Multidimensional Proximity Research Articles

The Impact of Multidimensional Proximity on Enterprise Cooperative Innovation Performance

The Impact of Multidimensional Proximity on Enterprise Cooperative Innovation Performance

Spatial Characteristics and Influencing Factors of Intercity Innovative Competition Relations in China

In the knowledge economy era, innovation has become a key emphasis for urban competitions. This paper constructs a theoretical research framework that integrates the basic understandings, influencing factors and ensuing results of intercity innovative competition relations. On the basis of data from the general programs of the National Natural Science Foundation of China from 2005 to 2019, this paper constructs intercity innovative competition relations in China, analyses their spatial distribution and quantitative characteristics, and quantitatively investigates the impact of urban innovation capacity and multidimensional proximity (e.g., geographical proximity, institutional proximity and cognitive proximity) on intercity innovative competition relations through a negative binomial model. The study obtained the following findings: (1) In terms of the overall intercity innovative competition relations, the intensity of China’s intercity innovative competition relations gradually increased from 2005 to 2019, with a spatial clustering towards cities with high administrative ranks (e.g., municipalities directly under the central government, sub-provincial cities and provincial capitals); Beijing is always at the centre of innovative competition relations, but its standing has slightly slipped in recent years. (2) From the perspective of disciplines, cities can become benchmarks in particular fields of innovative competitions by competing according to their disciplinary strengths; intercity innovative competition relations in China vary across various academic disciplines. (3) In terms of influencing factors, urban innovation capacity has significant positive effects on intercity innovative competition relations; geographical proximity, institutional proximity and cognitive proximity all have significant positive effects on innovative competition relations; and interactions occur between multidimensional proximities, including a complementary effect between geographical proximity and institutional proximity, a substitutive effect between cognitive proximity and geographical proximity, and a substitutive effect between cognitive proximity and institutional proximity.

Exploring collaborative innovation evolution of China’s energy conservation and environmental protection industry: a social network analysis based on patents

Purpose Energy conservation and environmental protection industry (ECEPI) is a strategic choice to promote energy conservation and emission reduction, develop green economy and circular economy. However, China’s ECEPI is still in the stage of rapid development and the overall scale is relatively small, what development periods have the ECEPI experienced? This study aims to contribute to a better understanding of collaborative innovation evolution based on social network analysis from the perspective of multi-dimensional proximity. Design/methodology/approach Methodologically, this study uses social network analysis method to explore the co-evolution of multidimensional collaboration networks. It divides China’s ECEPI into four periods based on national policies from 2001 to 2020. This contribution constructs collaborative innovation networks from geographical, technological and organizational proximity. Findings The results show that the collaborative innovation network was initially formed in the central region of China, gradually expanded to neighboring cities and the core positions of Beijing, Jiangsu and Guangdong have been continuously consolidated. C02F has been the core of the collaboration networks, and the research focus has gradually shifted from the treatment of wastewater, sewage or sludge to the separation field. Enterprises always occupy a dominant position in the collaboration networks. Originality/value This research investigates the dynamic evolution process of collaborative innovation network in China’s ECEPI from the perspective of multidimensional proximity, explores the community structure, important nodes and multidimensional proximity features in the network, expands the research perspective on evolution characteristics of innovative network and the research field of social network analysis. Theoretically, this study enriches collaborative innovation theory, social network theory and multi-dimensional proximity theory.

