A Multidimensional Framework to Uncover Insights of Group Performance and Outcomes in Competitive Environments With a Case Study of FIFA World Cups
Research on the performance of groups in competitive environments has traditionally focused on studying context-specific or collaboration factors without considering a multidimensional systems view integrating both. Additionally, there is limited research considering the co-dependence between the pe...
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10086527/ |
| _version_ | 1797850994607915008 |
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| author | Denisse Martinez-Mejorado Jose Emmanuel Ramirez-Marquez |
| author_facet | Denisse Martinez-Mejorado Jose Emmanuel Ramirez-Marquez |
| author_sort | Denisse Martinez-Mejorado |
| collection | DOAJ |
| description | Research on the performance of groups in competitive environments has traditionally focused on studying context-specific or collaboration factors without considering a multidimensional systems view integrating both. Additionally, there is limited research considering the co-dependence between the performance of a group and its adversaries. This paper proposes a framework to address these limitations by incorporating context-specific, network-based, and individual attributes to identify patterns and attributes of successful (and unsuccessful) groups. The framework provides a method to characterize performance patterns by searching for the dominant attributes that distinguish one pattern from another - relevant for decision-makers when dealing with many features. This analysis finds the different group behavior, both internal to the group and external, based on competition. The approach also identifies winning attributes through a machine-learning classification model. These factors allow differentiating a successful group and weighting context-specific network and opponent attributes. The framework is complemented with a visualization component illustrating competition with context-specific and network attributes at the player level. A case study is presented with data from FIFA World Cups in 2014 and 2018 to demonstrate the applicability of the proposed framework. |
| first_indexed | 2024-04-09T19:10:33Z |
| format | Article |
| id | doaj.art-bea44992c28446808d0124cb62cb4370 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-09T19:10:33Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-bea44992c28446808d0124cb62cb43702023-04-06T23:00:38ZengIEEEIEEE Access2169-35362023-01-0111327763279110.1109/ACCESS.2023.326304310086527A Multidimensional Framework to Uncover Insights of Group Performance and Outcomes in Competitive Environments With a Case Study of FIFA World CupsDenisse Martinez-Mejorado0https://orcid.org/0000-0002-0279-6159Jose Emmanuel Ramirez-Marquez1https://orcid.org/0000-0002-0965-1446School of Systems and Enterprises, Stevens Institute of Technology, Hoboken, NJ, USASchool of Systems and Enterprises, Stevens Institute of Technology, Hoboken, NJ, USAResearch on the performance of groups in competitive environments has traditionally focused on studying context-specific or collaboration factors without considering a multidimensional systems view integrating both. Additionally, there is limited research considering the co-dependence between the performance of a group and its adversaries. This paper proposes a framework to address these limitations by incorporating context-specific, network-based, and individual attributes to identify patterns and attributes of successful (and unsuccessful) groups. The framework provides a method to characterize performance patterns by searching for the dominant attributes that distinguish one pattern from another - relevant for decision-makers when dealing with many features. This analysis finds the different group behavior, both internal to the group and external, based on competition. The approach also identifies winning attributes through a machine-learning classification model. These factors allow differentiating a successful group and weighting context-specific network and opponent attributes. The framework is complemented with a visualization component illustrating competition with context-specific and network attributes at the player level. A case study is presented with data from FIFA World Cups in 2014 and 2018 to demonstrate the applicability of the proposed framework.https://ieeexplore.ieee.org/document/10086527/Performance analyticsgroup performanceteam performancecompetitionnetworks |
| spellingShingle | Denisse Martinez-Mejorado Jose Emmanuel Ramirez-Marquez A Multidimensional Framework to Uncover Insights of Group Performance and Outcomes in Competitive Environments With a Case Study of FIFA World Cups IEEE Access Performance analytics group performance team performance competition networks |
| title | A Multidimensional Framework to Uncover Insights of Group Performance and Outcomes in Competitive Environments With a Case Study of FIFA World Cups |
| title_full | A Multidimensional Framework to Uncover Insights of Group Performance and Outcomes in Competitive Environments With a Case Study of FIFA World Cups |
| title_fullStr | A Multidimensional Framework to Uncover Insights of Group Performance and Outcomes in Competitive Environments With a Case Study of FIFA World Cups |
| title_full_unstemmed | A Multidimensional Framework to Uncover Insights of Group Performance and Outcomes in Competitive Environments With a Case Study of FIFA World Cups |
| title_short | A Multidimensional Framework to Uncover Insights of Group Performance and Outcomes in Competitive Environments With a Case Study of FIFA World Cups |
| title_sort | multidimensional framework to uncover insights of group performance and outcomes in competitive environments with a case study of fifa world cups |
| topic | Performance analytics group performance team performance competition networks |
| url | https://ieeexplore.ieee.org/document/10086527/ |
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