The 2000s has witnessed increasing interests in cities′role of innovation in the era of knowledge-based economy.Compared with substantial empirical analysis on the world city hierarchy of innovation,this paper attemp...The 2000s has witnessed increasing interests in cities′role of innovation in the era of knowledge-based economy.Compared with substantial empirical analysis on the world city hierarchy of innovation,this paper attempts to examine the national urban hierarchy of innovation capability in China,in terms of ranking systems,spatial pattern and inter-city linkages of knowledge during the post-reform period since the late 1970s.Based on quantitative analysis such as principal component factor analysis and clustering analysis,this paper identifies the five-tier hierarchy of in-novation,which is headed by Beijing and Shanghai,followed by the capital cities of each province and regional centre cities.The development of China′s urban hierarchy of innovation capability has been driven by such factors as the scale of innovation,scientific scale,innovation potential and innovation environment.The paper further investigates the inter-city linkages of knowledge measured by the number of co-authored papers among the cities.Beijing is positioned in the central position of the knowledge diffusion and knowledge cooperation innovation.More knowledge diffusion among high level cities has occurred than that among the low level cities as well as between the low level cities and high level cities,and provincial capital cities and the regional central cities.展开更多
Based on patent cooperation data,this study used a range of city network analysis approaches in order to explore the structure of the Chinese city network which is driven by technological knowledge flows.The results r...Based on patent cooperation data,this study used a range of city network analysis approaches in order to explore the structure of the Chinese city network which is driven by technological knowledge flows.The results revealed the spatial structure,composition structure,hierarchical structure,group structure,and control structure of Chinese city network,as well as its dynamic factors.The major findings are:1) the spatial pattern presents a diamond structure,in which Wuhan is the central city;2) although the invention patent knowledge network is the main part of the broader inter-city innovative cooperation network,it is weaker than the utility model patent;3) as the senior level cities,Beijing,Shanghai and the cities in the Zhujiang(Pearl) River Delta Region show a strong capability of both spreading and controlling technological knowledge;4) whilst a national technology alliance has preliminarily formed,regional alliances have not been adequately established;5) even though the cooperation level amongst weak connection cities is not high,such cities still play an important role in the network as a result of their location within ′structural holes′ in the network;and 6) the major driving forces facilitating inter-city technological cooperation are geographical proximity,hierarchical proximity and technological proximity.展开更多
In order to highlight and analyze the influence of heterogeneous knowledge flows to enterprises in the modern service industry,based on a review of the Colonel Blotto game,some presumptions such as the game's util...In order to highlight and analyze the influence of heterogeneous knowledge flows to enterprises in the modern service industry,based on a review of the Colonel Blotto game,some presumptions such as the game's utility function are modified,and a mechanism to change tacit knowledge into explicit knowledge is constructed to carry out an analysis of a two-player knowledge flow management.The characteristics of the players' optimal reactions of knowledge flow management are studied,and the results bear evidence of the facts that a gap always exists under the spillover effect.Meanwhile,tacit knowledge seems more important to the development of enterprises than explicit knowledge.So it implies that the foremost task for the development of the modern service industry is to strengthen the settings and institutions for the flux of tacit knowledge and enterprise knowledge management.展开更多
Purpose:This paper aims to address the limitations in existing research on the evolution of knowledge flow networks by proposing a meso-level institutional field knowledge flow network evolution model(IKM).The purpose...Purpose:This paper aims to address the limitations in existing research on the evolution of knowledge flow networks by proposing a meso-level institutional field knowledge flow network evolution model(IKM).The purpose is to simulate the construction process of a knowledge flow network using knowledge organizations as units and to investigate its effectiveness in replicating institutional field knowledge flow networks.Design/Methodology/Approach:The IKM model enhances the preferential attachment and growth observed in scale-free