An empirical analysis is presented to investigate the factors that have significant influence on the share of public financing into the total initial investment required to develop build-operate-transfer (BOT) health-care projects. Based on a model describing the main risks associated with public participation in BOT projects, a linear regression analysis has been conducted on a data set of Italian BOT hospital projects to yield implications. Outcomes reveal that the size of investment, the financial strength of the concessionaire, the duration of the concession period, the number of services, and the level of borrowing of the local health-care granting agency are significant factors of the level of public funding. The study confirms that public funding is provided not only to cover the non-self-financing portion of investment but also as a way to undertake a project in periods of scarce public financial resources. The methodology may be useful to refine the decision criteria for determining the l...

A Framework to Select Techniques Supporting Project Risk Management | InTechOpen, Published on: 2012-09-12. Authors: Sabrina Grimaldi, Carlo Rafele and Anna Corinna Cagliano

Background: Warehouses play a vital role in logistics systems, not only for storing goods but also for providing value-added services. To improve warehouse productivity and reduce costs, it is essential to measure their performance and identify inefficiencies. Method: This paper introduces a new aggregated key performance indicator (KPI), called Overall Warehouse Effectiveness (OWE), to evaluate the efficiency effectiveness of the physical structure of a warehouse. OWE utilizes the concepts of Availability, Performance and Quality, similar to the Overall Equipment Effectiveness (OEE) metric used in manufacturing. Results: The proposed indicator is then applied to a case study to demonstrate its use and provide theoretical and practical implications. Conclusions: In terms of theoretical implications, the proposed metric fills a gap in the literature by providing an aggregated indicator specifically designed for storage systems. For practitioners, OWE enables the identification of efficiency waste, customer service faults and adequacy of inventory management policies.