enters a critical transition period towards a knowledge-based economy, the optimization of the educational attainment structure and spatial distribution of the civil service, a crucial component of modernizing the national governance system and capacity, exerts a profound influence on enhancing government efficiency and fostering social progress. Based on recruitment data from the 2023 Guangdong Provincial Civil Service Examination, this study employs spatial statistical methods and Multivariate Logistic Regression analysis to examine the urban hierarchy migration model of newly graduated students admitted to civil service positions and its influencing factors. The research findings indicate: (1)The migration model of admitted newly graduated students are predominantly migrate down the urban hierarchy. For non-equivalent-level migrations, destinations are mainly fourth-, third-, and first-tier cities, whereas for equivalent-level migrations, destinations are primarily fourth-, third-, and second-tier cities. (2)Among personal attributes (including gender, university ranking, and the tier of the city where the graduation school is located), except for graduates from universities in the fourth- and fifth-tier cities, all other groups predominantly migrated down the urban hierarchy. (3)In terms of work-unit level and job requirements (including educational qualifications and work experience), the admitted candidates across all groups predominantly migrated down the urban hierarchy. (4) The results of the multiple logistic regression showed that personal attributes, work-unit level, and job requirements jointly affected the choice of migration mode for admitted candidates. Personal attributes and job requirements have a relatively significant impact; the better the personal attributes and the higher the job requirements, the more likely they are to migrate up the urban hierarchy. The effect of job conditions was not significant. (5)The results of the mechanism analysis revealed that the choice of migration model among newly graduated students is a complex and dynamic decision-making process underpinned by the interplay of multiple factors, such as government policy guidance, job characteristics, personal factors, and urban conditions. The decision-making and selection process in the selection mechanism for the migration mode of newly recruited graduates in the civil service examination is complex and dynamic, involving the interaction of multiple factors, such as government policy guidance, job characteristics, personal factors, and urban conditions, with objective limitations, personal abilities and resources, and subjective willingness. Compared to other non-establishment employment models, this employment model has a stronger possibility of migrating down the urban hierarchy, which may be caused by significant differences in the sources of job settings, competition intensity, and subjective willingness. To achieve the strategic goal of building a high-quality young civil service, the government should consider the multifaceted and complex interactions within the recruitment process, leverage its administrative functions, flexibly adjust job settings, and attract and retain outstanding newly graduated students through measures such as optimizing the urban environment and enhancing public service levels. This study has significant implications for local governments in formulating scientific and reasonable civil service recruitment policies tailored to local conditions, and guiding newly graduated university students to make informed and rational decisions when applying for civil service positions.
With the vigorous development of the global sports industry and the continuous improvement of competitive sports, the cultivation and development of sports talent has become an important component of sports strategies in various countries. An in-depth exploration of the spatiotemporal evolution laws and driving mechanisms of high-level tennis players in China is of great significance in sports talent research. It reveals the spatiotemporal distribution characteristics of sports talent, analyzes the internal logic of evolution, and lays a theoretical foundation for sports talent cultivation and resource allocation optimization. This study focuses on a group of high-level tennis players in China, taking a unique approach from the perspective of geography of talented individuals, and comprehensively using multiple quantitative analysis methods to explore their spatiotemporal distribution characteristics and influencing factors: 1) From 2013 to 2022, the annual distribution of high-level tennis players in China was uneven. The eastern region, leveraging its early advantages in terms of economy, facilities, and talent cultivation, has long accounted for the majority of players. However, in the past decade, there has been a slight decrease, partly because of the maturity of talent pipelines and the outflow of talent. The central and western regions, bolstered by policies, tournaments, and the return of talent, have experienced frequent fluctuations in player numbers. In contrast, owing to industrial adjustments and changes in sports investment strategies, the northeastern region has experienced significant fluctuations in the number of players and instability in tennis talent cultivation. 2) In terms of spatial distribution, tennis players are concentrated mainly on the southeast side of the Hu Line, where the economy and culture are advanced and sports resources are abundant and readily available, forming a stark contrast with the northwest region. Further exploration of the spatial evolution trajectory revealed that the major axis of the standard deviational ellipse aligns in a northeast-southwest direction. Over the past decade, the area encompassed by the ellipse has expanded considerably, directly reflecting the expanding distribution range of tennis players, which is no longer confined to traditionally advantageous regions. Meanwhile, the spatial center of gravity has shifted towards the southwest, indicating that the southwestern region is gradually emerging as a hub for attracting and cultivating tennis talent and is becoming an emerging force in tennis development. 3)According to the factor analysis, the urbanization rate (regression coefficient 0.608), per capita GDP (0.518), and the number of regional tennis courts (0.493) were the core factors. The correlation coefficient between the urbanization rate and the number of regional tennis courts was 0.793, the correlation coefficient between per capita GDP and the number of regional tennis courts was 0.783, and the interaction coefficient between per capita GDP and urbanization rate was 0.758. The synergistic effect far exceeded that of a single factor. This study theoretically fills a gap in tennis talent geography, constructs an innovative analytical framework, and assists sports departments in implementing precise policies to promote tennis development. The literature opens new paths for subsequent research, provides empirical references, and triggers in-depth discussions in academia.