BA networks,while incorporating three adjustment parameters to simulate the selection of connection targets and the types of nodes involved in the network evolution process Using the PageRank algorithm to calculate the significance of nodes within the knowledge flow network.To compare its performance,the BA and DMS models are also employed for simulating the network.Pearson coefficient analysis is conducted on the simulated networks generated by the IKM,BA and DMS models,as well as on the actual network.Findings:The research findings demonstrate that the IKM model outperforms the BA and DMS models in replicating the institutional field knowledge flow network.It provides comprehensive insights into the evolution mechanism of knowledge flow networks in the scientific research realm.The model also exhibits potential applicability to other knowledge networks that involve knowledge organizations as node units.Research Limitations:This study has some limitations.Firstly,it primarily focuses on the evolution of knowledge flow networks within the field of physics,neglecting other fields.Additionally,the analysis is based on a specific set of data,which may limit the generalizability of the findings.Future research could address these limitations by exploring knowledge flow networks in diverse fields and utilizing broader datasets.Practical Implications:The proposed IKM model offers practical implications for the construction and analysis of knowledge flow networks within institutions.It provides a valuable tool for understanding and managing knowledge exchange between knowledge organizations.The model can aid in optimizing knowledge flow and enhancing collaboration within organizations.Originality/value:This research highlights the significance of meso-level studies in understanding knowledge organization and its impact on knowledge flow networks.The IKM model demonstrates its effectiveness in replicating institutional field knowledge flow networks and offers practical implications for knowledge management in institutions.Moreover,the model has the potential to be applied to other knowledge networks,which are formed by knowledge organizations as node units.展开更多
To increase the resilience of farmers’livelihood systems,detailed knowledge of adaptation strategies for dealing with the impacts of climate change is required.Knowledge co-production approach is an adaptation strate...To increase the resilience of farmers’livelihood systems,detailed knowledge of adaptation strategies for dealing with the impacts of climate change is required.Knowledge co-production approach is an adaptation strategy that is considered appropriate in the context of the increasing frequency of disasters caused by climate change.Previous research of knowledge co-production on climate change adaptation in Indonesia is insufficient,particularly at local level,so we examined the flow of climate change adaptation knowledge in the knowledge co-production process through climate field school(CFS)activities in this study.We interviewed 120 people living in Bulukumba Regency,South Sulawesi Province,Indonesia,involving 12 crowds including male and female farmers participated in CFS and not participated in CFS,local government officials,agriculture extension workers,agricultural traders,farmers’family members and neighbors,etc.In brief,the 12 groups of people mainly include two categories of people,i.e.,people involved in CFS activities and outside CFS.We applied descriptive method and Social network analysis(SNA)to determine how knowledge flow in the community network and which groups of actors are important for knowledge flow.The findings of this study reveal that participants in CFS activities convey the knowledge they acquired formally(i.e.,from TV,radio,government,etc.)and informally(i.e.,from market,friends,relatives,etc.)to other actors,especially to their families and neighbors.The results also show that the acquisition and sharing of knowledge facilitate the flow of climate change adaptation knowledge based on knowledge co-operation.In addition,the findings highlight the key role of actors in the knowledge transfer process,and key actors involved in disseminating information about climate change adaptation.To be specific,among all the actors,family member and neighbor of CFS actor are the most common actors in disseminating climate knowledge information and closest to other actors in the network;agricultural trader and family member of CFS actor collaborate most with other actors in the community network;and farmers participated in CFS,including those heads of farmer groups,agricultural extension workers,and local government officials are more willing to contact with other actors in the network.To facilitate the flow of knowledge on climate change adaptation,CFS activities should be conducted regularly and CFS models that fit the situation of farmers’vulnerability to climate change should be developed.展开更多
