Economic Models of Choice
Greg M. Allenby (),
Jaehwan Kim () and
Peter E. Rossi ()
Additional contact information
Greg M. Allenby: Ohio State University
Jaehwan Kim: Korea University Business School
Peter E. Rossi: UCLA
Chapter Chapter 7 in Handbook of Marketing Decision Models, 2017, pp 199-222 from Springer
Abstract:
Abstract This chapter provides an introduction to choice models based on the principle of direct utilityDirect utility maximization. Models of direct utility are characterized by specifications of the utility function and accompanying budget constraintBudget constraint that allows separation of what is gained (i.e., utility) from that which is given up in an exchange. Direct utility maximization rationalizes observed choice as arising from goal-oriented consumers who are resource constrained. Marketing data overwhelmingly reflects goal-oriented behavior on the part of consumers in the high rate of zero’s present in disaggregate data, indicating that most people choose to not purchase most products that are available. By developing alternative models of direct utilityDirect utility maximization, we hope to spur additional research on utility formation and a more in-depth understanding of optimal firm reaction to the demands and constraints of consumers.
Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (3)
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:isochp:978-3-319-56941-3_7
Ordering information: This item can be ordered from
http://www.springer.com/9783319569413
DOI: 10.1007/978-3-319-56941-3_7
Access Statistics for this chapter
More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().