Drifting towards collaborative innovation: Patent collaboration network of China’s nuclear power industry from multidimensional proximity perspective

In recent years, in order to solve the problem of resource shortage and environmental degradation, nuclear power has become the strategic choice of many countries due to its unique advantages. China's nuclear power started in the 1970s. After decades of development and continuous independent innovation, China has grown into one of the superpowers in nuclear field. But how does China's nuclear power develop and innovate? This study aims to provide valuable insights into cooperative innovation in China's nuclear energy industry from the perspective of network. By analyzing the patent data of China's nuclear energy industry from 1986 to 2019, we constructed a patent collaboration network in China's nuclear power field. Then, we analyze the structure of the network by using social network analysis (SNA) method, and explore the characteristics of the network we build from the perspective of multidimensional proximity. The result reveals that the patent collaboration network in China's nuclear energy industry is drifting toward collaborative innovation. Through the network, the innovation subjects in nuclear power field can better achieve resource sharing and promote the overall innovation level of the network. At the same time, we find that organizational proximity and technological similarity contribute to the cooperation between organizations in China's nuclear power field, while geographical proximity has little influence on the collaboration. This study has important implications for understanding collaborative innovation in China's nuclear energy industry and gives in-depth insights into network collaboration patterns, providing valuable references and guidance for the development of relevant policies and strategies.

A study on the multidimensional driving mechanism of cross-regional scientific collaboration network in China

ABSTRACT Multidimensional proximity has been considered the important factor affecting regional scientific collaboration network (RSCN) and has received extensive attention from scholars. This paper constructs a cross-RSCN based on co-authorship across 31 regions in China, incorporates traditional multidimensional proximity and network embedding proximity into a unified framework and proposes a five-factor driving model for dissecting the mechanism of cross-regional scientific collaborative innovation (CI). The results show that the scientific collaboration network is gradually becoming saturated with connections, and the polarisation of cross-regional collaboration is increasingly serious. The collaboration intensity is affected by the co-movement of several proximity factors, among which geographic proximity (GP) is the main but not the sole one that positively affects the cross-regional scientific collaboration. Based on the decision tree model, we conclude that structure proximity may compensate for low GP and low economic proximity (EP) on cross-regional CI performance. The positive effect of network location proximity on regional scientific collaboration is more sensitive when the EP is not high. The findings provide significant guidance for scientific research institutions, universities and regional policy-makers to select appropriate partners as well as network embedding strategies, and further contribute to long-term improvement of scientific innovation performance and stable regional economic growth.

Standard Radiation: A New Perspective Leading the Coordinated Development of Urban Agglomerations

With the increased communication among cities, coordinated development between regions has become a common trend. An urban agglomeration is a special spatial structure unit, which becomes an important driving force for the coordinated development of the region through the radiation effect generated by the central city. The existing studies on regional integration have focused more on the economic, financial, and technological innovation radiation effects. However, as an essential tool for economic development, technological progress, and social governance, the standard plays an irreplaceable role in promoting regional integration and enhancing the coordinated development of urban agglomerations due to its ability to consensus and cooperation sharing. Therefore, based on the theories of growth pole, radiation effect, and city field, this paper first puts forward the concept of the standard radiation effect and argues that the standardization level of the central city can lead and drive the development of the urban agglomerations through the method of theoretical elaboration. Secondly, we explain the mechanism of the standard radiation effect in promoting the coordinated development of urban agglomerations under the interaction of multi-dimensional proximity. Finally, taking the Beijing-Tianjin-Hebei urban agglomeration, the Yangtze River Delta urban agglomeration, and the Guangdong-Hong Kong-Macao Greater Bay Area in China as typical cases, this research explores and summarizes three different models of the standard radiation effect, which are dominated by institutional proximity, economical proximity, and geographical proximity, respectively. The results of the study show that the standard radiation has a regional leading role. Furthermore, the effect of the central city in different urban agglomerations is dominated by different proximity, and there are different models and paths. Thus, in the process of regional industrial collaboration, it is necessary to focus on the standard cooperation among cities, and according to the characteristics of different urban agglomerations, make the most effective use of advantageous proximity to promote the development of regional integration. The conclusion can enrich the relevant studies on the agglomeration and radiation effects, give theoretical explanations on how the standard radiation effect of the central city leads to regional development, and provide new thinking perspectives and practical references on the way to achieve coordinated development of urban agglomerations.

