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Identifying new innovative services using M&A data: An integrated approach of data-driven morphological analysis

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  • Ha, Sohee
  • Geum, Youngjung

Abstract

This study suggests a concrete framework for generating new service ideas using an M&A dataset. Addressing the limitations of previous works that neglected service-specific characteristics, we suggest methods to extract service-specific keywords and phrases from the text and restructure them to provide clear evidence for new service development. Therefore, we propose a process for building data-driven quality function deployment (QFD) and data-driven morphological analysis (MA). First, M&A transactions were collected from CrunchBase, which is an open platform that provides start-up information. Service actions and service contents are then extracted from the text using natural language processing. For each extracted keyword, a clustering analysis was performed to identify the new service patterns. For clustered service actions and contents, MA is employed to generate new service ideas. This study contributes to the technology management field by first employing M&A records for the data-driven morphological matrix and suggests how to extract service actions and service contents from the text. We also suggested a new systematic way of identifying new services using an integrated approach of QFD and MA. This work is expected to help managers in new service development by providing practical guidance and tools for utilizing textual data.

Suggested Citation

  • Ha, Sohee & Geum, Youngjung, 2022. "Identifying new innovative services using M&A data: An integrated approach of data-driven morphological analysis," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    • Handle: RePEc:eee:tefoso:v:174:y:2022:i:c:s0040162521006302
    DOI: 10.1016/j.techfore.2021.121197
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    References listed on IDEAS

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    1. Sojung Kim & Byungun Yoon, 2012. "Developing a process of concept generation for new product-service systems: a QFD and TRIZ-based approach," Service Business, Springer;Pan-Pacific Business Association, vol. 6(3), pages 323-348, September.
    2. Kayser, Victoria & Shala, Erduana, 2020. "Scenario development using web mining for outlining technology futures," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
    3. Kim, Kun & Park, Oun-joung & Yun, Seunghyun & Yun, Haejung, 2017. "What makes tourists feel negatively about tourism destinations? Application of hybrid text mining methodology to smart destination management," Technological Forecasting and Social Change, Elsevier, vol. 123(C), pages 362-369.
    4. Atanu Sengupta & Sanjoy De, 2020. "Review of Literature," India Studies in Business and Economics, in: Assessing Performance of Banks in India Fifty Years After Nationalization, chapter 0, pages 15-30, Springer.
    5. Geum, Youngjung & Park, Yongtae, 2016. "How to generate creative ideas for innovation: a hybrid approach of WordNet and morphological analysis," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 176-187.
    6. Ju, Yonghan & Sohn, So Young, 2015. "Patent-based QFD framework development for identification of emerging technologies and related business models: A case of robot technology in Korea," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 44-64.
    7. O'Brien, Frances A. & Meadows, Maureen & Griffiths, Sam, 2017. "Serialisation and the use of Twitter: Keeping the conversation alive in public policy scenario projects," Technological Forecasting and Social Change, Elsevier, vol. 124(C), pages 26-40.
    8. Hakyeon Lee & Hyunju Seol & Hyejong Min & Youngjung Geum, 2017. "The identification of new service opportunities: a case-based morphological analysis," Service Business, Springer;Pan-Pacific Business Association, vol. 11(1), pages 191-206, March.
    9. David A. Hull, 1996. "Stemming algorithms: A case study for detailed evaluation," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 47(1), pages 70-84, January.
    10. Johansen, Iver, 2018. "Scenario modelling with morphological analysis," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 116-125.
    11. Yoon, Byungun & Park, Inchae & Coh, Byoung-youl, 2014. "Exploring technological opportunities by linking technology and products: Application of morphology analysis and text mining," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 287-303.
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