Yun Ken

Profitability decided by patent quality? An empirical study of the U.S. semiconductor industry

The investment in research and development (R&D) for semiconductor industry is never small as the technology cycle time (TCT) is relatively short comparing to other industries, thus a semiconductor company requires lots of technological innovations and capital offerings to maintain. The semiconductor industry contributes primarily part of the micro-electronic industries. Advancing technology and patent application are the centre of attention within the semiconductor sector. This research examines the relationship between patent quality and the profits a patent creates for a company in this selected field. This study distinguishes itself from prior research by including cross-sectional data, time series data to simultaneously collect and analyze. The study result shows that some indicators of patent quality are statistically significant to return on assets.

Exploring the nonlinear effects of patent H index, patent citations, and essential technological strength on corporate performance by using artificial neural network

This study utilizes the artificial neural network to explore the nonlinear relationships between patent performance and the corporate performance of the pharmaceutical companies. Patent performance measured from patent H index, patent citations, and essential technological strength (ETS). The result shows that patent H index, patent citations, and ETS has the nonlinear effect on the corporate performance of the pharmaceutical companies.

Study of the time lag effect of patent impact on profitability of U.S. Pharmaceutical Industry from innovation to profit

This study intends to stretch the extent of the successful innovation process from a novel conception not only to its adoption to the market , but also to its launch for profit from innovation, and focus on probing into the deferred results of patent impacts of the American pharmacy industry and their profitability at the firm level. We find there are obvious relationships between the indexes of patent impact and profitability such as ROE and EPS. Moreover, our empirical research finds there is a time lag of 4 years between the indexes of patent impact and ROE, and 5 years of time lag with EPS. We consider the time lag in the pharmaceutical industry is longer than the results of other industries in the previous study, and suggest that investors regard scientific measures of the quality and quantity of inventive output as useful indicators of the economic profitability tied to patenting impact. The sample of firms for this study are drawn from Compustat database, from which we screened 255 listed companies and only had 72 to 80 complete samples left eventually. We searched every company of the USAs patent database and sum up the patent materials for nine years from 1994 to 2002.

The Support Vector Machine Classification System for Patent Document Information Importance Analysis

This study proposed a novel two-stage process of integrating support vector machine with expert screening technique to develop an automatic patent categorization system with high accuracy and high validity. The approach is tested on a real world case-the search history involving 264 patent documents of semiconductor equipment components. A 100% patent classification accuracy via the description portion of the patent documents was achieved using our proposed two-stage approach. The results showed that the proposed approach performed well in the real-world case of patent classification. The description field of the patent document was more than adequate for patent classification.

A study on the factors influencing license income of technology commercialization in United States Universities

Although high-tech industries and academics have the capability of research and development for technologies, the capability of technology commercialization is considered to be more important. If they only do R&D without commercialization, it might lead to no returns. Due to the spur of US governmental policies, research-oriented purposes in universities are switched to industrial purposes instead of science purposes. After the Bayh-Dole Act was enacted in 1980, the activities of technology transfer between academics and industries dramatically boosted. The factors, which influence the performances of technology transfer, were proposed by some pervious researches, and most of them suggested that researches expenditure, patents, and published articles carry significant weight. According to some case studies of famous journal, they pointed out that patents have no contribution. This study uses AUTM licensing survey to figure out the relationship between issued patents, published articles, and technology commercialization. The result of the study shows that published articles do have an effect, but issued patents do not make a significant effect on technology commercialization.

The Study of Classification on Patent Decisions: The Cases from U.S. CAFC

In the business environment of a knowledge-based economy, patents are a key factor that influences the competition and development of the high-tech industry. Taiwanese technology manufacturers, which are vital players in the global market, have been frequently accused by large foreign enterprises of patent infringement. Intellectual property lawsuits in the United States attract wide international attention because of the countrys market size and the prestige of its court opinions regarding patent lawsuits. Therefore, this study examined the types of issues involved in various litigations among U.S. patent lawsuits, and expanded complete patent decision networks to investigate key cases and the issue development path. This facilitates the understanding of U.S. court opinions and the preparations for relevant management practices. In addition, the objective of this study was to develop an analysis method by using a law database to collect 1,313 patent decisions issued by the U.S. Court of Appeals for the Federal Circuit between 1997 and 2007. The concept of co-citation in citation analysis was employed to interpret the foci of patent decision litigations in recent years. Following classification, the litigation issues were confirmed by U.S. patent attorneys to ensure that the classification method and logic used in this study possess practical validity. The purpose of this study is to provide future patent decision researchers with a systematic perspective and focused reading so that they can efficiently select the most appropriate patent decision classification method.

