ABSTRACT
Cities, characterised by scarce resources and facing increasing citizens’ requests for more liveable and attractive environments, need to define and implement more efficient urban freight transport policy interventions. It is strategically relevant to perform an ex-ante in-depth policy evaluation. The paper aims at investigating the relevance, the needs and the implications of the data acquisition process by combining a focused review with an original research study. It critically compares five categories of methodological approaches adopted for policy evaluation purposes with an explicit focus on the stated preference method given its behavioural peculiarity and robustness. The review, following a systematic procedure where scientific quality is complemented by relevance and coverage, underlines a high variability in the level of sophistication for data acquisition. While a stakeholder-specific approach seems natural in all those cases where local authorities want to adopt distinct policy instruments for each stakeholder, this is also needed when homogeneous policies impacting the various stakeholders are tested. Stakeholder-specific data acquisition translates into the creation of multiple experimental designs, explicitly conceived for each stakeholder considered. A case study, intended to compare two alternative strategies for data acquisition, provides a quantitative measure of potential distortions in policy evaluation due to the adoption of a stakeholder-generic approach. Results, in terms of willingness to pay measures, show that a stakeholder-specific approach is needed not only when modelling but also in the data acquisition process.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1 ISI web of knowledge is used since it is widely recognised as the most exclusive research database given the quality standards Journals need to respect to be indexed. Last access to the database was on 15 May 2015.
2 Specific thematic concentrations emerge from a first qualitative article clustering. In particular, the most numerous group relates to vehicle routing and efficiency maximisation of freight movements within city boundaries (e.g. Ehmke, Meisel, & Mattfeld, Citation2012; Hemmelmayr, Cordeau, & Crainic, Citation2012; Motraghi & Marinov, Citation2012; Nguyen, Prins, & Prodhon, Citation2012; Perboli, Tadei, & Vigo, Citation2011; Pillac, Gueret, & Medaglia, Citation2012). Another set concentrates on UFT environmental impacts and its regulation (e.g. Arvidsson, Citation2013; Figliozzi, Citation2011; Lee et al., Citation2012; Sathaye et al., Citation2010a, Citation2010b). Data acquisition issues have also catalysed consistent research efforts (e.g. Allen, Browne, & Cherrett, Citation2012b; McCabe, Kwan, & Roorda, Citation2013; Roorda, Citation2011), while minor attention has been paid to the effects of UFT disruptions (e.g. Friesz, Lee, & Lin, Citation2011; Mamasis, Minis, & Dikas, Citation2013) and agent-based modelling (e.g. Teo et al., Citation2012; Zhang, Peeta, & Friesz, Citation2005).
3 A similar study on urban consolidation centres is performed by Marcucci, Danielis, Paglione, and Gatta (Citation2007) where, on the contrary, the same choice scenarios are showed to all stakeholders.
4 Gatta and Marcucci (Citation2013) focus on preference heterogeneity for UFT policies within a single stakeholder type. Heterogeneity can be modelled by using advanced techniques (e.g. Marcucci & Gatta, Citation2011, Citation2012; Fabrizi, Farcomeni, & Gatta, Citation2012; Felici & Gatta, Citation2008).
5 Gatta and Marcucci (Citationin press) and Marcucci and Gatta (Citation2014) investigate the non-linear effects of policy intervention on retailers’ and transport providers' utility functions.
6 Gatta and Marcucci (in press) and Please see Hensher, Rose, and Greene (Citation2005) for an in-depth analysis of the strenght and weaknesses of a MNL model.
7 The Delta method relies on the joint and strong normality assumption for both the maximum likelihood estimates and their ratio. In practice, the Delta method is usually recommended when the cost coefficient is highly significant (Gatta, Marcucci, & Scaccia, Citation2015).
8 Attributes are normalised dividing each attribute level by its own minimum value (see Marcucci, Gatta, Valeri, et al., Citation2013). As an example, unnormalised LUB=400, 800, 1200 while normalised LUB=1, 2 and 3.
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Funding
The authors gratefully acknowledge the financial support of Volvo Research Foundation (‘Innovative solutions to freight distribution in the complex large urban area of Rome’, Grant #SP-2007–50).
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