IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i3p746-d135346.html
   My bibliography  Save this article

Analyzing Dynamic Change in Customer Requirements: An Approach Using Review-Based Kano Analysis

Author

Listed:
  • Hyejong Min

    (Department of Data Science, Seoul National University of Science and Technology (SeoulTech), Seoul 100744, Korea)

  • Junghwan Yun

    (Department of Data Science, Seoul National University of Science and Technology (SeoulTech), Seoul 100744, Korea)

  • Youngjung Geum

    (Department of Industrial & Information Systems Engineering, Seoul National University of Science and Technology (SeoulTech), Seoul 100744, Korea)

Abstract

To seek sustainable product development, understanding customer requirements is critically important where the life cycle of products or services is so fast, and continuous updates should be provided. In particular, how a customer feels for the specific function of the product/service and how their needs have changed is a critical question. According to Kano model dynamics, customer requirements for certain functions change over time, because customers firstly feel attracted to the new service characteristics but come to take them for granted over time. However, previous research on proving this theory has relied on customer surveys and interviews, which are highly time-consuming and expensive. In response, this study suggests customer review-based analysis to investigate Kano model dynamics, because customer reviews can be considered to be excellent sources for reflecting customer needs. This study firstly categorizes customer reviews into two types—positive reviews and supplementation-required reviews—and suggests a five-section framework according to the frequency of each review type. We define characteristics of each section from the perspective of the Kano model. Based on this framework, we analyze the dynamics of customer requirements in the online businesses, for which customer reviews are the main indicator of service quality.

