Next Issue
Volume 3, March
Previous Issue
Volume 2, September
 
 
Journal of Open Innovation: Technology, Market, and Complexity is published by MDPI from Volume 4 Issue 2 (2018). Previous articles were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence, and they are hosted by MDPI on mdpi.com as a courtesy and upon agreement with Springer.

J. Open Innov. Technol. Mark. Complex., Volume 2, Issue 4 (December 2016) – 5 articles

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Select all
Export citation of selected articles as:
1031 KiB  
Article
Configuring an alliance portfolio for eco-friendly innovation in the car industry: Hyundai and Toyota
by Hyeon Joo Jeong and Youngjoo Ko
J. Open Innov. Technol. Mark. Complex. 2016, 2(4), 24; https://doi.org/10.1186/s40852-016-0050-z - 01 Dec 2016
Cited by 13 | Viewed by 1288
Abstract
Purpose: This study aims to examine the strategic alliance portfolio and the characters of focal firm partners in the eco-friendly car market, and also suggest the important managerial implications and suggestions for firms’ managers and policy-makers using the patent information of Toyota and [...] Read more.
Purpose: This study aims to examine the strategic alliance portfolio and the characters of focal firm partners in the eco-friendly car market, and also suggest the important managerial implications and suggestions for firms’ managers and policy-makers using the patent information of Toyota and Hyundai as examples. This study identifies the fundamental differences in Hyundai’s strategic partnerships through the comparison with Toyota’s alliance portfolio.
Key literature reviews: This study analyzes the configuration of alliance portfolio using the patent citation information and various patent citation indexes. Many previous studies use patent citation information to analyze the flow of technological knowledge and the relative importance of the technology that companies produce (Hall, Jaffe, & Trajtenberg, 2005). Patents contain a lot of information, which researchers use to derive multiple properties related to technological innovation or technological excellence (Ernst, 2003). Especially, the Current Impact Index (CII), the Technology Strength (TS), the Technology Independence (TI) and the Science Linkage mean the technological innovation of companies (Chang, Chen, & Huang, 2012; Z. Huang et al., 2003; Sung, Wang, Huang, & Chen, 2015).
Design/ methodology/ approach: The paper employs patent data for collection of partnership data for both Hyundai and Toyota using joint patent filings, and the alliance portfolios are configured by using co-assignees as partners. In addition, we use patent citation indexes to analyze the relationship between firms’ technological alliance and innovation capability.
(Expected) findings/results: The results of this study show that; 1) Toyota is actively developing joint R&D activities but, Hyundai is not. Because of this, Toyota has the advantageous position to obtain knowledge and technology than Hyundai due to the high centrality in alliance portfolio. 2) The alliance portfolio of Toyota and Hyundai can be categorized four groups by the degree of collaboration and patent quality. 3) There are differences in the properties of four groups of Toyota’s alliance portfolio and Hyundai’s alliance portfolio.
Research limitations/implications: This study has several limitations. First, patent information indicates only the cross-section of the company’s innovation. Second, joint patents are not the only outcome of joint R&D, and comprise only a very small part of the output from joint R&D activities. In spite of these limitations, the findings suggest how firms can catch up to access the automotive bioplastic market, and offers contributions to theories related to portfolios. Full article
1126 KiB  
Article
Cultural correlates of national innovative capacity: a cross-national analysis of national culture and innovation rates
by Youngsun Jang, Youngjoo Ko and So Young Kim
J. Open Innov. Technol. Mark. Complex. 2016, 2(4), 23; https://doi.org/10.1186/s40852-016-0048-6 - 24 Nov 2016
Cited by 13 | Viewed by 1642
Abstract
Although it is conventional wisdom that innovation requires free mind, diversity, or creativity all of which are closely associated with political and organizational decentralization, it is in fact more politically centralized countries in East Asia that successfully capitalized on innovation to catapult their [...] Read more.
Although it is conventional wisdom that innovation requires free mind, diversity, or creativity all of which are closely associated with political and organizational decentralization, it is in fact more politically centralized countries in East Asia that successfully capitalized on innovation to catapult their economies onto the growth trajectory. Scholars have thus wondered if this is an exception rather a rule. Are more centralized countries innovative? Existing empirical research has produced mixed results. This study introduces a new perspective on this issue. Rather than the degree of centralization found in formal institutions, we focus on non-institutional or informal dimensions of centralization particularly associated with culture. Using Hofstede’s cross-national dataset capturing national culture, we explore how different dimensions of national culture are linked to national innovative capacity as proxied by patents. Our preliminary findings from the analysis of 34 OECD member states based on the patent data extracted from the Patent Cooperation Treaty (PCT) database suggest that non-institutional dimensions of centralization account more for the variations in national rates of patents per capita than more formal aspects of centralization measured by traditional political datasets such as POLCON. While cultural aspects have been examined in technology management at the individual and the firm level, this study fills a gap in the existing literature by exploring their relationship at the national level. More research is clearly needed to explore the roles of non-institutional features facilitating or hampering innovation. Full article
336 KiB  
Editorial
An open letter to Mr. Secretary general of the united nations to propose setting up global standards for conquering growth limits of capitalism
by JinHyo Joseph Yun, Philip Cooke, Fumio Kodama, Fred Phillips, Anil K. Gupta, Francisco Javier Carrillo Gamboa, Venni Krishna, Keun Lee, KongRae Lee, Ulrich Witt, Natalja Lace, SangOk Choi, KwangHo Jung, WooSung Jung, KyungBae Park, Sam Youl Lee, Jiyoung Park, Jaehoon Rhee, DongKyu Won, Taeho Park, Jeongho Yang, EuiSeob Jeong and JinWon Kangadd Show full author list remove Hide full author list
J. Open Innov. Technol. Mark. Complex. 2016, 2(4), 22; https://doi.org/10.1186/s40852-016-0049-5 - 21 Nov 2016
Cited by 15 | Viewed by 1260
Abstract
We propose an international economic agenda to overcome the growth limits of capitalism that can be supported by the United Nations. Sustainable Environment based global goals should be added to sustainable economy. For this, we propose dynamic balance between three sub-economies such as [...] Read more.
We propose an international economic agenda to overcome the growth limits of capitalism that can be supported by the United Nations. Sustainable Environment based global goals should be added to sustainable economy. For this, we propose dynamic balance between three sub-economies such as open innovation, closed innovation, and social innovation sub-economy. For this, we propose to set up a UN community and a long range plan. Full article
4899 KiB  
Article
Valuation method by regression analysis on real royalty-related data by using multiple input descriptors in royalty negotiations in Life Science area-focused on anticancer therapies
by Jeong Hee Lee, Bae Khee-Su, Joon Woo Lee, Youngyong In, Taehoon Kwon and Wangwoo Lee
J. Open Innov. Technol. Mark. Complex. 2016, 2(4), 21; https://doi.org/10.1186/s40852-016-0047-7 - 17 Oct 2016
Cited by 5 | Viewed by 1432
Abstract
Purpose: This research seeks to answer the basic question, “What would be the most determining factors if I perform regression analysis using several independent variables?” This paper suggests the way to estimate the proper royalty rate and up-front payment using multiple data I [...] Read more.
Purpose: This research seeks to answer the basic question, “What would be the most determining factors if I perform regression analysis using several independent variables?” This paper suggests the way to estimate the proper royalty rate and up-front payment using multiple data I can get simply as input.
Design/methodology/approach: This research analyzes the dataset, including the royalty-related data like running royalty rate (back-end payments) and up-front payment (up-front fee + milestones), regarding drug candidates for specific drug class of anticancer by regression analysis. Then, the formula to predict royalty-related data is derived using the attrition rate for the corresponding development phase of the drug candidate for the license deal, TCT (Technology Cycle Time) median value for the IPC code (IP) of the IP, Market size of the technology, CAGR (Compound Annual Growth Rate) of the corresponding market and the revenue data of the license buyer (licensee).
Findings: For the anticancer (antineoplastics) drug classes, the formula to predict the royalty rate and up-front payment is as follows.
<Drug Class: Anticancer activity candidates>

