ارج نهادن به اختراع ثبت شده علمی و مالکیت معنوی: بررسی دیدگاههای مختلف در مورد تمایل به پرداخت و فروش

Academic inventors tend to lack the ability of valuing technologies in their areas. We apply classification tree analysis to discover different perspectives of Willingness to Pay (WTP) and Sell (WTS) of academic inventors when valuing their patents and technologies. Predictor factors considered are development environment, technology characteristics, ownership and patenting policy, and technology transfer characteristics. According to the result of Korean student data, WTS and WTP are differently perceived for the same technology: WTP is higher than WTS for the low valued technologies. The ownership policy, scalability and degree of innovation of technology, among the discovery of significant factors on WTS and WTP, are mainly considered as the important factors on WTS and WTP. From the finding of this research, we provide the policy implication on academic patenting and its ownership for further development of academic patents.

Academic inventions are an important source of corporate innovations (Geuna and Nesta, 2006). Various studies have been conducted in terms of management, legal aspects, and technology transfers of academic patents (Duderstadt, 2001 and Jensen and Thursby, 2001; Mok et al., 2010; Sohn and Lee, 2012). Shane (2002) suggested a conceptual framework to verify the influence of patent effectiveness on the licensing, commercialization, royalty generation based on MIT inventions using various statistical models. Agrawal and Henderson (2002) investigated the degree to which patents are representative of the magnitude, direction, and impact of the knowledge spilling out of the university by focusing on the case of MIT using descriptive statistics and regression analysis. In terms of law, Colyvas et al. (2002) showed, using the case studies, how the intellectual property right can affect the commercialization of university inventions after Bayh–Dole act in 1980. They suggested that the IPR could be important for embryonic inventions and the marketing effort of university institution for technology transfer was important for university inventions. The authors also mentioned that the ability to issue exclusive licenses was most important for embryonic inventions while the dangers of exclusivity were greatest for these types of inventions. The increasing interest in academic inventions and patent made many researchers to focus on recognizing and exploiting the commercial opportunities; and promoting the community of practice between different stakeholders (D’Este et al., 2012 and Theodorakopoulos et al., 2012). Particularly, estimating value of academic inventions and understanding what factors affect it have emerged as the essential tasks to boost technology transfer activities from academia to commercial use. One of the largest studies regarding estimating patent value is the survey-based PatVal-EU project (Final Report of the PatVal-EU Project, 2005). But this project examined the value of retained patents that are not necessarily academic (Giuri et al., 2007 and Crespi et al., 2007). Mowery and Ziedonis (2002) found that governmental policy can affect academic patent quality and quantity in the United States. Sapsalis et al. (2006) studied the distribution and determinants of patent value by comparing academic patents to corporate patents in Belgium. These studies of academic patent and its value estimation, however, do not take into account the perspectives of engineering students who were highly involved in the development of the technologies themselves. Because engineering graduate students have the high possibility of continuously working in research and development (R&D) or related areas, it becomes more necessary for students to be educated about what the estimated value of developed technology can be and how the value can be related with factors, such as ownership policy and environment of development, technology characteristics, and patenting and technology transfer characteristics (Mok et al., 2010). Therefore, this paper investigates the estimated value of technology and related factors in the perspective of engineering students in Korea, one of the most R&D intensified and engineering education oriented countries. Particularly, the ownership policy of developed technology among the related factors can be the important issue to students. Generally, if students develop technology on their own, they are entitled to ownership of intellectual property (IP) rights. On the other hand, if students develop technology as part of a research team that is sponsored by or under contract with an industry or government, the ownership of IP rights does not belong to the inventors. While the view of researchers, including students, is not sufficiently considered in Korea, we can find the exceptional case that the teacher’s exception policy grants exclusive rights to academic inventors in Sweden, one of the R&D intensified countries (SOU 2005:95, 2005). While the teacher’s exception policy is currently effective in Sweden, most countries including Korea do not currently employ the teacher’s exception policy. Therefore, we assume that an ownership policy can be related with estimated value of patents or technology by students involved in corresponding R&D. To estimate the value of patents or technologies, several approaches have been used in terms of future cash flow projections generated by the patents: regression models of patent indicators, net present value, and real option pricing with Monte Carlo simulation (Gambardella et al., 2005, Giuri et al., 2007, Hall et al., 2007, Meng, 2008, Wartburg and Teichert, 2008 and Ernst et al., 2010). However, it would be inappropriate to expect engineering graduate students to estimate the values of academic patents using these approaches that depend on many assumptions. In this paper, we estimate the value of technology in terms of Willingness to Sell (WTS) and Willingness to Pay (WTP) based on the results of a survey administered to engineering graduate students in Korea involved in technology development. WTP measures the benefit received by individuals (Johannesson, 1996, Coate and Morris, 1999 and Jeon et al., 2010), and WTS represents the expected selling price for individuals (Hanemann, 1985). The measures of WTP and WTS, along with factors that influence them, are widely used to estimate the values of intangible goods (Shapiro, 1985, Johannesson, 1996, Noy et al., 2006 and LeVert et al., 2009). We consider that these measures can be especially suitable for estimating value of intangible assets by students. As WTS and WTP are different measures of valuing the same goods, we consider both for an overall, balanced understanding of the value of technology in academia. When purchasing a patent, customers consider a specific patent in particular. On the other hand, when inventors sell a patent, they can proceed with licensing the patent to several customers simultaneously. The estimated value of the same patent can vary according to inherent differences in patent buying and selling situations. This is why we consider both WTS and WTP to estimate the value of technology. Then we apply a decision tree (DT) to identify variables that influence WTS and WTP. Among data mining methods, DT is one of the most frequently used methods for knowledge discovery. Decision tree is easy to interpret, and it is robust to input noise (Gayatri et al., 2010, Szepannek et al., 2005 and Doctor et al., 2001). By analyzing both WTS and WTP using a decision tree, we expect to understand the relationship between related factors to the estimated value of technology evaluated by students. The structure of this paper is as follows. Section 2 summarizes the related literature. Section 3 presents our research design, and in Section 4, we analyze WTP and WTS and the associated factors using a decision tree. Lastly, in Section 5, we conclude the study and suggest directions for future research.

