Combinatorial...ition studies_XUE Shuaijun.pdf

J.Geogr.Sci.2023,33(4):705-718 DOI:https:/doi.org/10.1007/s11442-023-2102-1 2023 Science Press Springer-Verlag Combinatorial knowledge dynamics,innovative performance,and transition studies XUE Shuaijun1,*LIU Chengliang2,3,4 1.Department of Geography,Kiel University,Kiel 24118,Germany;2.School of Urban and Regional Sciences,East China Normal University,Shanghai 200241,China;3.Institute for Global Innovation and Development,East China Normal University,Shanghai 200062,China;4.Center of World Geography and Geo-strategical Studies,East China Normal University,Shanghai 200062,China Abstract:Cross-domain research and development has prevailed in regional transformation and disruptive innovation in the last 15 years.Recently,a new concept,termed combinatorial knowledge bases(CKBs),offers insights into combining knowledge dynamics and is consid-ered a good approach to explore recombinant innovative activities.Here,we review the liter-ature on CKBs in Western economic geography,and we introduce a research agenda for CKBs in Chinas economic geography.Concerning the latter,four aspects are elaborated:the co-evolution of the innovation chain and industrial chain,the geography of innovative activi-innovative entrepreneurship and new path development,and innovation system reconfigura-tion.This paper contributes to theoretical studies of Chinas geography by linking CKBs to Chinese-specific phenomena.Keywords:combinatorial knowledge bases;innovation;Chinas transformation 1 Introduction The concept of knowledge bases(KBs)was first put forward by Asheim and his colleagues(2005;2007;2011)and emphasizes three kinds of knowledge creation,analytical,synthetic,and symbolic KBs,that contribute to a new knowledge distinction.In comparison to old dis-tinctions,such as tacit versus codified knowledge(Gertler,2003),which are only weakly linked to knowledge generation dynamics,KBs are particularly related to these three kinds of innovation processes,providing a better understanding of the nature of knowledge sharing and innovative activities(Boschma,2018).Among these,analytical KBs,characterized by formal models,usually characterize innovative science-based projects(Asheim et al.,2011;Davids and Frenken,2018),as for instance with biomedicine(Ye and Zeng,2018).In con-trast,synthetic knowledge creation is mainly based on experiential learning,such as trial and Received:2022-05-16 Accepted:2023-01-23 Foundation:National Social Science Foundation of China,No.21ZDA011;China Scholarship Council,No.202008080097 Author:Xue Shuaijun,PhD Candidate,specialized in knowledge base combination and innovation studies.E-mail:xuegeographie.uni-kiel.de*Corresponding author:Liu Chengliang,Professor,specialized in regional innovation.E-mail: 706 Journal of Geographical Sciences error.This kind of knowledge is easier to observe in construction and traditional automobile industries(Asheim et al.,2011;Davids and Frenken 2018).The generation of symbolic knowledge is strongly associated with cultural codes or aesthetic elements within cultural industries(Asheim 2007;Klement and Strambach,2019).Based on this new approach,an extensive body of literature has connected KBs to different fields such as innovation systems,regional innovation policy,institutions,the geography of knowledge,and path dependence(Asheim et al.,2011;Plum and Hassink,2011;Van Tuijl and Walma van der Molen,2016;Benneworth et al.,2019;Chen and Hassink,2020).For example,Asheim and Coenen(2005,p.1180,p.1184)stated that in“a territorially embedded regional innovation system”,the in-novation process is mainly based on synthetic knowledge and local buzz between firms,where technological transfer is easier to observe.This stands in contrast to“a regionalized national innovation system”,where analytical knowledge dominates and innovative activi-ties are highly dependent on research institutes and universities.Furthermore,this differs from“a networked regional innovation system”,in which cutting-edge technologies associ-ated with synthetic and analytical knowledge are developed.Although one kind of KB can reflect the key knowledge generation in some industries,existing studies have indicated that strictly distinguishing KBs from each other in a single industry is unrealistic(Asheim et al.,2017;Manniche et al.,2017).For example,in the eco-building sector,analytical,synthetic,and symbolic KBs can be found(Strambach,2017).Additionally,in the process of industrial transformation or industrial upgrading,key knowledge creation in the industries may change over time.On this basis,the combinatorial knowledge base(CKB)approach has been suggested and can be viewed as a more advanced alternative.Combinatorial knowledge bases(CKBs)result from the combination of intra-KBs or in-ter-KBs,contributing to industrial transformation or cluster transformation(Manniche,2012;Asheim et al.,2017;Manniche et al.,2017;Plechero and Grillitsch,2022).Note that the diversified types of KBs in the region suggest a high probability