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A chance discovery-based approach for new product–service system (PSS) concepts

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  • Hyunseok Park
  • Janghyeok Yoon

Abstract

As a product–service system (PSS) attracts much attention as an alternative for sustainable development, studies have suggested ways to support the PSS development process. Despite the growing interest of PSS, however, little attention has been paid to generating PSS concepts from large-scale customer behaviors, situations, and relevant needs (BSNs) regarding a product. Although understanding customer BSNs comprehensively is the most prerequisite and fundamental in PSS development, the previous literature assumes that the identification of customer BSNs is completed or imputed to manual and intrinsic tasks by experts, such as customer surveys and interviews, which may be time-consuming and costly. Therefore, this paper proposes an approach to identifying new PSS concepts by combining the chance discovery theory and text mining of Web news. The approach helps PSS designers identify significant customer BSNs from massive news data over a wide-scope regarding a given product, and it facilitates PSS designers to ideate about PSS scenarios and concepts efficiently by providing breaking events which can act as PSS chances. To illustrate the working process of our approach, a case using Web news of electric bicycles is introduced. The proposed approach will contribute to the ideation process for new PSS concepts; it further holds the potential to create a synergetic effect in case of being incorporated into the existing PSS development methodologies. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • 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.
    • Handle: RePEc:spr:svcbiz:v:9:y:2015:i:1:p:115-135
    DOI: 10.1007/s11628-013-0222-x
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    References listed on IDEAS

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    1. Yukio Ohsawa, 2005. "Data Crystallization: Chance Discovery Extended For Dealing With Unobservable Events," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 1(03), pages 373-392.
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    Cited by:

    1. Jaehun Joo & Azizbek Marakhimov, 2018. "Antecedents of customer participation in business ecosystems: evidence of customers’ psychological ownership in Facebook," Service Business, Springer;Pan-Pacific Business Association, vol. 12(1), pages 1-23, March.
    2. Tomohiko Sakao & Abhijna Neramballi, 2020. "A Product/Service System Design Schema: Application to Big Data Analytics," Sustainability, MDPI, vol. 12(8), pages 1-22, April.
    3. 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.
    4. Chiehyeon Lim & Paul P. Maglio, 2018. "Data-Driven Understanding of Smart Service Systems Through Text Mining," Service Science, INFORMS, vol. 10(2), pages 154-180, June.
    5. Salman Alfarisi & Yuya Mitake & Yusuke Tsutsui & Hanfei Wang & Yoshiki Shimomura, 2023. "Nurture: A Novel Approach to PSS-Rebound Effect Identification," Sustainability, MDPI, vol. 15(9), pages 1-25, April.
    6. 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.
    7. Min-Jun Kim & Chie-Hyeon Lim & Chang-Ho Lee & Kwang-Jae Kim & Yongsung Park & Seunghwan Choi, 2018. "Approach to service design based on customer behavior data: a case study on eco-driving service design using bus drivers’ behavior data," Service Business, Springer;Pan-Pacific Business Association, vol. 12(1), pages 203-227, March.
    8. Shiu-Li Huang & Ming-Yen Kuo, 2020. "Critical success factors in the sharing economy: a customer perspective," Service Business, Springer;Pan-Pacific Business Association, vol. 14(4), pages 553-576, December.
    9. Just, Julian, 2024. "Natural language processing for innovation search – Reviewing an emerging non-human innovation intermediary," Technovation, Elsevier, vol. 129(C).
    10. Choi, Jaewoong & Oh, Seunghyun & Yoon, Janghyeok & Lee, Jae-Min & Coh, Byoung-Youl, 2020. "Identification of time-evolving product opportunities via social media mining," Technological Forecasting and Social Change, Elsevier, vol. 156(C).

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