Discovering customer value for marketing systems: an empirical case study

Wen-Yu Chiang

International Journal of Production Research, 2017, vol. 55, issue 17, 5157-5167

Abstract: Data mining technologies have been employed in a variety of business managements for discovering useful commercial knowledge or marketing model for many years. Hence, the major marketing issue for airlines is to identify and analyse valuable air travellers recently, so that airlines can attract them for enhancing the profits and growth rates. However, growth rates are always an important issue for airline industries. An empirical case of air travellers’ markets in Taiwan is implemented in this research. This research proposes a model (FSLC model, RFM model based) via the data mining technologies to discover valuable travellers for airlines. This study partitions the market of air travellers in Taiwan, and the paper generates useful association rules to find an optimised target market for dynamic marketing or CRM systems. Nevertheless, the results of this research can be applied on marketing or CRM systems of the airline industry for identifying valuable travellers. Finally, the purpose of this research is to find high-value markets for marketing or CRM systems of airlines in Taiwan, and the framework can be applied to other industries as well.

Date: 2017
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2016.1231429 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:55:y:2017:i:17:p:5157-5167

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2016.1231429

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().