Current Ranking Systems Research Articles

The Bradley-Terry Model in Binary Outcome Driven Rankings: An Application in Amateur Hockey

Ranking systems serve critical roles in sport settings, most notably in determining playoff participants and seeding. Many ranking methodologies exist that are flexible enough to incorporate many input measures and produce models that are highly predictive of game outcomes. However, there are circumstances—especially for amateur sport leagues—in which more complex inputs are either unavailable or not desirable, as they may lead to adverse performance incentives. Therefore, the goal of this paper is to highlight a ranking methodology that only considers binary game outcomes, i.e., wins and losses. Specifically, we consider the efficacy of the Bradley-Terry Model to efficiently rank sport teams for playoff consideration. We apply this method as a case study to the New England Prep School Ice Hockey Association (NEPSIHA), and compare the accuracy of their current ranking system to the Bradley-Terry model using simulation methods. We show that Bradley-Terry significantly outperforms NEPSIHA’s current method, especially when teams face unbalanced strengths of schedule. This result holds under various league competitive balance distributions.

Internet Marketing in E-Commerce: Maximizing Online Success Using TOPSIS Method

Internet marketing, also referred to as web marketing, online marketing, or e-marketing, is the process of advertising products or services online. Media are available to a global audience thanks to the Internet. The interactive nature of Internet marketing, which prompts immediate answers, is what makes it stand out from other forms of media. Internet marketing is sometimes regarded to have a broad meaning because it includes marketing that is done via e-mail and wireless media in addition to marketing on the Internet. The exchange of goods and services, or the transfer of money or data, over an electronic network—most notably the internet—is known as electronic commerce. Digital customer data management and electronic customer relationship management systems are also included. These business transactions may be B2B, B2C, C2C, or C2B (business-to-business, consumer, or business-to-business). It's common to use the terms e-business and e-commerce interchangeably. Making a decision includes deciding which e-commerce site is best. The current ranking system doesn't rate each website based on user pleasure. Additionally, considering the multiple attribute decision making (MADM) approaches and the volume of studies committed to finding the most significant influencing factors for online customer satisfaction ,it becomes vital to determine the relative importance of website quality attributes based on both user feedback and manager interests. In this study, cash payments come in top, and prepaid cards with a 6- to 24-hour validity period come in last. Using this methodology, our study evaluated several e-commerce tactics and ranked them according to their effectiveness. The TOPSIS MCDM theory's techniques and methods. In order to rank e-commerce websites, the evaluation is done by conducting a survey on the opinions of online visitors. The goal of this research is to evaluate e-commerce websites based on the level of customer satisfaction. We suggest a factor structural model of influence on customer satisfaction.

Defining standards for rankings: An investigation of global university rankings according to the Berlin Principles

AbstractThe role of universities as the engines of knowledge‐based economies drives global internationalisation of higher education. This contributes to a competitive environment where higher education rankings indicate market value. Even though rankings are influential and are used a lot, ranking systems have been heavily critiqued. One of the problems is that there are few if any external checks on how rankings are created. The purpose of the study on which this article reports was to evaluate ranking systems. Within the scope of the study, we have sought to reveal to what extent current ranking systems comply with the Berlin Principles—prepared to create certain rules for rankings, and to ensure that rankings represent quality. A document analysis of publicly available documents online was carried out together with a review of printed and electronic publications on ranking systems. An evaluation form was prepared and used in this study for field experts to fill in. Findings show that ranking systems comply with the Berlin Principles in terms of methodology, transparency, and acceptability at a level that ranges from moderate to low. Overall, rankings do not consider differences in higher education and are not transparent about the processes by which rankings are developed. Rankings should for this reason be interpreted carefully and methodological weaknesses of rankings that can lead to false inferences should be recognised.

Comparing the comparators: How should the quality of education offered by online universities be evaluated?

AbstractComparing universities and courses is of interest to a variety of stakeholders including potential students, policy makers, news and media organisations, ranking providers, and universities themselves. There are a range of existing university ranking schemes that provide comparisons (e.g. Academic Ranking of World Universities) but typically these are designed with face‐to‐face teaching and learning in mind. There is also a growing number of quality assurance tools and approaches aimed at ensuring the quality of online education This article reports on an analysis of a range of quality assurance systems for online higher education institutions and courses, together with variety of ranking systems targeting conventional universities—with the aim of establishing what they measure, and the metrics used to assess quality. The findings from this analytical study were compared with a meta‐analysis of the literature about how students choose their university in order to understand how these instruments influence current student opinion and can be used more proactively by universities themselves. The findings reveal: (1) current ranking systems are of limited value for most potential undergraduate students, particularly with reference to online education, (2) comparison systems that can be of value to students from a variety of different backgrounds are likely to be complex to set up and run, and (3) quality indicators that promote both formative and summative evaluation may be beneficial to both institutions and students.

