Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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.
In recent years the logistics outsourcing market has significantly expanded, driving also the growth of the logistics real estate sector. However, these subjects have been investigated separately, without empirical evidence on the assessment of warehouse features, nor studies matching those with 3PL providers' needs. This paper aims to fill this gap by providing a deeper understanding of the alignment between the 3PL industry's needs and the logistics real estate offering. An extensive literature review was used to investigate the characteristics of the logistics real estate industry and define the present and future challenges for the 3PL industry. Afterwards, 3PL warehouse features were analysed through data collected on 75 logistics buildings located in Italy. Results indicate that the logistics real estate seems relatively prepared to support the 3PL industry's needs. However, such alignment could be further strengthened through investments by the logistics real estate towards environmental sustainability and warehouse automation.
The recent trends in logistics outsourcing have led to the need to investigate the 3PL (third-party logistics) industry better. However, the attention has always been focused on operative performance, and the role of the warehouse has been skimmed over. This research aims to define the relationship between warehouse features and the performance indicators of 3PLs, filling the literature gap. This research provides insight into 3PLs’ way of thinking, helping 3PLs identify the right warehouse features to improve their performance and providing guidance for real estate companies in designing warehouses meeting 3PLs’ needs. The analysis uses a case study approach, carried out by interviewing 3PLs that provided data coded according to the dimensions of the Kano model. This methodology was used to generate an in-depth understanding of how 3PLs evaluate the different warehouse features that are able to drive their performance. The “perfect warehouse” is placed in an accessible location; it has loading bays, a standard layout, and a height suitable to optimize the flow of goods, and it utilises the spaces to make the service flexible and responsive. In addition, the warehouse should have internal areas, such as mezzanines, to deliver value-added services.
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