The Chinese urban system is currently experiencing a fundamental shift, as it moves from a size-based hierarchy to a network-based system. Contemporary studies of city networks have tended to focus on economic interac...The Chinese urban system is currently experiencing a fundamental shift, as it moves from a size-based hierarchy to a network-based system. Contemporary studies of city networks have tended to focus on economic interactions without paying sufficient attention to the issue of knowledge flow. Using data on co-authored papers obtained from China Academic Journal Network Publishing Database （CAJNPD） during 2014-2016, this study explores several features of the scientific collaboration network between Chinese mainland cities. The study concludes that： （1） the spatial organization of scientific cooperation amongst Chinese cities is shifting from a jurisdiction-based hierarchical system to a networked system; and （2） several highly intra-connected city regions were found to exist in the network of knowledge, and such regions had more average internal linkages （14.21） than external linkages （8.69）, and higher average internal linkage degrees （14.43） than external linkage degrees （10.43）; and （3） differences existed in terms of inter-region connectivity between the Western, Eastern, and Central China regional networks （the average INCD of the three regional networks were 109.65, 95.81, and 71.88）. We suggest that China should engage in the development of regional and subregional scientific centers to achieve the goal of building an innovative country. Whilst findings reveal a high degree of concentration in those networks - a characteristic which reflects the hierarchical nature of China＇s urban economic structure - the actual spatial distribution of city networks of knowledge flow was found to be different from that of city networks based on economic outputs or population.展开更多
Although serious efforts are made internationally and nationally, it is a slow process to make our physical environment accessible. In the actual design process, architects play a major role. But what kinds of knowled...Although serious efforts are made internationally and nationally, it is a slow process to make our physical environment accessible. In the actual design process, architects play a major role. But what kinds of knowledge, including research-based knowledge, do practicing architects make use of when designing accessible environments？ The answer to the question is crucially important since it affects how knowledge is distributed and how accessibility can be ensured. In order to get first-hand knowledge about the design process and the sources from which they gain knowledge, 11 qualitative interviews were conducted with architects with experience of designing for accessibility. The analysis draws on two theoretical distinctions. The first is research-based knowledge versus knowledge used by architects. The second is context-independent knowledge versus context-dependent knowledge. The practitioners found their primary support in context-dependent knowledge, whereas context-independent knowledge was criticized as being too prescriptive. Further, they tended to ask for assistance from the researcher in person rather than reading research publications. The findings challenge research in two ways--first, to produce context-dependent knowledge to structure the first step of the design process, second, to develop new ways to ensure a knowledge flow between research and practice.展开更多
Traffic flow prediction is a key component of intelligent transportation systems,particularly in datascarce regions where traditional models relying on complete datasets often fail to provide accurate forecasts.These ...Traffic flow prediction is a key component of intelligent transportation systems,particularly in datascarce regions where traditional models relying on complete datasets often fail to provide accurate forecasts.These regions are characterized by limited sensor coverage and sparse data collection,pose significant challenges for existing prediction methods.To address this,we propose a novel transfer learning framework called transfer learning with deep knowledge distillation(TL-DKD),which combines graph neural network(GNN)with deep knowledge distillation to enable effective knowledge transfer from data-rich to data-scarce domains.Our contributions are three-fold:(1)We introduce,for the first time,a unique integration of deep knowledge distillation and transfer learning,enhancing feature adaptability across diverse traffic datasets while addressing data scarcity.(2)We design an encoder-decoder architecture where the encoder retains generalized spatiotemporal patterns fromsource domains,and the decoder finetunes predictions for target domains,ensuring minimal information loss during transfer.