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A novel approach to regression analysis for the classification of quality attributes in the Kano model: an empirical test in the food and beverage industry

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  • Chen, Li-Fei

Abstract

Since its introduction in the 1980s, Kano's two-dimensional model has become one of the most popular models with which to evaluate quality, finding a place in a wide range of industries. For decades, various approaches to regression analysis have been applied to explore asymmetric and non-linear relationships in the Kano model. Although a number of authors have questioned the use of these regression methods, there has been a lack of validity testing to evaluate their convergence with the results of the Kano questionnaire in classifying quality attributes. This study proposes a novel approach to regression analysis for the classification of quality attributes, including must-be, one-dimensional, attractive, and indifferent categories, as well as mixed-class distribution. Using popular tools and techniques for the measurement of customer satisfaction, the proposed approach is capable of simplifying the process of collecting data making it far easier to implement than the list of functional and dysfunctional questions initiated by Kano. An empirical study of a food and beverage chain showed that the proposed approach is capable of returning acceptable classification results, compared to the Kano questionnaire. A validity test indicated that the proposed approach significantly outperformed dummy variable regression and the moderated regression. In conclusion, the proposed approach provides a more practical implementation, while maintaining classification power on par with the Kano questionnaire.

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  • Chen, Li-Fei, 2012. "A novel approach to regression analysis for the classification of quality attributes in the Kano model: an empirical test in the food and beverage industry," Omega, Elsevier, vol. 40(5), pages 651-659.
  • Handle: RePEc:eee:jomega:v:40:y:2012:i:5:p:651-659
    DOI: 10.1016/j.omega.2011.12.004
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    References listed on IDEAS

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    2. Zhang, Min & Sun, Lin & Wang, G. Alan & Li, Yuzhuo & He, Shuguang, 2022. "Using neutral sentiment reviews to improve customer requirement identification and product design strategies," International Journal of Production Economics, Elsevier, vol. 254(C).
    3. Hsiao, Yu-Hsiang & Chen, Li-Fei & Chang, Chao-Chin & Chiu, Fu-Hsuan, 2016. "Configurational path to customer satisfaction and stickiness for a restaurant chain using fuzzy set qualitative comparative analysis," Journal of Business Research, Elsevier, vol. 69(8), pages 2939-2949.
    4. Damjan Vavpotič & Marko Robnik-Šikonja & Tomaž Hovelja, 2020. "Exploring the Relations Between Net Benefits of IT Projects and CIOs’ Perception of Quality of Software Development Disciplines," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 62(4), pages 347-360, August.
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    6. Ferreira, D.C. & Marques, R.C. & Nunes, A.M. & Figueira, J.R., 2018. "Patients’ satisfaction: The medical appointments valence in Portuguese public hospitals," Omega, Elsevier, vol. 80(C), pages 58-76.
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    8. Chen, Li-Fei, 2014. "A novel framework for customer-driven service strategies: A case study of a restaurant chain," Tourism Management, Elsevier, vol. 41(C), pages 119-128.
    9. Sang-Gun Lee & Chang-Gyu Yang & Sin-Bok Lee & Jae-Beom Lee, 2015. "A study on the antecedents and consequences of satisfaction and dissatisfaction in web portal usage," Service Business, Springer;Pan-Pacific Business Association, vol. 9(3), pages 567-586, September.
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