Measuring efficiency and productivity in professional football teams: Evidence from the English Premier League

Professional football clubs are unusual businesses, their performance judged on and off the field of play. This study is concerned with measuring the efficiency of clubs in the English Premier League. Information from clubs’ financial statements is used as a measure of corporate performance. To measure changes in efficiency and productivity the Malmquist non-parametric technique has been used. This is derived from the Data Envelopment Analysis (DEA) linear programming approach, with Canonical Correlation Analysis (CCA) being used to ensure the cohesion of the input-output variables. The study concludes that while clubs operate close to efficient levels for the assessed models, there is limited technological advance in their performance in terms of the displacement of the technological frontier

A mixed-data evaluation in group TOPSIS with differentiated decision power

[[abstract]]This main objective of this paper is to provide decision support for mixed data in group Technique for Order Preference by Similarity to Idea Solution (TOPSIS) with differentiated decision power. We use a signum function to compare the ordinal performance of alternatives on any qualitative criterion, or the partial information provided by decision makers. The proposed process for ordinal information is uniformly coherent with the traditional TOPSIS steps, preserving the characteristic of distance-based utilities. Ordinal weights are also considered herein, and the decision power of the group members is formulated by their weights under an agreement in the group. Two examples demonstrate that the proposed approach has some benefits and achieves robustness with two types of sensitivity analyses. Some discussions and their limitations to the approach are also provided.[[notice]]補正完

Multiple attribute decision making based on fuzzy preference information on alternatives: Ranking and weighting

This paper investigates the multiple attribute decision making (MADM) problem with fuzzy preference information on alternatives and proposes an eigenvector method to rank them. Three optimization models are introduced to assess the relative importance weights of attributes in a MADM problem, which integrate subjective fuzzy preference relations and objective information in different ways. Since the decisions these models lead to are based on both subjective and objective information, they are more balanced and credible than those that consider only one type of information. An example is provided to illustrate the application of the proposed models. (c) 2005 Elsevier B.V. All rights reserved

A general multiple attribute decision-making approach for integrating subjective preferences and objective information

A general multiple attribute decision-making (MADM) approach is proposed to integrate subjective preferences and objective information and to assess the relative weights of attributes, where subjective preferences are expressed either by a fuzzy preference relation on decision alternatives or by a pairwise comparison matrix on the relative weights of attributes or by both of them and objective information is expressed by a decision matrix. Three special cases of the approach are investigated, which are the weighted least deviation norm (WLDN), the weighted least-square deviation norm (WLSDN) and the weighted minimax deviation norm (WMDN) approaches. The extension of the general approach to group decision-making and the choice of decision parameters are also discussed. A numerical example is examined to show the applications of the proposed MADM approaches. (C) 2005 Elsevier B.V. All rights reserved

Calculation of Investment Portfolios with Risk Free Borrowing and Lending

We consider the problem of portfolio selection for a risk averse investor wishing to allocate his resources among several investment opportunities in order to maximize the expected utility of final wealth. The calculation of the optimal investment proportions generally requires the solution of a stochastic program whose dimension is the number of risky investments. The computations are simplified dramatically when there is a risk free asset and the investment returns are jointly normally distributed. In this case Tobin has shown that the investment proportions in the risky assets are independent of the utility function and Lintner has shown that these proportions may be obtained from the solution of a fractional program. It is shown under mild hypotheses that the fractional program has a pseudo-concave objective and that the program always has a unique solution. The solution may be sought in several ways, perhaps moat efficiently via Lemke's algorithm applied to a linear complementarity problem. The optimal investment proportions in all assets may be found by solving a stochastic program having one random variable and one decision variable via a search technique. Data on the major pooled Canadian equity pension funds were used to provide an empirical test of the suggested solution approach. Five common classes of utility functions were utilised with varying parameter values. For each class there are smooth curves that related the investment in the risk free asset to the parameters of the utility function. The investor is more risk averse when faced with quarterly data.