PRINCIPAL COMPONENT ANALYSIS TO RANKING TECHNICAL EFFICIENCIES THROUGH STOCHASTIC FRONTIER ANALYSIS AND DEA

The Stochastic Frontier Analysis permits evaluating the Technical Efficiency scores for one output variable to obtain the corresponding Technical Efficiency of n Decision-Making Units (DMU). The objective of this work is a comparison between a Stochastic Frontier Analysis, with same input and different output variables, and the Data Envelopment Analysis. You get k Technical Efficiency TE(yi) which are unified by a Principal Component Analysis and compared with the results of a DEA on the same data

Critical comparison of the main methods for the technical efficiency

The Technical Efficiency is a basic tool to determine the factors that slow down the production. TE aims at evaluating and comparing the operating performance of a set of production units, such as Companies, Offices, Hospi- tals, Banks, Schools, Transport Systems, etc. This paper, after an overview of the literature regarding the methodologies for measuring the Technical Ef- ficiency, compares critically the two main approaches, the Data Envelopment Analysis (DEA) and the Stochastic Frontier Analysis (SFA). These method- ologies are also discussed within an original application that targets to study the efficiency of European Countries with respect to the Gross Domestic Product (GDP)

Entrepreneurship Education as a Process with the support of a Structural Equation Modelling

The need for an Entrepreneurial University, is caused not only by social and market changes but also by the emergence of a different way to innovate, which makes synergy its vision and, in which “working together” becomes its major tool. In an attempt to provide a contribution to the studies that aim to boost entrepreneurship education and the entrepreneurial activity of universities, I analysed and tested an experimental lab, the ExperimentaLab, a virtual platform to support entrepreneurial training programmes through a learning process that simulates the progression from idea to start-up, helping students or would-be entrepreneurs acquire entrepreneurial competences and skills, thus increasing their future likelihood of starting up a business. In so doing, the ExperimentaLab training process focuses on the third mission of the university, i.e., to promote economic and social development (Etzkowitz and Leydesdorff, 2000; Etzkowitz, 2004), as it seeks to educate would-be entrepreneurs by helping them practise the managerial and entrepreneurial functions of new venture creation. To evaluate the educational effectiveness of the virtual platform ExperimentaLab four simulations by role play were conducted, which allowed issues related to such a complex phenomenon to be dealt with. I adopt a structural equation model and multi-group analysis to evaluate the effectiveness of the ExperimentaLab. Results show that the ExperimentaLab could be a valid educational tool potentially implementable by entrepreneurial universities, providing students with an entrepreneurial training program, along with a robust process and a network to stimulate the progression from an idea to a real start-up

Gruppo Operativo Emersito++ Evento Sismico Ischia 2017: Campagne Di Misure Geofisiche, Rapporto N°1

Rapporto Tecnico n°1 della task force operativa EMERSITO++ (INGV) che descrive le campagne sismiche ed elettromagnetiche condotte nei comuni di Casamicciola Terme e di Lacco Ameno a seguito del terremoto di Ischia del 21 Agosto 2017.INGVPublished4T. Sismologia, geofisica e geologia per l'ingegneria sismica1SR. TERREMOTI - Servizi e ricerca per la SocietàN/A or not JC

Technical efficiency: a critical overview of the methods

Technical Efficiency (TE) is a basic tool to determine the factors that slow down production. TE aims to evaluate and compare the operating performance of a set of production units, such as Companies, Offices, Hospitals, Banks, Schools, Transport Systems, etc. The literature on the measurement of Technical Efficiency provides a range of methodologies. This paper presents an overview of the literature on the studies, comparing the main two approaches, namely Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA). DEA is the model most popular with many applications in various domains. The purpose of this paper is to provide a significant critical overview on the main pros and cons of measuring technical efficiency because less effort has been directed toward a competing efficiency model such as SFA. The target of this study is to expose critical observations to give an opportunity to be more careful in choosing the most appropriate method for evaluating Technical Efficiency

Ordinal principal component analysis for a common ranking of stochastic frontiers

The Stochastic Frontier Analysis (SFA) is a model to evaluate the Technical Efficiency (TE) for Production Units (PU). When SFA is applied on different output variables with same input, the analysis estimates different TEs for the PU. We refer to these TEs as the Multiple Technical Efficiency (MTE) of the PU. In this work, we present a method to unify the MTE in one ranking, in order to compute a synthetic index of the TE based on a parametric model. Our approach transforms the measures of efficiency into values on an ordinal scale. Then, using the Ordinal Principal Component Analysis and a genetic algorithm, we merge the multiple rankings

Critical comparison of the main methods for the technical efficiency

The Technical Efficiency is a basic tool to determine the factors that slow down the production. TE aims at evaluating and comparing the operating performance of a set of production units, such as Companies, Offices, Hospi- tals, Banks, Schools, Transport Systems, etc. This paper, after an overview of the literature regarding the methodologies for measuring the Technical Ef- ficiency, compares critically the two main approaches, the Data Envelopment Analysis (DEA) and the Stochastic Frontier Analysis (SFA). These method- ologies are also discussed within an original application that targets to study the efficiency of European Countries with respect to the Gross Domestic Product (GDP).

Combined Factorial and Stochastic Frontier Analysis. Theory and an application to study the Technical Efficiency of Secondary Schools

Our proposal occurs when we have more than one output variable and with Stochastic frontier Analysis (SFA) cannot be considered jointly as happens with Data Envelopment Analysis(DEA). Our goal is, therefore, to make more SFA and unify the Technical Efficiencies in a single list as for DEA. The main objective of this work is to obtain, by a genetic algorithm, a single ranking of different SFA

An Overview of the Data Envelopment Analysis and Stochastic Frontier Analysis

This work wants to compare the assumptions that form the basis of the two metods (SFA and DEA) in order to provide points of reflection to those who want to measure efficiency

Ordinal Principal Component for a Common Ranking of Stochastic Frontiers

In this paper we discuss the reasons that lead to the choice of the Stochastic Frontier Analysis instead of the Data Envelopment analysis