2013
DOI: 10.5755/j01.ee.24.4.3118
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The Use of Conjoint and Cluster Analysis For Preference-Based Market Segmentation

Abstract: Market segmentation implies dividing the market into smaller segments that are homogenous inside, and heterogenous in relation to one another. Market segmentation is a part of strategic marketing, together with targeting and positioning, preceded by marketing research and followed by creating, implementing and controlling the marketing mix. As well as being an essential field of academic research, market segmentation proved to be a very useful concept for managers. The market segmentation concept dates back al… Show more

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Cited by 16 publications
(11 citation statements)
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“…their (dis)satisfaction determine the quality of services [7]. For making appropriate marketing decisions and improving the quality of services, passenger satisfaction has to be permanently studied [8][9].…”
Section: Introductionmentioning
confidence: 99%
“…their (dis)satisfaction determine the quality of services [7]. For making appropriate marketing decisions and improving the quality of services, passenger satisfaction has to be permanently studied [8][9].…”
Section: Introductionmentioning
confidence: 99%
“…Cluster analysis is a common data-grouping method that reveals data trends and characteristics. Ward's method is a hierarchical clustering method that classifies the whole data in a well-balanced manner, and is often employed in marketing analyses (Djokic et al, 2013). As shown in Figure 3 (left panel), the present analysis of customer preference similarity yielded three customer preference clusters; Cluster 1 (with 7 members), Cluster 2 (also with 7 members) and Cluster 3 (with 6 members).…”
Section: 2: Classification Of Customer Preference and Requirement Amentioning
confidence: 71%
“…Socio‐demographic factors have been also wildly applied in consumer segmentation which has been confirmed a key aspect in marketing (Shim & Bickle, ). Market segmentation can be conducted using conjoint analysis in combination with cluster analysis which is designed to classify groups of entities that share certain familiar characteristics, has been an important and most fundamental tool in academic consumer studies and also applied marketing (Djokic, Salai, Kovac‐Znidersic, Djokic, & Tomic, ; Punj & Stewart, ). Presuppositions are not necessary in cluster analysis, while it supplies ways to apply post hoc, or cluster‐based segments, and the core idea is to let the data speak for themselves for seeking consumer groups who share common trade‐offs, attitude, preference towards products (Green et al, ).…”
Section: Methodsmentioning
confidence: 99%