Title: Empirical online big data analysis shopping behaviour based on fsQCA approach

Authors: Chun-Hui Wu; Huan-Ming Chuang; Chien-Ku Lin; Chyuan-Yuh Lin

Addresses: Department of Information Management, National Formosa University, No. 64, Wunhua Rd., Huwei Township, Yunlin County 632, Taiwan ' Department of Information Management, National Yunlin University of Science and Technology, 123, University Road, Section 3, Douliou, Yunlin 64002, Taiwan ' Department of Information Management, National Yunlin University of Science and Technology, 123, University Road, Section 3, Douliou, Yunlin 64002, Taiwan ' Department of Information Management, National Yunlin University of Science and Technology, 123, University Road, Section 3, Douliou, Yunlin 64002, Taiwan

Abstract: Social media networks flourishing make electronic store (e-store) to become wider variety of multimedia services. In order to provide customers with more high service quality, we must understand the key factors of customer shopping behaviour that improve e-store performance by reference. In order to understand the impact of business relationship between the customer and the e-store, we use fuzzy set qualitative comparative analysis (fsQCA) method to analyse the framework of the study with empirical data and conclude three directions as below: 1) the results of fsQCA reveal that situations combining promising positive reliability, responsiveness, assurance, environment quality, delivery quality and outcome quality can lead to a higher level of customer satisfaction and affective commitment; 2) the results exhibit that customers are more willing to purchase again if they experience positive service satisfaction or highly affective commitment; 3) positive affective commitment supports customer advocacy intention.

Keywords: social media; e-store; multimedia services; service quality; fuzzy set qualitative comparative analysis; fsQCA.

DOI: 10.1504/IJASS.2017.088918

International Journal of Applied Systemic Studies, 2017 Vol.7 No.1/2/3, pp.174 - 188

Received: 10 Oct 2016
Accepted: 15 Jun 2017
Published online: 02 Jan 2018 *

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