A smooth dynamic network model for patent collaboration data

The development and application of models, which take the evolution of network dynamics into account, are receiving increasing attention. We contribute to this field and focus on a profile likelihood approach to model time-stamped event data for a large-scale dynamic network. We investigate the collaboration of inventors using EU patent data. As event we consider the submission of a joint patent and we explore the driving forces for collaboration between inventors. We propose a flexible semiparametric model, which includes external and internal covariates, where the latter are built from the network history.

The Effect of Open Innovation on Technology Value and Technology Transfer: A Comparative Analysis of the Automotive, Robotics, and Aviation Industries of Korea

With the advent of the Fourth Industrial Revolution, the Korean industrial environment has been rapidly changing. As a result, several industries are facing different innovation conditions, including: the automotive industry, which is a traditional manufacturing industry in Korea; the aerospace industry, which has been vertically integrated, and has been led by a single large company—Korea Aerospace Industries—since Korea went through an economic crisis in the 1990s; and the robotics industry, which is currently emerging. This study used parameters related to patents originating from the automobile, robotics, and aerospace fields. The patents subjected to analysis were those registered in Korea from 2001 to 2014, and included those that were applied for, jointly applied for, or registered by Korean companies. This study analyzed the differences caused by the effect of open innovation in the three industries. According to our results, first, the three industries experienced different effects of open innovation. Second, when large companies controlled a given industry, open innovation either worked a little or did not work at all. According to this research result, the Korean robotics industry, which has a weak dominance of large companies, experienced a strong effect of open innovation, in that joint patent applications led to economic gains from the patents and an increase in technology transfer and technology value. The aerospace industry of Korea, which has the highest dominance of large companies, experienced a slight effect of open innovation, as the effect of joint patent application only improved the technology value. Finally, the automotive industry of Korea had an intermediate level of open innovation, between the aerospace and robotics sectors.

Innovative partnerships resulting from high-skilled emigration

Purpose This paper aims to examine whether emigration of high-skilled labor creates a positive effect in the home country by generating multi-country joint patent relationships between home and destination country-pairs. Design/methodology/approach A panel of data that uniquely captures the country of origin of patent applicants is used to assess if and how high-skilled emigration contributes to the prevalence of multi-country joint patents in a country. The analysis is conducted both in aggregate and across sub-samples based on the per capita income level of the home country. Finally, the role of absorptive capacity as a control variable is robustly considered. Findings Results suggest that emigration of high-skilled labor positively impacts the prevalence of multi-country joint patent ownership when emigration originates from middle- and high-income countries. Support for such “brain gain” via knowledge sharing in innovation is absent when high-skilled labor emigrates from low-income countries. Originality/value The analysis highlights a specific avenue by which the home country benefits from high-skilled emigration. It also provides comparative analysis across home countries of different income levels, which can provide insight into the external validity of papers using high-income country samples of innovative performance when assessing knowledge spillovers.

Network Analysis of Open Innovation

The way people innovate and create new ideas and bring them to the market is undergoing a fundamental change from closed innovation to open innovation. Why and how do firms perform open innovation? Firms’ open innovation is measured through the levels of firms’ joint patent applications. Next, we analyze network structures and characters of firms’ joint patent applications such as betweenness and degree centrality, structure hole, and closure. From this research, we drew conclusions as follows. First, the structure of collaboration networks has both direct and indirect effects on firms’ innovative performance. Second, in the process of joint patent applications, there is a long tail phenomenon in networks of joint patent applications. Third, the number of patents and International Patent Classification (IPC) subclasses together constitute a meaningful measure of the innovation performance of firms.

Network Analysis of Open Innovation

The way people innovate and create new ideas and bring them to the market is undergoing a fundamental change from closed innovation to open innovation. Why and how do firms perform open innovation? Firms’ open innovation is measured through the levels of firms’ joint patent applications. Next, we analyze network structures and characters of firms’ joint patent applications such as betweenness and degree centrality, structure hole, and closure. From this research, we drew four conclusions. First, the structure of collaboration networks has both direct and indirect effects on firms’ innovative performance. Second, in the process of joint patent applications, there is a long tail phenomenon in networks of joint patent applications. Third, the number of patents and IPC subclasses together constitute a meaningful measure of the innovation performance of firms.