Product: Management and Development
Product: Management and Development
Original Article

A systematic review of association rules in project management: opportunities for hybrid models

Michael Jordan Bianchi, Daniel Capaldo Amaral

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It is known that significant amounts of data are collected and stored in project management environments due to the use of digital communication and data storage technologies. At the same time, there is the challenge of managing increasingly complex projects in environments that require significant levels of agility. One way to deal with this problem is through hybrid management models. Could data mining techniques assist in the development of hybrid models, allowing organizations to deal with the complexity of their projects? This study identified the state of the art on the use of association rules in project management, identifying opportunities for research. Among data mining techniques, we prioritize association rules, which aim to find interesting patterns in large data sets. Through a systematic literature review, ten studies were found proposing the use of association rules in project management. As a result, we propose potential solutions using data mining to deal with complexity in the context of hybrid project management. The study aims to contribute to the advancement of project management literature and to shows new research opportunities in the area.


data mining, association rules, hybrid models, project management.


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