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Customer decision-making styles as a tool for segmenting digital products market in Iran

Customer decision-making styles as a tool for segmenting digital products market in Iran The purpose of this paper is to define and develop digital products market segments in Tehran based on consumers’ buying decision-making styles (CDS) and testing applicability of Sproles and Kendall’s model [consumer style inventory (CSI)] for this steady growing market in Tehran and contributing to theories of market segmentation.Design/methodology/approachThis research used exploratory factor analysis (EFA) to explore and identify digital products shoppers CDS. In addition, to determine whether the selected items and factors loaded, measured the identified CDS correctly, confirmatory factor analysis (CFA) was used to substantiate the number of explored CDS. Then, cluster analysis was executed to pinpoint decision-making groups and demographic characteristics such as gender, marital status, age, education and digital shopping experience to profile the diagnosed clusters.FindingsFive CDS were distinguished for digital products customers (four former styles and one new one’s named “Premeditated buying”) through EFA and CFA analysis as a tool for segmenting; four clusters are, namely, “Best Seekers”, “Premeditators”, “Innovation Seekers”, and “Price Insensitive”.Practical implicationsIt will be beneficial to companies focussing on the Iranian digital market. This study identifies each cluster behaviour based on demographic data too.Originality/valueThis is the first study focussing on market segmentation using extracting digital products decision-making styles. As the new shopping style, “Premeditated buying”, has been explored from this analysis and due to the nature of digital products, this CDS has not been found in previous studies and is unique to Iranian digital products shoppers. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Islamic Marketing Emerald Publishing

Customer decision-making styles as a tool for segmenting digital products market in Iran

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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1759-0833
DOI
10.1108/jima-04-2017-0041
Publisher site
See Article on Publisher Site

Abstract

The purpose of this paper is to define and develop digital products market segments in Tehran based on consumers’ buying decision-making styles (CDS) and testing applicability of Sproles and Kendall’s model [consumer style inventory (CSI)] for this steady growing market in Tehran and contributing to theories of market segmentation.Design/methodology/approachThis research used exploratory factor analysis (EFA) to explore and identify digital products shoppers CDS. In addition, to determine whether the selected items and factors loaded, measured the identified CDS correctly, confirmatory factor analysis (CFA) was used to substantiate the number of explored CDS. Then, cluster analysis was executed to pinpoint decision-making groups and demographic characteristics such as gender, marital status, age, education and digital shopping experience to profile the diagnosed clusters.FindingsFive CDS were distinguished for digital products customers (four former styles and one new one’s named “Premeditated buying”) through EFA and CFA analysis as a tool for segmenting; four clusters are, namely, “Best Seekers”, “Premeditators”, “Innovation Seekers”, and “Price Insensitive”.Practical implicationsIt will be beneficial to companies focussing on the Iranian digital market. This study identifies each cluster behaviour based on demographic data too.Originality/valueThis is the first study focussing on market segmentation using extracting digital products decision-making styles. As the new shopping style, “Premeditated buying”, has been explored from this analysis and due to the nature of digital products, this CDS has not been found in previous studies and is unique to Iranian digital products shoppers.

Journal

Journal of Islamic MarketingEmerald Publishing

Published: Oct 15, 2018

Keywords: Decision making; Islamic market segmentation; CSI; Digital products

References