Willingness to Pay for Multifunctional Megaprojects: A Stated Preference Analysis Among Firms in the Amsterdam Zuidas Area

Abstract

Urban (re-)development projects may generate various positive and negative spatial externalities to employers. The assessment of such benefits is fraught with many methodological and empirical problems. This study aims to assess the order of magnitude of expected net benefits for incumbent employers that may accrue from a large-scale development project in the Zuidas area in the South-Western part of Amsterdam, the Netherlands. This development project is planned to transform the area into a large multifunctional urban agglomeration. We employ a specific stated preference method (namely, a willingness-to-pay method) to gauge the project's net socio-economic benefits for the current firms in the area concerned, paying special attention to the benefits associated with multifunctionality.

Notes

We refer to De Graaff et al. (2007) and Rodenburg et al. (2008) for complementary empirical analyses on the impact of multifunctional land use on employees and residents.

In the remainder of this section, we provide a very concise description of the currently existing development plans for the Zuidas area. The interested reader is referred to Rodenburg (2005) for more details about the Amsterdam Zuidas area and the existing development plans.

A full (English) version of the questionnaire is available upon request.

Although the number of observations is admittedly limited, the sample seems to cover a rather representative set of firms located at the Amsterdam Zuidas. Combined with the in-depth interviews that were held, this research adds to the scarce evidence that exists on the relevance of multifunctional attributes in the development of sites such as the Amsterdam Zuidas. Evidently, the limitations imposed by the size of the sample have to be kept in mind when interpreting the results of this study.

In this t-test, we used the pooled variance as long as the population variances of the samples did not differ statistically significantly. In cases in which they did differ, we adopted the conservative approach by using the critical t-value with degrees of freedom based on the number of observations in the smallest sample (namely, min(n ₁, n ₂)–1).

The presence of North–South tram, a Amsterdam Zuidas-specific tramline, has not been presented to these companies, so the absence of this bar in Figure 3 does not imply a zero score.

The χ² test assesses the significance of the difference in means between categorical variables. The p-value in Figure 3 reflects the probability that a statistical result as extreme as the one observed would occur if the null hypothesis of equal means were true.

Averages have been weighted with firm size to correct for the variation in the size of companies. The average maximum WTP for the realization of a company's chosen optimal location package statistically significantly differs (at 5%) between companies located within and outside the Amsterdam Zuidas area.