Does attribute order influence attribute-information processing in discrete choice experiments?

被引:7
|
作者
Logar, Ivana [1 ]
Brouwer, Roy [1 ,2 ,3 ]
Campbell, Danny [4 ]
机构
[1] Swiss Fed Inst Aquat Sci & Technol, Eawag, Uberlandstr 133, CH-8600 Dubendorf, Switzerland
[2] Univ Waterloo, Dept Econ, 200 Univ Ave West, Waterloo, ON N2L 3G, Canada
[3] Univ Waterloo, Water Inst, 200 Univ Ave West, Waterloo, ON N2L 3G, Canada
[4] Univ Stirling, Stirling Management Sch, Econ Div, Stirling FK9 4LA, Scotland
关键词
Ordering effects; Information processing; Attribute non-attendance; Discrete choice experiment; Stated preferences; Convergent validity; WILLINGNESS-TO-PAY; NON-ATTENDANCE; CONTINGENT VALUATION; EYE-TRACKING; PREFERENCE HETEROGENEITY; IMPACT; BIAS; MODEL; BRAND;
D O I
10.1016/j.reseneeco.2020.101164
中图分类号
F [经济];
学科分类号
02 ;
摘要
The existing empirical evidence shows that both contingent valuation and discrete choice experiment (DCE) methods are susceptible to various ordering effects. However, very few studies have analysed attribute-ordering effects in DCEs, and no study has investigated their potential influence on information-processing strategies, such as attribute non-attendance (ANA). This paper tests for attribute-ordering effects and examines whether the order of attributes describing the alternatives affects respondents' propensity to attend to or ignore an attribute. A split-sample approach is used, where one sample received a DCE version in which the positions of the first and last non-monetary attributes are switched across the sequence of choice tasks compared with the other sample. The results show that attribute order does not affect welfare estimates in a significant way under the standard assumption of full attribute attendance, thus rejecting the notion of procedural bias. However, the welfare estimates for the attributes whose order was reversed and the share of respondents who ignored them differ significantly between the two attribute-ordering treatments once ANA behaviour is accounted for in the estimated choice models. These results highlight the important role of information-processing strategies in the design and evaluation of DCEs. (C) 2020 Elsevier B.V. All rights reserved.
引用
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页数:21
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