Suggested Citation

  • Hyejong Min & Junghwan Yun & Youngjung Geum, 2018. "Analyzing Dynamic Change in Customer Requirements: An Approach Using Review-Based Kano Analysis," Sustainability, MDPI, vol. 10(3), pages 1-17, March.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:3:p:746-:d:135346
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/3/746/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/10/3/746/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jieun Kim & Yongtae Park & Chulhyun Kim & Hakyeon Lee, 2014. "Mobile application service networks: Apple’s App Store," Service Business, Springer;Pan-Pacific Business Association, vol. 8(1), pages 1-27, March.
    2. Huiskonen, Janne & Pirttila, Timo, 1998. "Sharpening logistics customer service strategy planning by applying Kano's quality element classification," International Journal of Production Economics, Elsevier, vol. 56(1), pages 253-260, September.
    3. Bomi Song & Changyong Lee & Byungun Yoon & Yongtae Park, 2016. "Diagnosing service quality using customer reviews: an index approach based on sentiment and gap analyses," Service Business, Springer;Pan-Pacific Business Association, vol. 10(4), pages 775-798, December.
    4. Flie[ss], Sabine & Kleinaltenkamp, Michael, 2004. "Blueprinting the service company: Managing service processes efficiently," Journal of Business Research, Elsevier, vol. 57(4), pages 392-404, April.
    5. Yubo Chen & Jinhong Xie, 2008. "Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix," Management Science, INFORMS, vol. 54(3), pages 477-491, March.
    6. Joo, Young-Hyuck & Kim, Yunsik & Yang, Suk-Joon, 2011. "Valuing customers for social network services," Journal of Business Research, Elsevier, vol. 64(11), pages 1239-1244.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xuan Gong & Yunchan Zhu & Rizwan Ali & Ruijin Guo, 2019. "Capturing Associations and Sustainable Competitiveness of Brands from Social Tags," Sustainability, MDPI, vol. 11(6), pages 1-20, March.
    2. Elina Dace & Agnis Stibe & Lelde Timma, 2020. "A holistic approach to manage environmental quality by using the Kano model and social cognitive theory," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 27(2), pages 430-443, March.
    3. Lee, Ching-Hung & Li, Li & Li, Fan & Chen, Chun-Hsien, 2022. "Requirement-driven evolution and strategy-enabled service design for new customized quick-response product order fulfillment process," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    4. Junegak Joung & Kiwook Jung & Sanghyun Ko & Kwangsoo Kim, 2018. "Customer Complaints Analysis Using Text Mining and Outcome-Driven Innovation Method for Market-Oriented Product Development," Sustainability, MDPI, vol. 11(1), pages 1-14, December.
    5. Chi-Hung Lo, 2021. "Application of Refined Kano’s Model to Shoe Production and Consumer Satisfaction Assessment," Sustainability, MDPI, vol. 13(5), pages 1-22, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Youngjung Geum & Moon-Soo Kim & Sungjoo Lee, 2017. "Service Technology: Definition and Characteristics Based on a Patent Database," Service Science, INFORMS, vol. 9(2), pages 147-166, June.
    2. Yucheng Zhang & Zhiling Wang & Lin Xiao & Lijun Wang & Pei Huang, 2023. "Discovering the evolution of online reviews: A bibliometric review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-22, December.
    3. Joe Cox & Daniel Kaimann, 2013. "The Signaling Effect of Critics - Evidence from a Market for Experience Goods," Working Papers CIE 68, Paderborn University, CIE Center for International Economics.
    4. Suwelack, Thomas & Hogreve, Jens & Hoyer, Wayne D., 2011. "Understanding Money-Back Guarantees: Cognitive, Affective, and Behavioral Outcomes," Journal of Retailing, Elsevier, vol. 87(4), pages 462-478.
    5. Liuan Wang & Lu (Lucy) Yan & Tongxin Zhou & Xitong Guo & Gregory R. Heim, 2020. "Understanding Physicians’ Online-Offline Behavior Dynamics: An Empirical Study," Information Systems Research, INFORMS, vol. 31(2), pages 537-555, June.
    6. Xiaolun Wang & Xinlin Yao, 2020. "Fueling Pro-Environmental Behaviors with Gamification Design: Identifying Key Elements in Ant Forest with the Kano Model," Sustainability, MDPI, vol. 12(6), pages 1-17, March.
    7. M. Narciso, 2022. "The Unreliability of Online Review Mechanisms," Journal of Consumer Policy, Springer, vol. 45(3), pages 349-368, September.
    8. Yuanfang Lin & Amit Pazgal, 2016. "Hide Supremacy or Admit Inferiority—Market Entry Strategies in Response to Consumer Informational Needs," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 3(2), pages 94-103, June.
    9. Wu, Xingli & Liao, Huchang, 2021. "Modeling personalized cognition of customers in online shopping," Omega, Elsevier, vol. 104(C).
    10. Reinhold Decker, 2014. "Real-Time Analysis of Online Product Reviews by Means of Multi-Layer Feed-Forward Neural Networks," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 4(11), pages 60-70, November.
    11. Tingting Song & Jinghua Huang & Yong Tan & Yifan Yu, 2019. "Using User- and Marketer-Generated Content for Box Office Revenue Prediction: Differences Between Microblogging and Third-Party Platforms," Service Science, INFORMS, vol. 30(1), pages 191-203, March.
    12. Jiacong Wu & Yu Wang & Ru Zhang & Jing Cai, 2018. "An Approach to Discovering Product/Service Improvement Priorities: Using Dynamic Importance-Performance Analysis," Sustainability, MDPI, vol. 10(10), pages 1-26, October.
    13. Khim-Yong Goh & Cheng-Suang Heng & Zhijie Lin, 2013. "Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content," Information Systems Research, INFORMS, vol. 24(1), pages 88-107, March.
    14. Minnema, Alec & Bijmolt, Tammo H.A. & Gensler, Sonja & Wiesel, Thorsten, 2016. "To Keep or Not to Keep: Effects of Online Customer Reviews on Product Returns," Journal of Retailing, Elsevier, vol. 92(3), pages 253-267.
    15. Giovanni Bernardo & Massimo Ruberti & Roberto Verona, 2022. "Image is everything! Professional football players' visibility and wages: evidence from the Italian Serie A," Applied Economics, Taylor & Francis Journals, vol. 54(5), pages 595-614, January.
    16. Vimi Jham, 2023. "Filli Café: Experience Tea and Talk," Asian Journal of Management Cases, , vol. 20(1), pages 47-58, March.
    17. Baabdullah, Abdullah M. & Alalwan, Ali Abdallah & Algharabat, Raed S. & Metri, Bhimaraya & Rana, Nripendra P., 2022. "Virtual agents and flow experience: An empirical examination of AI-powered chatbots," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    18. Caldieraro, Fabio & Cunha, Marcus, 2022. "Consumers’ response to weak unique selling propositions: Implications for optimal product recommendation strategy," International Journal of Research in Marketing, Elsevier, vol. 39(3), pages 724-744.
    19. Sungsik Park & Woochoel Shin & Jinhong Xie, 2021. "The Fateful First Consumer Review," Marketing Science, INFORMS, vol. 40(3), pages 481-507, May.
    20. Yabing Jiang & Hong Guo, 2012. "Design of Consumer Review Systems and Product Pricing," Working Papers 12-10, NET Institute.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:10:y:2018:i:3:p:746-:d:135346. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.