Fuzzy inference suitability to determine the utilitarian quality of B2C websites

• Published in: Applied soft computing 2017-08, Vol.57, p.132-143
• Main Authors: Castro-Lopez, Adrian, Puente, Javier, Vazquez-Casielles, Rodolfo
• Format: Article
• Language: English
• ISSN: 1568-4946; 1872-9681
• DOI: 10.1016/j.asoc.2017.03.039

[Display omitted] •A model to evaluate the utilitarian quality in B2C websites is proposed.•The model is focused on the textile and fashion sector in Spain and it is empirically validated.•The B2C web evaluation by means of a fuzzy inference system shows two main advantages: a better management of non-linear behaviors and an easier way to collect and interpret the evaluation knowledge from experts or users through conditional linguistic rules −closer to the human reasoning mode-.•The model evaluation results can help companies identify their B2C websites strengths and weaknesses. The present paper proposes a new and intuitive model to evaluate the utilitarian e-service quality on textile and fashion B2C websites in Spain. The relevant variables to include into this model have been validated through an in-depth literature review and a reliability study based on an empirical investigation. Among the several methodologies used to develop the model, the paper proves that fuzzy inference systems (FIS) have numerous advantages. The following are particularly relevant: the ease to manage non-linear behaviours and the intuitive way of incorporating knowledge to evaluate B2C websites. This knowledge can stem both: from the expert know-how or from the evaluation of consumer satisfaction on these websites. The knowledge is made explicit through if-then rules which work with linguistic-type concepts −agreed upon by experts, closer to the human reasoning mode. Finally, the usefulness of the proposed model and the defined FIS suitability to evaluate the model are shown.