Royalty Rate = 9.997 + 0.063 * Attrition Rate + 1.655
* Licensee Revenue ‐ 0.410 * TCT Median

‐1.090 * Market Size ‐ 0.230 * CAGR (Formula 1)

Up‐Front Payment (Up‐front + Milestones) = 2.909 ‐ 0.006 * Attrition Rate + 0.306 *
Licensee Revenue ‐ 0.74 * TCT Median ‐ 0.113 * Market Size ‐ 0.009 * CAGR (Formula 2)

In the case of Equations Equation 1 to estimate the royalty rate, it is statistically meaningful at the significance level of 1 % (P-Value: 0.001); however, in the case of Equations Equation 2 to estimate the up-front payment it is statistically not meaningful (P-Value: 0.288), thus requiring further study.
Research limitations/implications (if applicable): This research is limited to the relationship between multiple input variables and royalty-related data in one drug class of anticancer (antineoplastics).
Practical implications (if applicable): Valuation for the drug candidate within a specific drug class can be possible, and the royalty rate can be a variable according to drug class and licensee revenue.

Full article
559 KiB  
Article
Implementing open innovation concept in social business
by Anna Svirina, Alfia Zabbarova and Karine Oganisjana
J. Open Innov. Technol. Mark. Complex. 2016, 2(4), 20; https://doi.org/10.1186/s40852-016-0046-8 - 12 Oct 2016
Cited by 24 | Viewed by 1490
Abstract
Social business is an emerging concept which requires additional research especially in terms of priority management tools that can be used. The paper aims to evaluate how closed and open innovation concepts are implemented by social enterprises in the emerging information economy. The [...] Read more.
Social business is an emerging concept which requires additional research especially in terms of priority management tools that can be used. The paper aims to evaluate how closed and open innovation concepts are implemented by social enterprises in the emerging information economy. The paper also studies social enterprises from the point of view of joint efficiency and innovation development concept evaluation to define best practices used by social entrepreneurs nowadays.
The paper provides comparative analysis of two types of social business models: the ones based on open innovation and the ones based on formal closed innovative process. Research question is to estimate how implementation of open innovation influences social businesses’ outcomes, and to define the way open innovation influences social enterprises’ efficiency. Full article
Previous Issue
Next Issue
Back to TopTop