Evaluating Intangible Software Quality Metrics for Effective Project Management Information Systems

In modern organizational environments, project management information systems (PMIS) play an important role in ensuring project success with the user requirements, keeping overall costs within the planned budget, and delivering projects at the agreed time. Selecting a high-quality PMIS is vital for the success of project management. A software quality model tailored to PMIS, summarizing the intangible software quality metrics (ISQM) that are effective in evaluating a PMIS, can help better decision-making on PMIS for project managers. However, there is limited research on the PMIS-tailored quality model. To fill the gap, this study evaluates effective SQM for PMIS quality assessment. There are two types of PMIS: Web-based PMIS and PMIS software applications. To narrow the context of PMIS, we focus on web-based PMIS since they are widely used across the industry, such as Microsoft Project and Jira. According to the PMIS features, we merely explored the tailored quality models that have been proven to be more appropriate for web-based PMIS rather than the basic models, such as ISO/IEC 9126, ISO/IEC 25010, and Bertoa. This research uses a qualitative approach to conduct the commonality screening among these models and find out the key evaluation metrics, such as usability and functionality, and the corresponding qualitative attributes suitable for Web-based PMIS quality assessment. The selected metrics and attributes are used to form a Web-based PMIS-tailored quality model. The scoring mechanism is introduced based on the PMIS-tailored quality model, where project managers can have a clear comparison among different web-based PMISs, leading to effective web-based PMIS selection for project management.

@article{Xin2025,
  title     = {Evaluating Intangible Software Quality Metrics for Effective Project Management Information Systems},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {7},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {Gu Xin and Rozi Nor Haizan Nor and Nur Ilyana Ismarau Tajuddin and Khairi Azhar Aziz},
  doi       = {10.14569/IJACSA.2025.0160706},
  url       = {https://doi.org/10.14569/IJACSA.2025.0160706}
}