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This paper aims to contribute to understanding the crucial influence of risks on the capital structure of project financing (PF) initiatives in the energy sector.

The debt leverage of a capital investment is selected as the response variable, and its relation with select identified risk factors is examined using a regression analysis on a data set of 72 projects carried out all over the world in the energy industry.

Results have highlighted that the debt leverage is significantly influenced by several sources of risk measured through specific indicators, namely, country stability index, the construction duration, the concession period and the average size of partners. Therefore, country, project and special purpose vehicle-related risks have been shown to have an impact on the debt leverage of a PF scheme.

The results could support both investors and lenders to better define the financial leverage of projects delivered under a PF mechanism. In particular, the study could help to have a better understanding of the main factors that influence the debt leverage in PF initiatives.

This paper contributes to filling the lack of works addressing the relationship between risk factors and capital structure in PF projects. In this way, this research leads to a better understanding of the risk factors that influence the capital structure of a PF initiative, and they have, therefore, been proposed as a basis for the establishment of improved methods to design refined capital structures.

The objective of this paper is to propose an approach to comparatively analyze the performance of drugs and consumable products warehouses belonging to different healthcare institutions.

A Cluster Analysis is completed in order to classify warehouses and identify common patterns based on similar organizational characteristics. The variables taken into account are associated with inventory levels, the number of SKUs, and incoming and outgoing flows.

The outcomes of the empirical analysis are confirmed by additional indicators reflecting the demand level and the associated logistics flows faced by the warehouses at issue. Also, the warehouses belonging to the same cluster show similar behaviors for all the indicators considered, meaning that the performed Cluster Analysis can be considered as coherent.

The study proposes an approach aimed at grouping healthcare warehouses based on relevant logistics aspects. Thus, it can foster the application of statistical analysis in the healthcare Supply Chain Management. The present work is associated with only one regional healthcare system.

The approach might support healthcare agencies in comparing the performance of their warehouses more accurately. Consequently, it could facilitate comprehensive investigations of the managerial similarities and differences that could be a first step toward warehouse aggregation in homogeneous logistics units.

This analysis puts forward an approach based on a consolidated statistical tool, to assess the logistics performances in a set of warehouses and, in turn to deepen the related understanding as well as the factors determining them.

The purpose of this paper is to contribute to the understanding of the crucial influence of risks on the capital structure of build-operate-transfer (BOT) projects.

The equity portion of capital injected in a BOT investment is selected as the response variable and its relation with select identified risk factors is examined using a regression analysis on a data set of BOT projects.

Results have pointed out that the level of equity is significantly influenced by several sources of risk. Country, revenue, project and special purpose vehicle-related risks have been shown to have an impact on the size of the equity share of a BOT investment.

The results could support both investors and lenders to better define the financial leverage of BOT projects. In particular, the study could help to have a better understanding of the main factors that influence the equity apportion of capital in BOT investments.

This paper contributes to fulfilling the lack of works addressing the relationship between risk factors and capital structure in BOT projects. In this way, this research leads to a better understanding of the risk factors that influence the capital structure of BOT project and they have therefore been proposed as a base for the establishment of improved methods to design refined capital structures in BOT projects.

The purpose of this paper is to investigate the diffusion dynamics of electric and hybrid commercial vans and its enabling factors in the city logistics (CL) contexts. The case of parcel delivery in Torino, Italy, is considered. Attention is paid to the influence on the choice of low impact vehicles of not only public strategies but also operational aspects characterizing urban freight distribution systems.

A System Dynamics model based on the Bass diffusion theory computes the number of adopters of low-emission vehicles together with the quantity of vans required and the associated economic savings. The model includes variables about freight demand, delivery frequency, van carrying capacity, routes, stops, distances traveled, and vehicle charging stations. A sensitivity analysis has been completed to identify the main diffusion levers. The focus is on advertising and other drivers, such as public contributions, taxes traditional polluting vehicles are subjected to, as well as on routing optimization strategies.

Advertising programs, green image, and word-of-mouth drive market saturation, although in a long time period. In fact, low-impact vehicles do not offer any economic advantage over traditional ones requiring higher investment and operating costs. Public incentives to purchase both green vehicles and charging stations, together with carbon taxes and a congestion charge affecting polluting vehicles, are able to shorten the adoption time. In particular, public intervention reveals to be effective only when it unfolds through a number of measures that both facilitate the use of environmentally friendly vehicles and discourage the adoption of traditional commercial vans. Route optimization also hastens the complete market saturation.

This work fosters research about the mutual relationships between the diffusion of low-emission commercial vehicles and the operational and contextual CL factors. It provides a structured approach for investigating the feasibility of innovative good vehicles that might be part of assessments of CL measures and requirements. Finally, the model supports studies about the cooperation among stakeholders to identify effective commercial vehicle fleets.

This study fosters collaboration among CL players by providing a roadmap to identify the key factors for the diffusion of environmentally friendly freight vehicles. It also enables freight carriers to assess the operational and economic feasibility of adopting low-impact vehicles. Finally, it might assist public authorities in capturing the effects of new urban transportation policies prior to their implementation.

Most of the current CL literature defines policies and analyzes their effects. Also, there are several contributions on the diffusion of low emission cars. The present study is one of the first works on the diffusion of low-impact commercial vehicles in urban areas by considering the associated key operational factors. A further value is that the proposed model combines operational variables with economic and environmental issues.

