Research on the Behavior of Factors That Influence the International Virtual Project Team Performance, Using Data Modeling Techniques

Iulia Dumitraşcu-Băldău and Oana Dumitraşcu
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Iulia Dumitraşcu-Băldău: Industrial Engineering and Management Department, “Lucian Blaga” University of Sibiu, 550024 Sibiu, Romania
Oana Dumitraşcu: Industrial Machines and Equipment Department, “Lucian Blaga” University of Sibiu, 550024 Sibiu, Romania

Sustainability, 2019, vol. 11, issue 3, 1-21

Abstract: International projects have helped organizations around the world to better adapt to the new environmental conditions in which they operate, driven by the phenomenon of globalization. Electronic communication and information tools have enabled the creation of international virtual project teams (IVPTs), allowing team members to collaborate regardless of their geographic location or cultural, historical, socio-political, and educational differences. However, such an environment characterized by diversity will be productive only if the project team managers acknowledge and understand the behavior of influence factors comprised by the virtual environment, developing, accordingly, strategies that support team performance. In order to analyze the factors that influence IVPT performance, we used a C5.0 algorithm on the dataset through IBM SPSS Modeler software. Data collection was performed through an online survey, conducted within 107 IVPT members and managers, in order to answer the third question of the research. The predictive model created by the data mining algorithm revealed that the most important fields underlying the decision tree building were the cognitive skills training programs, team culture, and selection of IVPT members based on the characterisics of their national cultures. These results demonstrate the hypothesis that culture represents one of the most important factors influencing team performance.

Keywords: green job; virtual team performance; international project management; factors of influence; culture; neuromanagement; data mining (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
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