The effects of improving coastal park attributes on the recreation demand—A case study in Dalian China

In this study, we use an estimation method of combining revealed preference (RP) with stated preference (SP) to measure the effects of park attribute improvement on the tourism demand and recreation benefits. Three categories of attributes are taken into account including nature, management, and economics. Five model estimations are made using RP, SP, and pooled data, respectively. The random effects negative binomial model is used with the SP data, and the mixed negative binomial model is used with the pooled data. The economic value of each specific park attribute improvement is measured by visitors’ marginal willingness to pay that directly addresses the issues of optimal attribute combinations beyond the observed range and scenarios. We survey a sample of the participants on the sites to obtain both revealed and stated behavior data for trips based on a management-relevant park attribute improvement and different park attribute combinations. Recreation demand models are used to derive total consumer surplus. The results indicate that the congestion reduction in the park has a relatively weak effect on the tourist demand, whereas trash reduction and improved seawater visibility appear to have the most important value to the tourists. Furthermore, the estimated consumer surplus at the present park conditions is about US$85 per recreation trip, and this consumer surplus will increase to US$101 as the quality of the park attribute improved. The overall park attribute improvement will increase recreational trip by 1.22 times per person per year from the present condition, and the net increase in consumer surplus reaches to US$205 per participant per year as a result of overall park attribute improvement.