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Conjoint analysis for intellectual property education

Author

Listed:
  • Mok, Min Seok
  • Sohn, So Young
  • Ju, Yong Han

Abstract

As the knowledge economy rapidly increases, intangible assets are more valuable to businesses and valuing them attracts much research from the field of technology management. Intangible assets include intellectual capital and intellectual property. To ensure that science students have the skills that match the information resources they will use as professionals, patent searching must become part of their information literacy instruction. This article is to design guidelines for intellectual property (IP) education from the perspective of the researchers and employees in university, private and public institution researchers and others. Applying conjoint analysis, this study shows not only the relative importance of the attributes related to IP education but also the most important conditions of the education. It is expected that this study may help to develop IP curricula in academia in Korea and elsewhere.

Suggested Citation

  • Mok, Min Seok & Sohn, So Young & Ju, Yong Han, 2010. "Conjoint analysis for intellectual property education," World Patent Information, Elsevier, vol. 32(2), pages 129-134, June.
    • Handle: RePEc:eee:worpat:v:32:y:2010:i:2:p:129-134
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    Cited by:

    1. Ardvin Kester S. Ong & Yogi Tri Prasetyo & Kerr Lorenzo Picazo & Kim Aaron Salvador & Bobby Ardiansyah Miraja & Yoshiki B. Kurata & Thanatorn Chuenyindee & Reny Nadlifatin & Anak Agung Ngurah Perwira , 2021. "Gym-Goers Preference Analysis of Fitness Centers during the COVID-19 Pandemic: A Conjoint Analysis Approach for Business Sustainability," Sustainability, MDPI, vol. 13(18), pages 1-17, September.
    2. Bojan Ćudić, 2021. "Factors impacting patent applications in European countries," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(3), pages 573-589, June.
    3. S. Ong, Ardvin Kester & Prasetyo, Yogi Tri & Chuenyindee, Thanatorn & Young, Michael Nayat & Doma, Bonifacio T. & Caballes, Dennis G. & Centeno, Raffy S. & Morfe, Anthony S. & Bautista, Christine S., 2022. "Preference analysis on the online learning attributes among senior high school students during the COVID-19 pandemic: A conjoint analysis approach," Evaluation and Program Planning, Elsevier, vol. 92(C).
    4. So Sohn & Mooyeob Lee, 2012. "Conjoint analysis of R&D contract agreements for industry-funded university research," The Journal of Technology Transfer, Springer, vol. 37(4), pages 532-549, August.
    5. Ardvin Kester S. Ong & Yogi Tri Prasetyo & Michael Nayat Young & John Francis T. Diaz & Thanatorn Chuenyindee & Poonyawat Kusonwattana & Nattakit Yuduang & Reny Nadlifatin & Anak Agung Ngurah Perwira , 2021. "Students’ Preference Analysis on Online Learning Attributes in Industrial Engineering Education during the COVID-19 Pandemic: A Conjoint Analysis Approach for Sustainable Industrial Engineers," Sustainability, MDPI, vol. 13(15), pages 1-20, July.
    6. Daniela Bolzani & Federico Munari & Einar Rasmussen & Laura Toschi, 2021. "Technology transfer offices as providers of science and technology entrepreneurship education," The Journal of Technology Transfer, Springer, vol. 46(2), pages 335-365, April.
    7. Bojan Ćudić & Iwona Skrodzka, 2021. "‘Soft’ Support Infrastructure And The Performance Of Small And Medium-Sized Enterprises In European Countries," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 66(230), pages 67-100, July – Se.

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