Summary: | Regarding the growing population and escalated development on the coasts, the environmental policymakers often face the dilemma of exploiting or protecting marine and coastal ecosystem services (ES). Therefore, the non-market valuation has become an essential instrument for supporting policymakers in eliciting preferences and welfare estimates regarding various ES, which further feed into the cost-benefit analyses (CBA). Among various non-market valuation techniques, the discrete choice experiment (DCE) methodology has gained ground in recent years for its advantages for capturing several trade- offs across multiple policy scenario alternatives and attributes. This thesis examines methodological issues regarding DCE applications on marine and coastal ES valuation and the further utilization of obtained non-market values in bio-economic models. Across three research papers utilizing DCE data collected in Arctic Norway, the results present implications for non-market valuation research and policymakers. The first paper studies the impact of including a socio-economic attribute in environmental policy DCE studies on the attendance paid to the other attributes. We utilize split sample DCE data to elicit preferences regarding coastal development on the Arctic coast, where we present an additional socio-economic attribute indicating the number of jobs created in the region in one version. The analysis suggests that a socio-economic attribute does not significantly alter the attention dedicated to other attributes. However, the obtained willingness-to-pay (WTP) measures significantly fluctuate across two samples, which can have important implications for the subsequent CBA. The second paper focuses on choice architecture interventions in DCE design. The study employs a three-way split sample for studying value activation through environmental and socio-economic signposts. Employing the case of coastal cod regulations and the controversial expansion of fishing tourism in Arctic Norway, the base DCE involves the ...
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