Details
Name
Maria Clara VazCluster
Industry and InnovationRole
External Research CollaboratorSince
01st March 2014
Centre
Industrial Engineering and ManagementContacts
+351 22 209 4190
maria.c.vaz@inesctec.pt
2018
Authors
Veloso, AS; Vaz, CB; Alves, J;
Publication
Springer Proceedings in Mathematics and Statistics
Abstract
This study aims to evaluate the economic efficiency of Nursing Homes owned by 96 Santas Casas da Misericórdia (SCM) and the determinants that influenced their efficiency in 2012 and 2013. The SCM are the oldest non-profit entities, which belong to Third Sector in Portugal, provide this social response and receive significant financial contributions annually from the state. The study is developed in two stages. In the first stage, the efficiency scores were calculated through the non-parametric DEA technique. In the second stage, Tobit regression is used to verify the effect of certain organizational variables on efficiency, namely the number of users and existence of Nursing Home chains. The results of the DEA model show that the efficiency average is 81.9%, and only 10 out of 96 Nursing Homes are efficient. Tobit regression shows that the number of users has a positive effect on the efficiency of Nursing Homes, whereas the existence of Nursing Home chains affects their efficiency negatively. © Springer International Publishing AG 2018.
2018
Authors
Fernandes, A; Vaz, CB; Monte, AP;
Publication
Springer Proceedings in Mathematics and Statistics
Abstract
This paper aims to analyse the bi-directional relationship between technical efficiency, as a measure of companies’ performance, and capital structure, under the agency cost theory as well as the pecking order and trade-off theory, to explain the capital structure decisions. The technical efficiency was estimated by the DEA method and corrected by using a suitable bootstrap to obtain statistical inferences. To test the agency cost hypothesis, asymmetric information hypothesis, risk-efficiency hypothesis and franchise value hypothesis (under pecking order and trade off theories framework), two models were applied using some determinants of capital structure such as size, profitability, tangibility, liquidity as control and explanatory variables through a truncated regression with bootstrapping. From an initial sample of 1024 small and medium sized companies from the interior of Portugal, for the period 2006–2009, a subsample of 210 SMEs from secondary and tertiary sectors was selected. The results suggest that medium sized companies have higher average bias-corrected efficiency than small companies; that short-term leverage is positively related to efficiency and that the companies in the sample follow pecking order theory. © Springer International Publishing AG 2018.
2016
Authors
Oliveira, F; Vaz, CB;
Publication
Lecture Notes in Management and Industrial Engineering - Engineering Systems and Networks
Abstract
2015
Authors
Ferreira, AP; Vaz, CB;
Publication
2015 INTERNATIONAL CONFERENCE ON CLEAN ELECTRICAL POWER (ICCEP)
Abstract
This paper intends to give some insights on the performance comparison of two main conversion system technologies from a set of wind farms from two major promoters in the Portuguese wind energy sector. Conversion system technologies under analysis are based on the generator type, synchronous and asynchronous, which are the basis of the dominant technological trends in actual market. The performance assessment is accomplished using Data Envelopment Analysis (DEA) methodology, by computing the Malmquist index for group's comparison. From the obtained results, it is possible to conclude that farms with conversion systems based on synchronous generators have a better performance than the ones using conversion systems based on asynchronous generators. These conclusions may support the decision makers in repowering and overpowering processes.
2015
Authors
Vaz, CB; Ferreira, ÂP;
Publication
Assessment methodologies: energy, mobility and other real world application
Abstract
Supervised Thesis
2016
Author
Fernanda Maria Martins Oliveira
Institution
IPP-ISCAP
2016
Author
Cristian Gomes Carvalheiro.
Institution
IPB
2016
Author
Ana Catarina Rodrigues Martins
Institution
IPB
2016
Author
Ivo Manuel Raposo Mendes
Institution
IPB
2016
Author
Rafael Sousa Soares
Institution
IPB
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