Research on the Enterprise Collaborative Innovation Performance in the Economic Circle of Chengdu-Chongqing from the Perspective of Proximity

Based on the perspective of proximity, in the context of the Economic Circle of Chengdu-Chongqing of China, we use invention patent data provided by the China National Intellectual Property Administration and conduct negative binomial models to empirically test the impact of multidimensional proximity on enterprise collaborative innovation performance. We further examine the moderating effect of enterprise innovation capacity on the relationship between multidimensional proximity and enterprise collaborative innovation performance. The results show that technological proximity, geographical proximity, and institutional proximity all positively affect enterprise collaborative innovation performance. Enterprise innovation capability has a negative moderating effect on the relationship between institutional proximity and enterprise collaborative innovation performance, but it cannot negatively moderate the positive effects of technological proximity and geographical proximity on enterprise collaborative innovation performance.

Investigating the effect of university enterprise collaboration on individual innovation in underdeveloped regions

<abstract> <p>The innovation capability index of underdeveloped regions lags far behind that of the eastern coastal areas. This imbalance in innovation capability poses a critical challenge for underdeveloped regions in implementing its innovation-driven development strategy and economic transformation. Individual collaborative innovation ability is an essential skill that allows individuals to transform knowledge and resources into economic value. Presently, research on individual collaborative innovation capability focuses only on the external environment, cooperation mode and benefit allocation. This approach fails to reveal how organizational factors affect individual collaborative innovation capability, and there is a lack of research on underdeveloped regions. Collaborative innovation theory proposes that deep cooperation between industries or institutions through acquiring resources and knowledge can have a positive impact on other environments. Improving individual collaborative innovation capabilities must be achieved through the integration of heterogeneous innovation resources owned by the two core innovation entities, to achieve full integration of innovation elements. Therefore, collaborative innovation theory can effectively address this problem. This article adopts a quantitative research method. A sample of 911 teachers was selected from thirty vocational colleges in Inner Mongolia. The data were analyzed using the Hierarchical Linear Modeling (HLM) model and the proposed relationship was validated. The research findings indicate that cognitive, social and geographical proximity have significant positive effects on collaborative behavior. Collaborative behavior has a significant positive impact on individual collaborative innovation ability. Collaborative behavior plays a mediating role between multidimensional proximity and individual collaborative innovation ability. This study will add information on the collaborative innovation theory, help to understand the formation and impact mechanism of cooperative relationships in school-enterprise cooperation in underdeveloped regions, and thus promote the development of STEM education in underdeveloped areas.</p> </abstract>

Global–Local Knowledge Spillover Strategic Coupling Network: Biopharmaceutical Industry Study of GBA, China

Strategic coupling is a hot field in the research of global production networks. The existing literature mostly consists of studies from the perspective of countries, regions, and enterprises, and relatively lacks the content for describing global–local strategic coupling networks and their evolution path with industries as carriers. The GBA is a bridgehead for China to participate in the global production network. Based on the systematic construction of the strategic coupling network analysis framework of global–local knowledge spillovers, this paper, taking the biopharmaceutical industry of GBA as an example, depicts the evolution process of its coupling network nodes, structures, and networks from 1990 to 2019 by using system analysis, social network analysis, and other methods, and analyzes node centrality, network structure, coupling paths, and their influencing factors. We found that the strategic coupling of global–local knowledge spillover is typically a networked structure, with the network organization presenting a multi-element sub-system hierarchical state. The overall network structure, with knowledge spillover as the carrier, shows obvious phased differences, having gone through three path stages from exploratory to expanding to stable. The path selection shows a spatial progression and a temporal sequence. The main factors affecting the path selection of the coupling network are the bargaining power of regional knowledge, behavioral subjects’ will, and multi-dimensional proximity.

