6533b873fe1ef96bd12d590e
RESEARCH PRODUCT
Project Management Information Systems (PMISs): A Statistical-Based Analysis for the Evaluation of Software Packages Features
Alberto LombardoConcetta Manuela La FataGiada La ScaliaRosa Micalesubject
Clustering; Conjoint analysis; Design of Experiment (DoE); Project Management Information System (PMIS); Ranking method; Surveyranking methodTechnologyComputer scienceQH301-705.5QC1-999SoftwareSettore ING-IND/17 - Impianti Industriali MeccaniciGeneral Materials SciencesurveyProject managementBiology (General)Cluster analysisInstrumentationQD1-999Fluid Flow and Transfer ProcessesCommercial softwareScope (project management)business.industryProcess Chemistry and TechnologyTPhysicsGeneral EngineeringProject Management Information System (PMIS); survey; Design of Experiment (DoE); conjoint analysis; ranking method; clusteringClustering Conjoint analysis Design of Experiment (DoE) Project Management Information System (PMIS) Ranking method SurveyProject Management Information System (PMIS)Engineering (General). Civil engineering (General)Data scienceDesign of Experiment (DoE)Computer Science ApplicationsConjoint analysisVariety (cybernetics)ChemistryRespondentconjoint analysisTA1-2040businessclusteringdescription
Project Managers (PMs) working in competitive markets are finding Project Management Information Systems (PMISs) useful for planning, organizing and controlling projects of varying complexity. A wide variety of PMIS software is available, suitable for projects differing in scope and user needs. This paper identifies the most useful features found in PMISs. An extensive literature review and analysis of commercial software is made to identify the main features of PMISs. Afterwards, the list is reduced by a panel of project management experts, and a statistical analysis is performed on data acquired by means of two different surveys. The relative importance of listed features is properly computed, and the interactions between the respondent’s profiles and PMIS features are also investigated by cluster and respondents’ analyses. The paper provides information for researchers and practitioners interested in PMISs packages and their applications. Furthermore, the analyses may help practitioners when choosing a PMIS, and also for developers of PMISs software in understanding user needs.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2021-11-26 | Applied Sciences; Volume 11; Issue 23; Pages: 11233 |