Consumer Intentions on Social Media: A fsQCA Analysis of Motivations

  • Patrick MikalefEmail author
  • Ilias O. Pappas
  • Michail Giannakos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9844)


With social media gaining rapidly in popularity, a large number of companies have initiated attempts to capitalize on the large user base present on such platforms. Yet, it still remains unclear how affordances that social media facilitate can influence consumer intentions to purchase and engage in word-of-mouth. This paper builds on the distinction between utilitarian and hedonic features, and empirically examines how these aspects present on social media platforms affect consumer behavior. Using survey data from 165 social media users we perform fuzzy set Qualitative Comparative Analyses (fsQCA) to extract patterns of factors that impact both purchase, and word-of-mouth intentions. The outcomes of the analyses demonstrate that realizing high purchase and word-of-mouth intentions can be achieved through multiple ways which also depend on gender and spending history. Practical and theoretical implications are discussed, particularly concerning how these findings can guide the design of successful social media outlets for commerce.


Online Shopping Qualitative Comparative Analysis Social Media Platform Personal Recommendation Product Selection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Open image in new window This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 704110.

This work was carried out during the tenure of an ERCIM “Alain Bensoussan” Fellowship Programme.


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Copyright information

© IFIP International Federation for Information Processing 2016

Authors and Affiliations

  • Patrick Mikalef
    • 1
    Email author
  • Ilias O. Pappas
    • 1
  • Michail Giannakos
    • 1
  1. 1.Department of Computer and Information ScienceNorwegian University of Science and TechnologyTrondheimNorway

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