(3)Extensive experiments on five real-world datasets(METR-LA,PeMS-Bay,PeMS03/04/08)demonstrate the framework’s robustness.The TL-DKD model achieves significant improvements in prediction accuracy,especially in data-scarce scenarios.For example,the PEMSD4 dataset in multi-region experiments,it achieves a mean absolute error(MAE)of 20.08,a mean absolute percentage error(MAPE)of 13.59%,and a root mean squared error(RMSE)of 31.75 for 30-min forecasts.Additionally,noise-augmented experiments show improved adaptability under perturbed data conditions.These results highlight the framework’s practical impact,offering a scalable solution for accurate traffic predictions in resource-constrained environments.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.41071103)Guangdong Natural Science Foundation(No.9151051501000061)+1 种基金Foundation of Humanities and Social Sciences(No.10ZGXM79006)Foundation of Guangzhou Education Bureau(No.10A030)
文摘The 2000s has witnessed increasing interests in cities′role of innovation in the era of knowledge-based economy.Compared with substantial empirical analysis on the world city hierarchy of innovation,this paper attempts to examine the national urban hierarchy of innovation capability in China,in terms of ranking systems,spatial pattern and inter-city linkages of knowledge during the post-reform period since the late 1970s.Based on quantitative analysis such as principal component factor analysis and clustering analysis,this paper identifies the five-tier hierarchy of in-novation,which is headed by Beijing and Shanghai,followed by the capital cities of each province and regional centre cities.The development of China′s urban hierarchy of innovation capability has been driven by such factors as the scale of innovation,scientific scale,innovation potential and innovation environment.The paper further investigates the inter-city linkages of knowledge measured by the number of co-authored papers among the cities.Beijing is positioned in the central position of the knowledge diffusion and knowledge cooperation innovation.More knowledge diffusion among high level cities has occurred than that among the low level cities as well as between the low level cities and high level cities,and provincial capital cities and the regional central cities.
基金Under the auspices of Major Project of National Social Science Foundation of China(No.13&ZD027)National Natural Science Foundation of China(No.41201128,71433008)
文摘Based on patent cooperation data,this study used a range of city network analysis approaches in order to explore the structure of the Chinese city network which is driven by technological knowledge flows.The results revealed the spatial structure,composition structure,hierarchical structure,group structure,and control structure of Chinese city network,as well as its dynamic factors.The major findings are:1) the spatial pattern presents a diamond structure,in which Wuhan is the central city;2) although the invention patent knowledge network is the main part of the broader inter-city innovative cooperation network,it is weaker than the utility model patent;3) as the senior level cities,Beijing,Shanghai and the cities in the Zhujiang(Pearl) River Delta Region show a strong capability of both spreading and controlling technological knowledge;4) whilst a national technology alliance has preliminarily formed,regional alliances have not been adequately established;5) even though the cooperation level amongst weak connection cities is not high,such cities still play an important role in the network as a result of their location within ′structural holes′ in the network;and 6) the major driving forces facilitating inter-city technological cooperation are geographical proximity,hierarchical proximity and technological proximity.
基金The National Key Technology R&D Program of China during the 11th Five-Year Plan Period(No.2006BAH02A06)
文摘In order to highlight and analyze the influence of heterogeneous knowledge flows to enterprises in the modern service industry,based on a review of the Colonel Blotto game,some presumptions such as the game's utility function are modified,and a mechanism to change tacit knowledge into explicit knowledge is constructed to carry out an analysis of a two-player knowledge flow management.The characteristics of the players' optimal reactions of knowledge flow management are studied,and the results bear evidence of the facts that a gap always exists under the spillover effect.Meanwhile,tacit knowledge seems more important to the development of enterprises than explicit knowledge.So it implies that the foremost task for the development of the modern service industry is to strengthen the settings and institutions for the flux of tacit knowledge and enterprise knowledge management.
基金supported in part by the National Natural Science Foundation of China under Grant 72264036in part by the West Light Foundation of The Chinese Academy of Sciences under Grant 2020-XBQNXZ-020+1 种基金Social Science Foundation of Xinjiang under Grant 2023BGL077the Research Program for High-level Talent Program of Xinjiang University of Finance and Economics 2022XGC041,2022XGC042.