In the knowledge economy era, technological innovation has become increasingly crucial in forming international competitive advantages and driving national economic development. However, the global distribution of technological innovation remains uneven, with a sustained "core-periphery" structure. From the perspective of evolutionary economic geography, technological development paths are closely linked to the local knowledge base, making it generally difficult to overcome spatial constraints. Consequently, the path-dependent nature of national technological development may reinforce the disadvantageous position of late-developed countries in global technological progress, further widening the technological development gap. In this context, exploring how latecomer countries can achieve innovation breakthroughs spatially becomes essential. From the viewpoint of talent mobility, we employ a global patent database and data on the stock of highly skilled mobile talent to construct a country-time-level econometric model to analyze the impact of birthplace diversity among highly skilled talent on the ability of destination countries to achieve place-breaking innovations. Additionally, we conduct group regression based on multidimensional proximity (geographic, cultural, and institutional) to analyze the varying roles of different talent groups. Our findings reveal that greater diversity in the birthplaces of mobile talent significantly increases the likelihood of destination countries accessing new technological fields unrelated to their existing knowledge base. This suggests that the diversity of talent's country of origin positively influences place-breaking innovations in the destination country. Moreover, we find that multidimensional proximity affects the mechanism by which talent diversity drives place-breaking innovations. Specifically, talent diversity has a stronger impact on breakthroughs between geographically and culturally distant countries, while institutional distance appears less significant. This is likely because mobile talent from geographically distant countries brings more differentiated knowledge and skills, helping destination countries overcome geographical constraints on technological development. In contrast, between culturally closer countries, mobile talent faces fewer communication and integration barriers, which enhances the positive effects of their birthplace diversity. The results suggest that, when introducing highly skilled migrants, countries should focus not only on the scale and quality of talent but also the diversity of talent origins. Actively recruiting highly skilled individuals with diverse skills and differentiated knowledge can foster technological development, help overcome geographical constraints, and achieve technological catch-up. Additionally, countries should cultivate supportive linguistic, cultural, and social environments to ease the cross-cultural adaptation challenges faced by highly skilled immigrants. Simultaneously, countries should promote interaction among diverse talent groups, facilitate communication with local talent, and build affiliation networks to better leverage the benefits of talent diversity. These insights provide important guidance for latecomer countries in designing immigration and innovation policies and offer a new direction for future research. Future studies should explore non-proprietary innovation behaviors, delve into the integration and exchange among different talent groups at the micro level, and examine the underlying mechanisms using both quantitative and qualitative methods.
Industry and occupation are closely interwoven. Focusing solely on industrial structure cannot adequately address regional development challenges. Multifactor cross-relatedness provides a theoretical foundation for understanding the interplay between regional industrial and occupational relatedness. This study introduces the concept of industry-occupation cross-relatedness to investigate how urban labor skills influence industrial evolution in China, while also analyzing regional and industrial heterogeneity. Specifically, we construct a city-industry panel dataset using Chinese customs import-export data (2000-2015), census data (2000 and 2010), and population sampling survey data (2005 and 2015). This dataset enables us to analyze the structural evolution of the spatial network of industry-occupation interactions. Employing a linear probability model, we examine the impact of industrial relatedness and industry–occupation cross-relatedness on industrial evolution, with a focus on regional and industrial heterogeneity. The main findings are as follows: (1) The cross-relatedness between industries and occupations in Chinese cities has increased over time. Average industrial relatedness density exhibits a significant increase, particularly in eastern regions. Cross-relatedness density shows an increase in regions with moderate cross-relatedness values but a noticeable decline in the northeastern regions. The spatial distribution of the average industrial relatedness density and industry-occupation cross-relatedness density exhibits high consistency. (2) Industry-occupation interaction drives industrial evolution in Chinese cities. A path-dependence effect is evident in industrial evolution. The synergy between industries and occupations enhances regional industrial comparative advantages. The spillover effect of locally related industries strongly supports industrial comparative advantages, second only to the influence of pre-existing industrial foundations. (3) Regional and industrial heterogeneity is notable. Regionally, the probability of previous-stage dominant industries remaining dominant decreases from east to west. Industrial path dependence also declines from east to west, while cross-relatedness has a more significant impact on forming comparative advantages in eastern regions, followed by central regions. Larger cities exhibit a higher probability of path breakthroughs through skill-relatedness. Industrial heterogeneity shows that skill structures contribute the most to the diversification of technology-intensive industries, followed by capital- and labor-intensive industries. This study also provides several policy implications. First, regions should adhere to the principles of economic and social development to formulate reasonable talent demand. Second, vocational education should undergo deeper supply-side structural reforms to better meet industry needs. Finally, cities in different regions should adopt differentiated industrial and labor policies to align with their unique contexts and development stages. Compared with previous research, the marginal contributions of this study are threefold. First, it emphasizes the critical role of human capital as a foundation for high-quality regional industrial development, offering theoretical and methodological insights for promoting employment and addressing structural employment challenges. Second, it explores the bidirectional influence of labor and industry from a multi-factor interaction perspective, advancing research integration in evolutionary economic, industrial, and labor geography. Third, by focusing on coordinated development between industries and occupations, this study provides practical insights for aligning industrial and labor policies, facilitating the deep integration of industrial and talent chains to achieve high-quality development.
