Assessing the economic impact of tourist attractions typically adopts a demand-side economic approach frequently based on visitor surveys that ask, for example, about visitors' on-site spending and the nature of their visiting modalities. This approach has several limitations, particularly that it is not based on causal analysis and that the results of surveys may be biased. This study proposes an integrated framework combining causal inference and demand-side economic analysis. As a case study, the impact of the Sensoria experience museum in Holzminden, Germany (opened in September 2024) on tourism demand (monthly overnight stays) is examined. Two difference-in-differences (DiD) approaches are employed to quantify the number of additional overnight stays in the treatment city: a conventional DiD model using a control group and a DiD model using a synthetic control unit (SCU). The results are converted into industry-specific expenditures, from which the direct and indirect effects of Sensoria are determined. The results are mixed: the DiD model detects a significantly positive impact in the first year of operation of the new tourist attraction, whereas the SCU model shows a positive but insignificant treatment effect. The significant DiD estimate corresponds to 4,995 additional overnight stays in the first year. When this is offset against the average expenditure of overnight guests, the result is an additional gross turnover of approximately 0.60 million EUR across the hospitality and retail industries and other services. The resulting direct effects and indirect effects amount to approximately 0.24 and 0.22 million EUR, respectively. However, long-term effects cannot (yet) be determined. This study demonstrates that combining the two approaches mentioned holds promise, yet requires a more in-depth analysis, for which suggestions are also discussed regarding how it could be conducted.

翻译：暂无翻译