Measuring the performance of private higher education institutions in Malaysia

PurposeThe purpose of this paper is to propose a comprehensive model using balanced scorecard (BSC) approach instead of the current ranking system to measure the performance of private higher education institutions (PHEIs) in Malaysia as the ranking system is deemed inaccurate and certain items in the system are redundant.Design/methodology/approachA cross-sectional survey was conducted involving 105 academicians from seven PHEIs in Malaysia. The data were analyzed for factor analysis using Principal Axis method with Promax rotation in IBM SPSS Statistics Version 20.FindingsThe result demonstrates that 22 items were successfully extracted into four dimensions that suited the BSC approach with acceptable range of composite reliability and factor loading values.Research limitations/implicationsThe paper reveals the issues of ranking system of the current method in measuring performance of PHEIs. The proposed BSC model should be tested on more PHEIs to increase its validity and reliability.Practical implicationsThis research analyzes the performance of PHEIs from academicians’ perspectives based on the four BSC perspectives. It can be considered as an alternative model for PHEIs’ managers to measure performance of PHEIs in Malaysia rather than the current ranking system.Social implicationsIn the midst of intense competition in private higher education industry in Malaysia, it is crucial to understand that a high performance PHEI is expected to deliver quality tertiary education. This research assists the society to evaluate the strength of a particular PHEI in Malaysia, and further enable them to make a deliberate choice on which PHEI to enter.Originality/valueA growing concern for sustainability of PHEIs requires a method to be undertaken by the authority to measure PHEIs’ performance. This paper addresses this concern by offering 22 items to measure PHEIs’ performance and dictating the need to manage PHEIs in a strategic manner, not by ranking system per se.

College Rankings: Creating an Equitable Model of Transformation and Institutional Effectiveness

Colleges that serve working-class students show up poorly in traditional rankings of US colleges. Without appropriate outcome measures, measures of ‘quality’ of inputs drive most current ranking systems. The trouble is that quality is often just a measure of pre-existing privilege (e.g., selectivity, average SAT scores). In this article, I demonstrate the viability of a model that uses economic returns data while factoring in the relative lack of privilege of students attending any particular institution as a way of ranking that institution’s transformative efficacy and institutional effectiveness. The model was then tested on a diverse sample of 655 US colleges and universities for whom reliable economic returns and institutional effectiveness data are available. Unlike widely used rankings models, this proposed alternative model can distinguish between reproducing privilege (high economic returns as expected, low defaults, timely year to degree and fewer incompleters) and facilitating social mobility (higher returns and persistence than would be expected given the incoming characteristics of students). The article concludes with a discussion of the uses to which such a model could be best put.

Deep Graph Embedding for Ranking Optimization in E-commerce.

Matching buyers with most suitable sellers providing relevant items (e.g., products) is essential for e-commerce platforms to guarantee customer experience. This matching process is usually achieved through modeling inter-group (buyer-seller) proximity by e-commerce ranking systems. However, current ranking systems often match buyers with sellers of various qualities, and the mismatch is detrimental to not only buyers' level of satisfaction but also the platforms' return on investment (ROI). In this paper, we address this problem by incorporating intra-group structural information (e.g., buyer-buyer proximity implied by buyer attributes) into the ranking systems. Specifically, we propose Deep Graph Embedding (DEGREE), a deep learning based method, to exploit both inter-group and intra-group proximities jointly for structural learning. With a sparse filtering technique, DEGREE can significantly improve the matching performance with computation resources less than that of alternative deep learning based methods. Experimental results demonstrate that DEGREE outperforms state-of-the-art graph embedding methods on real-world e-commence datasets. In particular, our solution boosts the average unit price in purchases during an online A/B test by up to 11.93%, leading to better operational efficiency and shopping experience.

