Introduction of an objective model to measure open innovation and its application to the information technology convergence sector

Yun, JinHyo Joseph; Avvari, Mohan V.; Jeong, Eui Seob; Lim, Dong Wook

doi:10.1504/ijtpm.2014.065025

Cited by 19 publications

(18 citation statements)

References 25 publications

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“…One study analyzed the open innovation of cities by the average number of joint applicants of each patent, and the ratio of jointly applied patents in target cities [36]. Another study measured the breadth of open innovation through the ratio of jointly applied patents from the total patents of a firm, and the depth of open innovation by the average number of joint applicants of each patent of a firm [37]. Another study analyzed the effect of distance on open innovation and its difference among institutions, and used the ratio of patents with joint applicants and the average number of joint applicants of each patent to measure the depth and breadth of open innovation, respectively [38].…”

Section: Research Scope and Methodsmentioning

confidence: 99%

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

Yun

Jeong

Lee³

et al. 2018

Sustainability

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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.

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Section: Research Scope and Methodsmentioning

confidence: 99%

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

Yun

Jeong

Lee³

et al. 2018

Sustainability

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“…Moreover, the selected business incubators focus on innovative start-ups belonging to ICT, digital, and high-tech sectors. This enhance a higher open innovation performance, in terms of width and depth, as it has proved to be strictly linked to the IT content [30]. From the other side, they differ in the infrastructure and in their main objectives.…”

Section: Methodsmentioning

confidence: 97%

“…From the other side, they differ in the infrastructure and in their main objectives. Indeed, the innovation relationship enabled by a different location (e.g., within a context such an university), and the mission mainly focused on mentoring rather than networking, can result in different open innovation performance [17,30]. Another variation criterion was the focus on start-ups showing a higher technological base, rather than a cross-disciplinary background, as this influence the mentoring and networking practices for stimulating purposive inflows and outflows of knowledge [24].…”

Section: Methodsmentioning

confidence: 99%

Framing Open Innovation in Start-Ups’ Incubators: A Complexity Theory Perspective

Battistella

Toni

Pessot

2018

Journal of Open Innovation: Technology, Market, and Complexity

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Recently, concepts and principles from the Complexity Theory (or, generally speaking, the complexity sciences) have been applied as a perspective for capturing the influence of the context, interaction, and adaption in the innovation processes, such as the ones enabled in the business incubators. The purpose of this paper is to implement a frame of reference for understanding the start-ups' incubator as a complex system where innovation, learning, and self-organization take place. We build on the interfaces between the Complexity Theory (i.e., complexity sciences) and Open Innovation literature to identify principles, patterns, and conditions that frame the incubation practices as simple rules aimed to sustain the innovation process towards the creation of new ventures. Results from the multiple case studies conducted in five incubators show that the features of variety, nonlinear interaction, interdependence, autonomy, and emergence of the incubation process framed as a complex system are enabled in different ways by the combination of the open innovation practices and services provided by the start-ups' incubators, including the provision of physical infrastructure, access to funding streams, experts/entrepreneurs networking, education/workshops, mentorship, and advice.

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“…In a study in which the ratio of joint patent application cases among all patents of companies is defined as the breadth of OI, and in which the average of the patent applicants of each patent of a company is the depth of OI, the concept of collaboration of joint patent application is materialized as OI [22]. Yun et al [22] use two concepts, the breadth of OI, which means the ratio of all people who gave positive answers to the survey of OI, and the depth of OI, which means the percentage of all people who gave positive answers about OI with high intensity, to develop the width and depth of OI and to connect this concept with joint patent application [23].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Yun et al [22] use two concepts, the breadth of OI, which means the ratio of all people who gave positive answers to the survey of OI, and the depth of OI, which means the percentage of all people who gave positive answers about OI with high intensity, to develop the width and depth of OI and to connect this concept with joint patent application [23]. To measure the synergy in an innovative system, such as OI and triple helix, it is necessary to consider diverse aspects of patents, such as citations, joint patent applications, etc.…”

Section: Literature Reviewmentioning

confidence: 99%

Effect of Distance on Open Innovation: Differences among Institutions According to Patent Citation and Reference

et al. 2017

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Abstract:The main topic of this paper is the effects of distance between technology and the market, on open innovation. For this, we set up two research questions, as follows: Is there any relation between the distance between technology and the market, and open innovation? If there is, what differences are there in the relation among Fortune 500 companies, non-Fortune 500 companies, laboratories, universities, and start-ups? First, this study measured the distance between technology and the market of a patent by the size of its list of references and citations. Second, the OI network among patent application subjects was described based on patent similarity. Third and most importantly, regression analyses were used to answer the research questions. The first result was that there were differences in the distance and OI among Fortune 500 firms, Fortune non-500 firms, laboratories, universities, and start-ups. Thus, there are relations between the distance between technology and the market, and open innovation. The second result was that the distance between technology and the market was found to moderate the open innovation effect in Fortune 500 companies and laboratories.

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Introduction of an objective model to measure open innovation and its application to the information technology convergence sector

Cited by 19 publications

References 25 publications

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

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

Framing Open Innovation in Start-Ups’ Incubators: A Complexity Theory Perspective

Effect of Distance on Open Innovation: Differences among Institutions According to Patent Citation and Reference

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