EconPapers    
Economics at your fingertips  
 

Agent simulation-based ordinal optimisation for new product design

Hoyeop Lee, Jongsu Lim, Keeheon Lee and Chang Ouk Kim

Journal of the Operational Research Society, 2019, vol. 70, issue 3, 502-515

Abstract: A decision tool that can accurately predict the market diffusion of a new product can be helpful in the establishment of product design. This study simulates product diffusion through multi-agent simulation (MAS) and determines product specifications that can maximise future sales by adapting ordinal optimisation. MAS constructs a virtual market of agents (consumers) and predicts the sales volume by simulating the product selection process of individual agents. By interacting with the MAS, the ordinal optimisation rapidly determines the product specifications of maximum sales with few computations. An empirical experiment conducted on the Korean smartphone market yielded interesting results, i.e., it is desirable for companies with high brand values not to offer low-performance products but to make additional efforts to increase satisfaction with hardware specifications, while a high-end policy of product quality and a low-price sales strategy may be more beneficial for increasing sales volumes for companies with low brand values.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/01605682.2018.1447250 (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:tjorxx:v:70:y:2019:i:3:p:502-515

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjor20

DOI: 10.1080/01605682.2018.1447250

Access Statistics for this article

Journal of the Operational Research Society is currently edited by Tom Archibald

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

 
Page updated 2025-03-20
Handle: RePEc:taf:tjorxx:v:70:y:2019:i:3:p:502-515