Measuring efficiency of a hierarchical organization with fuzzy DEA method

The paper analyses how the data envelopment analysis (DEA) and fuzzy set theory can be used to measure and evaluate the efficiency of a hierarchical system with n decision making units and a coordinating unit. It is presented a model for determining the of activity levels of decision making units so as to achieve both fuzzy objectives of achieving global target levels of coordination unit on the inputs and outputs and individual target levels of decision making units, and then some methods to resolve fuzzy models are proposed.fuzzy DEA, policy making in multi-level organisations, efficiency analysis

Assessing the overall perceived quality of the undergraduate students

Purpose - The paper is twofold aimed: (i) defining and validating a scale to assess the quality of the university experienced by students and (ii) analyzing the role of the aforementioned di- mensions and their impact on students’ satisfaction. Methodology/Approach - A survey of 2,557 undergraduate students that finished their degrees in 2013 at universities located in the region of Catalonia has been analyzed using Structural Equation Modeling (SEM). An exploratory analysis suggests the final dimensions that were confirmed in a confirmatory analysis. The psychometric characteristics of the scale are provided to show reliability and validity of the constructs. An extra model (also using SEM) assesses the impact of these dimensions on overall satisfac- tion. Findings - The quality is a multifactor construct composed by: (i) “syllabus”, which refers to the quality of the learning methods and the coordination efforts through the whole study period; (ii) “skills development”, referring to the skills that students might acquire along their studies and (iii) “services and facilities” of the university. Moreover, the first and third factors act as “enablers” for the second factor one. Nevertheless, only “Syllabus” dimension affects significantly on students’ satisfaction, whereas “services and facilities” do not have a significant role, although they are necessary in order to provide a good service. Research Limitation/implication - Although the sample is large enough to draw robust re- sults, it is limited the Catalonia. The paper provides recommendations for university managers and public administration authorities in order to allocate the available resources. Originality/Value of paper - In an era of global competition, universities are trying to adapt to these new requirements by expanding they academic offer, introducing innovative teaching methods, providing teaching resources to lecturers, and updating the general services of the university among others. All these services will be considered when students evaluate their experience at the university. The paper contributes with an assessment scale for the holistic service provided by the university within the period that the student is in the university. These findings can be applied to help define attractive academic programs and provide useful insights on how the supporting facilities should be designed to allow students take advantage of their learning process at universities.Postprint (published version

A methodology for the selection of new technologies in the aviation industry

The purpose of this report is to present a technology selection methodology to quantify both tangible and intangible benefits of certain technology alternatives within a fuzzy environment. Specifically, it describes an application of the theory of fuzzy sets to hierarchical structural analysis and economic evaluations for utilisation in the industry. The report proposes a complete methodology to accurately select new technologies. A computer based prototype model has been developed to handle the more complex fuzzy calculations. Decision-makers are only required to express their opinions on comparative importance of various factors in linguistic terms rather than exact numerical values. These linguistic variable scales, such as ‘very high’, ‘high’, ‘medium’, ‘low’ and ‘very low’, are then converted into fuzzy numbers, since it becomes more meaningful to quantify a subjective measurement into a range rather than in an exact value. By aggregating the hierarchy, the preferential weight of each alternative technology is found, which is called fuzzy appropriate index. The fuzzy appropriate indices of different technologies are then ranked and preferential ranking orders of technologies are found. From the economic evaluation perspective, a fuzzy cash flow analysis is employed. This deals quantitatively with imprecision or uncertainties, as the cash flows are modelled as triangular fuzzy numbers which represent ‘the most likely possible value’, ‘the most pessimistic value’ and ‘the most optimistic value’. By using this methodology, the ambiguities involved in the assessment data can be effectively represented and processed to assure a more convincing and effective decision- making process when selecting new technologies in which to invest. The prototype model was validated with a case study within the aviation industry that ensured it was properly configured to meet the