{"title":"认知接近、技术机制与知识积累:基于主体的企业间知识交换模型","authors":"Jiebing Wu, Yanni Yuan, B. Guo","doi":"10.1080/19761597.2022.2060274","DOIUrl":null,"url":null,"abstract":"ABSTRACT Innovations in industrial clusters are highly dependent on a combination of internal and external knowledge among cluster firms with optimal levels of cognitive proximity. Meanwhile, all innovation activities in a cluster are affected by technological regime within that cluster, which is captured in terms of knowledge cumulativeness and knowledge distribution in this paper. Based on knowledge-based theory, this study develops an agent-based model of interfirm knowledge exchange, exploring the interplay of cognitive proximity and technological regime on a cluster’s knowledge accumulation. The results corroborate that cognitive proximity and cumulativeness condition jointly exert a significant inverted ‘U’-shaped effect on a cluster’s knowledge accumulation. The strength and shape of this effect are different for clusters with low versus high levels of cognitive proximity. Furthermore, the study extends the literature on technological regime by distinguishing the effects between knowledge cumulativeness and knowledge distribution, and the results reveal that large firm clusters (/SME clusters) perform best under a high (/low) level of knowledge cumulativeness. By simulating the sequential process of innovation dynamics, the study deepens understanding of mechanism behind how proximity affects innovation within clusters, thereby contributing to disentangling the interrelationships between cognitive proximity and technological regime.","PeriodicalId":45884,"journal":{"name":"Asian Journal of Technology Innovation","volume":"31 1","pages":"336 - 355"},"PeriodicalIF":1.8000,"publicationDate":"2022-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Cognitive proximity, technological regime and knowledge accumulation: an agent-based model of interfirm knowledge exchange\",\"authors\":\"Jiebing Wu, Yanni Yuan, B. Guo\",\"doi\":\"10.1080/19761597.2022.2060274\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Innovations in industrial clusters are highly dependent on a combination of internal and external knowledge among cluster firms with optimal levels of cognitive proximity. Meanwhile, all innovation activities in a cluster are affected by technological regime within that cluster, which is captured in terms of knowledge cumulativeness and knowledge distribution in this paper. Based on knowledge-based theory, this study develops an agent-based model of interfirm knowledge exchange, exploring the interplay of cognitive proximity and technological regime on a cluster’s knowledge accumulation. The results corroborate that cognitive proximity and cumulativeness condition jointly exert a significant inverted ‘U’-shaped effect on a cluster’s knowledge accumulation. The strength and shape of this effect are different for clusters with low versus high levels of cognitive proximity. Furthermore, the study extends the literature on technological regime by distinguishing the effects between knowledge cumulativeness and knowledge distribution, and the results reveal that large firm clusters (/SME clusters) perform best under a high (/low) level of knowledge cumulativeness. By simulating the sequential process of innovation dynamics, the study deepens understanding of mechanism behind how proximity affects innovation within clusters, thereby contributing to disentangling the interrelationships between cognitive proximity and technological regime.\",\"PeriodicalId\":45884,\"journal\":{\"name\":\"Asian Journal of Technology Innovation\",\"volume\":\"31 1\",\"pages\":\"336 - 355\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2022-04-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Asian Journal of Technology Innovation\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1080/19761597.2022.2060274\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asian Journal of Technology Innovation","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1080/19761597.2022.2060274","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BUSINESS","Score":null,"Total":0}
Cognitive proximity, technological regime and knowledge accumulation: an agent-based model of interfirm knowledge exchange
ABSTRACT Innovations in industrial clusters are highly dependent on a combination of internal and external knowledge among cluster firms with optimal levels of cognitive proximity. Meanwhile, all innovation activities in a cluster are affected by technological regime within that cluster, which is captured in terms of knowledge cumulativeness and knowledge distribution in this paper. Based on knowledge-based theory, this study develops an agent-based model of interfirm knowledge exchange, exploring the interplay of cognitive proximity and technological regime on a cluster’s knowledge accumulation. The results corroborate that cognitive proximity and cumulativeness condition jointly exert a significant inverted ‘U’-shaped effect on a cluster’s knowledge accumulation. The strength and shape of this effect are different for clusters with low versus high levels of cognitive proximity. Furthermore, the study extends the literature on technological regime by distinguishing the effects between knowledge cumulativeness and knowledge distribution, and the results reveal that large firm clusters (/SME clusters) perform best under a high (/low) level of knowledge cumulativeness. By simulating the sequential process of innovation dynamics, the study deepens understanding of mechanism behind how proximity affects innovation within clusters, thereby contributing to disentangling the interrelationships between cognitive proximity and technological regime.