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Investigating the non-linear effects of e-service quality dimensions on customer satisfaction

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  • Finn, Adam

Abstract

The literature on service quality initially focused on identifying the service attributes that drive overall measures of customer satisfaction. More recently, the assumption that attribute-level performance is linearly related to customer satisfaction has been challenged. Inspired by Kano’s work on product quality, service researchers have used questionable methods to classify service attributes as attractive, one-dimensional, or a must-be, based on the observed shape of their satisfaction response functions. Valid assessment of the shape of satisfaction response functions for services requires crossed service by respondent ratings data to control for differences in respondent’s scale use in service assessment. Application of a recommended approach identifies download speed as a must-be performance dimension that interacts negatively with site functionality as the only non-linearity for online retailers. Currently used methods produce quite different results.

Suggested Citation

  • Finn, Adam, 2011. "Investigating the non-linear effects of e-service quality dimensions on customer satisfaction," Journal of Retailing and Consumer Services, Elsevier, vol. 18(1), pages 27-37.
  • Handle: RePEc:eee:joreco:v:18:y:2011:i:1:p:27-37
    DOI: 10.1016/j.jretconser.2010.09.002
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Joachim Büschken & Thomas Otter & Greg M. Allenby, 2013. "The Dimensionality of Customer Satisfaction Survey Responses and Implications for Driver Analysis," Marketing Science, INFORMS, vol. 32(4), pages 533-553, July.
    2. Ziyuan Tang & Hasan Dinçer, 2019. "Selecting the House-of-Quality-Based Energy Investment Policies for the Sustainable Emerging Economies," Sustainability, MDPI, Open Access Journal, vol. 11(13), pages 1-22, June.
    3. Betancourt, Roger R. & Chocarro, Raquel & Cortiñas, Monica & Elorz, Margarita & Mugica, Jose Miguel, 2017. "Private Sales Clubs: A 21st Century Distribution Channel," Journal of Interactive Marketing, Elsevier, vol. 37(C), pages 44-56.
    4. Nikhashemi, S.R. & Jebarajakirthy, Charles & Nusair, Khaldoon, 2019. "Uncovering the roles of retail brand experience and brand love in the apparel industry: Non-linear structural equation modelling approach," Journal of Retailing and Consumer Services, Elsevier, vol. 48(C), pages 122-135.
    5. Suryandari, Retno Tanding & Paswan, Audhesh K., 2014. "Online customer service and retail type-product congruence," Journal of Retailing and Consumer Services, Elsevier, vol. 21(1), pages 69-76.
    6. Gao, Yanan & Rasouli, Soora & Timmermans, Harry & Wang, Yuanqing, 2018. "Trip stage satisfaction of public transport users: A reference-based model incorporating trip attributes, perceived service quality, psychological disposition and difference tolerance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 759-775.
    7. Tontini, Gerson, 2016. "Identifying opportunities for improvement in online shopping sites," Journal of Retailing and Consumer Services, Elsevier, vol. 31(C), pages 228-238.
    8. Auh, Seigyoung & Menguc, Bulent & Fisher, Michelle & Haddad, Abeer, 2011. "The perceived autonomy–perceived service climate relationship: The contingency effect of store-level tenure diversity," Journal of Retailing and Consumer Services, Elsevier, vol. 18(6), pages 509-520.

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