Segmenting Freight Forwarders in Turkey

Authors : Gökçay BALCI, Onur Hüseyin DOĞU

Pages : 1-8

View : 34 | Download : 19

Publication Date : 2020-06-25

Article Type : Research Paper

Abstract :Container lines have been facing tough market conditions in recent years. Although the market has become more concentrated, the competition among container lines keeps its pace. In such a competitive and challenging environment, container lines need to better understand their customers’ needs and wants to achieve customer retention. Freight forwarders are major customers of container lines. However, most of the studies in container shipping literature focused on shippers when studying customer selection or segmentation in container shipping. Therefore, it is crucial to reveal container line selection criteria of freight forwarders. However, the expectations of customers are also heterogeneous and specific needs of different groups of customers must be identified for a more effective marketing offering. Accordingly, the purpose of this study was twofold. First, this paper aimed to investigate selection criteria of freight forwarders when choosing a container line. Second, the study aimed to classify freight forwarders based on their container line selection criteria. This paper conducted a survey study on freight forwarders in Turkey. Exploratory factor analysis and cluster analysis were carried out. According to the results, freight forwarders consider that cost and availability of shipment are the most important factors while the information technology factor is the lowest important one. The results of exploratory factor analysis revealed a total of 5 constructs that explain container line selection criteria of freight forwarders in Turkey. The cluster analysis, based on factor scores of each respondent, produced two clusters, which are Service-Focused segment and Cost-Focused Segment. Significant differences are found between the two segments.
Keywords : Shipping, container line, freight forwarders, segmentation, factor analysis, cluster analysis

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