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Electronic Commerce Research
Published in: Electronic Commerce Research 3/2018

04-11-2017

Recognition of business risks when purchasing goods on the Internet using GIS: experience from Slovakia

Authors: Pavol Kita, Zdenek Szczyrba, David Fiedor, Ales Letal

Published in: Electronic Commerce Research | Issue 3/2018

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Abstract

For operators of Internet shops and their investors on the one hand, and suppliers on the other hand, knowledge of the consumer market is becoming critical in terms of the risk of non-payment for purchased goods, as most small e-shops maintain their stocks according to current demand. The aim of this paper is to identify customers who come from different districts of Slovakia and display a certain type of consumer behavior regarding the risk connected with willingness to pay for goods purchased via the Internet. To solve this problem we used data from a specialized e-retailer and Geographic Information Systems (GIS) as a Decision Support System generator for constructing maps of consumers to investigate the operation of an e-shop. In the article, we used data from the years 2012–2015 concerning 489 buyers, including their addresses and other geographical data about the consumers and their purchases, and integrated them into the GIS environment. Subsequently, the data were analyzed and documented by means of GIS and maps of consumers were generated. The result of this study is to show that GIS can play a significant role in the decision-making process of e-shops in support of a manager’s experience. The geographical results were evaluated statistically in order to offer a better information capability.
previous article Marketing strategy of internet-banking service based on perceptions of service quality in Vietnam

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Footnotes
5
Considering the fact that there is no district in Slovakia with more than 85% of the population in rural municipalities, this type of rural district was not defined in the methodology.
 
6
The number of purchases was, as a result of repeated purchases by the same customers, replaced by the number of shoppers. In the original model with the independent variable of the number of purchases the repeated purchases of the same customers proved to be significant, which concealed the effect of socioeconomic variables on buying behavior.
 
7
The variable share of university graduates in the total population aged over 15 has been excluded from the resulting regression model since it does not increase the share of variability of the dependent variable explained by the model.
 
8
The coefficient of determination can be artificially increased by a higher number of variables that enter into the analysis. Considering the number of cases (79 districts of Slovakia), three independent variables seems to be an ideal number. Therefore, in this case, the adjusted coefficient of determination (Adjusted R Square) differs only slightly from the normal coefficient of determination; its value is 0.586.
 
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Metadata
Title
Recognition of business risks when purchasing goods on the Internet using GIS: experience from Slovakia
Authors
Pavol Kita
Zdenek Szczyrba
David Fiedor
Ales Letal
Publication date
04-11-2017
Publisher
Springer US
Published in
Electronic Commerce Research / Issue 3/2018
Print ISSN: 1389-5753
Electronic ISSN: 1572-9362
DOI
https://doi.org/10.1007/s10660-017-9276-5

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