In the context of intersecting knowledge economies and globalization, attracting international academic migrants has become a crucial external driver for fostering innovation and sustainable development at national and regional levels. The knowledge production activities of international academic migrants in their host countries are embedded within local institutional and cultural environments, and involve multidimensional interactions that engage in economic and sociocultural geographies. However, limited research has examined how different types of collaborative network embeddedness affect the knowledge production of these migrants and the intricate sociocultural mechanisms underlying these dynamics. This study examined network embeddedness in knowledge production by combining the "buzz-pipeline" framework with strong- and weak-tie models, focusing on the structure and characteristics of three types of collaborative networks: local buzz collaborations, domestic pipeline collaborations, and international pipeline collaborations. In-depth interviews with international academics provided qualitative insights into the sociocultural dynamics that drive network embeddedness. Key findings include: (1) Spatial characteristics: Local buzz collaborations among international academics in China are largely concentrated in cities, such as Suzhou, Ningbo, Shantou, and Shenzhen, underscoring the importance of localized networks. Regional hubs, such as Guangzhou and Shanghai play a pivotal role in facilitating cross-city exchanges within urban clusters. Domestic pipeline collaborations are predominantly found in provincial capitals, with Beijing leading the most. International pipeline collaborations are mainly oriented toward developed countries, particularly in Europe and the United States. (2) Network relationships: Domestic pipeline collaborations positively influence both local buzz and international pipeline collaborations. However, a negative correlation exists between local buzz and international pipeline collaboration, suggesting that scholars engaged in strong local networks may be less likely to establish extensive international ties. (3) Impact of network embeddedness: Both "buzz" (regional cooperation) and "pipeline" (cross-regional and cross-national cooperation) have a significant positive impact on the knowledge production of international scholars. However, in terms of knowledge spillover, domestic pipeline collaborations yielded better results in terms of paper output and quality than that by local buzz and international pipeline networks. Strong-tie local buzz networks are the most effective models for maintaining the research productivity. (4) Social and cultural mechanisms: Sino-foreign cooperative universities play an important role in fostering strong institutional ties, resulting in a "broad weak-tie domestic pipeline and a stable strong-tie local buzz" model that maximizes knowledge production. On one hand, Local weak-tie collaborations serve as bridges between international scholars and key research resources. On the other hand, international collaboration networks favor strong-tie international pipelines because of the difficulties international scholars face in completely embedding them into local cultural and institutional contexts. Simultaneously, a stable international collaboration network, particularly one established prior to their arrival in China, can enhance the competitiveness of academic community in China. Concludingly, this study contributes to the literature by offering a nuanced understanding of the multi-scalar and sociocultural dimensions of collaborative networks that shape the knowledge production of international academic migrants. This study provides valuable policy insights for enhancing the ability of China to attract, integrate, and retain global talent. Strengthening institutional support, fostering deeper local embeddedness, and facilitating cross-regional and international collaborations are essential for consolidating the position of China in the global knowledge economy.
