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

Celebrating Faculty Achievement 2015

https://digitalcommons.lasalle.edu/celebratingfaculty/1003/thumbnail.jp

Operational Research in Education

Operational Research (OR) techniques have been applied, from the early stages of the discipline, to a wide variety of issues in education. At the government level, these include questions of what resources should be allocated to education as a whole and how these should be divided amongst the individual sectors of education and the institutions within the sectors. Another pertinent issue concerns the efficient operation of institutions, how to measure it, and whether resource allocation can be used to incentivise efficiency savings. Local governments, as well as being concerned with issues of resource allocation, may also need to make decisions regarding, for example, the creation and location of new institutions or closure of existing ones, as well as the day-to-day logistics of getting pupils to schools. Issues of concern for managers within schools and colleges include allocating the budgets, scheduling lessons and the assignment of students to courses. This survey provides an overview of the diverse problems faced by government, managers and consumers of education, and the OR techniques which have typically been applied in an effort to improve operations and provide solutions

An Integrated Fuzzy Clustering Cooperative Game Data Envelopment Analysis Model with application in Hospital Efficiency

Hospitals are the main sub-section of health care systems and evaluation of hospitals is one of the most important issue for health policy makers. Data Envelopment Analysis (DEA) is a nonparametric method that has recently been used for measuring efficiency and productivity of Decision Making Units (DMUs) and commonly applied for comparison of hospitals. However, one of the important assumption in DEA is that DMUs must be homogenous. The crucial issue in hospital efficiency is that hospitals are providing different services and so may not be comparable. In this paper, we propose an integrated fuzzy clustering cooperative game DEA approach. In fact, due to the lack of homogeneity among DMUs, we first propose to use a fuzzy C-means technique to cluster the DMUs. Then we apply DEA combined with the game theory where each DMU is considered as a player, using Core and Shapley value approaches within each cluster. The procedure has successfully been applied for performances measurement of 288 hospitals in 31 provinces of Iran. Finally, since the classical DEA model is not capable to distinguish between efficient DMUs, efficient hospitals within each cluster, are ranked using combined DEA model and cooperative game approach. The results show that the Core and Shapley values are suitable for fully ranking of efficient hospitals in the healthcare systems

Strategic sourcing:a combined QFD and AHP approach in manufacturing

Purpose – This paper aims to develop an integrated analytical approach, combining quality function deployment (QFD) and analytic hierarchy process (AHP) approach, to enhance the effectiveness of sourcing decisions. Design/methodology/approach – In the approach, QFD is used to translate the company stakeholder requirements into multiple evaluating factors for supplier selection, which are used to benchmark the suppliers. AHP is used to determine the importance of evaluating factors and preference of each supplier with respect to each selection criterion. Findings – The effectiveness of the proposed approach is demonstrated by applying it to a UK-based automobile manufacturing company. With QFD, the evaluating factors are related to the strategic intent of the company through the involvement of concerned stakeholders. This ensures successful strategic sourcing. The application of AHP ensures consistent supplier performance measurement using benchmarking approach. Research limitations/implications – The proposed integrated approach can be principally adopted in other decision-making scenarios for effective management of the supply chain. Practical implications – The proposed integrated approach can be used as a group-based decision support system for supplier selection, in which all relevant stakeholders are involved to identify various quantitative and qualitative evaluating criteria, and their importance. Originality/value – Various approaches that can deal with multiple and conflicting criteria have been adopted for the supplier selection. However, they fail to consider the impact of business objectives and the requirements of company stakeholders in the identification of evaluating criteria for strategic supplier selection. The proposed integrated approach outranks the conventional approaches to supplier selection and supplier performance measurement because the sourcing strategy and supplier selection are derived from the corporate/business strategy

Multiple Attribute Decision Making Based on Cross-Evaluation with Uncertain Decision Parameters

Multiple attribute decision making (MADM) problem is one of the most common and popular research fields in the theory of decision science. A variety of methods have been proposed to deal with such problems. Nevertheless, many of them assumed that attribute weights are determined by different types of additional preference information which will result in subjective decision making. In order to solve such problems, in this paper, we propose a novel MADM approach based on cross-evaluation with uncertain parameters. Specifically, the proposed approach assumes that all attribute weights are uncertain. It can overcome the drawback in prior research that the alternatives’ ranking may be determined by a single attribute with an overestimated weight. In addition, the proposed method can also balance the mean and deviation of each alternative’s cross-evaluation score to guarantee the stability of evaluation. Then, this method is extended to a more generalized situation where the attribute values are also uncertain. Finally, we illustrate the applicability of the proposed method by revisiting two reported studies and by a case study on the selection of community service companies in the city of Hefei in China

Application of Multi-Criteria Decision Making (MCDM) Approached on Teachers' Performance Evaluation and Appraisal

Education quality is the ultimate result of significant contribution by each stake holder in an education system. However, it is believed that faculty quality has direct bearing on improving and sustaining quality in education. Teacher’s performance evaluation is nothing but a Multi Criteria Decision Making Problem (MCDM). There are several quality attributes that influence the efficiency of a potential teacher while guiding his/her students towards a positive and value added academic outcome. However, the extent of significance of quality attributes may vary from individuals’ viewpoint. In other words, different attributes may have different weightage according to their priority of significance while evaluating quality/performance level of a teacher. But there is no clear-cut methodology for assigning this priority weightage for the attributes. Therefore, expert opinion is indeed required to estimate those attribute weightage values. In the present reporting, a methodology adapted from Multi-Criteria-Decision Making (MCDM) has been proposed in order to evaluate performance of a teacher. Grey relational analysis has been explored in order to prioritize quality attributes that are expected to influence performance level of a teacher. Based on COPRAS- method, numerical values (interval scores) on different attributes assigned for a group of teachers (multiplied by individual weightage) have been accumulated to compute an overall quality estimate indicating performance level of individual teachers. Application feasibility as well as efficiency of this method and guidelines in solving such a multi-attribute decision making problem has been described illustratively in this paper