Ranking of endurance horses in training based on some selected biochemical and physical parameters

Objective: This study aims to appraise the ranking of endurance horses in training based on some selected biochemical and physical parameters. The increase in skill and gusto in equine endurance sport demands an upsurge in standardized exercise tests and competition to be enforced on endurance sport horses. Materials and methods: Nine seemingly fit Arabians endurance horses between the ages of 5 and 17 years and with a body weight of 350 and 450 kg were included in the research in Malaysia. We designed a point scale in training based on biochemical and physical parameters of endurance horses for lactate, plasma protein, creatine kinase, heart rate, and rectal temperature. Results: The results indicated an accumulated lower point of 1 for the biochemical and physical parameters for an individual horse to have an excellent ranking in training and placing in endurance race contrasted with horses that had higher points of 4 to 6. The lower the points, the lower will be the values of the parameters and the higher the points the higher will be the values of the parameters. It is observed that placing in race tally with the ranking in training. Conclusion: In conclusion, it is observed that placing in race tally with the ranking in training. Therefore, it is suggested that the current ranking system in training could be valid to be used to predict endurance horses’ performance in an actual race. http://doi.org/10.5455/javar.2018.e280

Ranking and prediction of collegiate wrestling

College wrestling rankings have a major impact upon the sport, as they are one of the criteria used to determine advancement to postseason championships and seeding, thereby benchmarking individual, team, and program success. In addition to ordering athletes based upon past performance, rankings may function as predictors for future match outcomes. This research identifies potential biases in traditional ranking methodologies and offers alternatives based on the networkbased PageRank and Elo ratings. Using data from the 2013-2014 NCAA Division I wrestling season, we evaluate both existing and our new rankings on the basis of predictive accuracy. Our new methods significantly improve upon a baseline of 67% accuracy and several of the existing ranking methods. These results and follow-up analyses suggest that Elo presents an especially attractive alternative to current ranking systems for college wrestling, with potential extensions to the prediction of point differentials, ensemble methods, and generalizability to other combat sports. 6

Background and the current healthcare ranking systems in the US

Background and the current healthcare ranking systems in the US

A questionnaire survey of factors which affect OMFS trainees’ choice of deanery at application to ST3

Background: Recruitment to OMFS Higher Training is currently undersubscribed overall. This is in stark comparison to other surgical specialties which are heavily oversubscribed at entry to ST3 level. The current ranking system of Deaneries and Applicants by National Recruitment to OMFS means trainees are not equally distributed to deaneries across the UK, leading to oversubscription in some areas, but more importantly a shortfall of trainees in others.

Evaluating subtopic retrieval methods: Clustering versus diversification of search results

To address the inability of current ranking systems to support subtopic retrieval, two main post-processing techniques of search results have been investigated: clustering and diversification. In this paper we present a comparative study of their performance, using a set of complementary evaluation measures that can be applied to both partitions and ranked lists, and two specialized test collections focusing on broad and ambiguous queries, respectively. The main finding of our experiments is that diversification of top hits is more useful for quick coverage of distinct subtopics whereas clustering is better for full retrieval of single subtopics, with a better balance in performance achieved through generating multiple subsets of diverse search results. We also found that there is little scope for improvement over the search engine baseline unless we are interested in strict full-subtopic retrieval, and that search results clustering methods do not perform well on queries with low divergence subtopics, mainly due to the difficulty of generating discriminative cluster labels.

A Multi-Criteria Metric Algorithm for Recommender Systems

Information overload and an abundance of choices create situations where selecting one option becomes extremely difficult or even worse, a guessing game. Collaborative ranking systems are widely used to alleviate this problem by creating intelligent rankings of items based on an aggregation of user opinions. Current ranking systems can still be improved in a number of areas, including accuracy, transparency and flexibility. This paper presents a multi-criteria ranking algorithm that can be used on a non-rigid set of criteria. The system implementing the algorithm fares well with respect to the above qualities.