文摘Purpose:This paper aims to address the limitations in existing research on the evolution of knowledge flow networks by proposing a meso-level institutional field knowledge flow network evolution model(IKM).The purpose is to simulate the construction process of a knowledge flow network using knowledge organizations as units and to investigate its effectiveness in replicating institutional field knowledge flow networks.Design/Methodology/Approach:The IKM model enhances the preferential attachment and growth observed in scale-free BA networks,while incorporating three adjustment parameters to simulate the selection of connection targets and the types of nodes involved in the network evolution process Using the PageRank algorithm to calculate the significance of nodes within the knowledge flow network.To compare its performance,the BA and DMS models are also employed for simulating the network.Pearson coefficient analysis is conducted on the simulated networks generated by the IKM,BA and DMS models,as well as on the actual network.Findings:The research findings demonstrate that the IKM model outperforms the BA and DMS models in replicating the institutional field knowledge flow network.It provides comprehensive insights into the evolution mechanism of knowledge flow networks in the scientific research realm.The model also exhibits potential applicability to other knowledge networks that involve knowledge organizations as node units.Research Limitations:This study has some limitations.Firstly,it primarily focuses on the evolution of knowledge flow networks within the field of physics,neglecting other fields.Additionally,the analysis is based on a specific set of data,which may limit the generalizability of the findings.Future research could address these limitations by exploring knowledge flow networks in diverse fields and utilizing broader datasets.Practical Implications:The proposed IKM model offers practical implications for the construction and analysis of knowledge flow networks within institutions.It provides a valuable tool for understanding and managing knowledge exchange between knowledge organizations.The model can aid in optimizing knowledge flow and enhancing collaboration within organizations.Originality/value:This research highlights the significance of meso-level studies in understanding knowledge organization and its impact on knowledge flow networks.The IKM model demonstrates its effectiveness in replicating institutional field knowledge flow networks and offers practical implications for knowledge management in institutions.Moreover,the model has the potential to be applied to other knowledge networks,which are formed by knowledge organizations as node units.
文摘To increase the resilience of farmers’livelihood systems,detailed knowledge of adaptation strategies for dealing with the impacts of climate change is required.Knowledge co-production approach is an adaptation strategy that is considered appropriate in the context of the increasing frequency of disasters caused by climate change.Previous research of knowledge co-production on climate change adaptation in Indonesia is insufficient,particularly at local level,so we examined the flow of climate change adaptation knowledge in the knowledge co-production process through climate field school(CFS)activities in this study.We interviewed 120 people living in Bulukumba Regency,South Sulawesi Province,Indonesia,involving 12 crowds including male and female farmers participated in CFS and not participated in CFS,local government officials,agriculture extension workers,agricultural traders,farmers’family members and neighbors,etc.In brief,the 12 groups of people mainly include two categories of people,i.e.,people involved in CFS activities and outside CFS.We applied descriptive method and Social network analysis(SNA)to determine how knowledge flow in the community network and which groups of actors are important for knowledge flow.The findings of this study reveal that participants in CFS activities convey the knowledge they acquired formally(i.e.,from TV,radio,government,etc.)and informally(i.e.,from market,friends,relatives,etc.)to other actors,especially to their families and neighbors.The results also show that the acquisition and sharing of knowledge facilitate the flow of climate change adaptation knowledge based on knowledge co-operation.In addition,the findings highlight the key role of actors in the knowledge transfer process,and key actors involved in disseminating information about climate change adaptation.To be specific,among all the actors,family member and neighbor of CFS actor are the most common actors in disseminating climate knowledge information and closest to other actors in the network;agricultural trader and family member of CFS actor collaborate most with other actors in the community network;and farmers participated in CFS,including those heads of farmer groups,agricultural extension workers,and local government officials are more willing to contact with other actors in the network.To facilitate the flow of knowledge on climate change adaptation,CFS activities should be conducted regularly and CFS models that fit the situation of farmers’vulnerability to climate change should be developed.
