Designing Choice Sets for Stated Preference Methods: The Effects of Complexity on Choice Consistency

By J. Deshazo, G. Fermo. 2002

826 citations recorded by the source corpus.

Subfields: Economics and Econometrics, General Decision Sciences, Marketing

View Paper: https://www.semanticscholar.org/paper/a4d24370f8633e8c0632018b123719885faa8081

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Citations in the corpus

Contemporary Guidance for Stated Preference Studies (2017, background): “These often arise from individuals applying simplified decision rules to reduce the cognitive burden presented by a survey (Kahneman and Tversky 1979; Schoemaker 1982; Mazzotta and Opaluch 1995; DeShazo and Fermo 2002).”
Small-sample properties of tests for heteroscedasticity in the conditional logit model (2006, methodology): “Following DeShazo and Fermo (2002) and Hensher et al. (1999) an alternative to the conditional logit model which allows for unequal variances across individuals is given by: Pni = exp( nXni ) JX j=1 exp( nXnj ) (5) where n is a function of individual characteristics that in uence the magnitude of…”
Handling respondent uncertainty in Choice Experiments: Evaluating recoding approaches against explicit modelling of uncertainty (2009, background): “To uncover these, several studies have focused on the scale parameters dependence on variables like choice complexity, effort and fatigue (Bradley and Daly 1994; Swait and Adamowicz 2001; Hensher et al. 2001; DeShazo and Fermo 2002; Sælensminde 2001), as well as demographic variables of the responde”
Uncertainty and risk in wildland fire management: a review. (2011, background): “…with multiple, conflicting criteria, in turn limiting their ability to accurately articulate preferences (Ariely, 2009; Brown et al., 2008; Reiskamp et al., 2006; Braga and Starmer, 2005; Holmes and Boyle, 2005; Maguire and Albright, 2005; DeShazo and Fermo, 2002; Samuelson and Zeckhauser, 1988).”
German car buyers’ willingness to pay to reduce CO2 emissions (2012, neutral): “There is a growing literature addressing the effect of design dimensions on the consistency of stated choices (e.g., Hensher 2006; Caussade et al. 2005; DeShazo and Fermo 2002).”
Asymmetric preference formation in willingness to pay estimates in discrete choice models (2008, result): “Although we have used a specific type of SP experiment relating the SP alternatives of the experiment to respondent specific RP alternatives via pivoted designs, our findings are in line with those of other researchers using more conventional experiments, who found that differences in preference spa”
Design of Stated Preference Surveys: Is There More to Learn from Behavioral Economics? (2010, background): “Task complexity can potentially affect both the extent of inconsistent choices, the decision rules adopted by the respondents, and the welfare estimates (see, e.g., De Shazo and Fermo 2002; Swait and Adamowicz 2001).”
Energy Efficiency Investments in the Home: Swiss Homeowners and Expectations about Future Energy Prices (2013, background): “…alternatives in the choice task, the number of attributes whose levels differ across alternatives, and overall variation in the attribute levels; see DeShazo and Fermo, 2002), attribute non-attendance, fatigue v. learning effects, credibility failure, and position and precedent dependence (Day et…”
Allowing for intra-respondent variations in coefficients estimated on repeated choice data (2009, background): “For example, it is known that respondents do, over the course of a SC experiment, experience both learning and cognitive burden effects (e.g. Des- hazo and Fermo, 2002; Arentze et al., 2003).”
Augmenting short Cheap Talk scripts with a repeated Opt-Out Reminder in Choice Experiment surveys (2014, background): “Several authors have found evidence of choice complexity in CE leading to seemingly irrational behaviour (Bradley and Daly 1994; Mazzotta and Opaluch 1995; Swait and Adamowicz 2001; DeShazo and Fermo 2002; Caussade et al. 2005).”
Designs with a priori information for nonmarket valuation with choice experiments: A Monte Carlo study (2007, background): “DeShazo and Fermo [21] 4=9 2=7 — Factorial orthogonal Heteroskedastic 1800=2100 (JEEM) randomised MNL Sælensminde [60] 3=4 2 9 Fractional factorial Binary 2568 (ERE) orthogonal Logit Hanley et al.”
Dissecting the Random Component of Utility (2002, background): “For example, de Palma, et al. (1994) posit an alternative to standard rational choice that can be tested by analysis of the random component and DeShazo and Fermo (2001b) provide an empirical test of a rival to standard rational choice.”