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Identifying Service Opportunities Based on Outcome-Driven Innovation Framework and Deep Learning: A Case Study of Hotel Service

Author

Listed:
  • Sunghyun Nam

    (Samsung Research, Seoul 04763, Korea)

  • Sejun Yoon

    (Department of Information Systems, Hanyang University, Seoul 04763, Korea)

  • Nagarajan Raghavan

    (Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD), Singapore 487372, Singapore)

  • Hyunseok Park

    (Department of Information Systems, Hanyang University, Seoul 04763, Korea)

Abstract

This research proposes a data-driven systematic method to discover service opportunities in a specific service sector. Specifically, the method quantitatively identifies the important but unsatisfied customer needs by analyzing online review data. To represent customer needs in a structured form, the job-to-be-done -based customer outcomes are adopted from the outcome-driven innovation (ODI) framework. Therefore, job-to-be-done information is extracted from the review data and is transformed into customer outcomes. The outcomes having high service opportunities are selected by metrics for quantifying the importance and satisfaction score of the outcomes. This paper conducted an empirical study for hotel service using relevant review data. The results show that the method can identify customer needs in hotel service—e.g., maximizing safety to pay price/deposit, and maximizing possibility to avoid waiting at lobby—and objectively prioritize strategic directions for service innovation. Therefore, the proposed method can be used as an intelligent tool for the effective development of a business strategy.

Suggested Citation

  • Sunghyun Nam & Sejun Yoon & Nagarajan Raghavan & Hyunseok Park, 2021. "Identifying Service Opportunities Based on Outcome-Driven Innovation Framework and Deep Learning: A Case Study of Hotel Service," Sustainability, MDPI, vol. 13(1), pages 1-25, January.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:1:p:391-:d:474527
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    References listed on IDEAS

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    1. Hyun-Jeong Ban & Hayeon Choi & Eun-Kyong Choi & Sanghyeop Lee & Hak-Seon Kim, 2019. "Investigating Key Attributes in Experience and Satisfaction of Hotel Customer Using Online Review Data," Sustainability, MDPI, vol. 11(23), pages 1-13, November.
    2. Joohyung Lim & Sungchul Choi & Chiehyeon Lim & Kwangsoo Kim, 2017. "SAO-Based Semantic Mining of Patents for Semi-Automatic Construction of a Customer Job Map," Sustainability, MDPI, vol. 9(8), pages 1-17, August.
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    4. Mun, Changbae & Kim, Yongmin & Yoo, Donghyun & Yoon, Sejun & Hyun, Heesu & Raghavan, Nagarajan & Park, Hyunseok, 2019. "Discovering business diversification opportunities using patent information and open innovation cases," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 144-154.
    5. Hyunseok Park & Janghyeok Yoon & Kwangsoo Kim, 2012. "Identifying patent infringement using SAO based semantic technological similarities," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(2), pages 515-529, February.
    6. Michael Fritsch & Pamela Mueller & Antje Weyh, 2005. "Direct and indirect effects of new business formation on regional employment," Applied Economics Letters, Taylor & Francis Journals, vol. 12(9), pages 545-548.
    7. Hyunseok Park & Janghyeok Yoon, 2015. "A chance discovery-based approach for new product–service system (PSS) concepts," Service Business, Springer;Pan-Pacific Business Association, vol. 9(1), pages 115-135, March.
    8. Hyunseok Park & Janghyeok Yoon & Kwangsoo Kim, 2013. "Identification and evaluation of corporations for merger and acquisition strategies using patent information and text mining," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 883-909, December.
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    Cited by:

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    2. Justyna Witkowska & Sylwia Stachowska, 2021. "Competencies of Sales Employees as a Determinant of the Quality of Provided Services Based on the Insurance Market," European Research Studies Journal, European Research Studies Journal, vol. 0(2), pages 841-855.

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