Estimating attributes importance for container shipping industry by closing the listening gap with maximum convergent validity. (July 2015)

• Record Type: Journal Article
• Authors: Chen, Kee-Kuo; Ho, Hui-Ping; Chang, Ching-Ter
• Is Part Of: Transportation research. Volume 79(2015)
• Page Start: 145
• Page End: 163
• Publication Date: 2015-07
• Subjects: Attribute importance -- Convergent validity -- Minimum cross entropy -- Prospect purchase intention -- Revealed-stated preferences; Logistics -- Periodicals; Transportation -- Periodicals; 388.011
• DOI: 10.1016/j.tre.2015.04.006
• Languages: English
• ISSNs: 1366-5545

Abstract

Highlights: A method which can combine two data sets with maximum convergent validity is verified. A model is proposed to estimate attributes importance to prospects purchase intention. The listening gap between customers and managers of container shipping firms is almost closed. Freight and discount, personal selling and word of mouth are the most important attributes. Abstract: This paper estimates the relationship of attributes importance (AI) to prospect purchase intention by closing the listening gap between customers and managers of container shipping companies. A proposition of minimum cross entropy is proposed to find a solution to the problem with maximum convergent validity, and this proposition is used to estimate AI, in which both opinions about AI of customers and managers of container shipping companies are included. Results indicate that price, discount, personal selling, and word of mouth, are the most important attributes to prospect purchase intention, within the industry. In addition, managerial implications are also discussed.