Logistics real estate has been experiencing a recent rebirth led by the growth of retailing and e-commerce. Although these sectors are looking for facilities matching their logistics needs, the identification of the most suitable building becomes a challenging task. To date, from both the practitioner’s and academic perspectives there is a lack of models for assessing the quality of logistics facilities together with functionality (i.e. whether a warehouse is suitable for hosting a given logistics activity). The purpose of this paper is to fill this gap by developing a rating model for assessing the quality and functionality of logistics facilities.
A three-pronged methodology was adopted. First, a Systematic Literature Network Analysis (SLNA) was carried out to identify the relevant features that must be taken into consideration when assessing logistics real estate. Second, a Delphi method involving experts in the field was used to fine-tune the list of features that emerged from the SLNA process and to evaluate the importance of each feature from a company perspective. The rating model was developed and validated through pilot tests on 27 logistics facilities.
The rating model is divided into four sections: location, technical specifications, external spaces and internal areas. As an output, the model determines the building quality and main functionality, together with a gap analysis to detect the weakest emerging elements.
This research fills an identified research gap in the logistics real estate literature. Specifically, it offers a quantitative and shared evaluation method, which can be used to estimate building quality and functionality, thus extending the scope of the previous assessment methods available.
Baglio, M., Perotti, S., Dallari, F. and Garagiola, E.R. (2020), "Benchmarking logistics facilities: a rating model to assess building quality and functionality", Benchmarking: An International Journal, Vol. 27 No. 3, pp. 1239-1260. https://doi.org/10.1108/BIJ-01-2019-0029
Emerald Publishing Limited
Copyright © 2019, Emerald Publishing Limited