Assessing the Relative Performance of University Departments: Teaching vs. Research

Data Envelopment Analysis (DEA) is known as a non-parametric method to evaluate the relative efficiencies of a set of homogenous decision-making units (DMUs) (i.e., banking, health, education, etc.) that use multiple inputs to produce multiple outputs. DEA models also have applications for universities or specifically, departments of a university. In practice, determining input and output measures may be based on the available data. However, lack of defining an important measure or use of invalid data may mislead the decision maker. Therefore, this study aims to assess the affect of missing values such as by discarding of outputs on DMU’s efficiency values. The up-to-date data for the departments of an engineering faculty are considered and their performances are presented based on teaching and research oriented measures.Data Envelopment Analysis, Higher Education, University Departments, Teaching, Research

Using Problem-Based Learning (PBL) in an Undergraduate Ergonomics Course

Ergonomics courses typically cover a range of topics related to the design and organization of workplaces to optimize human performance and well-being while minimizing injury risk and discomfort. This study introduces the PBL application steps to attract attention to the importance of noise not only in workplaces but also in daily life. The driving question is determined as “How can we assess and minimize the perceived daily noise exposure of people to sustain hearing health?”. Then, the students are asked to evaluate the PBL activities at the end of the term. Among the students who completed all activities, 60% strongly agreed, 32% agreed that PBL contributed to the understanding of the subject, and only 8% stated that PBL didn’t make a significant contribution when learning the topic of concern. The PBL framework developed for “noise” has the potential to be enhanced and adapted for other topics in this course.

Assessing the efficiency of airports considering health and safety issues: A pilot study for Turkey

Purpose: Airport management is influenced by several related critical decisions on financial and technical operations. Optimum utilization of resources, including assets and personnel, is critical to achieve better service quality for the passengers and an efficient airport. Due to its importance, this paper aims to assess the performance of airports based on security, safety, and possible work-related health problems by considering the uncertain and unclear number of passengers and their baggage. Design/methodology: The efficiency of 30 airports in Turkey is evaluated with a basic Data Envelopment Analysis (DEA) model with two inputs and five outputs. Then, the model is redefined with an undesired output. High, medium, and low seasons are defined in the second DEA model to estimate the number of passenger baggage. The third model utilizes the principles of Fuzzy DEA (F-DEA) that aims to handle the uncertainty for the undesired output data. Findings: The results of three models confirm that the number and weight of baggage and consequently health and safety issues in airports should not be overlooked when optimizing airport efficiency. Utilizing the fuzzy theory has the potential to help managers to improve the operational efficiency of airports when dealing with an uncertain number of passengers and estimating the workload of baggage handlers. Research limitations/implications: No permission was given to make interviews with the ground handling personnel and gather real-life data to analyze task durations and workers’ body movements. Practical implications: Inputs, outputs, and undesired output defined in this study can be used to assess the airports in any other country. Social implications: The importance of health and safety issues for passengers, airport personnel, baggage handlers, and the residents who live close to the airports is considered. Originality/value: This study contributes to the airport performance assessment literature by considering the uncertain and dynamic data related to health and safety issues. This pioneering study, up-to-best knowledge, is the first to assess the airports in Turkey by DEA with the defined undesired output (baggage handler workload) and also utilizing the fuzzy model for the uncertain data.Peer Reviewe

Efficiency Analysis of Airports in Turkey Considering Environmental Effects

Aim: This paper aims to attract attention to the “green airport” term that is basically related with environmental legislations. Design / Research methods: A Data Envelopment Analysis (DEA) model is introduced to assess the efficiency of 22 airports in Turkey with the definition of undesirable output as emission values. Conclusions / findings: Results illustrate that only two airports are efficient based on the considered outputs and undesirable output. Originality / value of the article: Up-to-best knowledge, green gas emission data of airports in Turkey are considered in a DEA model for the first time. To minimize the undesirable output, it is considered as a desirable input in the model. Results are expected to support official authorities during decision making.Limitations of the study: Data for noise levels and the exposed area and/or number of exposed people and buildings were not available for the airports in concern