{"title":"A payroll efficiency analysis of Europe’s top football leagues","authors":"G. Villa, S. Lozano","doi":"10.1093/imaman/dpae014","DOIUrl":"https://doi.org/10.1093/imaman/dpae014","url":null,"abstract":"\u0000 Accepted by: Ali Emrouznejad\u0000 Top European football teams have large budgets mainly due to the high wage bills they pay to the players. Therefore, it would be interesting to determine if these football teams are paying inflated salaries considering the sports results that they obtain each season in both national and international competitions. This study focuses on the top five European football leagues (Italian, Spanish, English, French and German). We propose a novel non-convex, non-parametric metafrontier analysis approach to determine whether the football clubs are overpaying their players considering their sporting performance. Goals against in both national and international competitions are modelled as undesirable outputs. Each football team is benchmarked first within its own league and then against all five leagues. From this, apart from estimating the payroll efficiency of each team, the average efficiency of each of these five leagues can also be computed. An exhaustive analysis and discussion of the results is presented using data from three seasons (2020–2023). Some ‘important’ football clubs pay salaries that are not justified by their performance when compared with other, more modest, clubs that pay salaries more in line with the sports results obtained. Ligue 1 is the league that, on average, makes the most efficient use of their payroll, followed by the Bundesliga and, somewhat behind, La Liga and Serie A. The Premier League occupies the last position in terms of average payroll efficiency.","PeriodicalId":503767,"journal":{"name":"IMA Journal of Management Mathematics","volume":"100 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141105891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Cross-efficiency aggregation by ordered visibility graph averaging: method, and application in portfolio selection","authors":"Reenu Kumari, Abha Aggarwal, Anjana Gupta","doi":"10.1093/imaman/dpae012","DOIUrl":"https://doi.org/10.1093/imaman/dpae012","url":null,"abstract":"\u0000 In research and practice of Data Envelopment Analysis (DEA), the arithmetic average is commonly used to aggregate cross-efficiency scores. For this, each decision-making unit (DMU) contributes an equal weight, and many essential decision-making details are lost in the final aggregated cross-efficiency. We propose a novel application of the ordered visibility graph averaging (OVGA) operator for DEA cross-efficiency aggregation and apply the proposed method to study the portfolio selection problem. When solving this problem, several practical concerns, such as a budget, cardinality, buy-in requirements, and restrictions against short selling are also considered. The proposed OVGA aggregated cross-efficiency approach is explained through a numerical example, followed by the formulation of optimal portfolios based on these cross-efficiencies. The suggested method is also tested using empirical data from the Indian banking industry. The results of this study can be used to create the most acceptable portfolio in stock companies, financial institutions, and businesses in the public and private sectors.","PeriodicalId":503767,"journal":{"name":"IMA Journal of Management Mathematics","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140980871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}