Tools
Tools
Taylor, MJ, Kwasnica, V, Reilly, D and Ravindran, S (2019) Game theory modelling of retail marketing discount strategies. Marketing Intelligence and Planning, 37 (5). pp. 555-566. ISSN 0263-4503
|
Text
Game theory modelling of retail marketing discount strategies .pdf - Accepted Version Download (330kB) | Preview |
Abstract
Purpose: The use of game theory combined with Monte Carlo simulation modelling to support the analysis of different retail marketing strategies, in particular the use of payoff matrices for modelling the likely outcomes from different retail marketing strategies.
Design/methodology/approach: Theoretical research was utilised to develop a practical approach for applying game theory to retail marketing strategies via payoff matrices combined with Monte Carlo simulation modelling.
Findings: Game theory combined with Monte Carlo simulation modelling can provide a formal approach to understanding consumer decision making in a retail environment, which can support the development of retail marketing strategies.
Research limitations/implications: Game theory combined with Monte Carlo simulation modelling can support the modelling of the interaction between retail marketing actions and consumer responses in a practical formal probabilistic manner, which can inform marketing strategies used by retail companies in a practical manner.
Practical implications: Game theory combined with Monte Carlo simulation modelling can provide a formalised mechanism for examining how consumers may respond to different retail marketing strategies.
Originality/value: The originality of this research is the practical application of game theory to retail marketing, in particular the use of payoff matrices combined with Monte Carlo simulation modelling to examine likely consumer behaviour in response to different retail marketing approaches.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | 1505 Marketing |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Computer Science & Mathematics |
| Publisher: | Emerald |
| Date Deposited: | 07 Jan 2019 11:03 |
| Last Modified: | 04 Sep 2021 09:49 |
| DOI or ID number: | 10.1108/MIP-11-2018-0489 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/9880 |
 |
View Item |