Identifying Critical Success Factors in University Commercialization: The First Disclosure on the Linkage between Scientific Publications and Technology Transfer Performance (TTP)

This article constructs a technology transfer performance (TTP) evaluation model and tries to identify critical success factors for university commercialization. Different from most of previous researches which ignore the impact of academic capacity (i.e. scientific publications) on TTP, this paper examines the linkage between academic capacity and TTP. This study applies the structural equation model (SEM) to analyze the relations among five factors of TTP. The research results show that publishing capacity is the critical success factor in university commercialization. The increasing of research expenditures brings commercial benefit by means of the accumulation of scientific publications. Research expenditures also indirectly increase patent volume but may not promote TTP. Patenting activities may not the critical activities for university appropriation in technology transfer process. Patent volume may not bring license income; patent quality may be beneficial to university commercialization. Finally, this research visualizes TTP to articulate performance creation paths of university commercialization.

An innovative supply chain management strategy for green smart light emitting diode (LED) industry

Economic development has led to increased demand for energy; however, energy consumption has also led to continued worsening of greenhouse gas emissions and global warming. After the Kyoto Protocol came into effect, advanced nations worldwide pledged to actively expand national strategies in order to reduce greenhouse gas emissions. On June 5, 2008, the Executive Yuan of the Republic of China passed a Sustainable Energy Policy, which proposed the construction of a “high-efficiency”, “high-value”, “low-emission” and “low-dependency” energy consumption model and supply system. Based on this premise, businesses that wish to enhance their competitive abilities should respond as soon as possible to the interim goals of energy conservation and carbon reduction. Using high efficiency LED (light emitting diode) lighting fixtures is an easy, low cost, and effective method of reaching the goal of energy conservation and carbon reduction. This has also led to the emergence of the LED lighting industry as a technology industry with great potential. Using a developer in the LED corporate market as a research target, this study utilized case study methods to investigate the innovation model and sales strategy of this company. This study found that the subject company used long tail strategy and blue ocean strategy, in combination with niche marketing strategy, to satisfy market demands with the customized smart LED green lighting products. Based on the results of this study, our conclusions are as follows: 1. when a company’s brand awareness and economic scale cannot match those of well-known front-line companies in the mainstream market, such a company can use leading technology, R and D, and innovation to produce products that are differentiated from those of large manufacturers. 2. Based on the long tail strategy, small and medium enterprises (SMEs) can utilize the blue ocean strategy to select a niche market according to their unique advantages and develop high-margin products through product customization strategies.

A novel integrated SEM based on DEMATEL for evaluating technology license income performance

This study proposes a novel two stage approach which combines DEcision-MAking Trial and Evaluation Laboratory (DEMATEL) with structural equation modeling (SEM) for addressing and identifying the interrelationships of determinants and decision factors that influence or impact technology transfer. In the first stage, DEMATEL analysis is capable of revealing the central components and illustrating the interrelation structure of key factors that influence technology license income. Second, the result of DEMATEL offers SEM for further analyzing technology transfer performance. Research results provide a visualized framework to assist in assessing and predicting technology transfer performance — license income in universities.

Super-efficiency DEA model for evaluating technology transfer performance of U.S. university

American research universities have been allowed to receive license income from licensing patent rights to private sectors for further development and commercialization after the passage of University and Small Business Patent Procedures Act (Bayh-Dole Act) in 1980. The Act made huge fundamental and policy change in encouraging universities to rapidly increase their patenting and licensing activities. In the age of fundamental change, technology management especially technology transfer performance (TTP) has become an important issue among the entire American research universities. Nowadays, due to the complexity of patenting and licensing activities, a direct and precisely TTP evaluation and comparison is usually important but difficult. Unfortunately, few studies have devoted to proposing an objective and quantitative mechanism or technique for precisely evaluating TTP so far. Therefore, this study employs and compares two alternative data envelopment analysis (DEA) models — Charnes-Cooper-Rhodes (CCR) and supper-efficiency slack-based measure (SBM) to determine relative efficiencies and to measure the slack values among universities on the basis of AUTM licensing survey data whereby TTP is transformed into monetary value. Our research results will be able to sort the performance and provide managerial suggestions for each university to improve their TTP.