基金National Natural Science Foundation of China,No.41571151,No.41590842,No.71433008
文摘The Chinese urban system is currently experiencing a fundamental shift, as it moves from a size-based hierarchy to a network-based system. Contemporary studies of city networks have tended to focus on economic interactions without paying sufficient attention to the issue of knowledge flow. Using data on co-authored papers obtained from China Academic Journal Network Publishing Database （CAJNPD） during 2014-2016, this study explores several features of the scientific collaboration network between Chinese mainland cities. The study concludes that： （1） the spatial organization of scientific cooperation amongst Chinese cities is shifting from a jurisdiction-based hierarchical system to a networked system; and （2） several highly intra-connected city regions were found to exist in the network of knowledge, and such regions had more average internal linkages （14.21） than external linkages （8.69）, and higher average internal linkage degrees （14.43） than external linkage degrees （10.43）; and （3） differences existed in terms of inter-region connectivity between the Western, Eastern, and Central China regional networks （the average INCD of the three regional networks were 109.65, 95.81, and 71.88）. We suggest that China should engage in the development of regional and subregional scientific centers to achieve the goal of building an innovative country. Whilst findings reveal a high degree of concentration in those networks - a characteristic which reflects the hierarchical nature of China＇s urban economic structure - the actual spatial distribution of city networks of knowledge flow was found to be different from that of city networks based on economic outputs or population.
文摘Although serious efforts are made internationally and nationally, it is a slow process to make our physical environment accessible. In the actual design process, architects play a major role. But what kinds of knowledge, including research-based knowledge, do practicing architects make use of when designing accessible environments？ The answer to the question is crucially important since it affects how knowledge is distributed and how accessibility can be ensured. In order to get first-hand knowledge about the design process and the sources from which they gain knowledge, 11 qualitative interviews were conducted with architects with experience of designing for accessibility. The analysis draws on two theoretical distinctions. The first is research-based knowledge versus knowledge used by architects. The second is context-independent knowledge versus context-dependent knowledge. The practitioners found their primary support in context-dependent knowledge, whereas context-independent knowledge was criticized as being too prescriptive. Further, they tended to ask for assistance from the researcher in person rather than reading research publications. The findings challenge research in two ways--first, to produce context-dependent knowledge to structure the first step of the design process, second, to develop new ways to ensure a knowledge flow between research and practice.
基金supported by the National Natural Science Foundation of China(Grant No.52002031)the Shaanxi Province Key R&D Plan Project(No.2024GX-YBXM-002).
文摘Traffic flow prediction is a key component of intelligent transportation systems,particularly in datascarce regions where traditional models relying on complete datasets often fail to provide accurate forecasts.These regions are characterized by limited sensor coverage and sparse data collection,pose significant challenges for existing prediction methods.To address this,we propose a novel transfer learning framework called transfer learning with deep knowledge distillation(TL-DKD),which combines graph neural network(GNN)with deep knowledge distillation to enable effective knowledge transfer from data-rich to data-scarce domains.Our contributions are three-fold:(1)We introduce,for the first time,a unique integration of deep knowledge distillation and transfer learning,enhancing feature adaptability across diverse traffic datasets while addressing data scarcity.(2)We design an encoder-decoder architecture where the encoder retains generalized spatiotemporal patterns fromsource domains,and the decoder finetunes predictions for target domains,ensuring minimal information loss during transfer.(3)Extensive experiments on five real-world datasets(METR-LA,PeMS-Bay,PeMS03/04/08)demonstrate the framework’s robustness.The TL-DKD model achieves significant improvements in prediction accuracy,especially in data-scarce scenarios.For example,the PEMSD4 dataset in multi-region experiments,it achieves a mean absolute error(MAE)of 20.08,a mean absolute percentage error(MAPE)of 13.59%,and a root mean squared error(RMSE)of 31.75 for 30-min forecasts.Additionally,noise-augmented experiments show improved adaptability under perturbed data conditions.These results highlight the framework’s practical impact,offering a scalable solution for accurate traffic predictions in resource-constrained environments.