University Rankings: Diversity, Excellence and the European Initiative

International rankings of universities influence the perceptions and priorities of governments, of businesses and students. Rectors and university councils see the achievement of high ranking as a strategic imperative. However, their value and benefit is questionable. The fundamental problems are two-fold: Most seek to capture characteristics that cannot be measured directly, and require indirect proxies. How good are the proxies? Different universities fulfil different roles, which a single monotonic scale cannot capture. How can different roles be compared in meaningful ways? None of the current ranking systems have the validity, rigour or meaning to be of real value, except those based on citations to evaluate research, and even here, they fall short in assessing research in the humanities and the social sciences. Institutions tend to target a high score irrespective of whether the metrics are good proxies for the underlying value of the institution. Rankings will at best be irrelevant to those values or, at worst, undermine them. They encourage convergence towards a research-dominated model, reducing system diversity and undermining the potential to contribute to society in other ways. But rankings have such a hold on the public imagination that they are likely to be permanent features of the landscape. Can they be improved? Two approaches have been funded by the European Commission. U-Map is an attempt at classification describing the diversity of universities by mapping activities, not quality: its purpose being transparency for stakeholders. U-Multirank is an attempt at ranking evaluating quality in dimensions analogous to those of U-Map: its purpose assessing how well universities perform their different roles, rather than holding all to research-dominated criteria. Both have serious defects. They suffer from imprecise proxies and the profound difficulty of finding comparable data between countries. The temptations will be to: require ever more burdensome detail in the hope of penetrating to the heart of the matter, formalise the distinctions that mapping reveals, promote further the idea of the university as merely a source of modular products currently in vogue. LERU applauds the attempt to create U-Map as a description of diversity, but is less enthusiastic about U-Multirank,

Reputation Beyond the Rankings: A Conceptual Framework for Business School Research

Despite the global explosion of the business school rankings industry, the validity of current ranking systems and league tables as credible measures of business school reputation has been questioned by scholars, accreditation agencies and consumers worldwide. Critics have begun calling for more substantive assessments of educational quality and more meaningful, theory-driven strategies for studying reputation in the business school context. This paper responds to these critiques, introducing a conceptual model of business school reputation that applies recent advances in reputation theory and research to the specifics of the business school setting. The literature anchoring the model is reviewed, the variables in the model are introduced and theoretical propositions suggested. The paper concludes with discussion of the model's practical implications, an analysis of limitations and suggestions for future research.

Minimizing Game Score Violations in College Football Rankings

One metric used to evaluate the myriad ranking systems in college football is retrodictive accuracy. Maximizing retrodictive accuracy is equivalent to minimizing game score violations: the number of times a past game’s winner is ranked behind its loser. None of the roughly 100 current ranking systems achieves this objective. Using a model for minimizing violations that exploits problem characteristics found in college football, I found that all previous ranking systems generated violations that were at least 38 percent higher than the minimum. A minimum-violations criterion commonly would have affected the consensus top five and changed participants in the designated national championship game in 2000 and 2001—but not in the way most would have expected. A final regular season ranking using the model was perhaps the best prebowl ranking published online in 2004, as it maximized retrodictive accuracy and was nearly the best at predicting the 28 bowl winners.

A market-based mechanism for allocating space Shuttle secondary payload priority

This is an investigation into the design of a market-based process to replace NASA's current committee process for allocating Shuttle secondary payload resources (lockers, Watts and crew). The market-based process allocates budgets of tokens to NASA internal organizations that in turn use the budget to bid for priority for their middeck payloads. The scheduling algorithm selects payloads by priority class and maximizes the number of tokens bid to determine a manifest. The results of a number of controlled experiments show that such a system tends to allocate resources more efficiently by guiding participants to make resource and payload tradeoffs. Most participants were able to improve their position over NASA's current ranking system. Furthermore, those that are better off make large improvements while the few that do worse have relatively small losses.

Bridge Management for the 21st Century

Bridge management has been a subject of intense interest and development for the past 10 years. In support of improved bridge management, FHWA funded the development of the Pontis bridge computer program, which is now in use by approximately 40 of the 50 states. In addition, many new guide specifications have been produced to assist bridge managers in their efforts to better manage the nation’s aging bridge inventory. The AASHTO Subcommittee on Bridges and Structures has taken the lead along with FHWA in implementing the improved bridge management systems. California and a few other states have been critical of the current ranking system for bridge maintenance and have been working to develop an improved performance measure. The bridge health index (HI), an improved and more comprehensive numerical rating system that uses the element inspection data to determine the remaining asset value of a bridge or network of bridges, is discussed. The HI is more consistent with the element-level evaluation data collected and reported in the Pontis program. Examples of the application of the HI are included.

Measuring the Impact of the Discovery and Cleaning of Identified Hazardous Waste Sites on House Values

The current ranking system for Su- perfund sites considers only the costs of physically cleaning the site, ignoring the social benefits ob- tained by cleaning. This study estimates the effect of the existence of toxic sites on house values from before information on their toxicity was released by the federal government until several years after cleaning strategies were announced. The results in- dicate that community knowledge of the site, as well as government agency announcements, causes house prices to decline. It does not appear that assurances that the sites will be cleaned in the future lead to a rebound in house prices. (JEL R14, Q20)