A comparative multi criteria decision analysis of football teams: evidence on FIFA world cup. Issue 3 (1st June 2021)

• Record Type: Journal Article
• Authors: Gökgöz, Fazıl; Yalçın, Engin
• Is Part Of: Team performance management. Volume 27:Issue 3/4(2021)
• Page Start: 177
• Page End: 191
• Publication Date: 2021-06-01
• Subjects: Sport performance -- World cup -- Multi-criteria decision-making -- TOPSIS -- WASPAS; Teams in the workplace -- Periodicals; Employee empowerment -- Periodicals; Management -- Employee participation -- Periodicals; 658.402
• DOI: 10.1108/TPM-05-2020-0039
• Languages: English
• ISSNs: 1352-7592

Abstract

Abstract : Purpose: World Cup tournament is one of the most popular international organizations in football. The purpose of this paper is to investigate the overall performance of World Cup 2018 teams via multi-criteria decision-making (MCDM) approaches. Design/methodology/approach: The presented approach adopts entropy integrated Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Weighted Aggregated Sum Product Assessment (WASPAS) approaches to weight the criteria and evaluate the performance of World Cup 2018 teams. Initially, the authors compute weight criteria via Shannon Entropy method. Then, the authors compute and compare the results of TOPSIS and WASPAS methods so as to evaluate the performance of World Cup 2018 teams. Findings: According to TOPSIS and WASPAS results, Belgium has demonstrated better performance in comparison to other teams. As per to the empirical results, both methods have shown a significant harmony in terms of performance figures. There is also strong positive correlation between TOPSIS and WASPAS method results. This result confirms the stability of the analysis. Originality/value: This paper contributes to sport performance management literature by using MCDM methods in FIFA World Cup 2018 teams. To the best of the authors' knowledge, this is the first paper to measure performance of an international football organization via MCDM methods.