In this paper, we surveyed both the WTP and WTS of engineering graduate students in Korea for academic patents (technology), along with related variables. As a result, we discovered that WTS and WTP are perceived differently for the same technology. One interesting point is that WTP is higher than WTS when the estimated value of the developed technology is low. This result is not consistent with the general understanding that WTS is usually higher than WTP (Bockstael and McConnell, 1980). We discovered that values of WTS and WTP vary according to different academic majors. The value of WTS was highest in industrial engineering while the value of WTP was highest in material science and engineering. Bioengineering and material science and engineering have a smaller gap between WTS and WTP than other majors. Computer engineering has the lowest WTS and WTP. We found well-informed estimations of the market price of patents in material science and engineering and bioengineering, represented by the significantly small gap between WTS and WTP in these academic fields. We also examined if both WTS and WTP are associated with categories of ownership policy and environment of development, technology characteristics, and patenting and technology transfer characteristics. In terms of the technology ownership and environment category, perception of the usefulness of the teacher’s exception policy was positively related with WTS. The high possibility for expansion and a high uniqueness of technology positively influence WTS. In addition, the innovation level of technology is highly related to both WTS and WTP. In the case of patenting and technology transfer characteristics, the expected life of patent, type of ownership, and number of participating researchers in R&D have an effect on WTP. The results of DT analysis show that perceptions of the usefulness of the teacher’s exception policy are considered the single most important variable with regard to WTS, while possibilities of expansion to various technology sectors is the most important variable for WTP. In particular, rules 1–1 and 1–2 of the DT for WTS suggest that (1) if the teacher’s exception policy is considered useful, (2) if the possibility of expansion to various technology sectors is high, and (3) if the developed technology is at the innovation stage, then WTS is high. This result implies that the teacher’s exception policy should be introduced as an option for graduate student researchers at the universities surveyed for this study, and arguably to engineering graduate schools in general. Inventors are also required to develop a highly expandable technology in order to enhance the patent value. Decision tree analysis for WTP explains that if the possibility for expansion of relevant technology to various technology sectors is low, then WTP is low. Rule 2–4 of the DT for WTP also shows that (1) if the expansion possibility of relevant technology is high, and (2) patent ownership is granted to the developer or university, then WTP is high. Researchers should therefore consider scalability and ownership in the development of their technology. From the findings of this research, we suggest important areas for further investigation for academic patenting. First, it is necessary to further analyze the gap between WTS and WTP in terms of paired comparison. Based on the existence of inter-evaluator variability (Sohn et al., 2012), in this way, we expect to provide useful information in understanding the value of academic patents. Further analysis should be focused on three cases in particular: (1) WTS being higher than WTP, (2) WTS and WTP being of equal value, and (3) WTS being lower than WTP. In this study we found examples of WTS being lower than WTP when the estimated value of technological inventions is low, or in other words, when the market value is cheap. Second, it would be worthwhile to conduct a similar study in the corporate realm. It is critically important to consider the perspectives of corporations, which are the biggest purchasers of technology, when estimating the value of academic patents (technology) objectively. Third, we need to concentrate on the relationship between academic patent value and academic patenting policy, especially ownership policy that benefits the academic inventor. Fourth, it is necessary to conduct a cross-country survey to analyze the relationship between academic patent value and ownership policy by country. This would help us understand how ownership policy is related to patent value. Above all, creativity education for the researchers is needed to improve and induce innovative ideas for invention which can increase both WTS and WTP (Sohn and Jung, 2010 and Sohn and Ju, 2011). These areas are left for further research that can add valuable insight to the implications for academic patenting revealed in our study.