Formulation of A Sale Price Prediction Model Based on Fuzzy Regression Analysis
Michihiro Amagasa ()
Additional contact information
Michihiro Amagasa: Hokkai-Gakuen University
A chapter in Operations Research Proceedings 2011, 2012, pp 567-572 from Springer
Abstract:
Abstract It is indispensable for companies to take some marketing strategy to predict and analyze the sale price met to customer satisfaction. In sale price prediction model, human factors are included in the elements composing the model, and it is getting more difficult to define and describe entire systems precisely. Therefore in case we obtain data from such a model, the data are accompanied by human subjective and experiential uncertainty. In this paper, we develop a theoretical formulation of sale price prediction model based on fuzzy regression with fuzzy input-output data (SPP-model). The solutions of SPP-model is found by solving two LP problems, both Min- and Max-problems, and each of them indicates upper and lower bounds of possibility for solutions (prices).
Keywords: Fuzzy Number; Customer Satisfaction; Linear Regression Model; Marketing Strategy; Fuzzy Data (search for similar items in EconPapers)
Date: 2012
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:oprchp:978-3-642-29210-1_90
Ordering information: This item can be ordered from
http://www.springer.com/9783642292101
DOI: 10.1007/978-3-642-29210-1_90
Access Statistics for this chapter
More chapters in Operations Research Proceedings from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().