Quality and Efficiency Evaluation of Airlines Services. Frontier analysis methods are able to investigate the technical efficiency of service productive systems. In our opinion, in the service sector field the analysis of service productivity must be also linked to service quality. Hence, the aim of this work is to outlines a new efficiency assessment based on these two productivity components (technical efficiency and service quality). More specifically, we adapt efficiency measurement techniques to airline industry by also considering an indicator of service quality represented by the average delay. We then evaluate the operational performance of an Italian airline by applying a Principal Component Analysis (PCA)  Data Envelopment Analysis (DEA) model and we verify which airline routes are ranked among the most efficient ones by also including, in the proposed model, the presence of this undesirable output.

QualityOriented Network DEA Model for the Research Efficiency of Philippine Universities In response to the Philippines education systemu0027s development plan in strengthening the research culture of the different higher education institutions, this study was conducted to assess the research efficiency of 18 research universities in the country. Standard Data Envelopment Analysis (DEA) models, have been used in previous researches to measure the relative efficiency of research performance of universities with quantityoriented indicators inputs and outputs. This study proposed the use of a network DEA (NDEA) model considering quality indicators in assessing the efficiency of the research performance of universities. NDEA allows the measurement of efficiency per stage of a process. The main finding is that the standard DEA tends to exaggerate the research efficiency compared to that of NDEA. The use of qualityoriented publication indicator also revealed that the use of quantityoriented indicators alone exaggerates the performance of the universities as it is mainly based on the number of researches produced, not considering the impact or quality of each research. Some of the topperforming universities ranked lower with the use of quantityoriented indicators.