Testing Validity of Probability-One Assumption in MS-Based Brand Choice Model
Kanghyun Yoon ()
Additional contact information
Kanghyun Yoon: University of Central Oklahoma
A chapter in Advances in National Brand and Private Label Marketing, 2025, pp 103-111 from Springer
Abstract:
Abstract The Mover-Stayer (MS) model, originally introduced by (Blumen et al. 1955), has served as a foundational statistical framework to achieve several research purposes in various academic disciplines. This study examines the validity of the Probability-One assumption embedded in the Mover-Stayer (MS) model and its impact on brand choice analysis. Probability-One assumption, which fixes the transition probability of stayers at zero, leads to biased parameter estimates by underestimating potential transitions and overfitting movers’ switching behaviors. By challenging this assumption, our findings highlight the need for a more flexible framework that better accounts for consumer heterogeneity and real-world purchasing dynamics. The results contribute to advancing MS-based brand choice models by improving their capacity to reflect actual consumer behavior.
Keywords: Mover-stayer model; Brand switching behavior; Probability-one assumption; MS-based brand choice model (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
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:prbchp:978-3-031-97133-4_12
Ordering information: This item can be ordered from
http://www.springer.com/9783031971334
DOI: 10.1007/978-3-031-97133-4_12
Access Statistics for this chapter
More chapters in Springer Proceedings in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().