Abstract: For the last few years firm alliances have been dramatically growing up and the competition pattern between individual firms has been transformed into a competitive pattern among cliques. Clique is a special structural unit in the meso-perspective network structure, which has become an important driving force for global high-tech firms to carry out cross-domain integration. The different cooperation patterns, cooperation degrees and participant types among the firms within the cliques play an important role in firms’ innovativeness, and they have a knock-on effect on the firms that are outside the cliques in the cognitive, strategic decision-making and innovation performance, etc. If a firm selects a wrong cooperation pattern or an inappropriate partner, it may face the threat of opportunistic behavior or disclosure of technical secrets. Previous research has examined the effects of network structure on the firms’ innovativeness. However, there is little work on the relationship between the type of cliques and firms’ innovativeness, and the cooperation mechanism among firms within cliques in alliance innovation network. In this paper, we focus on the relationships between clique types and firms’ innovativeness based on the theory of social network, and we propose a new method for clique classification in terms of non-structural attributes. Furthermore, cliques can be classified into nine types by their location in the value chain, cooperation patterns, and participant types. Based on different location of the value chain, cliques can be divided into R&D Cliques, Marketing Cliques, and Production Cliques. According to cooperation patterns, cliques can be subdivided into Informal Cliques, Contractual Cliques, and Equity Cliques. In terms of participant types, cliques can be classified into Government-led Cliques, Industry-University-Research Cliques, and Commercial Cliques. In addition, we introduce a new concept of node as Liaison Firm whose network location is among cliques. Finally, we measure the Cliques Segregation and Cross-cliques Convergence of the alliance innovation network to reveal the status of cliques’ development and the degree of high-tech industry convergence. Building on the literature on Cliques and firm’s innovativeness, we posit five hypotheses concerning how different types of clique and Liaison Firms affect firms’ innovativeness. Hypothesis 1 claims that Contractual Cliques are more conducive to firms’ innovativeness than Informal Cliques and Equity Cliques; Hypothesis 2 claims that Contractual Cliques are more conducive to firms’ innovativeness than Marketing Cliques and Production Cliques; Hypothesis 3 claims that Government-led Cliques, Industry-University-Research Cliques, and Commercial Cliques all have positive effects on firms’ innovativeness; Hypothesis 4 claims that Liaison Firm has a negative impact on firms’ innovativeness; and Hypothesis 5 claims that Liaison Firm plays a negative moderating role in the relationship between nine clique types and firms’ innovativeness.We constructed a firm alliance database that covers several Chinese high-tech industries over the period 2010-2015. Choosing firm alliances from nine high-tech industries made it possible for us to test the hypotheses including Semiconductors Industry, Automobile Body and Parts Industry, Chemistry and Chemical Industry, Aircraft and Aerospace Equipment Industry, Computer Video-audio Industry, New Energy and Environmental Protection Industry, Information and Communication Equipment Industry, Medical Equipment Industry, Pharmaceuticals and Biology Industry. The measures of the firm’s innovativeness bases draw on patent data from China Intellectual Property Net and the INNOJOY website. In addition, because our dependent variable is a count variable with a high degree of variance relative to its means, we use negative binomial regression analyses with random effects to demonstrate these hypotheses.The findings show that most of the cliques are isolated from each other in the network of the nine Chinese high-tech industries and Cross-cliques Convergence is also relatively low, which means high-tech firm alliances are in a relatively closed network environment In addition, the influence of different clique types on firms’ innovativeness is extremely diverse, and Liaison Firm does not have any rich resource advantages compared to other nodes in the alliance innovation network. The specific findings of our empirical research are as follows. Firstly, hypothesis 1 is strongly supported: since R&D Cliques have a positive effect on firms’ innovativeness. However, both Marketing Cliques and Production Cliques don’t show any influence on firms’ innovativeness. Secondly, hypothesis 2 is also strongly supported: because Contractual Cliques have a positive effect on firms’ innovativeness but Equity Cliques show a negative impact on firm innovativeness. Furthermore, there is no support of any relationship between Informal Cliques and firm innovativeness. Thirdly, hypothesis 3 is weakly supported: since there is only Commercial Cliques have a positive effect on firm innovativeness. Unexpectedly, Government-led Cliques have a negative impact on firm innovativeness, and Industry-University-Research Cliques don’t have any influence on firms’ innovativeness. Finally, Hypothesis 4 and Hypothesis 5 are strongly and weakly supported respectively: because Liaison Firm has a negative impact on firms’ innovativeness and plays a negative moderating role in the relationship between the Commercial Cliques and firms’ innovativeness but it does not show any moderating effects on the other two clique types and firm’s innovativeness.This work contributes to a new perspective on the classification of cliques in terms of non-structural attributes and puts forward a new concept of “Liaison Firm”. The results show that the firms’ innovativeness can be evaluated and predicted by the features of the innovation network, such as the Cliques Segregation, Cross-cliques Convergence. Further, we argue to understand how cliques affect firms’ innovativeness, it is necessary to disaggregate these cliques into different types, and it is also important to consider the Liaison Firm and network environment, which may have an effect on the firm’s innovativeness. Our findings also provide references for firms on how to select a win-win alliance partner, an advanced innovativeness clique, and a good position in the alliance network to enhance their innovation performance. In this way, our study suggests that firms should be embedded in the cliques that have advanced innovativeness, such as Contractual Cliques, Commercial Cliques, and R&D Cliques in view of the closed alliance innovation network environment in the nine high-tech industries of China and Liaison Firm should be embedded in relatively open cliques to avoid the risk of "Keep a Foot in Both Camps, Lose Trust on Both Sides".

Key words: innovation network, clique types, liaison firms, firm innovation capability