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

Sustainable educational supply chain performance measurement through DEA and Differential Evolution: a case on Indian HEI

Data envelopment analysis or DEA methodology is employed for assessing the relative efficiency of different homogeneous units. Through DEA one can analyze the areas which need more attention and can suggest measures for improving the performance of different sectors. Through this article, the authors have tried to analyze the relative efficiency of IITR (The Indian Institute of Technology Roorkee), a higher educational institute (HEI) in India. The efficiency of nineteen academic departments of IIT Roorkee is measured with respect to teaching and research. The novlty of the paper is twofold (1) the authiors have considered the environmental aspects (sustainability criteria) while measuring efficiency (2) Differential Evolution (DE) algorithm is employed in accordance with DEA on the fractional model generated for calculating efficiency

Assessing the Efficiency of Mass Transit Systems in the United States

Frustrated with increased parking problems, unstable gasoline prices, and stifling traffic congestion, a growing number of metropolitan city dwellers consider utilizing the mass transit system. Reflecting this sentiment, a ridership of the mass transit system across the United States has been on the rise for the past several years. A growing demand for the mass transit system, however, necessitates the expansion of service offerings, the improvement of basic infrastructure/routes, and the additional employment of mass transit workers, including drivers and maintenance crews. Such a need requires the optimal allocation of financial and human resources to the mass transit system in times of shrinking budgets and government downsizing. Thus, the public transit authority is faced with the dilemma of “doing more with less.” That is to say, the public transit authority needs to develop a “lean” strategy which can maximize transit services with the minimum expenses. To help the public transit authority develop such a lean strategy, this report identifies the best-in-class practices in the U.S. transit service sector and proposes transit policy guidelines that can best exploit lean principles built upon best-in-class practices

The effect of ICT on schools’ efficiency: Empirical evidence on 23 European countries

In the last two decades, ICT use in schools grew exponentially. In this paper, the relationship between ICT and school’s efficiency and the mechanisms through which ICT can enhance schools’ productivity are investigated, using PISA 2018 data for about 5400 schools. Empirically, we analyze school’s efficiency in producing ICT-mediated instructional time as well as final educational output, by implementing a network Data Envelopment Analysis (DEA) model. The analysis is complemented by a conditional DEA to account for the presence of possible external drivers of schools’ efficiency. Results show that the average schools’ efficiency in using ICT is relatively low, and that it is mainly driven by the ability of translating ICT-mediated instructional time into learning, rather than by the amount of ICT and human resources. This evidence is consistent across countries. By investigating the role of ICT in schools’ efficiency the paper provides insights to guide the transition of digital technology into learning

Reconstructing nonparametric productivity networks

Network models provide a general representation of inter-connected system dynamics. This ability to connect systems has led to a proliferation of network models for economic productivity analysis, primarily estimated non-parametrically using Data Envelopment Analysis (DEA). While network DEA models can be used to measure system performance, they lack a statistical framework for inference, due in part to the complex structure of network processes. We fill this gap by developing a general framework to infer the network structure in a Bayesian sense, in order to better understand the underlying relationships driving system performance. Our approach draws on recent advances in information science, machine learning and statistical inference from the physics of complex systems to estimate unobserved network linkages. To illustrate, we apply our framework to analyze the production of knowledge, via own and cross-disciplinary research, for a world-country panel of bibliometric data. We find significant interactions between related disciplinary research output, both in terms of quantity and quality. In the context of research productivity, our results on cross-disciplinary linkages could be used to better target research funding across disciplines and institutions. More generally, our framework for inferring the underlying network production technology could be applied to both public and private settings which entail spillovers, including intra-and inter-firm managerial decisions and public agency coordination. This framework also provides a systematic approach to model selection when the underlying network structure is unknown

Measuring Efficiency and Productivity of ICT Infrastructure Utilization

Several researches have been carried out with respect to ICT Infrastructure Investments made by nations in a bid to bridge the digital divide and improve quality of life and the Human Development Index (HDI). With a strong argument being made in the literature for continued investments in ICT Infrastructure, this research investigated the relative efficiency and productivity of ICT Infrastructure Utilization in Education. The research employed the Data Envelopment Analysis (DEA) and Malmquist Index (MI) non-parametric research methodology with Arab States, Europe, Sub-Saharan Africa and World regions forming the Decision-Making Units. With Data collected from the United Nations Educational, Scientific and Cultural Organization (UNESCO) and the International Tel-ecommunications Union (ITU), findings show a relatively efficient utilization and steady increase in productivity for the regions but with only Europe and Arab States currently operating in a state of positive growth in produc-tivity

Evaluating the performance of university course units using data envelopment analysis

The technique of data envelopment analysis (DEA) for measuring the relative efficiency has been widely used in the higher education sector. However, measuring the performance of a set of course units or modules that are part of a university curriculum has received little attention. In this article, DEA was used in a visual way to measure the performance of 12 course units that are part of a Photogrammetry curriculum taught at Aalto University. The results pinpointed the weakest performing units, i.e. units where the provided teaching efforts might not be adequately reflected in the students’ marks in the unit. Based on the results, a single unit was considered to offer poor performance with respect to its teaching resources and was selected as a candidate for revision of its contents. Financial resources were not used as such; instead, the performance of students in previous pre-requisite units was used as the inputs. For clarity, a single output covering the overall student performance in the examined unit was used. The technique should be widely applicable assuming the grade point averages of the students who took the course unit are available along with the marks obtained in the evaluated units and their pre-requisites

Financial crises and bank failures: a review of prediction methods

In this article we analyze financial and economic circumstances associated with the U.S. subprime mortgage crisis and the global financial turmoil that has led to severe crises in many countries. We suggest that the level of cross-border holdings of long-term securities between the United States and the rest of the world may indicate a direct link between the turmoil in the securitized market originated in the United States and that in other countries. We provide a summary of empirical results obtained in several Economics and Operations Research papers that attempt to explain, predict, or suggest remedies for financial crises or banking defaults; we also extensively outline the methodologies used in them. The intent of this article is to promote future empirical research for preventing financial crises.Subprime mortgage ; Financial crises

Neural Network Based Models for Efficiency Frontier Analysis: An Application to East Asian Economies' Growth Decomposition

There has been a long tradition in business and economics to use frontier analysis to assess a production unit’s performance. The first attempt utilized the data envelopment analysis (DEA) which is based on a piecewise linear and mathematical programming approach, whilst the other employed the parametric approach to estimate the stochastic frontier functions. Both approaches have their advantages as well as limitations. This paper sets out to use an alternative approach, i.e. artificial neural networks (ANNs) for measuring efficiency and productivity growth for seven East Asian economies at manufacturing level, for the period 1963 to 1998, and the relevant comparisons are carried out between DEA and ANN, and stochastic frontier analysis (SFA) and ANN in order to test the ANNs’ ability to assess the performance of production units. The results suggest that ANNs are a promising alternative to traditional approaches, to approximate production functions more accurately and measure efficiency and productivity under non-linear contexts, with minimum assumptions.total factor productivity, neural networks, stochastic frontier analysis, DEA, East Asian economies