Discrete choice experiments with multiple price vectors for products sold in a wide price range.

Discrete choice experiments with multiple price vectors Experimental design Price preference heterogeneity Quality cue Willingness to pay Wine

Journal

MethodsX
ISSN: 2215-0161
Titre abrégé: MethodsX
Pays: Netherlands
ID NLM: 101639829

Informations de publication

Date de publication:
2019
Historique:
received: 06 03 2019
accepted: 24 07 2019
entrez: 21 8 2019
pubmed: 21 8 2019
medline: 21 8 2019
Statut: epublish

Résumé

The discrete choice experiment is a widely used methodology in consumer studies. However, applying this method to investigate the market of products sold in a wide price range could present issues as to the quality of the estimate of preferences. In fact, for this type of product, frequently consumers may have different behaviours when faced with different price levels. For example, some market segments may refrain from purchasing products below certain price thresholds, considering them of an unacceptable quality, while others choose only below certain prices. To work around this problem area, we propose a methodology in which each respondent declares his own price interval of reference and consequently participates in a choice experiment with a price vector coherent with his habits. In this manner, we are able to grasp and include in the estimations the heterogeneity of consumers with respect to price and thus obtain more accurate willingness to pay estimates. •The method describes a procedure to bypass issues related to identifying the price vector in discrete choice experiments that involve products sold in a wide price range.•We propose a discrete choice experiment with different price vectors for consumer segments with different price preferences.

Identifiants

pubmed: 31428567
doi: 10.1016/j.mex.2019.07.026
pii: S2215-0161(19)30201-8
pmc: PMC6695271
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1774-1778

Références

Health Econ. 2003 Jun;12(6):479-91
pubmed: 12759917

Auteurs

Caterina Contini (C)

University of Florence, Italy.

Fabio Boncinelli (F)

University of Florence, Italy.

Caterina Romano (C)

University of Florence, Italy.

Gabriele Scozzafava (G)

University of Florence, Italy.

Leonardo Casini (L)

University of Florence, Italy.

Classifications MeSH