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Exploring Suitable Technology for Small and Medium-Sized Enterprises (SMEs) Based on a Hidden Markov Model Using Patent Information and Value Chain Analysis

Author

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  • Keeeun Lee

    (Department of Industrial & Systems Engineering, School of Engineering, Dongguk University-Seoul, 30, Pildong-ro 1 gil, Jung-gu, Seoul 100-715, Korea)

  • Deaun Go

    (Department of Industrial & Systems Engineering, School of Engineering, Dongguk University-Seoul, 30, Pildong-ro 1 gil, Jung-gu, Seoul 100-715, Korea)

  • Inchae Park

    (Department of Industrial & Systems Engineering, School of Engineering, Dongguk University-Seoul, 30, Pildong-ro 1 gil, Jung-gu, Seoul 100-715, Korea)

  • Byungun Yoon

    (Department of Industrial & Systems Engineering, School of Engineering, Dongguk University-Seoul, 30, Pildong-ro 1 gil, Jung-gu, Seoul 100-715, Korea)

Abstract

R&D cooperative efforts between large firms and small and medium-sized enterprises (SMEs) have been accelerated to develop innovative projects and deploy profitable businesses. In general, win-win alliances between large firms and SMEs for sustainable growth require the pre-evaluation of their capabilities to explore high potential partners for successful collaborations. Thus, this research proposes a systematic method that identifies SME-suitable technology where SMEs have a competitive edge in R&D collaborations. First, such technology fields are identified by various factors that influence successful R&D activities by applying the Hidden Markov Model (HMM) and using information on value chains of an industry. To identify these fields, innovation factors such as the current impact index and technology cycle time are composed using the bibliographic information of patents. Second, patent information is analyzed to obtain observation probability in terms of technical competitiveness, and value chain data is used to calculate transition probability in HMMs. Finally, the Viterbi algorithm is employed to formulate the aforementioned two types of probability as a tool for selecting appropriate fields for SMEs. This paper applies the proposed approach to the solar photovoltaic industry to explore SME-suitable technologies. This research can contribute to help develop successful R&D partnership between large firms and SMEs.

Suggested Citation

  • Keeeun Lee & Deaun Go & Inchae Park & Byungun Yoon, 2017. "Exploring Suitable Technology for Small and Medium-Sized Enterprises (SMEs) Based on a Hidden Markov Model Using Patent Information and Value Chain Analysis," Sustainability, MDPI, vol. 9(7), pages 1-19, June.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:7:p:1100-:d:102438
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    References listed on IDEAS

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    2. Maciej Chrzanowski & Piotr Zawada, 2023. "Fraction Separation Potential in the Recycling Process of Photovoltaic Panels at the Installation Site—A Conceptual Framework from an Economic and Ecological Safety Perspective," Energies, MDPI, vol. 16(5), pages 1-10, February.
    3. Shuai Liu & Xiao-Yu Xu & Kai Zhao & Li-Ming Xiao & Qi Li, 2021. "Understanding the Complexity of Regional Innovation Capacity Dynamics in China: From the Perspective of Hidden Markov Model," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
    4. Changbyung Yoon & Keeeun Lee & Byungun Yoon & Omar Toulan, 2017. "Typology and Success Factors of Collaboration for Sustainable Growth in the IT Service Industry," Sustainability, MDPI, vol. 9(11), pages 1-20, November.
    5. Xiaofeng Xu & Dongdong He & Tao Wang & Xiangyu Chen & Yichen Zhou, 2023. "Technological Innovation Efficiency of Listed Carbon Capture Companies in China: Based on the Dual Dimensions of Legal Policy and Technology," Energies, MDPI, vol. 16(3), pages 1-16, January.
    6. Choi, Jaewoong & Jeong, Byeongki & Yoon, Janghyeok, 2019. "Technology opportunity discovery under the dynamic change of focus technology fields: Application of sequential pattern mining to patent classifications," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    7. Menglin Xing & Fuzhou Luo, 2018. "Comparative Study on the Optimization Path of Industrial Value Chain in China’s Resource-Based Cities," Sustainability, MDPI, vol. 10(5), pages 1-20, April.
    8. Diana-Teodora Trip & Ramona Simut & Daniel Badulescu, 2023. "Do Size and Ownership Determine the Willingness for Sustainable Innovations in Spa and Health Tourism? A Case Study on Baile Felix Spa Resort, Romania," Sustainability, MDPI, vol. 15(19), pages 1-17, October.
    9. María E. Aguilar-Fernández & José Ramon Otegi-Olaso, 2018. "Firm Size and the Business Model for Sustainable Innovation," Sustainability, MDPI, vol. 10(12), pages 1-27, December.

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