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

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  • 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
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    References listed on IDEAS

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    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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
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    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.

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