Matching Mechanism Of Inside Knowledge Base And Innovation Network Composition For Latecomers

Serving as the important actors in technology catch-up in emerging countries, latecomer firms always receive consistent attention from scholars and managers. Along with the reconstruction of global value network and development of emerging technologies, innovation network building becomes an important way for latecomers to gain and integrate global technology resources. During the process, how to build effective innovation network to better transform to frontiers becomes key question. Practically speaking, latecomers has transformed from imitative learning of MNEs technology spillover to interactive learning based on innovation network composed of kinds of technology cooperation. However, latecomers still face the challenge of ’refused by the superior and refuse the inferior’, which the technology knowledge is too high to integrate or too low to learn nothing. So, building an effective innovation network to solve the inefficiency learning problem becomes key practical problem. Theoretically speaking, new phenomenon emerging from latecomers technology catch-up has still stayed on the description of cases, which also lack of theoretical focus and mechanism explanation, that it’s hard to build talk with mainstream strategic management researches. And partner choice which is critical to build effective network still remains on dual level to specific kind of actors, and do not connect with performance. What’s more, it is incomplete to portray innovation network only from the dimension of node heterogeneity.Base on above practical and theoretical background, this study is aimed to explore how latecomers can choose appropriate node(s) or partners to build effective innovation network. Drawing on extended resource-based view, this study portray different configuration types based on inside knowledge base breadth/depth and innovation network composition which is formed of knowledge heterogeneity/quality, and explore the relationships between different configuration types and innovation catch-up performance to solve the key question. This study formed four sub-researches to answer four sub-questions surrounding the key question. The first sub-research uses 6 case studies, and proposes four kinds of configuration types composed of inside knowledge base and innovation network composition and the corresponding organizational learning mechanism which can achieve high innovation catch-up performance. The second sub-research uses fsQCA to verify the configuration types and corresponding organizational learning mechanism proposed by the first sub-research. The third sub-research also uses fsQCA to explore how strategic orientation and industry characteristics moderate the relationship between configuration types and innovation catch-up performance. The forth sub-research is based on evolutionary perspective and use 3 case studies which has transform to the frontiers to portray the specific path by which latecomers choose appropriate node(s) to build effective innovation network. This study mainly comes to several conclusions as follows:(1)The first sub-research summarizes four configuration types that contribute to innovation catch-up. Namely, when the inside knowledge base breadth is high and the depth is low, it’s better to allocate innovation network characterized by high knowledge heterogeneity and high knowledge quality (Type Ⅰ). When the inside knowledge base breadth and depth is both high, it’s also better to allocate innovation network characterized by high knowledge heterogeneity and high knowledge quality (Type Ⅱ). When the inside knowledge base breadth and depth is both low, it can allocate innovation network characterized by low knowledge heterogeneity and high knowledge quality (Type Ⅳ).When the inside knowledge base breadth is low and depth is high, it can also allocate innovation network characterized by low knowledge heterogeneity and high knowledge quality (Type Ⅴ).The empirical findings of fsQCA from the second sub-research verify the above four configuration types, and futher find that when the inside knowledge base breadth and depth is both low, it can also allocate innovation network characterized by high knowledge heterogeneity and high knowledge quality (Type Ⅲ)(2) When the inside knowledge base breadth and depth are both low, it’s better to choose exploitive learning to improve innovation performance. When the inside knowledge base breadth is low while knowledge depth is high, it’s better to balance exploitive learning and explorative learning to improve innovation performance. When the inside knowledge base breadth is high while knowledge depth is low, it’s better to choose exploitive learning to improve innovation performance. When the inside knowledge base breadth and depth are both high, it’s better to balance exploitive learning and explorative learning to improve innovation performance.(3) Strategic orientation and industry characteristics both moderate the relationship between different configuration types and innovation catch-up performance. For strategic orientation, when technology orientation and market orientation are both high, latecomers can freely choose inside knowledge base allocation, while better choose high knowledge heterogeneity and high knowledge quality innovation network when inside knowledge base breadth and depth are both low, namely type Ⅰ/Ⅱ/Ⅲ/Ⅴ. When technology orientation is higher than market orientation, it’s better to choose high knowledge heterogeneity and high knowledge quality innovation network when inside knowledge base breadth and depth are both high, namely type Ⅱ. When market orientation is higher than technology orientation, it’s better to choose low knowledge heterogeneity and high knowledge quality innovation network when inside knowledge base breadth and depth are both low, namely type IV. For industry characteristics, when firms in industry that technology changes fast and the technology gap with frontiers is low, it’s better to choose type Ⅰ/Ⅱ to better catch-up. When firms in industry that technology changes slowly and the technology gap with frontiers is high, it’s better to choose type Ⅲ to better catch-up.(4) Based on the phase development model proposed by Detrenit(2004), this study focuses on complex product making related latecomers and further uses knowledge breadth and depth to describe the characteristics of knowledge base. This study comes out two knowledge base allocation path, that one focuses on component technology development, and the other focuses on system technology development. The knowledge heterogeneity of innovation network nodes built by the former path is higher while the latter is lower. What’s more, the nodes allocation and organization learning mode during different development phase changes accordingly.1) During the phase of building necessary knowledge base, latecomer has intensive inside R&D orientation, and build initial operation and equipment upgrading capability through exploitive learning of mature technology by the means of independent R&D or employ experts outside.2)During the transition phase, latecomers gradually moves to inside R&D combined of new product development based on mature technology and technology frontier or cross-field technology exploration, which gains organization learning ambidexterity inside. Firms also begins to cooperate with partners on technology matching and problem tackling during new product development, and achieve parity with competitors.3) During the phase of building complex knowledge base, latecomer establishes complete innovation cooperation system based on technology center, and achieve organization learning ambidexterity combined of inside and outside. Then latecomers transform to frontiers that can compete with excellent global firms in many technical functions.The main theoretical contributions are as follows:(1) This study bridge latecomer technology catch-up theory with strategic management researches through solving the core question that how latecomers build effective innovation network. Through exploring how latecomers transform to frontiers through innovation network building, this study riches the catch-up theory which focus on imitative innovation from leading companies. Meanwhile, through focusing on the specific condition of latecomers technology catch-up, this study concludes the specific path how latecomers can build organizational learning ambidexterity, which also deepens the latecomers’technological catch-up studies based on organizational learning.(2) Different from former partner choice researches which focus on specific partner or dyadic level, this study considers partners choice from network level, which deepens partner choice researches. And this study connect partner choice with performance, fill the gaps of former researches.(3) Drawing on extended resource-based view, this study focuses on the network composition stream on innovation network research, which fill the gap of innovation researches which based on network theory that see the nodes as equal. What’s more, this study switches the description of innovation network from macro perspective to network configuration analysis from micro level, and explores the deep relationships among latecomers’inside knowledge base, outside innovation network configuration and innovation catch-up performance with the moderator effect from inside element (strategic orientation) and environment element (industry characteristics).This study analyze the mechanism and process of how latecomers choose appropriate partners or node(s) to build effective innovation network, which provides important guidance to managers to reconstruct cooperation effort, and also guidance to the technology development and different innovation network allocation choice. Firstly, latecomers should change the logic when they build innovation network. They should first consider the resource endowment of partners, then develop different innovation structure and relationship to gain needed resource. Secondly, latecomers should have exact measurement of their own knowledge resources, not only the breadth of knowledge, but also the ability to assimilate and absorb external knowledge. Thirdly, managers should also consider the effect brought by strategic orientation and environmental element.