Data Envelopment Analysis in University Rankings 1.0 Introduction Data Envelopment Analysis (DEA) is a means of producing a performance measure where sets of organisational decision making units (DMUs) have multiple inputs and outputs. (Dyson, 2000, OR Insight Vol13 Issue 4). DEA considers each unit in turn through linear programming and selects the most favourable weights for it. In this investigation the DMUs are universities, and the outputs are the different categories, ie ‘Completion Rate’ 1.1 Data Set Chosen / Assumptions From the Times Top 100 universities a list of 12 was made from what was considered to be the top “Computer Science” universities listed on the Times Website (Appendix d). “Computer Science” was chosen solely as a means of selecting 12 Universities. These 12 universities were then investigated using Data Envelopment Analysis (DEA) in EXPRESS-IVE. In the appendices the rankings were altered so that the selected universities were also ranked 1 to 12 in the order they appeared in the Times league table. This facilitated comparisons. Weightings of variables were changed and are therefore subjective as to how I perceived their importance. 4 decimal places were used as a minimum to ensure as greater accuracy as possible. 2.0 Calculating efficiency scores for each university & comparison with Times listing (Appendix a) The criteria used in the Times Top 100 University DEA model were all assigned a minimum weighting (0.0001). The item number (representing where the university placed in the league table) was then altered to the required university before compiling and then run/re-... ... middle of paper ... ...arios, Oxford appears to be the best option as it deviates from 1st only once (when compared to The Times rankings) where it ends up 2nd in the table (when looking at the “good times at University and good job afterwards” scenario). Cambridge and Imperial appear to consistently perform well. However even these change in the final scenario. People cannot be put into boxes, and in a sense DEA could be considered a victim of its own creation; by eliminating so much of the subjectivity associated with it, it creates an initial stage of subjectivity; that of deciding the weightings. Individuals have different needs and goals and therefore a model such as this needs to be used cautiously as evidently there are various other factors that need to be taken into consideration, many of which are unquantifiable without bias.
With the correct metrics in place information can be gathered and reported on in order to form knowledge. Data is raw numbers, information is data with context, and knowledge is the information with understanding, which leads to decisions (Hunter Whitney, 2007). Basing decisions on every metric is a waste of resources and time. As a result, Key Performance Indicators (KPIs) distill the vast amount of data into information that is pertinent to the decision making. Some KPIs could be the items per hour, visitors per day, customer retention rate, conversion rate, etc. However, not all companies need to know all of the indicators, that is why KPIs are based on the business model and needs of the company.
After reading “Gladiator University” by Jennifer Marino Walters, and “Did Gladiators Always Fight to the Death?”, it is obvious to the reader how recent archaeological developments have changed the ways we understand how gladiators lived. What, precisely, has changed about the ways we understand how gladiators live? Buckle up, because this one is going to be a fun ride.
Now, with all of the conditions known, we can start to apply properties of the CTMC to rank college football teams. Before starting anything, the state space has to be identified. The state space is simply just a list for all the possible states in the system. This list consists of all teams in college football that played against at least 2 FBS (Football Bowl Subdivision) opponents. I chose such a specific guideline so that teams that only played one game were left out as to avoid skewed or peculiar results. We now need to define the transition rates between the states. The transition rates here will simply be the number of points scored by one team against another as the rate of going from one state to the other. These points scored by
Sabermetrics is a systematic approach to management that attempts to increase wins, but lower salary cost per unit, by measuring in-game activity. This form of ratio analysis is said to be applicable to invasion sports and is one of two tools used for performance benchmarking. However due to its bivariate nature it may not be applicable to organisations that use multiple inputs and outputs, unless they themselves are clearly divisible or they can be attached to a standard unit of measurement, often money (Gerrard, 2007). Due to the complex nature of invasio...
Desire Satisfaction Theory states that: a life goes best if and only if desires for that life are satisfied. The variability of desires from person to person, along with Desire Satisfaction Theory, makes it possible to have many types of lifes that are different yet all of them making the life of anyone who desire to live them go well; for example if someone desires to make a living as an engineer, the fulfillment of that desire makes his life go best, and at the same time another person who desires to write music would be better off studying music rather than engineering.
Tapinos, E., Dyson, R.G. & Meadows, M. (2005). The impact of performance measurement in strategic planning. International Journal of Productivity and Performance Management, 54(5/6), 370-384.
This scholarship will help to support my progress in my education here at MSUM in many ways. If I have the opportunity to receive this scholarship, all of the scholarship money will be used directly towards my education costs. This scholarship would help me with textbook and classroom expenses, and tuition. As a sophomore in college, I hold two part-time jobs throughout the school year and work full-time over the summer to make sure that I am able to pay my way through schools and living expenses. Any aide is greatly appreciated and will be put to good use.
Veronneau, M. H., Koestner, R. F., & Abela, J. R. (2005). Intrinsic need satisfaction and well-
Great Schools, a national school ranking organization, gives Apex schools a score of 9 of 10 overall. A score higher than 8 means the school system is above average. Greater Schools rank schools based on student achievement, student growth, and college readiness.
Murray, C.J.L. & Frenk, J. (2010). Ranking 37th – Measuring the performance of the U.S.
Overall analysing the figures in Tables 5&6 – there is very little in the way of dramatic increases or decreases in efficiency over the period in question. A key ratio used to measure overall business / sales performance, however, is
Academic Success, the goal of most students, requires: effort, perseverance, and motivation. Although most want it, many fall short; not because they are unintelligent, but because they lack the drive and mindset necessary to achieve it. A negative outlook can lead to many troubles down the road; authors Carol Dweck (“Brainology: Transforming Students’ Motivation to Learn”) and Rebecca Cox ( “ The Student Fear Factor”) share the same beliefs; a student's mindset is crucial for the basis of their academic performance.
For Key Performance Indicators (KPI) to be successful, it needs to have the following characteristics:
Educational productivity is the improvement of students outcomes with little or no additional financial resources, or a consistent level of student performance at a lower level of spending. Educational productivity is based on effectiveness. This is the linkage between student outcomes and the level and use of finacial resources in the schools. Production functions are concerned with how money is related to student learning and lifetime earnings. Other approaches are cost functions, data envelopment, and the impact of smaller class size on the student learning. Although there has been extensive research about educational productive functions, there are still many disagreement among researchers as to whether or not a statistical link can be found between student outcomes and money. However, it is agreed upon that the single largest expendidture in the public school system is teacher expenditure.
Punniyamoorthy, M. & Murali, R. 2008, "Balanced score for the balanced scorecard: a benchmarking tool", Benchmarking, vol. 15, no. 4, pp. 420-443. Emerald, Direct [Accessed 10th February 2014]