Dynamic customer interdependence

Zhaoyong Zhang

Journal of the Academy of Marketing Science, 2019, vol. 47, issue 4, No 10, 723-746

Abstract: Abstract In managing today’s customer base, firms need to consider not only interactions with customers but also interactions among customers. Much like the interactions between customers and firms, the interactions among customers are dynamic in nature and thus create a dynamic structure of preference interdependencies between customers. This research proposes a Bayesian spatio-temporal model that simultaneously captures the effects of the interactions between customers and the firm, the static interdependence due to customers’ inherent similarities, and the dynamic interdependence arising from observed interactions among customers. The model is applied to a rich dataset of university alumni donation and event attendance spanning 27 years. The results yield significant static and dynamic interdependence among the group as well as synergistic effects between static and dynamic structures. This research demonstrates that not accounting for such interdependence, when such interdependence exists, would provide a biased view of firms' marketing effectiveness, yield inferior prediction of customer behaviors in group settings, and miss opportunities to develop group marketing strategies.

Keywords: CRM models; Bayesian models; Econometric models; Group marketing; Charitable giving; Customer dynamic behaviors (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s11747-019-00627-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:joamsc:v:47:y:2019:i:4:d:10.1007_s11747-019-00627-z

Ordering information: This journal article can be ordered from
https://www.springer ... gement/journal/11747

DOI: 10.1007/s11747-019-00627-z

Access Statistics for this article

Journal of the Academy of Marketing Science is currently edited by John Hulland, Anne Hoekman and Mark Houston

More articles in Journal of the Academy of Marketing Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().