Predicting the Outcomes of NCAA Basketball Championship Games

This paper uses the difference in seeding ranks to predict the outcome of March Madness games. It updates the Boulier-Stekler method by predicting the outcomes by rounds. We also use the consensus rankings obtained from individuals, systems and poll. We conclude that the consensus rankings were slightly better predictors in the early rounds but had the same limitations as the seedings in the later rounds.Sports forecasts, March Madness, Ranking methods, Expert forecasts, Consensus forecasts

Fixed-Parameter Algorithms for Computing Kemeny Scores - Theory and Practice

The central problem in this work is to compute a ranking of a set of elements which is "closest to" a given set of input rankings of the elements. We define "closest to" in an established way as having the minimum sum of Kendall-Tau distances to each input ranking. Unfortunately, the resulting problem Kemeny consensus is NP-hard for instances with n input rankings, n being an even integer greater than three. Nevertheless this problem plays a central role in many rank aggregation problems. It was shown that one can compute the corresponding Kemeny consensus list in f(k) + poly(n) time, being f(k) a computable function in one of the parameters "score of the consensus", "maximum distance between two input rankings", "number of candidates" and "average pairwise Kendall-Tau distance" and poly(n) a polynomial in the input size. This work will demonstrate the practical usefulness of the corresponding algorithms by applying them to randomly generated and several real-world data. Thus, we show that these fixed-parameter algorithms are not only of theoretical interest. In a more theoretical part of this work we will develop an improved fixed-parameter algorithm for the parameter "score of the consensus" having a better upper bound for the running time than previous algorithms.Comment: Studienarbei

Quantifying consensus of rankings based on q-support patterns

Rankings, representing preferences over a set of candidates, are widely used in many information systems, e.g., group decision making and information retrieval. It is of great importance to evaluate the consensus of the obtained rankings from multiple agents. An overall measure of the consensus degree provides an insight into the ranking data. Moreover, it could provide a quantitative indicator for consensus comparison between groups and further improvement of a ranking system. Existing studies are insufficient in assessing the overall consensus of a ranking set. They did not provide an evaluation of the consensus degree of preference patterns in most rankings. In this paper, a novel consensus quantifying approach, without the need for any correlation or distance functions as in existing studies of consensus, is proposed based on a concept of q-support patterns of rankings. The q-support patterns represent the commonality embedded in a set of rankings. A method for detecting outliers in a set of rankings is naturally derived from the proposed consensus quantifying approach. Experimental studies are conducted to demonstrate the effectiveness of the proposed approach

Egalitarianism in the rank aggregation problem: a new dimension for democracy

Winner selection by majority, in an election between two candidates, is the only rule compatible with democratic principles. Instead, when the candidates are three or more and the voters rank candidates in order of preference, there are no univocal criteria for the selection of the winning (consensus) ranking and the outcome is known to depend sensibly on the adopted rule. Building upon XVIII century Condorcet theory, whose idea was to maximize total voter satisfaction, we propose here the addition of a new basic principle (dimension) to guide the selection: satisfaction should be distributed among voters as equally as possible. With this new criterion we identify an optimal set of rankings. They range from the Condorcet solution to the one which is the most egalitarian with respect to the voters. We show that highly egalitarian rankings have the important property to be more stable with respect to fluctuations and that classical consensus rankings (Copeland, Tideman, Schulze) often turn out to be non optimal. The new dimension we have introduced provides, when used together with that of Condorcet, a clear classification of all the possible rankings. By increasing awareness in selecting a consensus ranking our method may lead to social choices which are more egalitarian compared to those achieved by presently available voting systems.Comment: 18 pages, 14 page appendix, RateIt Web Tool: http://www.sapienzaapps.it/rateit.php, RankIt Android mobile application: https://play.google.com/store/apps/details?id=sapienza.informatica.rankit. Appears in Quality & Quantity, 10 Apr 2015, Online Firs

Weathering the Storm of Business Climate Rankings

This paper explores current usage of the term business climate. It discusses multiple definitions and measures of what constitutes a region's business climate. It also examines how usage of the term varies over time and geography. Finally, it addresses some issues related to business climate rankings, their role in economic development policy, and whether the multiplicity of published state rankings contribute consensus or confusion to the meaning of the term business climate.

Deriving consensus rankings via multicriteria decision making methodology

Purpose - This paper seeks to take a cautionary stance to the impact of the marketing mix on customer satisfaction, via a case study deriving consensus rankings for benchmarking on selected retail stores in Malaysia. Design/methodology/approach - The ELECTRE I model is used in deriving consensus rankings via multicriteria decision making method for benchmarking base on the marketing mix model 4P's. Descriptive analysis is used to analyze best practice among the four marketing tactics. Findings - Outranking methods in consequence constitute a strong base on which to found the entire structure of the behavioral theory of benchmarking applied to development of marketing strategy. Research limitations/implications - This study looks only at a limited part of the puzzle of how consumer satisfaction translates into behavioral outcomes. Practical implications - The study provides managers with guidance on how to generate a rough outline of potential marketing activities that can be used to take advantage of capabilities and convert weaknesses and threats. Originality/value - The paper interestingly portrays the effective usage of multicriteria decision-making and ranking method to help marketing managers predict their marketing trends