### Abstract

Within the context of a profit making firm, the job of a design engineer is to choose design parameters and product attributes that maximize the expected utility of profit. To do this effectively, the engineer needs to have an estimate of the demand for the product as a function of its price and its attributes. The firm may conduct a survey to elicit consumer preferences for the product at a given price and would like to update their belief about demand given the survey data. The purpose of this paper is to present a Bayesian methodology for demand estimation that meets this need. The estimation process begins with a prior probability distribution of demand at a given price. Using Bayesian analysis, we show how to update demand for the product given various pieces of information such as market analysis, polls and a variety of other methods. We also discuss situations where consumers can demand multiple units of the product at the given price.

Original language | English |
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Title of host publication | ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2012 |

Pages | 785-792 |

Number of pages | 8 |

Volume | 7 |

DOIs | |

Publication status | Published - 2012 |

Event | ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2012 - Chicago, IL, United States Duration: Aug 12 2012 → Aug 12 2012 |

### Other

Other | ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2012 |
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Country | United States |

City | Chicago, IL |

Period | 8/12/12 → 8/12/12 |

### Fingerprint

### ASJC Scopus subject areas

- Modelling and Simulation
- Mechanical Engineering
- Computer Science Applications
- Computer Graphics and Computer-Aided Design

### Cite this

*ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2012*(Vol. 7, pp. 785-792) https://doi.org/10.1115/DETC2012-70153

**Bayesian inference for the demand of engineering products.** / Abbas, Ali E.; Hazelrigg, George A.; Alkindi, Mahmood.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2012.*vol. 7, pp. 785-792, ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2012, Chicago, IL, United States, 8/12/12. https://doi.org/10.1115/DETC2012-70153

}

TY - GEN

T1 - Bayesian inference for the demand of engineering products

AU - Abbas, Ali E.

AU - Hazelrigg, George A.

AU - Alkindi, Mahmood

PY - 2012

Y1 - 2012

N2 - Within the context of a profit making firm, the job of a design engineer is to choose design parameters and product attributes that maximize the expected utility of profit. To do this effectively, the engineer needs to have an estimate of the demand for the product as a function of its price and its attributes. The firm may conduct a survey to elicit consumer preferences for the product at a given price and would like to update their belief about demand given the survey data. The purpose of this paper is to present a Bayesian methodology for demand estimation that meets this need. The estimation process begins with a prior probability distribution of demand at a given price. Using Bayesian analysis, we show how to update demand for the product given various pieces of information such as market analysis, polls and a variety of other methods. We also discuss situations where consumers can demand multiple units of the product at the given price.

AB - Within the context of a profit making firm, the job of a design engineer is to choose design parameters and product attributes that maximize the expected utility of profit. To do this effectively, the engineer needs to have an estimate of the demand for the product as a function of its price and its attributes. The firm may conduct a survey to elicit consumer preferences for the product at a given price and would like to update their belief about demand given the survey data. The purpose of this paper is to present a Bayesian methodology for demand estimation that meets this need. The estimation process begins with a prior probability distribution of demand at a given price. Using Bayesian analysis, we show how to update demand for the product given various pieces of information such as market analysis, polls and a variety of other methods. We also discuss situations where consumers can demand multiple units of the product at the given price.

UR - http://www.scopus.com/inward/record.url?scp=84884664684&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84884664684&partnerID=8YFLogxK

U2 - 10.1115/DETC2012-70153

DO - 10.1115/DETC2012-70153

M3 - Conference contribution

AN - SCOPUS:84884664684

SN - 9780791845066

VL - 7

SP - 785

EP - 792

BT - ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2012

ER -