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Publications

Publications by Ana Camanho

2015

A nonparametric methodology for evaluating convergence in a multi-input multi-output setting

Authors
Horta, IM; Camanho, AS;

Publication
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Abstract
This paper presents a novel nonparametric methodology to evaluate convergence in an industry, considering a multi-input multi-output setting for the assessment of total factor productivity. In particular, we develop two new indexes to evaluate sigma-convergence and beta-convergence that can be computed using nonparametric techniques such as Data Envelopment Analysis. The methodology developed is particularly useful to enhance productivity assessments based on the Malmquist index. The methodology is applied to a real world context, consisting of a sample of Portuguese construction companies that operated in the sector between 2008 and 2010. The empirical results show that Portuguese companies tended to converge, both in the sense of a and beta, in all construction activity segments in the aftermath of the financial crisis.

2015

Benchmarking clinical practice in surgery: looking beyond traditional mortality rates

Authors
Castro, RAS; Oliveira, PN; Portela, CS; Camanho, AS; Queiroz e Melo, JQE;

Publication
HEALTH CARE MANAGEMENT SCIENCE

Abstract
This paper proposes two new measures to assess performance of surgical practice based on observed mortality: reliability, measured as the area under the ROC curve and a living score, the sum of individual risk among surviving patients, divided by the total number of patients. A Monte Carlo simulation of surgeons' practice was used for conceptual validation and an analysis of a real-world hospital department was used for managerial validation. We modelled surgical practice as a bivariate distribution function of risk and final state. We sampled 250 distributions, varying the maximum risk each surgeon faced, the distribution of risk among dead patients, the mortality rate and the number of surgeries performed yearly. We applied the measures developed to a Portuguese cardiothoracic department. We found that the joint use of the reliability and living score measures overcomes the limitations of risk adjustedmortality rates, as it enables a different valuation of deaths, according to their risk levels. Reliability favours surgeons with casualties, predominantly, in high values of risk and penalizes surgeons with deaths in relatively low levels of risk. The living score is positively influenced by the maximum risk for which a surgeon yields surviving patients. These measures enable a deeper understanding of surgical practice and, as risk adjusted mortality rates, they rely only on mortality and risk scores data. The case study revealed that the performance of the department analysed could be improved with enhanced policies of risk management, involving the assignment of surgeries based on surgeon's reliability and living score.

2016

Improving the Service Level of Bus Transportation Systems: Evaluation and Optimization of Bus Schedules' Robustness

Authors
Hora, J; Dias, TG; Camanho, A;

Publication
EXPLORING SERVICES SCIENCE (IESS 2016)

Abstract
This study proposes an optimization model to improve the robustness of an existing bus schedule. Robustness represents the ability of schedules to absorb deviations from the timetable and to prevent their propagation through the daily operations. The model developed proposes an optimal assignment of arrival times and distribution of slacks among Time Control Points of a bus line, in order to minimize delays and anticipations from schedule. This required the use of data collected through GPS devices installed in buses, informing the location of buses during their daily operation. The robustness of bus schedules was evaluated through the quantification of delays and anticipations of real observations of bus shifts by comparison with the timetable. The performance measures used to evaluate robustness are the average delay (or anticipation) of buses by comparison with the timetable, and the probability that a passenger that arrives on time according to the timetable will miss the bus or have to wait more than a specified threshold at a Time Control Point. We also compared the improvement of the schedule proposed by the optimization model with the original schedule. The results obtained in a real-world case study, corresponding to a bus line operating in Porto, showed that the model could return an improved schedule for all performance measures considered when compared with the original schedule.

2015

Measurement of input-specific productivity growth with an application to the construction industry in Spain and Portugal

Authors
Kapelko, M; Horta, IM; Camanho, AS; Lansink, AO;

Publication
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS

Abstract
Decision making in companies requires an assessment of the efficiency and productivity of individual inputs to provide insights into the scope for improvement of inputs' use. This paper estimates an input-specific Luenberger productivity growth indicator that can be decomposed to identify the contributions of input-specific technological change, technical efficiency change and scale efficiency change. These components for a specific input sum up to the aggregated indicators which are then compared with the traditional Luenberger indicator. The application focuses on panel data of Spanish and Portuguese construction firms over the period 2002-2011, accounting for three inputs: materials, labor and capital. The results show that aggregated productivity change and its components computed from the input-specific productivity indicator are different from those obtained using a traditional approach. The results also indicate that productivity change is negative for labor and capital for construction firms in both Spain and Portugal, while productivity change of materials is positive for Portugal and negative for Spain. Productivity decline is worse for capital in the Spanish construction firms, and for labor in Portugal.

2016

The Assessment of Municipal Services: Environmental Efficiency of Buildings Construction

Authors
Horta, IM; Camanho, AS; Dias, TG; Niza, S;

Publication
EXPLORING SERVICES SCIENCE (IESS 2016)

Abstract
This paper develops an innovative methodology to assess municipal performance concerning the environmental efficiency of new buildings construction, focusing on the consumption of different types of materials. This study aims to support local governments in the definition of policies for improvements in service provision based on the results of a benchmarking study. The methodology developed includes two stages. The first step concerns the evaluation of municipal environmental efficiency using Data Envelopment Analysis and the identification of factors that may explain different levels of performance. The second step enables the classification of municipalities in terms of the efforts required to achieve environmental efficiency. For this purpose, we used clustering analysis, namely the k-means algorithm. To illustrate the methodology developed, we analyzed the data of the major materials used in the construction of new buildings (metals, non-metallic minerals, fossil fuels, and biomass) in the municipalities of Lisbon metropolitan area between 2003 and 2009. The study revealed that the environmental efficiency of new buildings construction varies considerably among municipalities, suggesting a high potential for performance improvement.

2017

Predicting direct marketing response in banking: comparison of class imbalance methods

Authors
Migueis, VL; Camanho, AS; Borges, J;

Publication
SERVICE BUSINESS

Abstract
Customers' response is an important topic in direct marketing. This study proposes a data mining response model supported by random forests to support the definition of target customers for banking campaigns. Class imbalance is a typical problem in telemarketing that can affect the performance of the data mining techniques. This study also contributes to the literature by exploring the use of class imbalance methods in the banking context. The performance of an undersampling method (the EasyEnsemble algorithm) is compared with that of an oversampling method (the Synthetic Minority Oversampling Technique) in order to determine the most appropriate specification. The importance of the attribute features included in the response model is also explored. In particular, discriminative performance was enhanced by the inclusion of demographic information, contact details and socio-economic features. Random forests, supported by an undersampling algorithm, presented very high prediction performance, outperforming the other techniques explored.

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