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Bibliometric analysis of service innovation research: Identifying knowledge domain and global network of knowledge

Author

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  • Sakata, Ichiro
  • Sasaki, Hajime
  • Akiyama, Masanori
  • Sawatani, Yuriko
  • Shibata, Naoki
  • Kajikawa, Yuya

Abstract

The concept of service innovation is significant for innovation strategy and economic growth. However, since the term “service innovation” represents a broad sense, there does not exist common understanding about what is service innovation even among experts. We developed a methodology to determine the structure and geographical distribution of knowledge, as well as to reveal the structure of research collaboration in such an interdisciplinary area as service innovation by performing journal information analysis, citation network analysis and visualization. Our results show that there are mainly two groups relating to service innovation. Knowledge in these areas has been growing rapidly in recent years. In particular, the fields of ecosystem and IT & Web are exhibiting high growth. We also demonstrated that the global network of knowledge is formed around the powerful hub of the US. The research competency of Asian countries lags behind that of the US and EU. With respect to research collaboration, we identify room for enhancing international collaboration. Our methodology could be useful in forming policies to promote service innovation. Finally, we propose the creation of an international collaboration fund.

Suggested Citation

  • Sakata, Ichiro & Sasaki, Hajime & Akiyama, Masanori & Sawatani, Yuriko & Shibata, Naoki & Kajikawa, Yuya, 2013. "Bibliometric analysis of service innovation research: Identifying knowledge domain and global network of knowledge," Technological Forecasting and Social Change, Elsevier, vol. 80(6), pages 1085-1093.
    • Handle: RePEc:eee:tefoso:v:80:y:2013:i:6:p:1085-1093
    DOI: 10.1016/j.techfore.2012.03.009
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    Citations

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    Cited by:

    1. Christian Bartelheimer & Philipp Heiden & Hedda Lüttenberg & Daniel Beverungen, 2022. "Systematizing the lexicon of platforms in information systems: a data-driven study," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(1), pages 375-396, March.
    2. Gaviria-Marin, Magaly & Merigó, José M. & Baier-Fuentes, Hugo, 2019. "Knowledge management: A global examination based on bibliometric analysis," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 194-220.
    3. Yuan Zhou & Fang Dong & Yufei Liu & Liang Ran, 2021. "A deep learning framework to early identify emerging technologies in large-scale outlier patents: an empirical study of CNC machine tool," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 969-994, February.
    4. Chen, Kaui-Hwang & Wang, Chun-Hsien & Huang, Shi-Zheng & Shen, George C., 2016. "Service innovation and new product performance: The influence of market-linking capabilities and market turbulence," International Journal of Production Economics, Elsevier, vol. 172(C), pages 54-64.
    5. Tsujimoto, Masaharu & Kajikawa, Yuya & Tomita, Junichi & Matsumoto, Yoichi, 2018. "A review of the ecosystem concept — Towards coherent ecosystem design," Technological Forecasting and Social Change, Elsevier, vol. 136(C), pages 49-58.
    6. Daniel Feser & Till Proeger, 2018. "Knowledge-Intensive Business Services as Credence Goods—a Demand-Side Approach," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 9(1), pages 62-80, March.
    7. Dejing Kong & Jianzhong Yang & Lingfeng Li, 2020. "Early identification of technological convergence in numerical control machine tool: a deep learning approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 1983-2009, December.
    8. Daim, Tugrul U. & Yoon, Byung-Sung & Lindenberg, John & Grizzi, Robert & Estep, Judith & Oliver, Terry, 2018. "Strategic roadmapping of robotics technologies for the power industry: A multicriteria technology assessment," Technological Forecasting and Social Change, Elsevier, vol. 131(C), pages 49-66.
    9. John N. Walsh & Jamie O’Brien, 2018. "Knowledge Asymmetries and Service Management: Three Case Studies," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 17(03), pages 1-26, September.
    10. Dzikowski, Piotr, 2018. "A bibliometric analysis of born global firms," Journal of Business Research, Elsevier, vol. 85(C), pages 281-294.
    11. Sungchul Kim & Ronald Giachetti & Sangsung Park, 2018. "Real Options Analysis for Acquisition of New Technology: A Case Study of Korea K2 Tank’s Powerpack," Sustainability, MDPI, vol. 10(11), pages 1-18, October.
    12. Homayounfard, Amir & Zaefarian, Ghasem, 2022. "Key challenges and opportunities of service innovation processes in technology supplier-service provider partnerships," Journal of Business Research, Elsevier, vol. 139(C), pages 1284-1302.
    13. Zhou, Yuan & Dong, Fang & Kong, Dejing & Liu, Yufei, 2019. "Unfolding the convergence process of scientific knowledge for the early identification of emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 205-220.
    14. Grzegorz Mentel & Anna Lewandowska & Justyna Berniak-Woźny & Waldemar Tarczyński, 2023. "Green and Renewable Energy Innovations: A Comprehensive Bibliometric Analysis," Energies, MDPI, vol. 16(3), pages 1-21, February.
    15. Santos-Vijande, María Leticia & López-Sánchez, Jose Ángel & Pascual-Fernández, Primitiva & Rudd, John M., 2021. "Service innovation management in a modern economy: Insights on the interplay between firms’ innovative culture and project-level success factors," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    16. Sungchul Kim & Dongsik Jang & Sunghae Jun & Sangsung Park, 2015. "A Novel Forecasting Methodology for Sustainable Management of Defense Technology," Sustainability, MDPI, vol. 7(12), pages 1-17, December.

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