Evolution of innovation networks in industrial clusters and multidimensional proximity: A case of Chinese cultural clusters

The innovation and optimization of cultural industry clusters is important to the promotion of economic structural transformation and high-quality development. Taking 31 provinces (municipalities directly under the Central Government and autonomous regions in China) as the research object, the cross-sectional data included the number of joint patent applications for culture and related industries among provinces (regions) in 2014, 2016, 2018 and 2020. Then, the cluster innovation network was constructed using social network analysis (SNA) based on scientific identification of cultural industry clusters. This new cluster innovation network structure and its spatial evolution characteristics are accessible with the help of UCINet and ArcGIS tools. Finally, the multiple regression-quadratic assignment procedure (MR-QAP) method is used to determine the influence of geographical proximity, technological proximity, and social proximity on the evolution pattern of the cultural industry cluster innovation network. The results of the study are important for improving the efficiency of national cultural industry innovation and promoting regional synergistic development.

Spatio-temporal evolution and influencing factors of scientific and technological innovation level: A multidimensional proximity perspective.

Through a literature analysis, this study proposes that the difference between scientific innovation and technological innovation has been ignored in the current research on the level of scientific and technological innovation and its influencing factors. Combined with multidimensional proximity and knowledge type of current research, a theoretical induction has been carried on their corresponding relation with scientific innovation and technological innovation, research hypotheses were proposed the multidimensional proximity effect on the mode and degree of scientific innovation and technological innovation, five theoretical factors, which are the economic development level, regional economic structure, the level of opening to the outside world, science and technology input and education input, are proposed to affect the level of scientific innovation and technological innovation. In this study, the Yangtze River Delta region of China from 2001 to 2018 is selected as the research sample, and the two hypotheses proposed are tested through a mixed method of exploratory spatial data analysis and spatial panel econometric model. The main conclusions are as follows: i) As an exogenous variable, geographical proximity has a small impact on the level of scientific innovation, but a large impact on the level of technological innovation; ii) As endogenous variables, theoretical influencing factors may not play a significant role in the actual environment due to the complex influence of multidimensional proximity; iii) Based on the idea of improving multidimensional proximity and the actual situation of the region and the city, we can formulate policies conducive to improving the regional and urban innovation environment.

Review of Relationship between Business Innovation and Geographic Areas in China

Business innovation plays an essential role in its development. There are various factors affecting business innovation. Business innovation plays a vital role in its development. There are many factors that affect business innovation. Based on the existing research results, this paper sorts out and summarizes the research results of geographical characteristics, business innovation and the relationship between the two. The research results show that geographic proximity can promote business innovation through knowledge and technology spillovers, and multi-dimensional proximity and combination models such as cognition and institutions will bring about differences in corporate innovation performance. This article can help investors evaluate the above factors, determine the direction of investment, and make the right investment to promote economic development. This can also encourage the growth and expansion of potential SMEs.

Mapping Presence: An Exploration of Embodiment and Knowledge Transfers in Cyber-Mediated Classrooms

As teachers and students navigated the forced transition to online education, their physical and social interaction became possible only through technology. How did this mediated interaction affect learning outcomes, teacher presence, and their performance, in synchronous classroom spaces? What was lost in the translation of in-person instruction? What might this lost element tell us about the epistemology of embodiment, the transfer of knowledge in the classroom, and the roles of teachers and students within these knowledge frameworks? Through autoethnographical performative inquiry, this paper argues that embodiment—individual and collective—and multidimensional proximity construct sites of knowledge transfer.

