Digitální knihovnaUPCE
 

Diverse group of smartphone users and their shopping activities

ČlánekOtevřený přístuppeer-reviewedpublished
Náhled

Datum publikování

2018

Vedoucí práce

Oponent

Název časopisu

Název svazku

Vydavatel

Univerzita Pardubice

Abstrakt

The analysis of customers’ purchasing activities, their preferences and future potential are the subject of interest of many experts in the field of marketing. Smartphones became the common devices used during purchasing process. By examining purchasing behavior of smartphone owners, the valuable insights useful for modeling new selling strategies could be mined. The main objective of this study is to analyze different behavioral patterns of smartphone users during the pre-purchase stage of the purchase process. To achieve these goal, we analyzed the data from Consumer Barometer containg data for 56 countries and 78,920 respondents. We created 3 new latent variables – factors - while reducing the number of variables (11) entering the cluster analysis by using factor analysis. Subsequently, using the cluster analysis and the method of k-medians, we created four clusters of users. Even though there are more active and less active clusters, the most popular activities involved getting store directions and checking where to buy a certain product. Users from European countries (represented by Cluster 1 and 2) use smartphones in the prepurchase process very little, showing conservative approach towards smartphones in these countries. On the other hand, users in Cluster 3 and 4 seem to be the most active smartphone users in terms of purchasing process.

Rozsah stran

p. 5 - 16

ISSN

1211-555X (Print)
1804-8048 (Online)

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Projekt

Zdrojový dokument

Scientific papers of the University of Pardubice. Series D, Faculty of Economics and Administration. 43/2018

Vydavatelská verze

Přístup k e-verzi

open access

Název akce

ISBN

Studijní obor

Studijní program

Signatura tištěné verze

Umístění tištěné verze

Přístup k tištěné verzi

Klíčová slova

smartphone user, mobile shopping, mobile-first, k-medians, cluster analysis

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