This paper aims to propose a simulation model integrated with an empirical regression analysis to provide a new mathematical formulation for automated storage and retrieval system (AS/RS) travel time estimation under class-based storage and different input/output (I/O) point vertical levels.

A simulation approach is adopted to compute the travel time under different warehouse scenarios. Simulation runs with several I/O point levels and multiple shape factor values.

The proposed model is extremely precise for both single command (SC) and dual command (DC) cycles and very well fitted for a reliable computation of travel times.

The proposed mathematical formulation for estimating the AS/RS travel time advances widely applied methodologies existing in literature. As well as, it provides a practical implication by supporting faster and more accurate travel time computations for both SC and DC cycles. However, the regression analysis is conducted based on simulated data and can be refined by numerical values coming from real warehouses.

This work provides a new simulation model and a refined mathematical equation to estimate AS/RS travel time.

This paper aims to evaluate different logistics configuration to deliver batteries from the supplier to the production lines of a European carmaker who is implementing new propulsions for its models.

Several scenarios about the supply chain for traction batteries have been identified based on the company’s requirements and constraints. Then, the variables used for the assessment of each scenario have been selected to calculate the unit battery supply chain cost.

The results underline that a direct transport without intermediate nodes is the cheapest one. On the contrary, an additional warehouse makes the organization of the network more complex. However, with this configuration, it is possible to cover the risk of supply since that a certain level of inventory is always guaranteed.

This study is limited to the analysis of only one model car, and just manual operations have been taken into account for computing the human resource time and cost. The present study is one of the first works exploring the organization of the supply chain for the batteries integrated in electric and hybrid vehicles together with the choice of the location of the related warehouses.

This paper is one of the first work on the assessment of batteries’ supply chain that are going to be integrated in low impact vehicles, focusing on location of the associated warehouse. The evaluation is carried out by taking into account all the sources of cost.

The purpose of this paper is to provide a literature review on the different ways of carrying out facility management and related topics in order to uncover that there is limited research regarding the impact of facility management on the logistics and operational performance of warehouses.

Four different focus areas have been identified and for each one different methodologies and streams of research have been studied.

The study underlines the importance of facility management for the logistics operations; therefore it supports the notion that investments aiming at preserving the status of the building and service components of warehouses are crucial.

This paper aims to suggest to facilities management managers that they can contribute to enhance business performance by designing effective facility management strategies.

The purpose of this paper is to suggest the usage of the project finance (PF) scheme as a suitable mechanism to fund energy efficiency projects at the urban scale and present its advantages and adoption barriers.

A case study is developed to renew the traffic lighting system of an Italian town via replacement of the old lamps with new light-emitting diode (LED) technology. Several partners are involved in the case project to construct a viable PF arrangement.

The case study presents the viability of the proposed PF scheme that provides for acceptable financial returns and bankability. However, it also shows that the need for short concession periods may call for a public contribution to the initial funding to make the project more attractive to private investors.

This case study is a useful guideline for governments and promoters to using the PF arrangement to fund energy efficiency investments in urban settings. It helps designing an appropriate PF scheme and understanding the advantages of PF to reduce risk and, consequently, increase the debt leverage and profitability of energy efficiency projects.

This paper contributes to bridging the gap about the lack of works addressing the implementation of the PF mechanism in the energy efficiency sector in urban areas. The importance of this paper is also associated with the shortage of traditional public finance faced by many cities that forces to seek for alternate forms of financing.

The purpose of this paper is to determine the fundamental factors influencing maintenance costs of logistic buildings and to provide benchmark indications for designing maintenance efficient warehouses that contribute to the enhancement of business performance.

The relations between factors and indicators of building facilities maintenance costs are examined using regression analysis of a dataset collected from about 100 distribution warehouses leased by a leading global freight provider throughout Italy.

Maintenance cost reduction can only be achieved by making appropriate design decisions on the strategic characteristics of warehouse facilities. In particular, the location and the age of a building are relevant factors of breakdown maintenance, while the monthly volume of freight transiting the warehouse is a significant cost factor of maintenance due to damage.

This paper is limited to logistic service providing organisations, has local impact, and does not consider operational requirements in suggesting design criteria. Further research may gainfully generalise the model by examining other businesses, geographical areas and industrial operations issues. Leasing and frequently relocating facilities have emerged as appropriate distribution management strategies to control location, size and age of a building, and thus to face dynamic business conditions.

This paper provides maintenance cost benchmarks and supports design decision making of distribution warehouse facilities.

This study aims at capturing the perspectives of construction professionals into a classified taxonomy of the various characteristics of smart buildings and at developing an index able to define their level of smartness.

A questionnaire survey has been administrated to construction professionals in the service of designers, constructors and owners. Results have been analyzed with the Kruskal–Wallis test and they have been used to develop a smartness index.

Designers and owners are more focused on the energy issue than constructors. The energy captures the attention of practitioners with less years of experience, confirming that the awareness of the energy topic is rather recent.

The main characteristics of smart buildings have been structured in domains and subdomains. Their importance has been rated by construction professional and a smartness index for smart building has been developed to provide with a convenient tool for evaluation and benchmarking.