The Price of Coastal Erosion and Flood Risk: A Hedonic Pricing Approach

Accelerated coastal erosion and elevated risks of flooding due to global warming put enormous burden on the ecosystems and economic health of coastal communities. Optimal policies to lessen these negative impacts require an estimation of their costs and benefits. The aim of this paper is to calculate the costs of beach erosion and flood risk through the valuation of property prices in Hilton Head Island, a barrier island located in South Carolina, USA. Spatial lag hedonic pricing was introduced in order to account for spatial autocorrelation in the dataset. The results show that properties that are located within the zone of high, or very high, flood risk experience a 15.6% reduction in value. The implicit price of being located close to an eroded beach is approximately 26% of the price of an oceanfront property. However, this negative impact on property value diminishes with distance from the shoreline.

Amateur innkeepers utilization of minimum length stay restrictions

Purpose The purpose of this paper is to determine how much the lodging shared economy (LSE) utilizes minimum length of stay (MLOS) controls to maximize revenue and reduce housekeeping expense, since cleaning between guest visits represents a substantial variable cost for each guest’s stay. Hosts in the LSE are becoming increasingly perceptive in maximizing revenues. Design/methodology/approach Daily data for one year were collected for Vacation Rental by Owner properties in Hilton Head Island, SC and Orlando, FL. The collected data include daily vacancies for two different lengths of stay. Linear regression was used to explore the relationship between relative demand and vacancy length of stay differences. Findings During high-demand periods, there were few differences between the availability of short-term and longer-term reservation vacancies, which indicated hosts were not encouraging guests to stay longer during each visit. These results reveal differences in vacancies for three-night vs six-night reservations. A host can generate more revenue and decrease expenses by maximizing booked nights per visit. Research limitations/implications Due to confidentiality issues, this study does not capture vacation bookings but instead captures vacancies. In addition, Average Daily Rate was not utilized in this study. Practical implications LSE hosts can maximize revenues using MLOS controls. Minimizing housekeeping costs boosts a host’s profitability. Originality/value Although this research has been conducted for hotel MLOS, there is a gap in the literature regarding LSE hosts’ use of MLOS.