Are Fast Responses More Random? Testing the Effect of Response Time on Scale in an Online Choice Experiment

Scepticism over stated preference surveys conducted online revolves around the concerns over “professional respondents” who might rush through the questionnaire without sufficiently considering the information provided. To gain insight on the validity of this phenomenon and test the effect of response time on choice randomness, this study makes use of a recently conducted choice experiment survey on ecological and amenity effects of an offshore windfarm in the UK. The positive relationship between self-rated and inferred attribute attendance and response time is taken as evidence for a link between response time and cognitive effort. Subsequently, the generalised multinomial logit model is employed to test the effect of response time on scale, which indicates the weight of the deterministic relative to the error component in the random utility model. Results show that longer response time increases scale, i.e. decreases choice randomness. This positive scale effect of response time is further found to be non-linear and wear off at some point beyond which extreme response time decreases scale. While response time does not systematically affect welfare estimates, higher response time increases the precision of such estimates. These effects persist when self-reported choice certainty is controlled for. Implications of the results for online stated preference surveys and further research are discussed.

An Objective Framework to Test the Quality of Candidate Indicators of Good Environmental Status

Large efforts are on-going within the EU to prepare the Marine Strategy Framework Directive’s (MSFD) assessment of the environmental status of the European seas. This assessment will only be as good as the indicators chosen to monitor the eleven descriptors of good environmental status (GEnS). An objective and transparent framework to determine whether chosen indicators actually support the aims of this policy is, however, not yet in place. Such frameworks are needed to ensure that the limited resources available to this assessment optimize the likelihood of achieving GEnS within collaborating states. Here, we developed a hypothesis-based protocol to evaluate whether candidate indicators meet quality criteria explicit to the MSFD, which the assessment community aspires to. Eight quality criteria are distilled from existing initiatives, and a testing and scoring protocol for each of them is presented. We exemplify its application in three worked examples, covering indicators for three GEnS descriptors (1, 5 and 6), various habitat components (seaweeds, seagrasses, benthic macrofauna and plankton), and assessment regions (Danish, Lithuanian and UK waters). We argue that this framework provides a necessary, transparent and standardized structure to support the comparison of candidate indicators, and the decision-making process leading to indicator selection. Its application could help identify potential limitations in currently available candidate metrics and, in such cases, help focus the development of more adequate indicators. Use of such standardized approaches will facilitate the sharing of knowledge gained across the MSFD parties despite context-specificity across assessment regions, and support the evidence-based management of European seas.

An Objective Framework to Test the Quality of Candidate Indicators of Good Environmental Status

Large efforts are on-going within the EU to prepare the Marine Strategy Framework Directive’s (MSFD) assessment of the environmental status of the European seas. This assessment will only be as good as the indicators chosen to monitor the eleven descriptors of good environmental status (GEnS). An objective and transparent framework to determine whether chosen indicators actually support the aims of this policy is, however, not yet in place. Such frameworks are needed to ensure that the limited resources available to this assessment optimize the likelihood of achieving GEnS within collaborating states. Here, we developed a hypothesis-based protocol to evaluate whether candidate indicators meet quality criteria explicit to the MSFD, which the assessment community aspires to. Eight quality criteria are distilled from existing initiatives, and a testing and scoring protocol for each of them is presented. We exemplify its application in three worked examples, covering indicators for three GEnS descriptors (1, 5 and 6), various habitat components (seaweeds, seagrasses, benthic macrofauna and plankton), and assessment regions (Danish, Lithuanian and UK waters). We argue that this framework provides a necessary, transparent and standardized structure to support the comparison of candidate indicators, and the decision-making process leading to indicator selection. Its application could help identify potential limitations in currently available candidate metrics and, in such cases, help focus the development of more adequate indicators. Use of such standardized approaches will facilitate the sharing of knowledge gained across the MSFD parties despite context-specificity across assessment regions, and support the evidence-based management of European seas.