A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Validating Citizens’ Preferences for Restoring Urban Riverscape: Discrete Choice Experiment versus Analytical Hierarchy Process
The discrete choice experiment (DCE) has been widely employed to examine public preferences for changes in environmental/social welfare brought about by various policy and development proposals so as to solicit social efforts and engage civic communities to collaboratively produce sustainable societies. If DCE estimates are to inform relevant policies and decisions, it is crucial that valid responses be collected via DCE surveys. This paper examines the convergent validity of individual-level preferences for restoring an urban riverscape in Guangzhou (south China) by comparing the consistency of respondents’ stated purchasing preferences (utility) derived from the DCE approach and their theoretical stated preferences (importance) obtained from the analytic hierarchy process (AHP). Our econometric analysis of a data set, which is composed of 462 responses from an online questionnaire survey, reveals that DCE and AHP could generate similar utility-importance rankings at the group level, yet distinct discrepancies exist at the individual level. A novel finite mixture model is then recruited to explore the association of individual respondents’ utility estimate (derived from DCE) and importance weight (derived from AHP) for every attribute pertaining to the proposed river restoration, which identifies three subgroups (components) of respondents exhibiting different patterns of convergence/nonconvergence and preference heterogeneity. The AHP importance weights for respondents belonging to Component 1 (20%) and Component 2 (42%) have a statistically significant explanatory power for DCE utility estimates, suggesting that the majority of respondents provided valid responses. The respondents of Component 3 (38%) manifest a statistically insignificant relationship, showing invalid responses. Censoring this group of respondents from DCE modeling could deflate the estimates of average willingness to pay for restoring the urban riverscape and change the degree of preference heterogeneity. This pioneer individual-level validity examination of DCE sheds new light on how to combine AHP with DCE in order to derive reliable information to support decision-making.
Validating Citizens’ Preferences for Restoring Urban Riverscape: Discrete Choice Experiment versus Analytical Hierarchy Process
The discrete choice experiment (DCE) has been widely employed to examine public preferences for changes in environmental/social welfare brought about by various policy and development proposals so as to solicit social efforts and engage civic communities to collaboratively produce sustainable societies. If DCE estimates are to inform relevant policies and decisions, it is crucial that valid responses be collected via DCE surveys. This paper examines the convergent validity of individual-level preferences for restoring an urban riverscape in Guangzhou (south China) by comparing the consistency of respondents’ stated purchasing preferences (utility) derived from the DCE approach and their theoretical stated preferences (importance) obtained from the analytic hierarchy process (AHP). Our econometric analysis of a data set, which is composed of 462 responses from an online questionnaire survey, reveals that DCE and AHP could generate similar utility-importance rankings at the group level, yet distinct discrepancies exist at the individual level. A novel finite mixture model is then recruited to explore the association of individual respondents’ utility estimate (derived from DCE) and importance weight (derived from AHP) for every attribute pertaining to the proposed river restoration, which identifies three subgroups (components) of respondents exhibiting different patterns of convergence/nonconvergence and preference heterogeneity. The AHP importance weights for respondents belonging to Component 1 (20%) and Component 2 (42%) have a statistically significant explanatory power for DCE utility estimates, suggesting that the majority of respondents provided valid responses. The respondents of Component 3 (38%) manifest a statistically insignificant relationship, showing invalid responses. Censoring this group of respondents from DCE modeling could deflate the estimates of average willingness to pay for restoring the urban riverscape and change the degree of preference heterogeneity. This pioneer individual-level validity examination of DCE sheds new light on how to combine AHP with DCE in order to derive reliable information to support decision-making.
Validating Citizens’ Preferences for Restoring Urban Riverscape: Discrete Choice Experiment versus Analytical Hierarchy Process
Ting Cho, Frankie Hin (author) / Chen, Wendy Y. (author) / Hua, Junyi (author)
2021-04-21
Article (Journal)
Electronic Resource
Unknown
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