The effects of proximities on the evolving structure of intercity innovation networks in the Guangdong–Hong Kong–Macao Greater Bay Area: comparison between scientific and technology knowledge

ABSTRACT The various knowledge flows shape and change the regional innovation patterns, which are also influenced by regional conditions. What are the similarities, differences and connections between science and technology linkage, as two different types of knowledge network, deserve to be explored in depth. Drawing on scientific paper co-publications and patent transfer data, we constructed two different types of intercity innovation networks during 2006–2016 in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA), a city region special for its ‘one country, two systems’ structure. After that, we explored the evolutionary characteristics of the networks and further examined the different impacts of multidimensional proximity on scientific collaboration and technology transfer. Our results show that technology transfer is more sensitive to spatial factors, institutional barriers caused by ‘one country, two systems’ is a bigger obstacle to technology transfer between cities, cultural proximity and cognitive proximity have a more significant impact on paper cooperation network. Moreover, geographical proximity can indirectly affect knowledge spillover by acting on the proximity of other dimensions. As for scientific collaboration, social, cognitive and institutional proximities can compensate for the lack of geographical proximity, and cultural proximity frequently goes along with geographical proximity; as for technology transfer, geographical proximity has neither substitutional or complementarity relations with cultural and cognitive proximities, the interrelatedness between geographical and institutional and social proximities are complementarity which is opposed to paper co-publications. This study explores the differences in spillover mechanisms of different knowledge types and contributes to enriching the empirical framework of multidimensional proximities and innovation network researches.

Transboundary Water Cooperation in the Post-Cold War Era: Spatial Patterns and the Role of Proximity.

Transboundary water cooperation (TWC) is an important theme of international cooperation. We conducted macro-level research on TWC from the perspective of inter-country relations and constructed a theoretical framework in which multidimensional proximity influences the formation of global TWC. We explained how multidimensional proximity and the constituent elements comprehensively influence the cooperative willingness and ability of actors, which directly drive the generation of global TWC. During the empirical research phase, we constructed the TWC frequency and intensity networks based on historical TWC events data from 1992 to 2013. By using social network analysis and QAP regression analysis, the spatial structure and proximity effect of water cooperation linkages are examined. It can be found that: (1) the reconstruction of territorial space on the eve of the end of the Cold War led to the peak of water cooperation events in 1992. The overall scale of events in the Post-Cold War era was relatively high and fluctuated steadily. (2) Water cooperation linkages have distinct spatial heterogeneity and are concentrated in the Eurasian and the African continents. Water cooperation is sensitive to geographical distance, and high-intensity water cooperation linkages exist in only a few areas. (3) China, Egypt, Germany, the United States, and Russia have prominent positions in the network. The United States, Japan, and other extra-regional powers actively participated in TWC in the Eastern Hemisphere. (4) The regression results show that geographical, economic, organizational, and colonial proximity significantly affect the intensity of water cooperation among countries.

Agricultural Science and Technology Innovation, Spatial Spillover and Agricultural Green Development—Taking 30 Provinces in China as the Research Object

In the face of increasingly severe resource and environmental constraints, accelerating the transformation of agricultural green development through agricultural science and technology innovation is an effective measure to reduce agricultural pollution and improve agricultural production efficiency. From the perspective of multidimensional proximity, this paper expounds the mechanism of agricultural science and technology innovation on agricultural green development through spatial spillover from two perspectives: factor spillover path and product spillover path. Based on panel data of 30 provinces in China from 2006 to 2019, using the gray correlation analysis method, the level of agricultural green development in China was measured, and its spatial–temporal evolution trend was analyzed. The spatial economic matrix was selected as the spatial weight matrix, and the spatial econometric model was used to analyze the spatial spillover effect of agricultural science and technology innovation on agricultural green development. The results showed the following: (1) Agricultural green development had distinct spatial characteristics. The development level of green agriculture in eastern and northwestern China showed a trend of fluctuation decline, while that in southwest China showed a trend of fluctuation increase. The overall spatial distribution of green agriculture was high in the east and low in the west. (2) The spatial distribution of agricultural science, technological innovation and the agricultural green development level showed a significant positive global spatial autocorrelation, and the local spatial pattern characteristics of a number of provinces showed high-value agglomeration (HH), low-value agglomeration (LL), low-value collapse (LH) and high-value bulge (HL) as the auxiliary local spatial distribution. (3) Under the economic matrix, the improvement of the agricultural science and technology innovation level not only had a significant promoting effect on agricultural green development within each province but also promoted agricultural green development in neighboring provinces through positive spillover effects. This study provides insights that can help make up for the lack of regional agricultural science and technology investment, formulate scientific regional agricultural science and technology innovation policies and promote agricultural green development.