Social changes have triggered a drive for change among young people, leading to a spatial reverse mobility trend among university graduates in China, amid shifts in both domestic and international contexts. Using university graduates in Guangzhou as a case study, this study employed a mixed-methods approach, integrating questionnaire surveys, cyber-ethnography, and in-depth interviews. Grounded in spatial and social mobility theories, this study explores the motivations, processes, and outcomes of reverse mobility from the perspectives of structural factors and individual agencies. The findings reveal that: (1) the unequal distribution of spatial resources, shifts in mobility within modern society, and the unique socio-historical environment of Generation Z graduates jointly shape their reverse mobility preferences, with the unequal distribution of spatial resources driving university graduates to consider their location choices from both urban and individual perspectives. Resources available in cities are uneven, and individuals have varying access to these resources. They need to uncover comparative advantages in order to "overtake on a curve." The transformation of societal mobility further facilitates the diversification of movement. Spatially, rapid intercity movement enabled by technology allows some local resources, previously exclusive to first-tier cities, to be more easily accessed across regions. The rapid flow of information further amplifies regional disparities and provides a multifaceted understanding of different cities. Graduates from Generation Z, who are in a unique historical era and social structure, increasingly focus on noneconomic factors such as class mobility, quality of life, and cultural consumption when making employment decisions, no longer simply considering economic opportunities. (2) The factors influencing the reverse migration of university graduates mainly include the realization of their economic, social, and educational cultural capital, as well as considerations of the cost of urban living and the overall environment. According to survey results, university graduates had a clear understanding of the differences between cities. They recognized that first-tier cities offer better matching job opportunities for their fields and higher social status in the future, along with superior cultural resources and public services. However, they are also aware that competition in first-tier cities is intense, the possibility of upward social mobility is relatively low, housing costs are high, and quality of life is lower compared to that in non-first-tier cities. (3) The interviews further confirmed that reverse spatial mobility to lower-tier cities does not necessarily signify a decline in the social status of graduates. Many adapt well to new locales, embedding themselves both spatially and culturally and constructing new social networks that afford a quality of life that is not easily attainable in larger cities. This study developed a new framework for understanding the mechanisms underlying university graduates' reverse mobility by systematically examining pre-migration motivations and post-migration local negotiations and adaptation. By taking a more comprehensive view encompassing economic, non-economic, structural, and agentic factors, this research deepens our understanding of man-milieu interactions during the social transition period. It offers insights into local development and talent attraction strategies and provides policy recommendations to promote balanced urban development in a highly mobile society.
In the digital economy, developing skills among women with disabilities is crucial for improving their employment opportunities and income. This study examines the Aide Training School in Yixing City, Jiangsu Province as a case study to explore skill development pathways for women with disabilities based on the empowerment theory. The integration of government, market, and social resources, enhances their expertise in traditional crafts, strengthens market competitiveness, promotes economic independence, and supports social integration. Research Methods This study employed qualitative research methods, including participatory observation and in-depth interviews. Targeted interviews were conducted with 25 participants, including women with disabilities, institution heads, and disabled artisans at the Aide Training School in Yixing City. Data related to the Training School was also collected. Using an intersectional perspective, this study draws on Sirivaddhana's (1998) three empowerment methods for women and Qian Ning's (2020 internal and external framework to analyze skill development and reemployment processes, leading to self-empowerment and identity transformation. Results and Conclusions: 1)The Aide Training School integrates government, market, and social resources, to provide comprehensive skill training and employment support for women with disabilities. This has significantly improved their proficiency in traditional crafts, such as Yixing purple sand pottery. The local cultural significance of Yixing purple sand pottery serves as "local identity capital" for women with disabilities, enhancing their market competitiveness and economic independence. 2) Skill development and re-employment transform the social identity and roles of women with disabilities. They transition from marginalized, unemployed, or low-income groups to skilled professionals with stable incomes, improving their social standing and self-perception. Additionally, they gain social recognition through the identity of "purple sand pottery culture communicators." 3) Skill development expand social participation opportunities. Through market sales, cultural exhibitions, and social services, these women build social networks, increase their influence, gain greater decision-making power, reinforcing empowerment outcomes. This study provides novel perspectives and methodologies for research on the skill development and reemployment among women with disabilities in China. Theoretically, it applies empirical case analysis to substantiate the explanatory utility of empowerment theory in elucidating the pathways and mechanisms of skill development for women with disabilities, thereby enriching the application of empowerment theory within this demographic and compensating for the previous neglect of this group within the empowerment theory. The proposed "human-land interaction empowerment" mechanism adds localized, intersectional insights to feminist geography. Practically, this research deepens the understanding of the empowerment process for women with disabilities, particularly in enhancing self-awareness, strengthening capabilities, and achieving skill development, thus providing a practical foundation for the evolution of subsequent related theories and, to some extent, advancing the career development of individuals with disabilities and providing innovative employment strategies.
