From the suppliers' perspective,this paper explores the impact of services for patent transactions provided by intermediaries on the patent transactions in China and whether the services for patent transactions moderate the relationship between firm's experiences and the probability of the firm's patents to be traded.The empirical results show that patents owned by firms without transaction experiences are less likely to be licensed or sold.Meanwhile,under certain condition services for patent transactions can negatively moderate the relationship.Specifically,patent intermediaries significantly facilitate the patent sale while show no impact on the patent license.Besides,the services for patent transactions are effective for small firms while they don't have effect on that of medium and large companies.The study produces implications for both industrial practitioners and policy makers.

Standards are an essential part of our society, and generate broad-ranging benefits. This chapter discusses the legal and economic literature on standard setting organizations (SSOs), standard essential patents (SEPs) and fair, reasonable and nondiscriminatory (FRAND) terms. It presents the literature review in two sections. First, it introduces relevant SSOs and their policies, and firms’ participation in the standardization activities. Second, it summarizes the literature on SEPs and FRAND terms, regarding the economic returns of SEPs, the essentiality of SEPs, licensing practices based on FRAND terms, and royalty calculation methods.

Based on the misclassification model，this paper evaluates grant decisions made by National Intellectual Property Adminis- tration (CNIPA)． The sample bases on G class of foreign invention patents ( foreign is defined as priority is filed outside of China) and filing date in CNIPA is during 2010-2015． The empirical results show that our country’s patent examination did not show a significant " false grant" phenomenon． However，there is about 4.4% of patents，whole oversea family patents obtained lots of forward patent cita- tions，were not granted by CNIPA，which is defined as "false rejection"． The proportion of "false rejection" risen to 5.8% in software － related patent samples． Furthermore，based on recognition of the erroneous decision，this article discussed the relationship between patent and patent applicants’characters and the probability of the false rejection．

Using data of patent licenses between Chinese universities and companies, this paper examines how development stage of the technology, the geographic distance between the university and potential licensees, and their collaboration experience influence the university’s propensity of licensing the technology exclusively. When faced with high risks, firms’willingness to commit requisite investment to commercializing the university’s technology will decrease. This study argues that the university can solve the problem through appropriate design of the licensing contract. Specifically, exclusive license can serve as a mechanism to increase mutual commitment, mitigating risks caused by technological immaturity, geographical distance and lack of collaboration experience and motivating companies to invest complementary assets, thus facilitating the university’s technology commercialization. Empirical results show that the early - stage technology and the lack of collaboration experience increase the university’s propensity of licensing the technology exclusively. Meanwhile，the negative relationship between the maturity of the licensed technology and university’s propensity of adopting exclusive license will be mitigated when the geographic distance between the licensee and the university is longer.

As the number of patent applications in CNIPA (China National Intellectual Property Administration) increases, patent value is of great interest throughout industries, governments, and academies. However, the existing statistic and econometric models cannot take advantage of huge samples of patent data for value prediction. Based on more than 850,000 patent applications field in 2010 and 2011, this paper provides a machine learning approach to predict patent forward citations at an early stage by using multiple patent indicators that can be defined immediately after the relevant patents are public. The developed model could provide a prediction on whether the relevant patent would receive forward citations; however it was weak in differentiating between high and low citations. Moreover, based on the Gini impurity, features of backward citations provide more information for value prediction. In other words, the prior art search process during the patent examination should be focused on. Finally, the paper discusses the limitations of the adopted model, as well as improvement methods for further studies.

This chapter analyzes the literature on IP and innovation management in the period 1986– 2018. Its primary goal is to review the development of IP and innovation studies and provide a quick reference for researchers interested in technology and innovation management, strategy or entrepreneurship.