Network Heterogeneity and Collaborative Innovation Performance: Considering the Dual Role of Multidimensional Proximity

Network Heterogeneity and Collaborative Innovation Performance: Considering the Dual Role of Multidimensional Proximity

Distance with Customers Effects on Green Product Innovation in SMEs: A Way Through Green Value Co-creation

Based on the perspective of multidimensional proximity, this paper examined the relationships between cognitive and social proximities with key customers and green product innovation performance via the mediation of green value co-creation by using data from 211 fine chemical small and medium-sized enterprises in clusters in China. Moderating effects of geographical distance and green project duration were assessed to further explore the relationship. The results revealed that social and cognitive proximities can promote green co-production and enhance green product innovation performance. Moreover, the relationship between social proximity and green co-production is hindered when customers are geographically distant or short duration partners of green projects. Eventually, this study was quite different from previous research by relating proximities to green value co-creation and green innovation performance in the context of small and medium-sized enterprises in emerging markets. The study provides a research framework for related research on green innovation.

Big Data-IoT: An Analysis of Multidimensional Proximity Implications on Green Innovation Performance—An Empirical Study of the Data from the Chinese Power Industry

With the global energy crisis and environmental degradation getting more rigorous, an essential approach is required to attain introverted development through structural optimization, autonomous invention, and technological innovation system. It is an important way to include energy conservation, emission reductions, and the implementation of a low-carbon mode in the power industry, which is a highly polluting sector of the national economy. This article is based on the State Intellectual Property Office of China’s patent search and analysis database. We choose the number of green patents jointly submitted for innovative topics in the power industry from 2016 to 2020. The negative binomial regression is constructed from the standpoint of multidimensional closeness by employing Gephi visual analysis, Ucinet, and the Stata 15 regional model. Furthermore, we investigate the impact of geographical closeness, technological closeness, and institutional closeness, as well as their interaction, on the green innovation performance of inventive organizations in China’s power industry. According to the findings of the study, geographical and institutional closeness have an important influence in increasing the green innovation performance. The suggested model applies to the power sector, and technological closeness has an inverted U-shaped association with green innovation performance in the power business. Furthermore, the model output at inference time is just a collection of successive parameters that improve the interaction of the closeness of innovation subjects to the green innovation performance of the power industry, all of which are represented as complementary effects.

Variance of destination region image according to multi-dimensional proximity: A case of the Greater Bay Area

Due to increasing accessibility and mobility, tourism destinations are broadening their spatial boundaries and cultural contexts. This study took as an example the Guangdong–Hong Kong–Macao Greater Bay Area, which consists of 11 cities, and explored how the new path creation of a regional tourism destination reshapes people's cognitive and affective images of the destination on a megalopolitan scale. Destination region image is neither a simple aggregation of the images of member cities nor dictated by the image of a single well-known destination. Both the physical and conceptual connections among multiple cities within the destination region are key nodes of the inclusive image of the region. Connectivity is not only embedded within institutional relations and discourses, but also represented through multi-functional tourism networks and regional culture. The study further explored the image heterogeneity of three proximity-based tourist clusters, divided in terms of cultural and geographical distance and previous travel experience. The research findings of this study can inform planning and marketing strategies for the path creation and development of metropolitan destination regions. • Three phases of path development in the Greater Bay Area are traced. • People's new cognitive system in response to regional path creation is identified. • The key node is connectivity in institutions, networks, and regional culture. • Image heterogeneity among proximity-based tourist clusters is identified. • Variances of destination region image have implications for destination innovation.