Performance Effects Of Technological Learning Strategy In Cluster Firms: The Mediating Effect Of Technological Learning Routine

During the past three decades, industrial clusters have been playing an increasingly important role in economic system, which enhance economy development and national competitiveness. Although clusters in manufacturing industries in China have achieved rapid growth recently, the R&D capacity of cluster firms is still in a low level, most of which do not have their own brands and Intellectual Property Rights. Technological learning may be the main measure for cluster firms to upgrade their technological capability.Based on the above background, the present studies mostly concentrate on learning and innovation behavior inside industrial clusters with the knowledge-based perspective, especially from the firm-level, with the aim to investigate how to improve the technological capability and innovative performance of cluster firms. However, the existing studies still have the following three drawbacks. First, among research on firms'technological learning behaviour and mechanism, most of them pays attention to single channel or mechanism of technological learning while ignoring systematically investigating multiple technological learning mechanisms. Second, the present studies focus on network attributes and firm characteristics as influential factors of technological learning while knowledge attributes are little mentioned, which causes we know limitedly about how knowledge attributes affect firms'performance.Third, the existing studies are lack of empirical evidence for routine, and also what role technological learning routine plays between the relationship of technological learning and firms'performance.Having considered the above mentioned research weaknesses, this dissertation mainly intends to answer three questions. First, how do knowledge attributes influence firms'technological learning strategy? And how does the network attribute moderate the relationship between knowledge attribute and technological learning strategy? Second, how do knowledge attributes impact firms'innovative performance through technological learning routine? Third, how does technological learning strategy affect firms'innovativeness through technological learning routine?Specifically speaking, this dissertation has conducted three sub-researches to empirically investigate the above questions.The first sub-research focuses on how knowledge attributes affect technological learning strategy, constructs the conceptual model in which knowledge tacitness and heterogeneity are the independent variables and depth-driven external knowledge acquisition strategy and breadth-driven external knowledge acquisition strategy are dependent variables, and further investigates how network centrality moderates the relationship between knowledge tacitness and technological learning strategy. Based on the questionnaire survey of 231 cluster firms, this sub-research applies reliability test, validity test, and multiple linear regression analysis to verify related hypotheses.The second sub-research demonstrates how knowledge attributes influence firms'innovativeness and builds the conceptual model, in which knowledge tacitness and knowledge heterogeneity are independent variables, the intensity and diversity of technological learning routine are mediating variables, and innovativeness is dependent variables. The related hypotheses are tested through structural model equation based on the sample of 231 cluster firms.The third sub-research investigates how technological learning strategy has impacts on innovative performance, constructs the conceptual model, and validates the research hypotheses with case study method.Through the three sub-researches, the following conclusion can be reached.(1)Knowledge attributes significantly influence technological learning strategy, and network centrality moderates the relationship between knowledge tacitness and technological learning strategy.Technological learning strategy is categorized into depth-driven and breadth-driven external knowledge acquisition strategies in this dissertation. Based on the multiple linear regression analysis of 231 firm samples, the empirical result shows that knowledge tacitness significantly and positively affects depth-driven external knowledge acquisition strategy, and has a significantly negative impact on breadth-driven external knowledge acquisition strategy; knowledge heterogeneity significantly and negatively influences breadth-driven external knowledge acquisition strategy. Besides, network centrality positively moderates the relationship between tacitness and depth-driven external knowledge acquisition strategy, while negatively moderates the relationship between tacitness and breadth-driven external knowledge acquisition strategy.(2) Knowledge attributes affect firms'innovative performance through the mediating effect of technological learning routine.This dissertation constructs the formation process and specific behavioral pattern of technological learning routine during different stage of knowledge management process inside firms, which can be used as measurement of technological learning routine. The structural model equation method was implemented to testify related hypotheses in the second sub-research. The empirical results display that knowledge tacitness and heterogeneity positively impact on firms'innovative performance. In addition, the intensity and diversity of technological learning routine play the mediating role in the relationship between tacitness and innovativeness, and the diversity of technological learning routine plays the mediating role in the relationship between heterogeneity and innovative performance.(3) Technological learning strategy has effects on firms'innovative performance through the mediating effect of technological learning routine.Case study method was conducted to validate the hypotheses posited by the third sub-research. The empirical results demonstrate that the intensity of technological learning routine mediates the relationship of depth-driven external knowledge acquisition strategy and innovativeness, and the diversity of technological learning routine mediates the relationship of breadth-driven external knowledge acquisition strategy and innovativeness.These research conclusions in this dissertation deepen the related studies on the influential factors of technological learning and the enhancing mechanism of firms' innovative performance. Specifically speaking, this dissertation adds strength to the existing related studies from three aspects.(1) Having fully considered various knowledge acquisition channels, it systematically demonstrates the impacts of knowledge attributes on technological learning strategy, and the moderating effect of network centrality on the above relationship.Firstly, this dissertation systematically investigates technological learning mechanism, and divides technological learning strategy into depth-driven external knowledge acquisition strategy and breadth-driven type based on 17 different knowledge acquisition channels. In addition, this research discusses the influence of knowledge tacitness and heterogeneity on technological learning strategy, which enriches studies on influential factors of technological learning. Lastly, it is proved that network centrality moderates the relationship of tacitness and technological learning strategy, which provides direction for further studies to include both knowledge attributes and network attributes as influential factors of technological learning. (2) It explores the influencial mechanism of knowledge attributes on firms' innovative performance when considering the mediating effect of technological learning routine.First of all, empirical research had been rarely conducted on routine since this concept was posited. This dissertation constructs specific routine behavior during different knowledge management stages inside firms. Moreover, this research selects technological learning routines as mediating variable, investigates how knowledge attributes affect innovativeness, trying to open up the black box between knowledge attributes and innovative performance. The empirical results show that knowledge attributes influence innovativeness through technological learning routine. This research finding encourages future studies to explore how context factors affects innovativeness through firms'internal technological learning behavior.(3) It investigates the influencial mechanism of technological learning strategy on firms'innovativeness when considering the mediating effect of technological learning routine.This research found that depth-driven external knowledge acquisition strategy affects firms'innovativeness through the intensity of technological learning routine, and breadth-driven external knowledge acquisition strategy affects firms' innovativeness through the diversity of technological learning routine. These research findings confirm the main logic that strategy instructs routine, and the enhancing effect of routine on performance, which promote future studies to discuss how technological learning impacts on innovative performance from firms'internal learning behavior.