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Comparing Serial, and Choice Task Stated and Inferred Attribute Non-Attendance Methods in Food Choice Experiments

Caputo, V. and van Loo, E. and Scarpa, R. and Nayga Jr., R.M. and Verbeke, W. (2018) 'Comparing Serial, and Choice Task Stated and Inferred Attribute Non-Attendance Methods in Food Choice Experiments.', Journal of agricultural economics., 69 (1). pp. 35-57.

Abstract

A number of choice experiment (CE) studies have shown that survey respondents employ heuristics such as attribute non-attendance (ANA) while evaluating food products. This paper addresses a set of related methodological questions using empirical consumer data from a CE on poultry meat with sustainability labels. First, it assesses whether there are differences in terms of marginal willingness to pay estimates between the two most common ways of collecting stated ANA (serial and choice task level). Second, it validates the self-reported ANA behaviour across both approaches. Third, it explores the concordance of stated methods with that of the inferred method. Results show that WTP estimates from serial-level data differ from those from choice task-level data. Also, self-reported measures on choice task ANA are found to be more congruent with model estimates than those for serial ANA, as well as with inferred ANA.

Item Type:Article
Full text:(AM) Accepted Manuscript
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Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1111/1477-9552.12246
Publisher statement:This is the accepted version of the following article: Caputo, V., Van Loo, E. J., Scarpa, R., Nayga, R. M. and Verbeke, W. (2017), Comparing Serial, and Choice Task Stated and Inferred Attribute Non-Attendance Methods in Food Choice Experiments. Journal of Agricultural Economics, which has been published in final form at https://doi.org/10.1111/1477-9552.12246. This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
Date accepted:29 May 2017
Date deposited:30 October 2017
Date of first online publication:20 October 2017
Date first made open access:20 October 2018

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