An experimental investigation comparing individual and collaborative work productivity when using desktop and cloud modeling tools

Successful modeling tools need to effectively support individual as well as team-based work (collaboration) within colocated and virtual environments. In the past, achieving this has been challenging, since traditional modeling tools are desktop-based and thus suitable for individual and colocated work only. However, with the rise of web-based architectures and the cloud paradigm, desktop modeling tools now have rivals in their web-based counterparts that are especially suited for online collaboration (e-collaboration). The objective of our research was to probe the question as to ‘which type of modeling tools (desktop or cloud-based) performs better in cases of individual work and e-collaboration’, and to obtain insights into the sources of the strengths and weaknesses regarding both types of modeling tools. A controlled experiment was performed in which we addressed two types of modeling tools—desktop and cloud-based, in respect to two types of work—individual and e-collaboration. Within these treatments, we observed the productivity of 129 undergraduate IT students, who performed different types of modeling activities. The experimental participants reported no statistical significant differences between self-reported expertise with the investigated tools as well as their overall characteristics. However, they did finish individual and e-collaborative activities faster when using cloud modeling tool, where significant differences in favor of the cloud modeling tool were detected during e-collaboration. If we aggregate the results, we can argue that cloud modeling tools are comparable with desktop modeling tools during individual activities and outperform them during e-collaboration. Our findings also correlate with the related research, stating that with the use of state-of-the-art Web technologies, cloud-based applications can achieve the user experience of desktop applications.